diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..e92cf9b594e8e4608b60733d93926bdec544b5c1 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,35 +1 @@ -*.7z filter=lfs diff=lfs merge=lfs -text -*.arrow filter=lfs diff=lfs merge=lfs -text -*.bin filter=lfs diff=lfs merge=lfs -text -*.bz2 filter=lfs diff=lfs merge=lfs -text -*.ckpt filter=lfs diff=lfs merge=lfs -text -*.ftz filter=lfs diff=lfs merge=lfs -text -*.gz filter=lfs diff=lfs merge=lfs -text -*.h5 filter=lfs diff=lfs merge=lfs -text -*.joblib filter=lfs diff=lfs merge=lfs -text -*.lfs.* filter=lfs diff=lfs merge=lfs -text -*.mlmodel filter=lfs diff=lfs merge=lfs -text -*.model filter=lfs diff=lfs merge=lfs -text -*.msgpack filter=lfs diff=lfs merge=lfs -text -*.npy filter=lfs diff=lfs merge=lfs -text -*.npz filter=lfs diff=lfs merge=lfs -text -*.onnx filter=lfs diff=lfs merge=lfs -text -*.ot filter=lfs diff=lfs merge=lfs -text -*.parquet filter=lfs diff=lfs merge=lfs -text -*.pb filter=lfs diff=lfs merge=lfs -text -*.pickle filter=lfs diff=lfs merge=lfs -text -*.pkl filter=lfs diff=lfs merge=lfs -text *.pt filter=lfs diff=lfs merge=lfs -text -*.pth filter=lfs diff=lfs merge=lfs -text -*.rar filter=lfs diff=lfs merge=lfs -text -*.safetensors filter=lfs diff=lfs merge=lfs -text -saved_model/**/* filter=lfs diff=lfs merge=lfs -text -*.tar.* filter=lfs diff=lfs merge=lfs -text -*.tar filter=lfs diff=lfs merge=lfs -text -*.tflite filter=lfs diff=lfs merge=lfs -text -*.tgz filter=lfs diff=lfs merge=lfs -text -*.wasm filter=lfs diff=lfs merge=lfs -text -*.xz filter=lfs diff=lfs merge=lfs -text -*.zip filter=lfs diff=lfs merge=lfs -text -*.zst filter=lfs diff=lfs merge=lfs -text -*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..61f1a76a969f32543910fefdf93db8dfc712bdbe --- /dev/null +++ b/.gitignore @@ -0,0 +1,212 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[codz] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py.cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# UV +# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +#uv.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock +#poetry.toml + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +# pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python. +# https://pdm-project.org/en/latest/usage/project/#working-with-version-control +#pdm.lock +#pdm.toml +.pdm-python +.pdm-build/ + +# pixi +# Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control. +#pixi.lock +# Pixi creates a virtual environment in the .pixi directory, just like venv module creates one +# in the .venv directory. It is recommended not to include this directory in version control. +.pixi + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.envrc +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +# Abstra +# Abstra is an AI-powered process automation framework. +# Ignore directories containing user credentials, local state, and settings. +# Learn more at https://abstra.io/docs +.abstra/ + +# Visual Studio Code +# Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore +# that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore +# and can be added to the global gitignore or merged into this file. However, if you prefer, +# you could uncomment the following to ignore the entire vscode folder +# .vscode/ + +# Ruff stuff: +.ruff_cache/ + +# PyPI configuration file +.pypirc + +# Cursor +# Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to +# exclude from AI features like autocomplete and code analysis. Recommended for sensitive data +# refer to https://docs.cursor.com/context/ignore-files +.cursorignore +.cursorindexingignore + +# Marimo +marimo/_static/ +marimo/_lsp/ +__marimo__/ + +*.DS_Store +all_data_lipophil.pt +all_data_lipophil_enriched.pt +richer_lipophil_data.pt \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..d1c91c8cd7c03361b0057da29e41e9216b707a5b --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2025 Rahul Khorana + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md index 7be5fc7f47d5db027d120b8024982df93db95b74..5594761cf979753ce313b67444e28746fd542573 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,15 @@ ---- -license: mit ---- +# PACT-Net (NeurIPS 2025) + +```python +python main.py --model polyatomic --rep polyatomic --dataset esol +``` + +``` +@inproceedings{khorana2025pactnet, + title = {Topological Feature Compression for Molecular Graph Neural Networks}, + author = {Rahul Khorana}, + booktitle = {Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS 2025) Workshop on AI for Science}, + year = {2025}, + note = {Poster presentation} +} +``` diff --git a/benchmark_csv/bindingdb.csv b/benchmark_csv/bindingdb.csv new file mode 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+COC(C1CCN(CC1)S(=O)(=O)c1c(C)nn(C)c1C)c1ccc(Cl)cc1,METTMGFMDDNATNTSTSFLSVLNPHGAHATSFPFNFSYSDYDMPLDEDEDVTNSRTFFAAKIVIGMALVGIMLVCGIGNFIFIAALVRYKKLRNLTNLLIANLAISDFLVAIVCCPFEMDYYVVRQLSWEHGHVLCTSVNYLRTVSLYVSTNALLAIAIDRYLAIVHPLRPRMKCQTATGLIALVWTVSILIAIPSAYFTTETVLVIVKSQEKIFCGQIWPVDQQLYYKSYFLFIFGIEFVGPVVTMTLCYARISRELWFKAVPGFQTEQIRKRLRCRRKTVLVLMCILTAYVLCWAPFYGFTIVRDFFPTVFVKEKHYLTAFYIVECIAMSNSMINTLCFVTVKNDTVKYFKKIMLLHWKASYNGGKSSADLDLKTIGMPATEEVDCIRLK,7.221848749616356 +CCCc1c(OC)ccc2cc(C(=O)Nc3ccc(cc3C)S(N)(=O)=O)c(=O)oc12,MGPTSVPLVKAHRSSVSDYVNYDIIVRHYNYTGKLNISADKENSIKLTSVVFILICCFIILENIFVLLTIWKTKKFHRPMYYFIGNLALSDLLAGVAYTANLLLSGATTYKLTPAQWFLREGSMFVALSASVFSLLAIAIERYITMLKMKLHNGSNNFRLFLLISACWVISLILGGLPIMGWNCISALSSCSTVLPLYHKHYILFCTTVFTLLLLSIVILYCRIYSLVRTRSRRLTFRKNISKASRSSEKSLALLKTVIIVLSVFIACWAPLFILLLLDVGCKVKTCDILFRAEYFLVLAVLNSGTNPIIYTLTNKEMRRAFIRIMSCCKCPSGDSAGKFKRPIIAGMEFSRSKSDNSSHPQKDEGDNPETIMSSGNVNSSS,7.844663962534938 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+OC1=C(C(C2=C(O)C(=O)c3ccccc3C2=O)c2ccc(O)cc2)C(=O)c2ccccc2C1=O,MKVENSKMGVKREQSHSNEDEEINEEDLNWWEQENLRIAMKGERRWETLAHNGVLFPPEYEPHGIPIFYDGREFKMTPEEEEVATMFAVMKEHDYYRMEVFRRNFFESWREILDKRQHPIRRLELCDFEPIYQWHLVQREKKLSRTKEEKKAIKEKQDAEAEPYRYCVWDGRREQVANFRVEPPGLFRGRGKHPLMGKLKVRVQPEDITINIGETAEVPVPPAGHKWAAVQHDHTVTWLAMWRDSVAGNMKYVMLAPSSSVKGQSDMVKFEKARKLKDKVDDIRASYMEDFKSNDLHVAQRAVAMYFIDRLALRVGNEKGEDEADTVGCCSLRVEHIQLMPDNIVRFDFLGKDSIRYQNDVAVLPEVYALLQRFTRRKSPGTDIFDQLNPTQLNDHLKSFMDGLSAKVFRTYNASITLDRWFKEKPVDPKWSTADKLAYFNKANTEVAILCNHQKSVSKNFKLQMMQLTTKSEYTRKTIELLEKAEVTAKKKSVEEAAKEFLEEQDRMQREWLESYGTEEQKKEFEEIVAKRAAPRVRSEKKKSTSGAKKAESASGKKRAAKKKKSAKKGGKVLSKKAASKSSKKAPKKLKEEDEDDVPLVSVAAKTKKTAGVKRQRANKVVSDDDDVPLAALRV,4.154901959985743 +CCOc1ccc(Cc2nc3cc(ccc3n2CCC(C)C)C(=O)N(CC)CC)cc1,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,8.346787486224656 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+CC(C)Oc1cc(ccc1C(O)=O)-c1ccc(CCN[C@@H](C)[C@H](O)c2ccccc2)cc1,MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL,5.0 +CN(C)C(=O)CCSC(SCCC(O)=O)c1cccc(\C=C\c2ccc3ccc(Cl)cc3n2)c1,MDETGNPTIPPASNNTCYDSIDDFRNQVYSTLYSMISVVGFFGNGFVLYVLVKTYHEKSAFQVYMINLAVADLLCVCTLPLRVAYYVHKGIWLFGDFLCRLSTYALYVNLYCSIFFMTAMSFFRCVAIVFPVQNISLVTQKKARLVCIAIWMFVILTSSPFLMANTYKDEKNNTKCFEPPQDNQAKNYVLILHYVSLFIGFIIPFITIIVCYTMIIFTLLKSSMKKNLSSRKRAIGMIIVVTAAFLVSFMPYHIQRTIHLHFLHNKTKPCDSILRMQKSVVITLSLAASNCCFDPLLYFFSGGNFRRRLSTIRKYSLSSMTYIPKKKTSLPQKGKDICKE,9.096910013008056 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+C[C@H]1CNCCc2ccc(Cl)c(Cl)c12,MDILCEENTSLSSTTNSLMQLNDDTRLYSNDFNSGEANTSDAFNWTVDSENRTNLSCEGCLSPSCLSLLHLQEKNWSALLTAVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAVWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVSFFIPLTIMVITYFLTIKSLQKEATLCVSDLGTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYTGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNEDVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENKKPLQLILVNTIPALAYKSSQLQMGQKKNSKQDAKTTDNDCSMVALGKQHSEEASKDNSDGVNEKVSCV,5.599980364934842 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+NS(=O)(=O)c1ccc(cc1)C#Cc1ccncc1,MSRQSISLRFPLLLLLLSPSPVFSADPGAPAPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPEIWTWLRTTLRPSPSFIHFLLTHGRWLWDFVNATFIRDTLMRLVLTVRSNLIPSPPTYNIAHDYISWESFSNVSYYTRILPSVPRDCPTPMDTKGKKQLPDAEFLSRRFLLRRKFIPDPQSTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQMLNGEVYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATIWLREHNRVCDLLKAEHPTWGDEQLFQTARLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGAQFQYRNRIAMEFNQLYHWHPLMPDSFRVGPQDYSYEQFLFNTSMLVDYGVEALVDAFSRQPAGRIGGGRNIDHHILHVAVDVIKESRVLRLQPFNEYRKRFGMKPYTSFQELTGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEMGAPFSLKGLLGNPICSPEYWKASTFGGEVGFNLVKTATLKKLVCLNTKTCPYVSFHVPDPRQEDRPGVERPPTEL,5.4089353929735005 +Cl.Cc1cnc2n(c(nc2c1)-c1cccnc1N)-c1ccc(CN)cc1,MSDVAIVKEGWLHKRGEYIKTWRPRYFLLKNDGTFIGYKERPQDVDQREAPLNNFSVAQCQLMKTERPRPNTFIIRCLQWTTVIERTFHVETPEEREEWTTAIQTVADGLKKQEEEEMDFRSGSPSDNSGAEEMEVSLAKPKHRVTMNEFEYLKLLGKGTFGKVILVKEKATGRYYAMKILKKEVIVAKDEVAHTLTENRVLQNSRHPFLTALKYSFQTHDRLCFVMEYANGGELFFHLSRERVFSEDRARFYGAEIVSALDYLHSEKNVVYRDLKLENLMLDKDGHIKITDFGLCKEGIKDGATMKTFCGTPEYLAPEVLEDNDYGRAVDWWGLGVVMYEMMCGRLPFYNQDHEKLFELILMEEIRFPRTLGPEAKSLLSGLLKKDPKQRLGGGSEDAKEIMQHRFFAGIVWQHVYEKKLSPPFKPQVTSETDTRYFDEEFTAQMITITPPDQDDSMECVDSERRPHFPQFSYSASGTA,6.568636235841012 +C[C@H](Cc1ccc(CCNC(=O)c2ccc(cc2)N(C)C(=O)CCN2CCC(CC2)OC(=O)Nc2ccccc2-c2ccccc2)cc1)NC[C@H](O)c1ccc(O)c2[nH]c(=O)ccc12,MTLHNNSTTSPLFPNISSSWIHSPSDAGLPPGTVTHFGSYNVSRAAGNFSSPDGTTDDPLGGHTVWQVVFIAFLTGILALVTIIGNILVIVSFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLAIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAETENFVHPTGSSRSCSSYELQQQSMKRSNRRKYGRCHFWFTTKSWKPSSEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSTILNSTKLPSSDNLQVPEEELGMVDLERKADKLQAQKSVDDGGSFPKSFSKLPIQLESAVDTAKTSDVNSSVGKSTATLPLSFKEATLAKRFALKTRSQITKRKRMSLVKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTFWNLGYWLCYINSTVNPVCYALCNKTFRTTFKMLLLCQCDKKKRRKQQYQQRQSVIFHKRAPEQAL,10.0 +N[C@@H](CCS(O)=O)C(O)=O,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,5.0 +CCN(CC)C(=O)c1ccc(cc1)C(=C1CC2CCC(C1)N2CCOc1ccccc1)c1ccccc1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,6.200659450546418 +Fc1ccccc1N1CCN(CCCCn2c3ccccc3oc2=O)CC1,MGAVTARRCVEWLLGLYFVSHIPITMFIDLQALLPPELYPQEFSNLLRWYSKEFKDPLMQEPPVWFKSFLFCELVFQLPFFPIAAYAFFKGSCRWIRIPAIIYAVHTITTLIPILYTILFEDFSKAIAFKGQRPENFRERLTLVGVYAPYLIIPLILLLFMLRNPYYKFEEKRKKK,8.554395796726402 +COC1(CN(C1)c1nc(C)cc(Nc2cc(C)[nH]n2)n1)C(=O)NCc1ccc(nc1)-n1cc(F)cn1,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,8.0 +CCN(CCO)CCCOc1ccc2c(Nc3cc(CC(=O)Nc4cccc(F)c4)n[nH]3)ncnc2c1,MGCVQCKDKEATKLTEERDGSLNQSSGYRYGTDPTPQHYPSFGVTSIPNYNNFHAAGGQGLTVFGGVNSSSHTGTLRTRGGTGVTLFVALYDYEARTEDDLSFHKGEKFQILNSSEGDWWEARSLTTGETGYIPSNYVAPVDSIQAEEWYFGKLGRKDAERQLLSFGNPRGTFLIRESETTKGAYSLSIRDWDDMKGDHVKHYKIRKLDNGGYYITTRAQFETLQQLVQHYSERAAGLCCRLVVPCHKGMPRLTDLSVKTKDVWEIPRESLQLIKRLGNGQFGEVWMGTWNGNTKVAIKTLKPGTMSPESFLEEAQIMKKLKHDKLVQLYAVVSEEPIYIVTEYMNKGSLLDFLKDGEGRALKLPNLVDMAAQVAAGMAYIERMNYIHRDLRSANILVGNGLICKIADFGLARLIEDNEYTARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELVTKGRVPYPGMNNREVLEQVERGYRMPCPQDCPISLHELMIHCWKKDPEERPTFEYLQSFLEDYFTATEPQYQPGENL,5.0 +CN(C1CC1)c1nccn2c(c(nc12)-c1ccc(F)cc1)-c1ccc2NC(=O)Cc2c1,MQHIFAFFCTGFLGAVVGANFPNNIQIGGLFPNQQSQEHAAFRFALSQLTEPPKLLPQIDIVNISDSFEMTYRFCSQFSKGVYAIFGFYERRTVNMLTSFCGALHVCFITPSFPVDTSNQFVLQLRPELQDALISIIDHYKWQKFVYIYDADRGLSVLQKVLDTAAEKNWQVTAVNILTTTEEGYRMLFQDLEKKKERLVVVDCESERLNAILGQIIKLEKNGIGYHYILANLGFMDIDLNKFKESGANVTGFQLVNYTDTIPAKIMQQWKNSDARDHTRVDWKRPKYTSALTYDGVKVMAEAFQSLRRQRIDISRRGNAGDCLANPAVPWGQGIDIQRALQQVRFEGLTGNVQFNEKGRRTNYTLHVIEMKHDGIRKIGYWNEDDKFVPAATDAQAGGDNSSVQNRTYIVTTILEDPYVMLKKNANQFEGNDRYEGYCVELAAEIAKHVGYSYRLEIVSDGKYGARDPDTKAWNGMVGELVYGRADVAVAPLTITLVREEVIDFSKPFMSLGISIMIKKPQKSKPGVFSFLDPLAYEIWMCIVFAYIGVSVVLFLVSRFSPYEWHSEEFEEGRDQTTSDQSNEFGIFNSLWFSLGAFMQQGCDISPRSLSGRIVGGVWWFFTLIIISSYTANLAAFLTVERMVSPIESAEDLAKQTEIAYGTLEAGSTKEFFRRSKIAVFEKMWTYMKSAEPSVFVRTTEEGMIRVRKSKGKYAYLLESTMNEYIEQRKPCDTMKVGGNLDSKGYGIATPKGSALRNPVNLAVLKLNEQGLLDKLKNKWWYDKGECGSGGGDSKDKTSALSLSNVAGVFYILIGGLGLAMLVALIEFCYKSRSESKRMKGFCLIPQQSINEAIRTSTLPRNSGAGASSGGSGENGRVVSHDFPKSMQSIPCMSHSSGMPLGATGL,8.301029995663981 +Cn1cc2c(n1)nc(NC(=O)NC1CCN(CC1)C(=O)Nc1ccncc1)n1nc(nc21)-c1ccco1,MPNNSTALSLANVTYITMEIFIGLCAIVGNVLVICVVKLNPSLQTTTFYFIVSLALADIAVGVLVMPLAIVVSLGITIHFYSCLFMTCLLLIFTHASIMSLLAIAVDRYLRVKLTVRYKRVTTHRRIWLALGLCWLVSFLVGLTPMFGWNMKLTSEYHRNVTFLSCQFVSVMRMDYMVYFSFLTWIFIPLVVMCAIYLDIFYIIRNKLSLNLSNSKETGAFYGREFKTAKSLFLVLFLFALSWLPLSIINCIIYFNGEVPQLVLYMGILLSHANSMMNPIVYAYKIKKFKETYLLILKACVVCHPSDSLDTSIEKNSE,7.6777807052660805 +CCNc1cc(cc(c1)C(=O)N[C@@H](Cc1ccccc1)[C@H](O)CNCc1cccc(OC(F)(F)F)c1)N1CCCC1=O,MGALARALLLPLLAQWLLRAAPELAPAPFTLPLRVAAATNRVVAPTPGPGTPAERHADGLALALEPALASPAGAANFLAMVDNLQGDSGRGYYLEMLIGTPPQKLQILVDTGSSNFAVAGTPHSYIDTYFDTERSSTYRSKGFDVTVKYTQGSWTGFVGEDLVTIPKGFNTSFLVNIATIFESENFFLPGIKWNGILGLAYATLAKPSSSLETFFDSLVTQANIPNVFSMQMCGAGLPVAGSGTNGGSLVLGGIEPSLYKGDIWYTPIKEEWYYQIEILKLEIGGQSLNLDCREYNADKAIVDSGTTLLRLPQKVFDAVVEAVARASLIPEFSDGFWTGSQLACWTNSETPWSYFPKISIYLRDENSSRSFRITILPQLYIQPMMGAGLNYECYRFGISPSTNALVIGATVMEGFYVIFDRAQKRVGFAASPCAEIAGAAVSEISGPFSTEDVASNCVPAQSLSEPILWIVSYALMSVCGAILLVLIVLLLLPFRCQRRPRDPEVVNDESSLVRHRWK,5.698970004336019 +N#CC1CCN(Cc2ccc(cc2)-c2cnc3[nH]c4cnc(cc4c3c2)C#N)CC1,MRPPQCLLHTPSLASPLLLLLLWLLGGGVGAEGREDAELLVTVRGGRLRGIRLKTPGGPVSAFLGIPFAEPPMGPRRFLPPEPKQPWSGVVDATTFQSVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLVWIYGGGFYSGASSLDVYDGRFLVQAERTVLVSMNYRVGAFGFLALPGSREAPGNVGLLDQRLALQWVQENVAAFGGDPTSVTLFGESAGAASVGMHLLSPPSRGLFHRAVLQSGAPNGPWATVGMGEARRRATQLAHLVGCPPGGTGGNDTELVACLRTRPAQVLVNHEWHVLPQESVFRFSFVPVVDGDFLSDTPEALINAGDFHGLQVLVGVVKDEGSYFLVYGAPGFSKDNESLISRAEFLAGVRVGVPQVSDLAAEAVVLHYTDWLHPEDPARLREALSDVVGDHNVVCPVAQLAGRLAAQGARVYAYVFEHRASTLSWPLWMGVPHGYEIEFIFGIPLDPSRNYTAEEKIFAQRLMRYWANFARTGDPNEPRDPKAPQWPPYTAGAQQYVSLDLRPLEVRRGLRAQACAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQDRCSDL,5.570247719997592 +Cn1c(Nc2ccc(cc2)C(F)(F)F)nc2cc(Oc3ccnc(c3)-c3ncc([nH]3)C(F)(F)F)ccc12,MGRGLLRGLWPLHIVLWTRIASTIPPHVQKSVNNDMIVTDNNGAVKFPQLCKFCDVRFSTCDNQKSCMSNCSITSICEKPQEVCVAVWRKNDENITLETVCHDPKLPYHDFILEDAASPKCIMKEKKKPGETFFMCSCSSDECNDNIIFSEEYNTSNPDLLLVIFQVTGISLLPPLGVAISVIIIFYCYRVNRQQKLSSTWETGKTRKLMEFSEHCAIILEDDRSDISSTCANNINHNTELLPIELDTLVGKGRFAEVYKAKLKQNTSEQFETVAVKIFPYEEYASWKTEKDIFSDINLKHENILQFLTAEERKTELGKQYWLITAFHAKGNLQEYLTRHVISWEDLRKLGSSLARGIAHLHSDHTPCGRPKMPIVHRDLKSSNILVKNDLTCCLCDFGLSLRLDPTLSVDDLANSGQVGTARYMAPEVLESRMNLENVESFKQTDVYSMALVLWEMTSRCNAVGEVKDYEPPFGSKVREHPCVESMKDNVLRDRGRPEIPSFWLNHQGIQMVCETLTECWDHDPEARLTAQCVAERFSELEHLDRLSGRSCSEEKIPEDGSLNTTK,5.0 +Fc1cccc(-c2ncccn2)c1C(=O)N1CC2CC(Oc3ccc(Br)cn3)C1C2,MEPSATPGAQPGVPTSSGEPFHLPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFLIALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAVMVPQAAVMECSSVLPELANRTRLFSVCDERWADELYPKIYHSCFFFVTYLAPLGLMGMAYFQIFRKLWGPQIPGTTSALVRNWKRPSEQLEAQHQGLCTEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPSSSARHKSLSLQSRCSVSKVSEHVVLTTVTTVLS,8.154901959985743 +CCSc1nnc2n(-c3ccccc3)c(=O)c3c4[C@H](C)CCCc4sc3n12,MEDFNMESDSFEDFWKGEDLSNYSYSSTLPPFLLDAAPCEPESLEINKYFVVIIYALVFLLSLLGNSLVMLVILYSRVGRSVTDVYLLNLALADLLFALTLPIWAASKVNGWIFGTFLCKVVSLLKEVNFYSGILLLACISVDRYLAIVHATRTLTQKRYLVKFICLSIWGLSLLLALPVLLFRRTVYSSNVSPACYEDMGNNTANWRMLLRILPQSFGFIVPLLIMLFCYGFTLRTLFKAHMGQKHRAMRVIFAVVLIFLLCWLPYNLVLLADTLMRTQVIQETCERRNHIDRALDATEILGILHSCLNPLIYAFIGQKFRHGLLKILAIHGLISKDSLPKDSRPSFVGSSSGHTSTTL,5.107905397309519 +Cc1ccccc1C[C@H](NCP(O)(O)=O)C(=O)N[C@@H](Cc1ccc(cc1)-c1ccccc1)C(O)=O,MGKSESQMDITDINTPKPKKKQRWTPLEISLSVLVLLLTIIAVTMIALYATYDDGICKSSDCIKSAARLIQNMDATTEPCTDFFKYACGGWLKRNVIPETSSRYGNFDILRDELEVVLKDVLQEPKTEDIVAVQKAKALYRSCINESAIDSRGGEPLLKLLPDIYGWPVATENWEQKYGASWTAEKAIAQLNSKYGKKVLINLFVGTDDKNSVNHVIHIDQPRLGLPSRDYYECTGIYKEACTAYVDFMISVARLIRQEERLPIDENQLALEMNKVMELEKEIANATAKPEDRNDPMLLYNKMTLAQIQNNFSLEINGKPFSWLNFTNEIMSTVNISITNEEDVVVYAPEYLTKLKPILTKYSARDLQNLMSWRFIMDLVSSLSRTYKESRNAFRKALYGTTSETATWRRCANYVNGNMENAVGRLYVEAAFAGESKHVVEDLIAQIREVFIQTLDDLTWMDAETKKRAEEKALAIKERIGYPDDIVSNDNKLNNEYLELNYKEDEYFENIIQNLKFSQSKQLKKLREKVDKDEWISGAAVVNAFYSSGRNQIVFPAGILQPPFFSAQQSNSLNYGGIGMVIGHEITHGFDDNGRNFNKDGDLVDWWTQQSASNFKEQSQCMVYQYGNFSWDLAGGQHLNGINTLGENIADNGGLGQAYRAYQNYIKKNGEEKLLPGLDLNHKQLFFLNFAQVWCGTYRPEYAVNSIKTDVHSPGNFRIIGTLQNSAEFSEAFHCRKNSYMNPEKKCRVW,7.017728766960431 +Cc1ccc(Nc2cc(=O)n(C)cc2C(N)=O)c(F)c1,MPKKKPTPIQLNPAPDGSAVNGTSSAETNLEALQKKLEELELDEQQRKRLEAFLTQKQKVGELKDDDFEKISELGAGNGGVVFKVSHKPSGLVMARKLIHLEIKPAIRNQIIRELQVLHECNSPYIVGFYGAFYSDGEISICMEHMDGGSLDQVLKKAGRIPEQILGKVSIAVIKGLTYLREKHKIMHRDVKPSNILVNSRGEIKLCDFGVSGQLIDSMANSFVGTRSYMSPERLQGTHYSVQSDIWSMGLSLVEMAVGRYPIPPPDAKELELMFGCQVEGDAAETPPRPRTPGRPLSSYGMDSRPPMAIFELLDYIVNEPPPKLPSGVFSLEFQDFVNKCLIKNPAERADLKQLMVHAFIKRSDAEEVDFAGWLCSTIGLNQPSTPTHAAGV,5.527243550682788 +FC(F)(F)c1ccc(cc1)-n1ccc(CN2CCC(CC(=O)NC(c3ccccc3)c3ccccn3)CC2)c1,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,5.638272163982407 +Cc1nc2c(Nc3ccccc3[S@](C)=O)cc(NC(=O)C3CC3)nc2[nH]1,PGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASD,8.259637310505756 +CC1CC(CC1C)N1CCN(CC1)C1CCc2ccc(OCc3noc(n3)-c3ccc(Cl)cc3)cc12,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,6.583359492661719 +COc1ccc(cc1)N1C[C@H](CN2CCC(CC2)c2ccc3OCOc3c2)OC1=O,MQWAVGRRWAWAALLLAVAAVLTQVVWLWLGTQSFVFQREEIAQLARQYAGLDHELAFSRLIVELRRLHPGHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSRGHSGRYWAEISDTIISGTFHQWREGTTKSEVFYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLAFALADTVFSTQDFLTLFYTLRSYARGLRLELTTYLFGQDP,7.721246399047171 +Clc1ccc(cc1Cl)C(=O)OCCN1C(=O)c2ccccc2C1=O,PISPITVPVKLKPGMDGPKVKQWPLTEEKIKALTEICTEMEKEGKIEKIGPENPYNTPVFAIKKKDSTKWRKVVDFRELNKRTQDFWEVQLGIPHPAGLKKKKSVTVLDVGDAYFSVPLDKDFRKYTAFTIPSINNETPGIRYQYNVLPQGWKGSPAIFQSSMTKILEPFRKQNPDIVIYQYMDDLYVGSDLEIEQHRAKIEELRQHLLRWGFTTPDKKHQKEPPFLWMGYELHPDKWTVQPIVLPEKDSWTVN,8.698970004336019 +Oc1cccc(CNC(=O)Nc2nc(cs2)-c2ccncc2)c1,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASTPTNATAASDANTGDRGQTNNAASASASNST,8.10790539730952 +C[C@H]1C2Cc3ccc(Nc4ccc(cc4)C(C)(C)C)cc3[C@@]1(C)CCN2CC1CC1,YTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKTVNVCNWI,7.7447274948966935 +CC(C)C[C@H](NC(=O)N1CCCCCC1)C(=O)N[C@H](Cc1c[nH]c2ccccc12)c1nc(C(O)=O)c(Cc2ccccc2)s1,MGVLCFLASFWLALVGGAIADNAERYSANLSSHVEDFTPFPGTEFNFLGTTLQPPNLALPSNGSMHGYCPQQTKITTAFKYINTVISCTIFIVGMVGNATLLRIIYQNKCMRNGPNALIASLALGDLIYVVIDLPINVFKLLAGRWPFDHNDFGVFLCKLFPFLQKSSVGITVLNLCALSVDRYRAVASWSRVQGIGIPLITAIEIVSIWILSFILAIPEAIGFVMVPFEYKGEQHRTCMLNATTKFMEFYQDVKDWWLFGFYFCMPLVCTAIFYTLMTCEMLNRRNGSLRIALSEHLKQRREVAKTVFCLVVIFALCWFPLHLSRILKKTVYDEMDKNRCELLSFLLLMDYIGINLATMNSCINPIALYFVSKKFKNCFQSCLCCCCHQSKSLMTSVPMNGTSIQWKNQEQNHNTERSSHKDSMN,4.4089353929735005 +CCCCCCCCO[C@@H]1C=C(C[C@H](N)[C@H]1NC(C)=O)C(O)=O,MLPSTVQTLTLLLTSGGVLLSLYVSASLSYLLYSDVLLKFSSTKTTAPTMSLECTNASNAQTVNHSATKEMTFPPPEPEWTYPRLSCQGSTFQKALLISPHRFGEIKGNSAPLIIREPFVACGPKECRHFALTHYAAQPGGYYNGTRKDRNKLRHLVSVKLGKIPTVENSIFHMAAWSGSACHDGREWTYIGVDGPDNDALVKIKYGEAYTDTYHSYAHNILRTQESACNCIGGDCYLMITDGSASGISKCRFLKIREGRIIKEILPTGRVEHTEECTCGFASNKTIECACRDNSYTAKRPFVKLNVETDTAEIRLMCTKTYLDTPRPDDGSIAGPCESNGDKWLGGIKGGFVHQRMASKIGRWYSRTMSKTNRMGMELYVKYDGDPWTDSDALTLSGVMVSIEEPGWYSFGFEIKDKKCDVPCIGIEMVHDGGKDTWHSAATAIYCLMGSGQLLWDTVTGVDMAL,5.455931955649724 +CCCCCCCCCc1ccc(OCCOCCOCCOCCOCCOCCOCCOCCOCCO)cc1,MDQHQHLNKTAESASSEKKKTRRCNGFKMFLAALSFSYIAKALGGIIMKISITQIERRFDISSSLAGLIDGSFEIGNLLVIVFVSYFGSKLHRPKLIGIGCLLMGTGSILTSLPHFFMGYYRYSKETHINPSENSTSSLSTCLINQTLSFNGTSPEIVEKDCVKESGSHMWIYVFMGNMLRGIGETPIVPLGISYIDDFAKEGHSSLYLGSLNAIGMIGPVIGFALGSLFAKMYVDIGYVDLSTIRITPKDSRWVGAWWLGFLVSGLFSIISSIPFFFLPKNPNKPQKERKISLSLHVLKTNDDRNQTANLTNQGKNVTKNVTGFFQSLKSILTNPLYVIFLLLTLLQVSSFIGSFTYVFKYMEQQYGQSASHANFLLGIITIPTVATGMFLGGFIIKKFKLSLVGIAKFSFLTSMISFLFQLLYFPLICESKSVAGLTLTYDGNNSVASHVDVPLSYCNSECNCDESQWEPVCGNNGITYLSPCLAGCKSSSGIKKHTVFYNCSCVEVTGLQNRNYSAHLGECPRDNTCTRKFFIYVAIQVINSLFSATGGTTFILLTVKIVQPELKALAMGFQSMVIRTLGGILAPIYFGALIDKTCMKWSTNSCGAQGACRIYNSVFFGRVYLGLSIALRFPALVLYIVFIFAMKKKFQGKDTKASDNERKVMDEANLEFLNNGEHFVPSAGTDSKTCNLDMQDNAAAN,5.542118103266008 +FC(F)(F)c1cccc(c1)C(=O)NCC(=O)N[C@@H]1CCN(CCN2CCN(CC2)C(=O)c2ccccc2)C1,MGLEALVPLAVIVAIFLLLVDLMHRRQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQLRRRFGDVFSLQLAWTPVVVLNGLAAVREALVTHGEDTADRPPVPITQILGFGPRSQGVFLARYGPAWREQRRFSVSTLRNLGLGKKSLEQWVTEEAACLCAAFANHSGRPFRPNGLLDKAVSNVIASLTCGRRFEYDDPRFLRLLDLAQEGLKEESGFLREVLNAVPVLLHIPALAGKVLRFQKAFLTQLDELLTEHRMTWDPAQPPRDLTEAFLAEMEKAKGNPESSFNDENLRIVVADLFSAGMVTTSTTLAWGLLLMILHPDVQRRVQQEIDDVIGQVRRPEMGDQAHMPYTTAVIHEVQRFGDIVPLGVTHMTSRDIEVQGFRIPKGTTLITNLSSVLKDEAVWEKPFRFHPEHFLDAQGHFVKPEAFLPFSAGRRACLGEPLARMELFLFFTSLLQHFSFSVPTGQPRPSHHGVFAFLVSPSPYELCAVPR,5.0 +CN[C@@H]1C[C@H]2O[C@@](C)([C@@H]1OC)n1c3ccccc3c3c4CNC(=O)c4c4c5ccccc5n2c4c13,MSLHFLYYCSEPTLDVKIAFCQGFDKQVDVSYIAKHYNMSKSKVDNQFYSVEVGDSTFTVLKRYQNLKPIGSGAQGIVCAAYDAVLDRNVAIKKLSRPFQNQTHAKRAYRELVLMKCVNHKNIISLLNVFTPQKTLEEFQDVYLVMELMDANLCQVIQMELDHERMSYLLYQMLCGIKHLHSAGIIHRDLKPSNIVVKSDCTLKILDFGLARTAGTSFMMTPYVVTRYYRAPEVILGMGYKENVDIWSVGCIMGEMVRHKILFPGRDYIDQWNKVIEQLGTPCPEFMKKLQPTVRNYVENRPKYAGLTFPKLFPDSLFPADSEHNKLKASQARDLLSKMLVIDPAKRISVDDALQHPYINVWYDPAEVEAPPPQIYDKQLDEREHTIEEWKELIYKEVMNSEEKTKNGVVKGQPSPSGAAVNSSESLPPSSSVNDISSMSTDQTLASDTDSSLEASAGPLGCCR,6.958607314841775 +COc1ccc2c(NC3CCN(Cc4ccccc4)CC3)nc(NCCNC(=O)CCCCCCC(=O)NO)nc2c1,MEEPEEPADSGQSLVPVYIYSPEYVSMCDSLAKIPKRASMVHSLIEAYALHKQMRIVKPKVASMEEMATFHTDAYLQHLQKVSQEGDDDHPDSIEYGLGYDCPATEGIFDYAAAIGGATITAAQCLIDGMCKVAINWSGGWHHAKKDEASGFCYLNDAVLGILRLRRKFERILYVDLDLHHGDGVEDAFSFTSKVMTVSLHKFSPGFFPGTGDVSDVGLGKGRYYSVNVPIQDGIQDEKYYQICESVLKEVYQAFNPKAVVLQLGADTIAGDPMCSFNMTPVGIGKCLKYILQWQLATLILGGGGYNLANTARCWTYLTGVILGKTLSSEIPDHEFFTAYGPDYVLEITPSCRPDRNEPHRIQQILNYIKGNLKHVV,4.814457845145625 +CN(C1CCN(C)CC1)c1cccc(c1)N(C)c1ccc(Oc2nc(O)c3ccncc3n2)cc1,MEVAEVESPLNPSCKIMTFRPSMEEFREFNKYLAYMESKGAHRAGLAKVIPPKEWKPRQCYDDIDNLLIPAPIQQMVTGQSGLFTQYNIQKKAMTVKEFRQLANSGKYCTPRYLDYEDLERKYWKNLTFVAPIYGADINGSIYDEGVDEWNIARLNTVLDVVEEECGISIEGVNTPYLYFGMWKTTFAWHTEDMDLYSINYLHFGEPKSWYAIPPEHGKRLERLAQGFFPSSSQGCDAFLRHKMTLISPSVLKKYGIPFDKITQEAGEFMITFPYGYHAGFNHGFNCAESTNFATVRWIDYGKVAKLCTCRKDMVKISMDIFVRKFQPDRYQLWKQGKDIYTIDHTKPTPASTPEVKAWLQRRRKVRKASRSFQCARSTSKRPKADEEEEVSDEVDGAEVPNPDSVTDDLKVSEKSEAAVKLRNTEASSEEESSASRMQVEQNLSDHIKLSGNSCLSTSVTEDIKTEDDKAYAYRSVPSISSEADDSIPLSSGYEKPEKSDPSELSWPKSPESCSSVAESNGVLTEGEESDVESHGNGLEPGEIPAVPSGERNSFKVPSIAEGENKTSKSWRHPLSRPPARSPMTLVKQQAPSDEELPEVLSIEEEVEETESWAKPLIHLWQTKSPNFAAEQEYNATVARMKPHCAICTLLMPYHKPDSSNEENDARWETKLDEVVTSEGKTKPLIPEMCFIYSEENIEYSPPNAFLEEDGTSLLISCAKCCVRVHASCYGIPSHEICDGWLCARCKRNAWTAECCLCNLRGGALKQTKNNKWAHVMCAVAVPEVRFTNVPERTQIDVGRIPLQRLKLKCIFCRHRVKRVSGACIQCSYGRCPASFHVTCAHAAGVLMEPDDWPYVVNITCFRHKVNPNVKSKACEKVISVGQTVITKHRNTRYYSCRVMAVTSQTFYEVMFDDGSFSRDTFPEDIVSRDCLKLGPPAEGEVVQVKWPDGKLYGAKYFGSNIAHMYQVEFEDGSQIAMKREDIYTLDEELPKRVKARFSTASDMRFEDTFYGADIIQGERKRQRVLSSRFKNEYVADPVYRTFLKSSFQKKCQKRQ,7.0 +Nc1ncc(cc1-c1ccc2C(=O)NCCc2c1)-c1cc(c(cc1F)C#C)[N+]([O-])=O,MDSRAQLWGLALNKRRATLPHPGGSTNLKADPEELFTKLEKIGKGSFGEVFKGIDNRTQKVVAIKIIDLEEAEDEIEDIQQEITVLSQCDSPYVTKYYGSYLKDTKLWIIMEYLGGGSALDLLEPGPLDETQIATILREILKGLDYLHSEKKIHRDIKAANVLLSEHGEVKLADFGVAGQLTDTQIKRNTFVGTPFWMAPEVIKQSAYDSKADIWSLGITAIELARGEPPHSELHPMKVLFLIPKNNPPTLEGNYSKPLKEFVEACLNKEPSFRPTAKELLKHKFILRNAKKTSYLTELIDRYKRWKAEQSHDDSSSEDSDAETDGQASGGSDSGDWIFTIREKDPKNLENGALQPSDLDRNKMKDIPKRPFSQCLSTIISPLFAELKEKSQACGGNLGSIEELRGAIYLAEEACPGISDTMVAQLVQRLQRYSLSGGGTSSH,6.0 +O=C(CC1CCCCC1)N1CCC2(CC2CNC(=O)C2Cc3cnccc3O2)CC1,MNPAAEAEFNILLATDSYKVTHYKQYPPNTSKVYSYFECREKKTENSKLRKVKYEETVFYGLQYILNKYLKGKVVTKEKIQEAKDVYKEHFQDDVFNEKGWNYILEKYDGHLPIEIKAVPEGFVIPRGNVLFTVENTDPECYWLTNWIETILVQSWYPITVATNSREQKKILAKYLLETSGNLDGLEYKLHDFGYRGVSSQETAGIGASAHLVNFKGTDTVAGLALIKKYYGTKDPVPGYSVPAAEHSTITAWGKDHEKDAFEHIVTQFSSVPVSVVSDSYDIYNACEKIWGEDLRHLIVSRSTQAPLIIRPDSGNPLDTVLKVLEILGKKFPVTENSKGYKLLPPYLRVIQGDGVDINTLQEIVEGMKQKMWSIENIAFGSGGGLLQKLTRDLLNCSFKCSYVVTNGLGINVFKDPVADPNKRSKKGRLSLHRTPAGNFVTLEEGKGDLEEYGQDLLHTVFKNGKVTKSYSFDEIRKNAQLNIELEAAHH,7.841637507904751 +CCc1cc2C(=O)c3c([nH]c4cc(ccc34)C#N)C(C)(C)c2cc1-c1cnn(C)c1,MGAIGLLWLLPLLLSTAAVGSGMGTGQRAGSPAAGPPLQPREPLSYSRLQRKSLAVDFVVPSLFRVYARDLLLPPSSSELKAGRPEARGSLALDCAPLLRLLGPAPGVSWTAGSPAPAEARTLSRVLKGGSVRKLRRAKQLVLELGEEAILEGCVGPPGEAAVGLLQFNLSELFSWWIRQGEGRLRIRLMPEKKASEVGREGRLSAAIRASQPRLLFQIFGTGHSSLESPTNMPSPSPDYFTWNLTWIMKDSFPFLSHRSRYGLECSFDFPCELEYSPPLHDLRNQSWSWRRIPSEEASQMDLLDGPGAERSKEMPRGSFLLLNTSADSKHTILSPWMRSSSEHCTLAVSVHRHLQPSGRYIAQLLPHNEAAREILLMPTPGKHGWTVLQGRIGRPDNPFRVALEYISSGNRSLSAVDFFALKNCSEGTSPGSKMALQSSFTCWNGTVLQLGQACDFHQDCAQGEDESQMCRKLPVGFYCNFEDGFCGWTQGTLSPHTPQWQVRTLKDARFQDHQDHALLLSTTDVPASESATVTSATFPAPIKSSPCELRMSWLIRGVLRGNVSLVLVENKTGKEQGRMVWHVAAYEGLSLWQWMVLPLLDVSDRFWLQMVAWWGQGSRAIVAFDNISISLDCYLTISGEDKILQNTAPKSRNLFERNPNKELKPGENSPRQTPIFDPTVHWLFTTCGASGPHGPTQAQCNNAYQNSNLSVEVGSEGPLKGIQIWKVPATDTYSISGYGAAGGKGGKNTMMRSHGVSVLGIFNLEKDDMLYILVGQQGEDACPSTNQLIQKVCIGENNVIEEEIRVNRSVHEWAGGGGGGGGATYVFKMKDGVPVPLIIAAGGGGRAYGAKTDTFHPERLENNSSVLGLNGNSGAAGGGGGWNDNTSLLWAGKSLQEGATGGHSCPQAMKKWGWETRGGFGGGGGGCSSGGGGGGYIGGNAASNNDPEMDGEDGVSFISPLGILYTPALKVMEGHGEVNIKHYLNCSHCEVDECHMDPESHKVICFCDHGTVLAEDGVSCIVSPTPEPHLPLSLILSVVTSALVAALVLAFSGIMIVYRRKHQELQAMQMELQSPEYKLSKLRTSTIMTDYNPNYCFAGKTSSISDLKEVPRKNITLIRGLGHGAFGEVYEGQVSGMPNDPSPLQVAVKTLPEVCSEQDELDFLMEALIISKFNHQNIVRCIGVSLQSLPRFILLELMAGGDLKSFLRETRPRPSQPSSLAMLDLLHVARDIACGCQYLEENHFIHRDIAARNCLLTCPGPGRVAKIGDFGMARDIYRASYYRKGGCAMLPVKWMPPEAFMEGIFTSKTDTWSFGVLLWEIFSLGYMPYPSKSNQEVLEFVTSGGRMDPPKNCPGPVYRIMTQCWQHQPEDRPNFAIILERIEYCTQDPDVINTALPIEYGPLVEEEEKVPVRPKDPEGVPPLLVSQQAKREEERSPAAPPPLPTTSSGKAAKKPTAAEISVRVPRGPAVEGGHVNMAFSQSNPPSELHKVHGSRNKPTSLWNPTYGSWFTEKPTKKNNPIAKKEPHDRGNLGLEGSCTVPPNVATGRLPGASLLLEPSSLTANMKEVPLFRLRHFPCGNVNYGYQQQGLPLEAATAPGAGHYEDTILKSKNSMNQPGP,7.6777807052660805 +C[C@@]1(O)CCC[C@H]1n1c2nc(NC3CCN(CC3)S(C)(=O)=O)ncc2cc(CC#N)c1=O,MATSRYEPVAEIGVGAYGTVYKARDPHSGHFVALKSVRVPNGGGGGGGLPISTVREVALLRRLEAFEHPNVVRLMDVCATSRTDREIKVTLVFEHVDQDLRTYLDKAPPPGLPAETIKDLMRQFLRGLDFLHANCIVHRDLKPENILVTSGGTVKLADFGLARIYSYQMALTPVVVTLWYRAPEVLLQSTYATPVDMWSVGCIFAEMFRRKPLFCGNSEADQLGKIFDLIGLPPEDDWPRDVSLPRGAFPPRGPRPVQSVVPEMEESGAQLLLEMLTFNPHKRISAFRALQHSYLHKDEGNPE,9.468521082957745 +COc1ccccc1N1CCN(Cc2cn3ccccc3n2)CC1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,6.031517051446065 +CS(=O)(=O)NC(=O)c1ccc(c(OC(F)F)c1)-c1cnc(Oc2cccc3ccccc23)c(Cl)c1,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,7.2225731776106885 +Nc1ccc(cn1)-c1ccc(cc1F)-c1ccccc1S(=O)(=O)N1CCS(=O)(=O)CC1,MGIQGLAKLIADVAPSAIRENDIKSYFGRKVAIDASMSIYQFLIAVRQGGDVLQNEEGETTSHLMGMFYRTIRMMENGIKPVYVFDGKPPQLKSGELAKRSERRAEAEKQLQQAQAAGAEQEVEKFTKRLVKVTKQHNDECKHLLSLMGIPYLDAPSEAEASCAALVKAGKVYAAATEDMDCLTFGSPVLMRHLTASEAKKLPIQEFHLSRILQELGLNQEQFVDLCILLGSDYCESIRGIGPKRAVDLIQKHKSIEEIVRRLDPNKYPVPENWLHKEAHQLFLEPEVLDPESVELKWSEPNEEELIKFMCGEKQFSEERIRSGVKRLSKSRQGSTQGRLDDFFKVTGSLSSAKRKEPEPKGSTKKKAKTGAAGKFKRGK,7.431798275933005 +CCN(CC(=O)N1C[C@H](C)N(C[C@H]1C)c1ccc2[nH]c(c(C(C)C)c2n1)-c1cn2ncnc2c(C)c1C)C(C)C,MENMFLQSSMLTCIFLLISGSCELCAEENFSRSYPCDEKKQNDSVIAECSNRRLQEVPQTVGKYVTELDLSDNFITHITNESFQGLQNLTKINLNHNPNVQHQNGNPGIQSNGLNITDGAFLNLKNLRELLLEDNQLPQIPSGLPESLTELSLIQNNIYNITKEGISRLINLKNLYLAWNCYFNKVCEKTNIEDGVFETLTNLELLSLSFNSLSHVPPKLPSSLRKLFLSNTQIKYISEEDFKGLINLTLLDLSGNCPRCFNAPFPCVPCDGGASINIDRFAFQNLTQLRYLNLSSTSLRKINAAWFKNMPHLKVLDLEFNYLVGEIASGAFLTMLPRLEILDLSFNYIKGSYPQHINISRNFSKLLSLRALHLRGYVFQELREDDFQPLMQLPNLSTINLGINFIKQIDFKLFQNFSNLEIIYLSENRISPLVKDTRQSYANSSSFQRHIRKRRSTDFEFDPHSNFYHFTRPLIKPQCAAYGKALDLSLNSIFFIGPNQFENLPDIACLNLSANSNAQVLSGTEFSAIPHVKYLDLTNNRLDFDNASALTELSDLEVLDLSYNSHYFRIAGVTHHLEFIQNFTNLKVLNLSHNNIYTLTDKYNLESKSLVELVFSGNRLDILWNDDDNRYISIFKGLKNLTRLDLSLNRLKHIPNEAFLNLPASLTELHINDNMLKFFNWTLLQQFPRLELLDLRGNKLLFLTDSLSDFTSSLRTLLLSHNRISHLPSGFLSEVSSLKHLDLSSNLLKTINKSALETKTTTKLSMLELHGNPFECTCDIGDFRRWMDEHLNVKIPRLVDVICASPGDQRGKSIVSLELTTCVSDVTAVILFFFTFFITTMVMLAALAHHLFYWDVWFIYNVCLAKVKGYRSLSTSQTFYDAYISYDTKDASVTDWVINELRYHLEESRDKNVLLCLEERDWDPGLAIIDNLMQSINQSKKTVFVLTKKYAKSWNFKTAFYLALQRLMDENMDVIIFILLEPVLQHSQYLRLRQRICKSSILQWPDNPKAEGLFWQTLRNVVLTENDSRYNNMYVDSIKQY,8.657577319177793 +CN(CCC1CCN(CC1)C(=O)\C=C\c1ccc(Cl)cc1Cn1nnc(C)n1)C(=O)c1c[nH]c(=O)o1,MARRSSFQSCQIISLFTFAVGVNICLGFTAHRIKRAEGWEEGPPTVLSDSPWTNISGSCKGRCFELQEAGPPDCRCDNLCKSYTSCCHDFDELCLKTARGWECTKDRCGEVRNEENACHCSEDCLARGDCCTNYQVVCKGESHWVDDDCEEIKAAECPAGFVRPPLIIFSVDGFRASYMKKGSKVMPNIEKLRSCGTHSPYMRPVYPTKTFPNLYTLATGLYPESHGIVGNSMYDPVFDATFHLRGREKFNHRWWGGQPLWITATKQGVKAGTFFWSVVIPHERRILTILQWLTLPDHERPSVYAFYSEQPDFSGHKYGPFGPEMTNPLREIDKIVGQLMDGLKQLKLHRCVNVIFVGDHGMEDVTCDRTEFLSNYLTNVDDITLVPGTLGRIRSKFSNNAKYDPKAIIANLTCKKPDQHFKPYLKQHLPKRLHYANNRRIEDIHLLVERRWHVARKPLDVYKKPSGKCFFQGDHGFDNKVNSMQTVFVGYGSTFKYKTKVPPFENIELYNVMCDLLGLKPAPNNGTHGSLNHLLRTNTFRPTMPEEVTRPNYPGIMYLQSDFDLGCTCDDKVEPKNKLDELNKRLHTKGSTEERHLLYGRPAVLYRTRYDILYHTDFESGYSEIFLMPLWTSYTVSKQAEVSSVPDHLTSCVRPDVRVSPSFSQNCLAYKNDKQMSYGFLFPPYLSSSPEAKYDAFLVTNMVPMYPAFKRVWNYFQRVLVKKYASERNGVNVISGPIFDYDYDGLHDTEDKIKQYVEGSSIPVPTHYYSIITSCLDFTQPADKCDGPLSVSSFILPHRPDNEESCNSSEDESKWVEELMKMHTARVRDIEHLTSLDFFRKTSRSYPEILTLKTYLHTYESEI,8.050609993355087 +COc1ccc(NCc2cnc3nc(N)nc(N)c3c2C)cc1OC,MVGSLNCIVAVSQNMGIGKNGDLPWPPLRNEFRYFQRMTTTSSVEGKQNLVIMGKKTWFSIPEKNRPLKGRINLVLSRELKEPPQGAHFLSRSLDDALKLTEQPELANKVDMVWIVGGSSVYKEAMNHPGHLKLFVTRIMQDFESDTFFPEIDLEKYKLLPEYPGVLSDVQEEKGIKYKFEVYEKND,8.292429823902063 +Nc1cnc(cn1)-c1ccc(cc1F)-c1ccccc1-c1cnc(nc1)N1CCOCC1,MDQETVGNVVLLAIVTLISVVQNGFFAHKVEHESRTQNGRSFQRTGTLAFERVYTANQNCVDAYPTFLAVLWSAGLLCSQVPAAFAGLMYLFVRQKYFVGYLGERTQSTPGYIFGKRIILFLFLMSVAGIFNYYLIFFFGSDFENYIKTISTTISPLLLIP,7.423658649794207 +COc1ccc2cc(ccc2c1)-c1[nH]c(nc1-c1ccncc1)-c1ccccc1C(C)C,MDSLASLVLCGVSLLLSGTVEGAMDLILINSLPLVSDAETSLTCIASGWRPHEPITIGRDFEALMNQHQDPLEVTQDVTREWAKKVVWKREKASKINGAYFCEGRVRGEAIRIRTMKMRQQASFLPATLTMTVDKGDNVNISFKKVLIKEEDAVIYKNGSFIHSVPRHEVPDILEVHLPHAQPQDAGVYSARYIGGNLFTSAFTRLIVRRCEAQKWGPECNHLCTACMNNGVCHEDTGECICPPGFMGRTCEKACELHTFGRTCKERCSGQEGCKSYVFCLPDPYGCSCATGWKGLQCNEACHPGFYGPDCKLRCSCNNGEMCDRFQGCLCSPGWQGLQCEREGIQRMTPKIVDLPDHIEVNSGKFNPICKASGWPLPTNEEMTLVKPDGTVLHPKDFNHTDHFSVAIFTIHRILPPDSGVWVCSVNTVAGMVEKPFNISVKVLPKPLNAPNVIDTGHNFAVINISSEPYFGDGPIKSKKLLYKPVNHYEAWQHIQVTNEIVTLNYLEPRTEYELCVQLVRRGEGGEGHPGPVRRFTTASIGLPPPRGLNLLPKSQTTLNLTWQPIFPSSEDDFYVEVERRSVQKSDQQNIKVPGNLTSVLLNNLHPREQYVVRARVNTKAQGEWSEDLTAWTLSDILPPQPENIKISNITHSSAVISWTILDGYSISSITIRYKVQGKNEDQHVDVKIKNATITQYQLKGLEPETAYQVDIFAENNIGSSNPAFSHELVTLPESQAPADLGGGKMLLIAILGSAGMTCLTVLLAFLIILQLKRANVQRRMAQAFQNVREEPAVQFNSGTLALNRKVKNNPDPTIYPVLDWNDIKFQDVIGEGNFGQVLKARIKKDGLRMDAAIKRMKEYASKDDHRDFAGELEVLCKLGHHPNIINLLGACEHRGYLYLAIEYAPHGNLLDFLRKSRVLETDPAFAIANSTASTLSSQQLLHFAADVARGMDYLSQKQFIHRDLAARNILVGENYVAKIADFGLSRGQEVYVKKTMGRLPVRWMAIESLNYSVYTTNSDVWSYGVLLWEIVSLGGTPYCGMTCAELYEKLPQGYRLEKPLNCDDEVYDLMRQCWREKPYERPSFAQILVSLNRMLEERKTYVNTTLYEKFTYAGIDCSAEEAA,6.077793722560983 +Clc1ccc(NC(=O)Nc2ccc(s2)-c2ccccc2)cc1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,5.7544873321858505 +CC(=O)Nc1nc(C)nc2cn(nc12)-c1ccccc1,MPNNSTALSLANVTYITMEIFIGLCAIVGNVLVICVVKLNPSLQTTTFYFIVSLALADIAVGVLVMPLAIVVSLGITIHFYSCLFMTCLLLIFTHASIMSLLAIAVDRYLRVKLTVRYKRVTTHRRIWLALGLCWLVSFLVGLTPMFGWNMKLTSEYHRNVTFLSCQFVSVMRMDYMVYFSFLTWIFIPLVVMCAIYLDIFYIIRNKLSLNLSNSKETGAFYGREFKTAKSLFLVLFLFALSWLPLSIINCIIYFNGEVPQLVLYMGILLSHANSMMNPIVYAYKIKKFKETYLLILKACVVCHPSDSLDTSIEKNSE,6.522878745280337 +C[C@@H]1CC(CCN1C(=O)[C@H]1CC[C@H](N)CO1)NC(=O)c1cc(on1)C1CC1,MEPLKVEKFATAKRGNGLRAVTPLRPGELLFRSDPLAYTVCKGSRGVVCDRCLLGKEKLMRCSQCRVAKYCSAKCQKKAWPDHKRECKCLKSCKPRYPPDSVRLLGRVVFKLMDGAPSESEKLYSFYDLESNINKLTEDKKEGLRQLVMTFQHFMREEIQDASQLPPAFDLFEAFAKVICNSFTICNAEMQEVGVGLYPSISLLNHSCDPNCSIVFNGPHLLLRAVRDIEVGEELTICYLDMLMTSEERRKQLRDQYCFECDCFRCQTQDKDADMLTGDEQVWKEVQESLKKIEELKAHWKWEQVLAMCQAIISSNSERLPDINIYQLKVLDCAMDACINLGLLEEALFYGTRTMEPYRIFFPGSHPVRGVQVMKVGKLQLHQGMFPQAMKNLRLAFDIMRVTHGREHSLIEDLILLLEECDANIRAS,6.681936665037238 +COc1ccc(F)cc1C(C)(C)CC(O)(Cc1cc2cccc(F)c2[nH]1)C(F)(F)F,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,7.823908740944319 +Cc1nc2ccccc2n1[C@@H]1C[C@@H]2CC[C@H](C1)N2CCC1(CCN(CC1)C(C(O)=O)c1cccc(C)c1C)c1ccccc1,MDYQVSSPIYDINYYTSEPCQKINVKQIAARLLPPLYSLVFIFGFVGNMLVILILINCKRLKSMTDIYLLNLAISDLFFLLTVPFWAHYAAAQWDFGNTMCQLLTGLYFIGFFSGIFFIILLTIDRYLAVVHAVFALKARTVTFGVVTSVITWVVAVFASLPGIIFTRSQKEGLHYTCSSHFPYSQYQFWKNFQTLKIVILGLVLPLLVMVICYSGILKTLLRCRNEKKRHRAVRLIFTIMIVYFLFWAPYNIVLLLNTFQEFFGLNNCSSSNRLDQAMQVTETLGMTHCCINPIIYAFVGEKFRNYLLVFFQKHIAKRFCKCCSIFQQEAPERASSVYTRSTGEQEISVGL,8.522878745280337 +OC1(CCN(CCCC(=O)c2ccc(F)cc2)CC1)c1ccc(Cl)cc1,MVNLGNAVRSLLMHLIGLLVWQFDISISPVAAIVTDTFNSSDGGRLFQFPDGVQNWPALSIVVIIIMTIGGNILVIMAVSMEKKLHNATNYFLMSLAIADMLVGLLVMPLSLLAILYDYVWPLPRYLCPVWISLDVLFSTASIMHLCAISLDRYVAIRNPIEHSRFNSRTKAIMKIAIVWAISIGVSVPIPVIGLRDESKVFVNNTTCVLNDPNFVLIGSFVAFFIPLTIMVITYFLTIYVLRRQTLMLLRGHTEEELANMSLNFLNCCCKKNGGEEENAPNPNPDQKPRRKKKEKRPRGTMQAINNEKKASKVLGIVFFVFLIMWCPFFITNILSVLCGKACNQKLMEKLLNVFVWIGYVCSGINPLVYTLFNKIYRRAFSKYLRCDYKPDKKPPVRQIPRVAATALSGRELNVNIYRHTNERVARKANDPEPGIEMQVENLELPVNPSNVVSERISSV,5.600001111982079 +CCNc1cc(ncc1-c1cn(C[C@H](C)O)nn1)-n1ncc2cc(cnc12)C#N,MNKPITPSTYVRCLNVGLIRKLSDFIDPQEGWKKLAVAIKKPSGDDRYNQFHIRRFEALLQTGKSPTSELLFDWGTTNCTVGDLVDLLIQNEFFAPASLLLPDAVPKTANTLPSKEAITVQQKQMPFCDKDRTLMTPVQNLEQSYMPPDSSSPENKSLEVSDTRFHSFSFYELKNVTNNFDERPISVGGNKMGEGGFGVVYKGYVNNTTVAVKKLAAMVDITTEELKQQFDQEIKVMAKCQHENLVELLGFSSDGDDLCLVYVYMPNGSLLDRLSCLDGTPPLSWHMRCKIAQGAANGINFLHENHHIHRDIKSANILLDEAFTAKISDFGLARASEKFAQTVMTSRIVGTTAYMAPEALRGEITPKSDIYSFGVVLLEIITGLPAVDEHREPQLLLDIKEEIEDEEKTIEDYIDKKMNDADSTSVEAMYSVASQCLHEKKNKRPDIKKVQQLLQEMTAS,7.3979400086720375 +COc1cc(CCc2cc(Nc3ccnc(NCc4cc(C)no4)n3)[nH]n2)cc(OC)c1,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,7.100015437450609 +COC(=O)[C@H](CCCCN)n1cc(nn1)-c1cc(cc(c1)-c1cn(nn1)[C@@H](Cc1c[nH]c2ccccc12)C(=O)OC)C(=O)N1CCNCC1,MDLAVGPGAAGPSNVPAFLTKLWTLVSDPDTDALICWSPSGNSFHVFDQGQFAKEVLPKYFKHNNMASFVRQLNMYGFRKVVHIEQGGLVKPERDDTEFQHPCFLRGQEQLLENIKRKVTSVSTLKSEDIKIRQDSVTRLLTDVQLMKGKQECMDSKLLAMKHENEALWREVASLRQKHAQQQKVVNKLIQFLISLVQSNRILGVKRKIPLMLSDSNSAHSVPKYGRQYSLEHVHGPGPYSAPSPAYSSSSLYSSDAVTSSGPIISDITELAPTSPLASPGRSIDERPLSSSTLVRVKQEPPSPPHSPRVLEASPGRPSSMDTPLSPTAFIDSILRESEPTPAASNTAPMDTTGAQAPALPTPSTPEKCLSVACLDKNELSDHLDAMDSNLDNLQTMLTSHGFSVDTSALLDLFSPSVTMPDMSLPDLDSSLASIQELLSPQEPPRPIEAENSNPDSGKQLVHYTAQPLFLLDPDAVDTGSSELPVLFELGESSYFSEGDDYTDDPTISLLTGTEPHKAKDPTVS,3.7099653886374817 +OC(CN1[C@H]2CC[C@@H]1C[C@@H](C2)OC1c2ccccc2CCc2ccccc12)c1ccccc1,MARRCGPVALLLGFGLLRLCSGVWGTDTEERLVEHLLDPSRYNKLIRPATNGSELVTVQLMVSLAQLISVHEREQIMTTNVWLTQEWEDYRLTWKPEEFDNMKKVRLPSKHIWLPDVVLYNNADGMYEVSFYSNAVVSYDGSIFWLPPAIYKSACKIEVKHFPFDQQNCTMKFRSWTYDRTEIDLVLKSEVASLDDFTPSGEWDIVALPGRRNENPDDSTYVDITYDFIIRRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTVFLLLISKIVPPTSLDVPLVGKYLMFTMVLVTFSIVTSVCVLNVHHRSPTTHTMAPWVKVVFLEKLPALLFMQQPRHHCARQRLRLRRRQREREGAGALFFREAPGADSCTCFVNRASVQGLAGAFGAEPAPVAGPGRSGEPCGCGLREAVDGVRFIADHMRSEDDDQSVSEDWKYVAMVIDRLFLWIFVFVCVFGTIGMFLQPLFQNYTTTTFLHSDHSAPSSK,4.499999953328896 +CCc1ccc(Nc2ncnc3cc(NC(=O)CCCCCCC(=O)NO)sc23)cc1,MTSTGQDSTTTRQRRSRQNPQSPPQDSSVTSKRNIKKGAVPRSIPNLAEVKKKGKMKKLGQAMEEDLIVGLQGMDLNLEAEALAGTGLVLDEQLNEFHCLWDDSFPEGPERLHAIKEQLIQEGLLDRCVSFQARFAEKEELMLVHSLEYIDLMETTQYMNEGELRVLADTYDSVYLHPNSYSCACLASGSVLRLVDAVLGAEIRNGMAIIRPPGHHAQHSLMDGYCMFNHVAVAARYAQQKHRIRRVLIVDWDVHHGQGTQFTFDQDPSVLYFSIHRYEQGRFWPHLKASNWSTTGFGQGQGYTINVPWNQVGMRDADYIAAFLHVLLPVALEFQPQLVLVAAGFDALQGDPKGEMAATPAGFAQLTHLLMGLAGGKLILSLEGGYNLRALAEGVSASLHTLLGDPCPMLESPGAPCRSAQASVSCALEALEPFWEVLVRSTETVERDNMEEDNVEESEEEGPWEPPVLPILTWPVLQSRTGLVYDQNMMNHCNLWDSHHPEVPQRILRIMCRLEELGLAGRCLTLTPRPATEAELLTCHSAEYVGHLRATEKMKTRELHRESSNFDSIYICPSTFACAQLATGAACRLVEAVLSGEVLNGAAVVRPPGHHAEQDAACGFCFFNSVAVAARHAQTISGHALRILIVDWDVHHGNGTQHMFEDDPSVLYVSLHRYDHGTFFPMGDEGASSQIGRAAGTGFTVNVAWNGPRMGDADYLAAWHRLVLPIAYEFNPELVLVSAGFDAARGDPLGGCQVSPEGYAHLTHLLMGLASGRIILILEGGYNLTSISESMAACTRSLLGDPPPLLTLPRPPLSGALASITETIQVHRRYWRSLRVMKVEDREGPSSSKLVTKKAPQPAKPRLAERMTTREKKVLEAGMGKVTSASFGEESTPGQTNSETAVVALTQDQPSEAATGGATLAQTISEAAIGGAMLGQTTSEEAVGGATPDQTTSEETVGGAILDQTTSEDAVGGATLGQTTSEEAVGGATLAQTTSEAAMEGATLDQTTSEEAPGGTELIQTPLASSTDHQTPPTSPVQGTTPQISPSTLIGSLRTLELGSESQGASESQAPGEENLLGEAAGGQDMADSMLMQGSRGLTDQAIFYAVTPLPWCPHLVAVCPIPAAGLDVTQPCGDCGTIQENWVCLSCYQVYCGRYINGHMLQHHGNSGHPLVLSYIDLSAWCYYCQAYVHHQALLDVKNIAHQNKFGEDMPHPH,7.008773924307505 +CC(C)C[C@@H]1NC(=O)[C@H](CCCC(O)=O)NC(=O)CSC[C@H](NC(=O)CCCCNC(=O)[C@H](CC(N)=O)NC(=O)[C@](C)(CCC(O)=O)NC(=O)[C@H](Cc2ccc(O)cc2)NC1=O)C(N)=O,MEAIAKYDFKATADDELSFKRGDILKVLNEECDQNWYKAELNGKDGFIPKNYIEMKPHPWFFGKIPRAKAEEMLSKQRHDGAFLIRESESAPGDFSLSVKFGNDVQHFKVLRDGAGKYFLWVVKFNSLNELVDYHRSTSVSRNQQIFLRDIEQVPQQPTYVQALFDFDPQEDGELGFRRGDFIHVMDNSDPNWWKGACHGQTGMFPRNYVTPVNRNV,4.154901959985743 +Cc1cncn1CCCN1Cc2ccccc2NC1=S,MAGGRHRRVVGTLHLLLLVAALPWASRGVSPSASAWPEEKNYHQPAILNSSALRQIAEGTSISEMWQNDLQPLLIERYPGSPGSYAARQHIMQRIQRLQADWVLEIDTFLSQTPYGYRSFSNIISTLNPTAKRHLVLACHYDSKYFSHWNNRVFVGATDSAVPCAMMLELARALDKKLLSLKTVSDSKPDLSLQLIFFDGEEAFLHWSPQDSLYGSRHLAAKMASTPHPPGARGTSQLHGMDLLVLLDLIGAPNPTFPNFFPNSARWFERLQAIEHELHELGLLKDHSLEGRYFQNYSYGGVIQDDHIPFLRRGVPVLHLIPSPFPEVWHTMDDNEENLDESTIDNLNKILQVFVLEYLHL,7.7447274948966935 +COc1cc2c(cc1Cl)c(nn(CC(=O)N(C)c1ccc3nc(C)oc3c1)c2=O)-c1cccc(Cl)c1,MQRSPLEKASVVSKLFFSWTRPILRKGYRQRLELSDIYQIPSVDSADNLSEKLEREWDRELASKKNPKLINALRRCFFWRFMFYGIFLYLGEVTKAVQPLLLGRIIASYDPDNKEERSIAIYLGIGLCLLFIVRTLLLHPAIFGLHHIGMQMRIAMFSLIYKKTLKLSSRVLDKISIGQLVSLLSNNLNKFDEGLALAHFVWIAPLQVALLMGLIWELLQASAFCGLGFLIVLALFQAGLGRMMMKYRDQRAGKISERLVITSEMIENIQSVKAYCWEEAMEKMIENLRQTELKLTRKAAYVRYFNSSAFFFSGFFVVFLSVLPYALIKGIILRKIFTTISFCIVLRMAVTRQFPWAVQTWYDSLGAINKIQDFLQKQEYKTLEYNLTTTEVVMENVTAFWEEGFGELFEKAKQNNNNRKTSNGDDSLFFSNFSLLGTPVLKDINFKIERGQLLAVAGSTGAGKTSLLMVIMGELEPSEGKIKHSGRISFCSQFSWIMPGTIKENIIGVSYDEYRYRSVIKACQLEEDISKFAEKDNIVLGEGGITLSGGQRARISLARAVYKDADLYLLDSPFGYLDVLTEKEIFESCVCKLMANKTRILVTSKMEHLKKADKILILHEGSSYFYGTFSELQNLQPDFSSKLMGCDSFDQFSAERRNSILTETLHRFSLEGDAPVSWTETKKQSFKQTGEFGEKRKNSILNPINSIRKFSIVQKTPLQMNGIEEDSDEPLERRLSLVPDSEQGEAILPRISVISTGPTLQARRRQSVLNLMTHSVNQGQNIHRKTTASTRKVSLAPQANLTELDIYSRRLSQETGLEISEEINEEDLKECFFDDMESIPAVTTWNTYLRYITVHKSLIFVLIWCLVIFLAEVAASLVVLWLLGNTPLQDKGNSTHSRNNSYAVIITSTSSYYVFYIYVGVADTLLAMGFFRGLPLVHTLITVSKILHHKMLHSVLQAPMSTLNTLKAGGILNRFSKDIAILDDLLPLTIFDFIQLLLIVIGAIAVVAVLQPYIFVATVPVIVAFIMLRAYFLQTSQQLKQLESEGRSPIFTHLVTSLKGLWTLRAFGRQPYFETLFHKALNLHTANWFLYLSTLRWFQMRIEMIFVIFFIAVTFISILTTGEGEGRVGIILTLAMNIMSTLQWAVNSSIDVDSLMRSVSRVFKFIDMPTEGKPTKSTKPYKNGQLSKVMIIENSHVKKDDIWPSGGQMTVKDLTAKYTEGGNAILENISFSISPGQRVGLLGRTGSGKSTLLSAFLRLLNTEGEIQIDGVSWDSITLQQWRKAFGVIPQKVFIFSGTFRKNLDPYEQWSDQEIWKVADEVGLRSVIEQFPGKLDFVLVDGGCVLSHGHKQLMCLARSVLSKAKILLLDEPSAHLDPVTYQIIRRTLKQAFADCTVILCEHRIEAMLECQQFLVIEENKVRQYDSIQKLLNERSLFRQAISPSDRVKLFPHRNSSKCKSKPQIAALKEETEEEVQDTRL,5.0 +OC1COCc2c1cncc2-c1ccc2NC(=O)CCc2c1,MALRAKAEVCVAAPWLSLQRARALGTRAARAPRTVLPFEAMPQHPGNRWLRLLQIWREQGYEHLHLEMHQTFQELGPIFRYNLGGPRMVCVMLPEDVEKLQQVDSLHPCRMILEPWVAYRQHRGHKCGVFLLNGPEWRFNRLRLNPDVLSPKAVQRFLPMVDAVARDFSQALKKKVLQNARGSLTLDVQPSIFHYTIEASNLALFGERLGLVGHSPSSASLNFLHALEVMFKSTVQLMFMPRSLSRWISPKVWKEHFEAWDCIFQYGDNCIQKIYQELAFNRPQHYTGIVAELLLKAELSLEAIKANSMELTAGSVDTTAFPLLMTLFELARNPDVQQILRQESLAAAASISEHPQKATTELPLLRAALKETLRLYPVGLFLERVVSSDLVLQNYHIPAGTLVQVFLYSLGRNAALFPRPERYNPQRWLDIRGSGRNFHHVPFGFGMRQCLGRRLAEAEMLLLLHHVLKHFLVETLTQEDIKMVYSFILRPGTSPLLTFRAIN,6.995678626217357 +CCc1nc2c(C)cc(C)nc2n1Cc1ccc(cc1)-c1ccsc1-c1nnn[nH]1,MKDNFSFAATSRNITSSLPFDNLNATGTNESAFNCSHKPADKHLEAIPVLYYMIFVIGFAVNIVVVSLFCCQKGPKKVSSIYIFNLAVADLLLLATLPLWATYYSYRYDWLFGPVMCKVFGSFLTLNMFASIFFITCMSVDRYQSVIYPFLSQRRNPWQASYVVPLVWCMACLSSLPTFYFRDVRTIEYLGVNACIMAFPPEKYAQWSAGIALMKNILGFIIPLIFIATCYFGIRKHLLKTNSYGKNRITRDQVLKMAAAVVLAFIICWLPFHVLTFLDALTWMGIINSCEVIAVIDLALPFAILLGFTNSCVNPFLYCFVGNRFQQKLRSVFRVPITWLQGKRETMSCRKSSSLREMDTFVS,7.522878745280337 +C[C@@H]1CC[C@H](CN1C(=O)c1cccc(F)c1-n1nccn1)Oc1cc(ccn1)C#N,MSGTKLEDSPPCRNWSSASELNETQEPFLNPTDYDDEEFLRYLWREYLHPKEYEWVLIAGYIIVFVVALIGNVLVCVAVWKNHHMRTVTNYFIVNLSLADVLVTITCLPATLVVDITETWFFGQSLCKVIPYLQTVSVSVSVLTLSCIALDRWYAICHPLMFKSTAKRARNSIVIIWIVSCIIMIPQAIVMECSTVFPGLANKTTLFTVCDERWGGEIYPKMYHICFFLVTYMAPLCLMVLAYLQIFRKLWCRQIPGTSSVVQRKWKPLQPVSQPRGPGQPTKSRMSAVAAEIKQIRARRKTARMLMIVLLVFAICYLPISILNVLKRVFGMFAHTEDRETVYAWFTFSHWLVYANSAANPIIYNFLSGKFREEFKAAFSCCCLGVHHRQEDRLTRGRTSTESRKSLTTQISNFDNISKLSEQVVLTSISTLPAANGAGPLQNW,8.259637310505756 +COc1cccc2C(CNCCCc3ccccc3)CCOc12,MDVLSPGQGNNTTSPPAPFETGGNTTGISDVTVSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVKKVEKTGADTRHGASPAPQPKKSVNGESGSRNWRLGVESKAGGALCANGAVRQGDDGAALEVIEVHRVGNSKEHLPLPSEAGPTPCAPASFERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPTLLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRQ,8.154901959985743 +CC(C)c1c([nH]c2ccc(nc12)N1CCN(C)CC1)-c1cn2ncnc2c(C)c1C,MVFPMWTLKRQILILFNIILISKLLGARWFPKTLPCDVTLDVPKNHVIVDCTDKHLTEIPGGIPTNTTNLTLTINHIPDISPASFHRLDHLVEIDFRCNCVPIPLGSKNNMCIKRLQIKPRSFSGLTYLKSLYLDGNQLLEIPQGLPPSLQLLSLEANNIFSIRKENLTELANIEILYLGQNCYYRNPCYVSYSIEKDAFLNLTKLKVLSLKDNNVTAVPTVLPSTLTELYLYNNMIAKIQEDDFNNLNQLQILDLSGNCPRCYNAPFPCAPCKNNSPLQIPVNAFDALTELKVLRLHSNSLQHVPPRWFKNINKLQELDLSQNFLAKEIGDAKFLHFLPSLIQLDLSFNFELQVYRASMNLSQAFSSLKSLKILRIRGYVFKELKSFNLSPLHNLQNLEVLDLGTNFIKIANLSMFKQFKRLKVIDLSVNKISPSGDSSEVGFCSNARTSVESYEPQVLEQLHYFRYDKYARSCRFKNKEASFMSVNESCYKYGQTLDLSKNSIFFVKSSDFQHLSFLKCLNLSGNLISQTLNGSEFQPLAELRYLDFSNNRLDLLHSTAFEELHKLEVLDISSNSHYFQSEGITHMLNFTKNLKVLQKLMMNDNDISSSTSRTMESESLRTLEFRGNHLDVLWREGDNRYLQLFKNLLKLEELDISKNSLSFLPSGVFDGMPPNLKNLSLAKNGLKSFSWKKLQCLKNLETLDLSHNQLTTVPERLSNCSRSLKNLILKNNQIRSLTKYFLQDAFQLRYLDLSSNKIQMIQKTSFPENVLNNLKMLLLHHNRFLCTCDAVWFVWWVNHTEVTIPYLATDVTCVGPGAHKGQSVISLDLYTCELDLTNLILFSLSISVSLFLMVMMTASHLYFWDVWYIYHFCKAKIKGYQRLISPDCCYDAFIVYDTKDPAVTEWVLAELVAKLEDPREKHFNLCLEERDWLPGQPVLENLSQSIQLSKKTVFVMTDKYAKTENFKIAFYLSHQRLMDEKVDVIILIFLEKPFQKSKFLQLRKRLCGSSVLEWPTNPQAHPYFWQCLKNALATDNHVAYSQVFKETV,8.823908740944319 +Nc1nccc2cc(CNC(=O)c3cncc(Cc4ccnc(c4)N4CCCC4CO)c3)ccc12,MWFLVLCLALSLGGTGAAPPIQSRIVGGWECEQHSQPWQAALYHFSTFQCGGILVHRQWVLTAAHCISDNYQLWLGRHNLFDDENTAQFVHVSESFPHPGFNMSLLENHTRQADEDYSHDLMLLRLTEPADTITDAVKVVELPTEEPEVGSTCLASGWGSIEPENFSFPDDLQCVDLKILPNDECKKAHVQKVTDFMLCVGHLEGGKDTCVGDSGGPLMCDGVLQGVTSWGYVPCGTPNKPSVAVRVLSYVKWIEDTIAENS,5.315154638355588 +COc1ccc(cc1)C(=O)Nc1ccc(-c2ccccc2)n(CC(=O)NC(C(C)C)C(=O)C(F)(F)F)c1=O,MTLGRRLACLFLACVLPALLLGGTALASEIVGGRRARPHAWPFMVSLQLRGGHFCGATLIAPNFVMSAAHCVANVNVRAVRVVLGAHNLSRREPTRQVFAVQRIFENGYDPVNLLNDIVILQLNGSATINANVQVAQLPAQGRRLGNGVQCLAMGWGLLGRNRGIASVLQELNVTVVTSLCRRSNVCTLVRGRQAGVCFGDSGSPLVCNGLIHGIASFVRGGCASGLYPDAFAPVAQFVNWIDSIIQRSEDNPCPHPRDPDPASRTH,6.318758762624412 +Cc1nc2cc(nn2c(C)c1C(=O)NCC(C)(C)NCC(=O)N1CCC[C@H]1C#N)-c1ccccc1,MKTPWKVLLGLLGAAALVTIITVPVVLLNKGTDDATADSRKTYTLTDYLKNTYRLKLYSLRWISDHEYLYKQENNILVFNAEYGNSSVFLENSTFDEFGHSINDYSISPDGQFILLEYNYVKQWRHSYTASYDIYDLNKRQLITEERIPNNTQWVTWSPVGHKLAYVWNNDIYVKIEPNLPSYRITWTGKEDIIYNGITDWVYEEEVFSAYSALWWSPNGTFLAYAQFNDTEVPLIEYSFYSDESLQYPKTVRVPYPKAGAVNPTVKFFVVNTDSLSSVTNATSIQITAPASMLIGDHYLCDVTWATQERISLQWLRRIQNYSVMDICDYDESSGRWNCLVARQHIEMSTTGWVGRFRPSEPHFTLDGNSFYKIISNEEGYRHICYFQIDKKDCTFITKGTWEVIGIEALTSDYLYYISNEYKGMPGGRNLYKIQLSDYTKVTCLSCELNPERCQYYSVSFSKEAKYYQLRCSGPGLPLYTLHSSVNDKGLRVLEDNSALDKMLQNVQMPSKKLDFIILNETKFWYQMILPPHFDKSKKYPLLLDVYAGPCSQKADTVFRLNWATYLASTENIIVASFDGRGSGYQGDKIMHAINRRLGTFEVEDQIEAARQFSKMGFVDNKRIAIWGWSYGGYVTSMVLGSGSGVFKCGIAVAPVSRWEYYDSVYTERYMGLPTPEDNLDHYRNSTVMSRAENFKQVEYLLIHGTADDNVHFQQSAQISKALVDVGVDFQAMWYTDEDHGIASSTAHQHIYTHMSHFIKQCFSLP,7.552841968657781 +Cc1cccc(n1)-n1nccc1-c1ccc2ncn(C)c(=O)c2c1,MTLGSPRKGLLMLLMALVTQGDPVKPSRGPLVTCTCESPHCKGPTCRGAWCTVVLVREEGRHPQEHRGCGNLHRELCRGRPTEFVNHYCCDSHLCNHNVSLVLEATQPPSEQPGTDGQLALILGPVLALLALVALGVLGLWHVRRRQEKQRGLHSELGESSLILKASEQGDSMLGDLLDSDCTTGSGSGLPFLVQRTVARQVALVECVGKGRYGEVWRGLWHGESVAVKIFSSRDEQSWFRETEIYNTVLLRHDNILGFIASDMTSRNSSTQLWLITHYHEHGSLYDFLQRQTLEPHLALRLAVSAACGLAHLHVEIFGTQGKPAIAHRDFKSRNVLVKSNLQCCIADLGLAVMHSQGSDYLDIGNNPRVGTKRYMAPEVLDEQIRTDCFESYKWTDIWAFGLVLWEIARRTIVNGIVEDYRPPFYDVVPNDPSFEDMKKVVCVDQQTPTIPNRLAADPVLSGLAQMMRECWYPNPSARLTALRIKKTLQKISNSPEKPKVIQ,5.301029995663981 +NCCS(=O)(=O)c1ccc(-c2cccc(NC(=O)[C@H](N)CO)c2)c(-c2nn[nH]n2)c1S(N)(=O)=O,MLKVISSLLVYMTASVMAVASPLAHSGEPSGEYPTVNEIPVGEVRLYQIADGVWSHIATQSFDGAVYPSNGLIVRDGDELLLIDTAWGAKNTAALLAEIEKQIGLPVTRAVSTHFHDDRVGGVDVLRAAGVATYASPSTRRLAEAEGNEIPTHSLEGLSSSGDAVRFGPVELFYPGAAHSTDNLVVYVPSANVLYGGCAVHELSSTSAGNVADADLAEWPTSVERIQKHYPEAEVVIPGHGLPGGLDLLQHTANVVKAHKNRSVAE,9.297569463554474 +COc1c(OCCF)cccc1C(O)C1CCN(CCc2ccc(cc2)[N+]([O-])=O)CC1,MEEPGAQCAPPPPAGSETWVPQANLSSAPSQNCSAKDYIYQDSISLPWKVLLVMLLALITLATTLSNAFVIATVYRTRKLHTPANYLIASLAVTDLLVSILVMPISTMYTVTGRWTLGQVVCDFWLSSDITCCTASILHLCVIALDRYWAITDAVEYSAKRTPKRAAVMIALVWVFSISISLPPFFWRQAKAEEEVSECVVNTDHILYTVYSTVGAFYFPTLLLIALYGRIYVEARSRILKQTPNRTGKRLTRAQLITDSPGSTSSVTSINSRVPDVPSESGSPVYVNQVKVRVSDALLEKKKLMAARERKATKTLGIILGAFIVCWLPFFIISLVMPICKDACWFHLAIFDFFTWLGYLNSLINPIIYTMSNEDFKQAFHKLIRFKCTS,5.0 +N[C@@H](Cc1ccc(cc1)C(=O)NCCc1ccc(cc1)-c1ccccc1)C(=O)N1Cc2ccccc2C[C@H]1C(O)=O,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,5.6439741428068775 +COc1ccc(CN(C)C)c(c1)-c1cc2c(Nc3ccc4[nH]ccc4c3C)c(cnc2s1)C#N,MSSGTMKFNGYLRVRIGEAVGLQPTRWSLRHSLFKKGHQLLDPYLTVSVDQVRVGQTSTKQKTNKPTYNEEFCANVTDGGHLELAVFHETPLGYDHFVANCTLQFQELLRTTGASDTFEGWVDLEPEGKVFVVITLTGSFTEATLQRDRIFKHFTRKRQRAMRRRVHQINGHKFMATYLRQPTYCSHCREFIWGVFGKQGYQCQVCTCVVHKRCHHLIVTACTCQNNINKVDSKIAEQRFGINIPHKFSIHNYKVPTFCDHCGSLLWGIMRQGLQCKICKMNVHIRCQANVAPNCGVNAVELAKTLAGMGLQPGNISPTSKLVSRSTLRRQGKESSKEGNGIGVNSSNRLGIDNFEFIRVLGKGSFGKVMLARVKETGDLYAVKVLKKDVILQDDDVECTMTEKRILSLARNHPFLTQLFCCFQTPDRLFFVMEFVNGGDLMFHIQKSRRFDEARARFYAAEIISALMFLHDKGIIYRDLKLDNVLLDHEGHCKLADFGMCKEGICNGVTTATFCGTPDYIAPEILQEMLYGPAVDWWAMGVLLYEMLCGHAPFEAENEDDLFEAILNDEVVYPTWLHEDATGILKSFMTKNPTMRLGSLTQGGEHAILRHPFFKEIDWAQLNHRQIEPPFRPRIKSREDVSNFDPDFIKEEPVLTPIDEGHLPMINQDEFRNFSYVSPELQP,3.4436974992327127 +COc1cc(cc(C=O)c1O)-c1ccncc1,MPARRLLLLLTLLLPGLGIFGSTSTVTLPETLLFVSTLDGSLHAVSKRTGSIKWTLKEDPVLQVPTHVEEPAFLPDPNDGSLYTLGSKNNEGLTKLPFTIPELVQASPCRSSDGILYMGKKQDIWYVIDLLTGEKQQTLSSAFADSLCPSTSLLYLGRTEYTITMYDTKTRELRWNATYFDYAASLPEDDVDYKMSHFVSNGDGLVVTVDSESGDVLWIQNYASPVVAFYVWQREGLRKVMHINVAVETLRYLTFMSGEVGRITKWKYPFPKETEAKSKLTPTLYVGKYSTSLYASPSMVHEGVAVVPRGSTLPLLEGPQTDGVTIGDKGECVITPSTDVKFDPGLKSKNKLNYLRNYWLLIGHHETPLSASTKMLERFPNNLPKHRENVIPADSEKKSFEEVINLVDQTSENAPTTVSRDVEEKPAHAPARPEAPVDSMLKDMATIILSTFLLIGWVAFIITYPLSMHQQQQLQHQQFQKELEKIQLLQQQQQQLPFHPPGDTAQDGELLDTSGPYSESSGTSSPSTSPRASNHSLCSGSSASKAGSSPSLEQDDGDEETSVVIVGKISFCPKDVLGHGAEGTIVYRGMFDNRDVAVKRILPECFSFADREVQLLRESDEHPNVIRYFCTEKDRQFQYIAIELCAATLQEYVEQKDFAHLGLEPITLLQQTTSGLAHLHSLNIVHRDLKPHNILISMPNAHGKIKAMISDFGLCKKLAVGRHSFSRRSGVPGTEGWIAPEMLSEDCKENPTYTVDIFSAGCVFYYVISEGSHPFGKSLQRQANILLGACSLDCLHPEKHEDVIARELIEKMIAMDPQKRPSAKHVLKHPFFWSLEKQLQFFQDVSDRIEKESLDGPIVKQLERGGRAVVKMDWRENITVPLQTDLRKFRTYKGGSVRDLLRAMRNKKHHYRELPAEVRETLGSLPDDFVCYFTSRFPHLLAHTYRAMELCSHERLFQPYYFHEPPEPQPPVTPDAL,6.982966660701219 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+CC1(N)CCN(CC1)c1cccnc1NC(=O)c1nc(cnc1N)-c1nc(nc2ccccc12)N1CCOCC1,MADVFPGNDSTASQDVANRFARKGALRQKNVHEVKDHKFIARFFKQPTFCSHCTDFIWGFGKQGFQCQVCCFVVHKRCHEFVTFSCPGADKGPDTDDPRSKHKFKIHTYGSPTFCDHCGSLLYGLIHQGMKCDTCDMNVHKQCVINVPSLCGMDHTEKRGRIYLKAEVADEKLHVTVRDAKNLIPMDPNGLSDPYVKLKLIPDPKNESKQKTKTIRSTLNPQWNESFTFKLKPSDKDRRLSVEIWDWDRTTRNDFMGSLSFGVSELMKMPASGWYKLLNQEEGEYYNVPIPEGDEEGNMELRQKFEKAKLGPAGNKVISPSEDRKQPSNNLDRVKLTDFNFLMVLGKGSFGKVMLADRKGTEELYAIKILKKDVVIQDDDVECTMVEKRVLALLDKPPFLTQLHSCFQTVDRLYFVMEYVNGGDLMYHIQQVGKFKEPQAVFYAAEISIGLFFLHKRGIIYRDLKLDNVMLDSEGHIKIADFGMCKEHMMDGVTTRTFCGTPDYIAPEIIAYQPYGKSVDWWAYGVLLYEMLAGQPPFDGEDEDELFQSIMEHNVSYPKSLSKEAVSVCKGLMTKHPAKRLGCGPEGERDVREHAFFRRIDWEKLENREIQPPFKPKVCGKGAENFDKFFTRGQPVLTPPDQLVIANIDQSDFEGFSYVNPQFVHPILQSAV,9.886056647693163 +CN1CCC(CCNc2ccc(cn2)[S+]([O-])(=O)Nc2c(C)nn(C)c2C)CC1,MSDSKDRKGKAPEGQSSEKKDGAVNITPQMAESLLENNPALRNETAGMDKDKAAEAMRKMNIAELLTGLSVSGKNQKDMASYKFWQTQPVPRFDETSTDTGGPIKIIDPEKVSKEPDALLEGFEWATLDLTNETELQELWDLLTYHYVEDDNAMFRFRYSQSFLHWALMSPGWKKEWHVGVRATKSRKLVASICGVPTEINVRNQKLKVVEINFLCIHKKLRSKRLTPVLIKEITRRCYLNGIYQAIYTAGVVLPTPVSSCRYYHRPLDWLKLYEVGFSPLPAGSTKARQITKNHLPSTTSTPGLRPMEPKDIDTVHDLLQRYLSRFALNQAFTREEVDHWLVHKPETVKEQVVWAYVVEDPETHKITDFFSFYNLESTVIQNPKHDNVRAAYLYYYATETAFTNNMKALKERLLMLMNDALILAKKAHFDVFNALTLHDNPLFLEQLKFGAGDGQLHFYLYNYRTAPVPGGVNEKNLPDEKRMGGVGIVML,5.823908740944319 +Cc1ccc(cc1)C1(O)OC(=O)C(=C1Cc1ccccc1)c1ccc2OCOc2c1,METLCLRASFWLALVGCVISDNPERYSTNLSNHVDDFTTFRGTELSFLVTTHQPTNLVLPSNGSMHNYCPQQTKITSAFKYINTVISCTIFIVGMVGNATLLRIIYQNKCMRNGPNALIASLALGDLIYVVIDLPINVFKLLAGRWPFDHNDFGVFLCKLFPFLQKSSVGITVLNLCALSVDRYRAVASWSRVQGIGIPLVTAIEIVSIWILSFILAIPEAIGFVMVPFEYRGEQHKTCMLNATSKFMEFYQDVKDWWLFGFYFCMPLVCTAIFYTLMTCEMLNRRNGSLRIALSEHLKQRREVAKTVFCLVVIFALCWFPLHLSRILKKTVYNEMDKNRCELLSFLLLMDYIGINLATMNSCINPIALYFVSKKFKNCFQSCLCCCCYQSKSLMTSVPMNGTSIQWKNHDQNNHNTDRSSHKDSMN,5.309803919971486 +OC(Cn1ccc2ccccc12)Cn1cnc2ccccc12,MAAGTAVGAWVLVLSLWGAVVGAQNITARIGEPLVLKCKGAPKKPPQRLEWKLNTGRTEAWKVLSPQGGGPWDSVARVLPNGSLFLPAVGIQDEGIFRCQAMNRNGKETKSNYRVRVYQIPGKPEIVDSASELTAGVPNKVGTCVSEGSYPAGTLSWHLDGKPLVPNEKGVSVKEQTRRHPETGLFTLQSELMVTPARGGDPRPTFSCSFSPGLPRHRALRTAPIQPRVWEPVPLEEVQLVVEPEGGAVAPGGTVTLTCEVPAQPSPQIHWMKDGVPLPLPPSPVLILPEIGPQDQGTYSCVATHSSHGPQESRAVSISIIEPGEEGPTAGSVGGSGLGTLALALGILGGLGTAALLIGVILWQRRQRRGEERKAPENQEEEEERAELNQSEEPEAGESSTGGP,8.698970004336019 +COc1cccc(CN2CCCn3c2nc2n(C)c(=O)n(CC#C)c(=O)c32)c1,MPNNSTALSLANVTYITMEIFIGLCAIVGNVLVICVVKLNPSLQTTTFYFIVSLALADIAVGVLVMPLAIVVSLGITIHFYSCLFMTCLLLIFTHASIMSLLAIAVDRYLRVKLTVRYKRVTTHRRIWLALGLCWLVSFLVGLTPMFGWNMKLTSEYHRNVTFLSCQFVSVMRMDYMVYFSFLTWIFIPLVVMCAIYLDIFYIIRNKLSLNLSNSKETGAFYGREFKTAKSLFLVLFLFALSWLPLSIINCIIYFNGEVPQLVLYMGILLSHANSMMNPIVYAYKIKKFKETYLLILKACVVCHPSDSLDTSIEKNSE,6.0 +CC(C)CC(NC(=O)[C@H](CC(O)=O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](NC(=O)[C@@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](C)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@H](CO)NC(=O)[C@@H](NC(=O)[C@H](CO)NC(=O)[C@H](CCCN=C(N)N)NC(=O)[C@H](CS)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CC(O)=O)NC(=O)[C@@H](N)C(C)O)[C@@H](C)O)C(C)C)C(C)C)C(O)=O,MASRPAASSPVEARAPVGGQEAGGPSAATQGEAAGAPLAHGHHVYCQRVNGVMVLSDKTPGSASYRISDNNFVQCGSNCTMIIDGDVVRGRPQDPGAAASPAPFVAVTNIGAGSDGGTAVVAFGGTPRRSAGTSTGTQTADVPTEALGGPPPPPRFTLGGGCCSCRDTRRRSAVFGGEGDPVGPAEFVSDDRSSDSDSDDSEDTDSETLSHASSDVSGGATYDDALDSDSSSDDSLQIDGPVCRPWSNDTAPLDVCPGTPGPGADAGGPSAVDPHAPTPEAGAGLAADPAVARDDAEGLSDPRPRLGTGTAYPVPLELTPENAEAVARFLGDAVNREPALMLEYFCRCAREETKRVPPRTFGSPPRLTEDDFGLLNYALVEMQRLCLDVPPVPPNAYMPYYLREYVTRLVNGFKPLVSRSARLYRILGVLVHLRIRTREASFEEWLRSKEVALDFGLTERLREHEAQLVILAQALDHYDCLIHSTPHTLVERGLQSALKYEEFYLKRFGGHYMESVFQMYTRIAGFLACRATRGMRHIALGREGSWWEMFKFFFHRLYDHQIVPSTPAMLNLGTRNYYTSSCYLVNPQATTNKATLRAITSNVSAILARNGGIGLCVQAFNDSGPGTASVMPALKVLDSLVAAHNKESARPTGACVYLEPWHTDVRAVLRMKGVLAGEEAQRCDNIFSALWMPDLFFKRLIRHLDGEKNVTWTLFDRDTSMSLADFHGEEFEKLYQHLEVMGFGEQIPIQELAYGIVRSAATTGSPFVMFKDAVNRHYIYDTQGAAIAGSNLCTEIVHPASKRSSGVCNLGSVNLARCVSRQTFDFGRLRDAVQACVLMVNIMIDSTLQPTPQCTRGNDNLRSMGIGMQGLHTACLKLGLDLESAEFQDLNKHIAEVMLLSAMKTSNALCVRGARPFNHFKRSMYRAGRFHWERFPDARPRYEGEWEMLRQSMMKHGLRNSQFVALMPTAASAQISDVSEGFAPLFTNLFSKVTRDGETLRPNTLLLKELERTFSGKRLLEVMDSLDAKQWSVAQALPCLEPTHPLRRFKTAFDYDQKLLIDLCADRAPYVDHSQSMTLYVTEKADGTLPASTLVRLLVHAYKRGLKTGMYYCKVRKATNSGVFGGDDNIVCMSCAL,4.259637310505756 +Cc1ccc(cc1)-c1cc(nn1-c1ccc(cc1)S(N)(=O)=O)C(F)(F)F,MSRQSISLRFPLLLLLLSPSPVFSADPGAPAPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPEIWTWLRTTLRPSPSFIHFLLTHGRWLWDFVNATFIRDTLMRLVLTVRSNLIPSPPTYNIAHDYISWESFSNVSYYTRILPSVPRDCPTPMDTKGKKQLPDAEFLSRRFLLRRKFIPDPQSTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQMLNGEVYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATIWLREHNRVCDLLKAEHPTWGDEQLFQTARLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGAQFQYRNRIAMEFNQLYHWHPLMPDSFRVGPQDYSYEQFLFNTSMLVDYGVEALVDAFSRQPAGRIGGGRNIDHHILHVAVDVIKESRVLRLQPFNEYRKRFGMKPYTSFQELTGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEMGAPFSLKGLLGNPICSPEYWKASTFGGEVGFNLVKTATLKKLVCLNTKTCPYVSFHVPDPRQEDRPGVERPPTEL,4.823908740944319 +NS(=O)(=O)OC[C@H]1C[C@@H](Nc2ccnc3cc(nn23)-c2ccc3c(c2)oc2ccccc32)[C@H](O)[C@@H]1O,MSSSPLSKKRRVSGPDPKPGSNCSPAQSVLSEVPSVPTNGMAKNGSEADIDEGLYSRQLYVLGHEAMKRLQTSSVLVSGLRGLGVEIAKNIILGGVKAVTLHDQGTAQWADLSSQFYLREEDIGKNRAEVSQPRLAELNSYVPVTAYTGPLVEDFLSGFQVVVLTNTPLEDQLRVGEFCHNRGIKLVVADTRGLFGQLFCDFGEEMILTDSNGEQPLSAMVSMVTKDNPGVVTCLDEARHGFESGDFVSFSEVQGMVELNGNQPMEIKVLGPYTFSICDTSNFSDYIRGGIVSQVKVPKKISFKSLVASLAEPDFVVTDFAKFSRPAQLHIGFQALHQFCAQHGRPPRPRNEEDAAELVALAQAVNARALPAVQQNNLDEDLIRKLAYVAAGDLAPINAFIGGLAAQEVMKACSGKFMPIMQWLYFDALECLPEDKEVLTEDKCLQRQNRYDGQVAVFGSDLQEKLGKQKYFLVGAGAIGCELLKNFAMIGLGCGEGGEIIVTDMDTIEKSNLNRQFLFRPWDVTKLKSDTAAAAVRQMNPHIRVTSHQNRVGPDTERIYDDDFFQNLDGVANALDNVDARMYMDRRCVYYRKPLLESGTLGTKGNVQVVIPFLTESYSSSQDPPEKSIPICTLKNFPNAIEHTLQWARDEFEGLFKQPAENVNQYLTDPKFVERTLRLAGTQPLEVLEAVQRSLVLQRPQTWADCVTWACHHWHTQYSNNIRQLLHNFPPDQLTSSGAPFWSGPKRCPHPLTFDVNNPLHLDYVMAAANLFAQTYGLTGSQDRAAVATFLQSVQVPEFTPKSGVKIHVSDQELQSANASVDDSRLEELKATLPSPDKLPGFKMYPIDFEKDDDSNFHMDFIVAASNLRAENYDIPSADRHKSKLIAGKIIPAIATTTAAVVGLVCLELYKVVQGHRQLDSYKNGFLNLALPFFGFSEPLAAPRHQYYNQEWTLWDRFEVQGLQPNGEEMTLKQFLDYFKTEHKLEITMLSQGVSMLYSFFMPAAKLKERLDQPMTEIVSRVSKRKLGRHVRALVLELCCNDESGEDVEVPYVRYTIR,8.0 +Cc1cccc(n1)-c1nc(NCc2cccc(c2)C#N)[nH]c1-c1ccc2OCOc2c1,MEAAVAAPRPRLLLLVLAAAAAAAAALLPGATALQCFCHLCTKDNFTCVTDGLCFVSVTETTDKVIHNSMCIAEIDLIPRDRPFVCAPSSKTGSVTTTYCCNQDHCNKIELPTTVKSSPGLGPVELAAVIAGPVCFVCISLMLMVYICHNRTVIHHRVPNEEDPSLDRPFISEGTTLKDLIYDMTTSGSGSGLPLLVQRTIARTIVLQESIGKGRFGEVWRGKWRGEEVAVKIFSSREERSWFREAEIYQTVMLRHENILGFIAADNKDNGTWTQLWLVSDYHEHGSLFDYLNRYTVTVEGMIKLALSTASGLAHLHMEIVGTQGKPAIAHRDLKSKNILVKKNGTCCIADLGLAVRHDSATDTIDIAPNHRVGTKRYMAPEVLDDSINMKHFESFKRADIYAMGLVFWEIARRCSIGGIHEDYQLPYYDLVPSDPSVEEMRKVVCEQKLRPNIPNRWQSCEALRVMAKIMRECWYANGAARLTALRIKKTLSQLSQQEGIKM,7.619788758288394 +NCC(O)c1ccc(O)c(O)c1F,MSGPTMDHQEPYSVQATAAIASAITFLILFTIFGNALVILAVLTSRSLRAPQNLFLVSLAAADILVATLIIPFSLANELLGYWYFWRAWCEVYLALDVLFCTSSIVHLCAISLDRYWAVSRALEYNSKRTPRRIKCIILTVWLIAAVISLPPLIYKGDQRPEPRGLPQCELNQEAWYILASSIGSFFAPCLIMILVYLRIYVIAKRSHCRGLGAKRGSGEGESKKPQPVAGGVPTSAKVPTLVSPLSSVGEANGHPKPPREKEEGETPEDPEARALPPTWSALPRSGQGQKKGTSGATAEEGDEEDEEEVEECEPQTLPASPASVCNPPLQQPQTSRVLATLRGQVLLGKNVGVASGQWWRRRTQLSREKRFTFVLAVVIGVFVVCWFPFFFSYSLGAICPQHCKVPHGLFQFFFWIGYCNSSLNPVIYTVFNQDFRRAFRRILCRPWTQTGW,5.853871964321762 +CC(C)[C@H](NC(=O)OCc1ccccc1)C(=O)NC(C)[C@@H]1O[C@@H]1[C@H](Cc1ccccc1)NC(=O)[C@H](NC(=O)OCc1ccccc1)C(C)C,PQVTLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKMIGGIGGFIKVRQYDQILIEICGHKAIGTVLVGPTPVNIIGRNLLTQIGCTLNF,8.397940008672037 +COc1cc(ccc1Nc1ncc(Cl)c(Nc2ccc(cc2NC(C)(C)C)N2CCN(CC2)C(C)=O)n1)N1CCN(CC1)C(C)=O,MGAIGLLWLLPLLLSTAAVGSGMGTGQRAGSPAAGPPLQPREPLSYSRLQRKSLAVDFVVPSLFRVYARDLLLPPSSSELKAGRPEARGSLALDCAPLLRLLGPAPGVSWTAGSPAPAEARTLSRVLKGGSVRKLRRAKQLVLELGEEAILEGCVGPPGEAAVGLLQFNLSELFSWWIRQGEGRLRIRLMPEKKASEVGREGRLSAAIRASQPRLLFQIFGTGHSSLESPTNMPSPSPDYFTWNLTWIMKDSFPFLSHRSRYGLECSFDFPCELEYSPPLHDLRNQSWSWRRIPSEEASQMDLLDGPGAERSKEMPRGSFLLLNTSADSKHTILSPWMRSSSEHCTLAVSVHRHLQPSGRYIAQLLPHNEAAREILLMPTPGKHGWTVLQGRIGRPDNPFRVALEYISSGNRSLSAVDFFALKNCSEGTSPGSKMALQSSFTCWNGTVLQLGQACDFHQDCAQGEDESQMCRKLPVGFYCNFEDGFCGWTQGTLSPHTPQWQVRTLKDARFQDHQDHALLLSTTDVPASESATVTSATFPAPIKSSPCELRMSWLIRGVLRGNVSLVLVENKTGKEQGRMVWHVAAYEGLSLWQWMVLPLLDVSDRFWLQMVAWWGQGSRAIVAFDNISISLDCYLTISGEDKILQNTAPKSRNLFERNPNKELKPGENSPRQTPIFDPTVHWLFTTCGASGPHGPTQAQCNNAYQNSNLSVEVGSEGPLKGIQIWKVPATDTYSISGYGAAGGKGGKNTMMRSHGVSVLGIFNLEKDDMLYILVGQQGEDACPSTNQLIQKVCIGENNVIEEEIRVNRSVHEWAGGGGGGGGATYVFKMKDGVPVPLIIAAGGGGRAYGAKTDTFHPERLENNSSVLGLNGNSGAAGGGGGWNDNTSLLWAGKSLQEGATGGHSCPQAMKKWGWETRGGFGGGGGGCSSGGGGGGYIGGNAASNNDPEMDGEDGVSFISPLGILYTPALKVMEGHGEVNIKHYLNCSHCEVDECHMDPESHKVICFCDHGTVLAEDGVSCIVSPTPEPHLPLSLILSVVTSALVAALVLAFSGIMIVYRRKHQELQAMQMELQSPEYKLSKLRTSTIMTDYNPNYCFAGKTSSISDLKEVPRKNITLIRGLGHGAFGEVYEGQVSGMPNDPSPLQVAVKTLPEVCSEQDELDFLMEALIISKFNHQNIVRCIGVSLQSLPRFILLELMAGGDLKSFLRETRPRPSQPSSLAMLDLLHVARDIACGCQYLEENHFIHRDIAARNCLLTCPGPGRVAKIGDFGMARDIYRASYYRKGGCAMLPVKWMPPEAFMEGIFTSKTDTWSFGVLLWEIFSLGYMPYPSKSNQEVLEFVTSGGRMDPPKNCPGPVYRIMTQCWQHQPEDRPNFAIILERIEYCTQDPDVINTALPIEYGPLVEEEEKVPVRPKDPEGVPPLLVSQQAKREEERSPAAPPPLPTTSSGKAAKKPTAAEISVRVPRGPAVEGGHVNMAFSQSNPPSELHKVHGSRNKPTSLWNPTYGSWFTEKPTKKNNPIAKKEPHDRGNLGLEGSCTVPPNVATGRLPGASLLLEPSSLTANMKEVPLFRLRHFPCGNVNYGYQQQGLPLEAATAPGAGHYEDTILKSKNSMNQPGP,6.236572006437062 +Nc1ccnc2n(cnc12)[C@@H]1O[C@H](CO)[C@@H](O)[C@H]1O,MQLETQDALYVALELVIAALAVAGNVLVCAAVGASSALQTPTNYFLVSLATADVAVGLFAIPFAITISLGFCTDFHSCLFLACFVLVLTQSSIFSLLAVAVDRYLAIRVPLRYKGLVTGTRARGIIAVLWVLAFGIGLTPFLGWNSKDRATSNCTEPGDGITNKSCCPVKCLFENVVPMSYMVYFNFFGCVLPPLLIMMVIYIKIFMVACKQLQHMELMEHSRTTLQREIHAAKSLAMIVGIFALCWLPVHAINCITLFHPALAKDKPKWVMNVAILLSHANSVVNPIVYAYRNRDFRYSFHRIISRYVLCQTDTKGGSGQAGGQSTFSLSL,5.5376020021010435 +NC(=O)c1cn(nc1Nc1ccccc1)C1(CC#N)CN(C1)C(=O)OCCCc1cccnc1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,6.351639989019068 +CCCc1cc(N2CCC2)c2cc(NC(=O)\C=C\c3ccc(cc3)C(F)(F)F)ccc2n1,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,8.55284196865778 +Clc1cccc(OC[C@H]2CN(CC(=O)N3CCc4ccccc34)CCO2)c1,MASSYKMSEQSTTSEHILQKTCDHLILTNRSGLETDSVAEEMKQTVEGQGHTVHWAALLILAVIIPTIGGNILVILAVALEKRLQYATNYFLMSLAIADLLVGLFVMPIALLTIMFEAIWPLPLALCPAWLFLDVLFSTASIMHLCAISLDRYIAIKKPIQANQCNSRATAFIKITVVWLISIGIAIPVPIKGIETDVINPHNVTCELTKDRFGSFMVFGSLAAFFAPLTIMVVTYFLTIHTLQKKAYLVKNKPPQRLTRWTVPTVFLREDSSFSSPEKVAMLDGSHRDKILPNSSDETLMRRMSSVGKRSAQTISNEQRASKALGVVFFLFLLMWCPFFITNLTLALCDSCNQTTLKTLLEIFVWIGYVSSGVNPLIYTLFNKTFREAFGRYITCNYRATKSVKALRKFSSTLCFGNSMVENSKFFTKHGIRNGINPAMYQSPMRLRSSTIQSSSIILLDTLLTENDGDKAEEQVSYI,5.62745619924093 +CCNc1nc2ccc(OC)cc2cc1Cc1cncc2cc(OC)c(OC)cc12,MRIEERKSQHLTGLTDEKVKAYLSLHPQVLDEFVSESVSAETVEKWLKRKNNKSEDESAPKEVSRYQDTNMQGVVYELNSYIEQRLDTGGDNQLLLYELSSIIKIATKADGFALYFLGECNNSLCIFTPPGIKEGKPRLIPAGPITQGTTVSAYVAKSRKTLLVEDILGDERFPRGTGLESGTRIQSVLCLPIVTAIGDLIGILELYRHWGKEAFCLSHQEVATANLAWASVAIHQVQVCRGLAKQTELNDFLLDVSKTYFDNIVAIDSLLEHIMIYAKNLVNADRCALFQVDHKNKELYSDLFDIGEEKEGKPVFKKTKEIRFSIEKGIAGQVARTGEVLNIPDAYADPRFNREVDLYTGYTTRNILCMPIVSRGSVIGVVQMVNKISGSAFSKTDENNFKMFAVFCALALHCANMYHRIRHSECIYRVTMEKLSYHSICTSEEWQGLMQFTLPVRLCKEIELFHFDIGPFENMWPGIFVYMVHRSCGTSCFELEKLCRFIMSVKKNYRRVPYHNWKHAVTVAHCMYAILQNNHTLFTDLERKGLLIACLCHDLDHRGFSNSYLQKFDHPLAALYSTSTMEQHHFSQTVSILQLEGHNIFSTLSSSEYEQVLEIIRKAIIATDLALYFGNRKQLEEMYQTGSLNLNNQSHRDRVIGLMMTACDLCSVTKLWPVTKLTANDIYAEFWAEGDEMKKLGIQPIPMMDRDKKDEVPQGQLGFYNAVAIPCYTTLTQILPPTEPLLKACRDNLSQWEKVIRGEETATWISSPSVAQKAAASED,7.494850021680094 +Cc1ncc(c(C)n1)-c1cnc(NCc2c3CCOc3ccc2F)n2cnc(-c3ncco3)c12,MSEREVSTAPAGTDMPAAKKQKLSSDENSNPDLSGDENDDAVSIESGTNTERPDTPTNTPNAPGRKSWGKGKWKSKKCKYSFKCVNSLKEDHNQPLFGVQFNWHSKEGDPLVFATVGSNRVTLYECHSQGEIRLLQSYVDADADENFYTCAWTYDSNTSHPLLAVAGSRGIIRIINPITMQCIKHYVGHGNAINELKFHPRDPNLLLSVSKDHALRLWNIQTDTLVAIFGGVEGHRDEVLSADYDLLGEKIMSCGMDHSLKLWRINSKRMMNAIKESYDYNPNKTNRPFISQKIHFPDFSTRDIHRNYVDCVRWLGDLILSKSCENAIVCWKPGKMEDDIDKIKPSESNVTILGRFDYSQCDIWYMRFSMDFWQKMLALGNQVGKLYVWDLEVEDPHKAKCTTLTHHKCGAAIRQTSFSRDSSILIAVCDDASIWRWDRLR,7.767003889607846 +CC(=O)c1cccc(c1)-c1cc(NC2CC2)n2ncc(\C=C3/NC(=O)NC3=O)c2n1,MSGPVPSRARVYTDVNTHRPREYWDYESHVVEWGNQDDYQLVRKLGRGKYSEVFEAINITNNEKVVVKILKPVKKKKIKREIKILENLRGGPNIITLADIVKDPVSRTPALVFEHVNNTDFKQLYQTLTDYDIRFYMYEILKALDYCHSMGIMHRDVKPHNVMIDHEHRKLRLIDWGLAEFYHPGQEYNVRVASRYFKGPELLVDYQMYDYSLDMWSLGCMLASMIFRKEPFFHGHDNYDQLVRIAKVLGTEDLYDYIDKYNIELDPRFNDILGRHSRKRWERFVHSENQHLVSPEALDFLDKLLRYDHQSRLTAREAMEHPYFYTVVKDQARMGSSSMPGGSTPVSSANMMSGISSVPTPSPLGPLAGSPVIAAANPLGMPVPAAAGAQQ,8.0 +Cc1nc(NCCCO)nc2ccc(NC(=O)\C=C\c3ccc(OC(F)(F)F)cc3)cc12,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,7.443697499232712 +COc1ccc2NC(=O)[C@@]3(C[C@H]3c3ccc4c(n[nH]c4c3)-c3ccc(CN4CCN(C)CC4)cc3)c2c1,MAQKENSYPWPYGRQTAPSGLSTLPQRVLRKEPVTPSALVLMSRSNVQPTAAPGQKVMENSSGTPDILTRHFTIDDFEIGRPLGKGKFGNVYLAREKKSHFIVALKVLFKSQIEKEGVEHQLRREIEIQAHLHHPNILRLYNYFYDRRRIYLILEYAPRGELYKELQKSCTFDEQRTATIMEELADALMYCHGKKVIHRDIKPENLLLGLKGELKIADFGWSVHAPSLRRKTMCGTLDYLPPEMIEGRMHNEKVDLWCIGVLCYELLVGNPPFESASHNETYRRIVKVDLKFPASVPMGAQDLISKLLRHNPSERLPLAQVSAHPWVRANSRRVLPPSALQSVA,7.0 +CCCC(=O)Nc1ccc(cc1)C(=O)NO,MSSQSHPDGLSGRDQPVELLNPARVNHMPSTVDVATALPLQVAPSAVPMDLRLDHQFSLPVAEPALREQQLQQELLALKQKQQIQRQILIAEFQRQHEQLSRQHEAQLHEHIKQQQEMLAMKHQQELLEHQRKLERHRQEQELEKQHREQKLQQLKNKEKGKESAVASTEVKMKLQEFVLNKKKALAHRNLNHCISSDPRYWYGKTQHSSLDQSSPPQSGVSTSYNHPVLGMYDAKDDFPLRKTASEPNLKLRSRLKQKVAERRSSPLLRRKDGPVVTALKKRPLDVTDSACSSAPGSGPSSPNNSSGSVSAENGIAPAVPSIPAETSLAHRLVAREGSAAPLPLYTSPSLPNITLGLPATGPSAGTAGQQDAERLTLPALQQRLSLFPGTHLTPYLSTSPLERDGGAAHSPLLQHMVLLEQPPAQAPLVTGLGALPLHAQSLVGADRVSPSIHKLRQHRPLGRTQSAPLPQNAQALQHLVIQQQHQQFLEKHKQQFQQQQLQMNKIIPKPSEPARQPESHPEETEEELREHQALLDEPYLDRLPGQKEAHAQAGVQVKQEPIESDEEEAEPPREVEPGQRQPSEQELLFRQQALLLEQQRIHQLRNYQASMEAAGIPVSFGGHRPLSRAQSSPASATFPVSVQEPPTKPRFTTGLVYDTLMLKHQCTCGSSSSHPEHAGRIQSIWSRLQETGLRGKCECIRGRKATLEELQTVHSEAHTLLYGTNPLNRQKLDSKKLLGSLASVFVRLPCGGVGVDSDTIWNEVHSAGAARLAVGCVVELVFKVATGELKNGFAVVRPPGHHAEESTPMGFCYFNSVAVAAKLLQQRLSVSKILIVDWDVHHGNGTQQAFYSDPSVLYMSLHRYDDGNFFPGSGAPDEVGTGPGVGFNVNMAFTGGLDPPMGDAEYLAAFRTVVMPIASEFAPDVVLVSSGFDAVEGHPTPLGGYNLSARCFGYLTKQLMGLAGGRIVLALEGGHDLTAICDASEACVSALLGNELDPLPEKVLQQRPNANAVRSMEKVMEIHSKYWRCLQRTTSTAGRSLIEAQTCENEEAETVTAMASLSVGVKPAEKRPDEEPMEEEPPL,5.823908740944319 +CN[C@@H](C)C(=O)N[C@H]1CN(C(=O)CS(C)(=O)=O)c2ccccc2N(Cc2c(OC)ccc3cc(Br)ccc23)C1=O,MTFNSFEGSKTCVPADINKEEEFVEEFNRLKTFANFPSGSPVSASTLARAGFLYTGEGDTVRCFSCHAAVDRWQYGDSAVGRHRKVSPNCRFINGFYLENSATQSTNSGIQNGQYKVENYLGSRDHFALDRPSETHADYLLRTGQVVDISDTIYPRNPAMYSEEARLKSFQNWPDYAHLTPRELASAGLYYTGIGDQVQCFCCGGKLKNWEPCDRAWSEHRRHFPNCFFVLGRNLNIRSESDAVSSDRNFPNSTNLPRNPSMADYEARIFTFGTWIYSVNKEQLARAGFYALGEGDKVKCFHCGGGLTDWKPSEDPWEQHAKWYPGCKYLLEQKGQEYINNIHLTHSLEECLVRTTEKTPSLTRRIDDTIFQNPMVQEAIRMGFSFKDIKKIMEEKIQISGSNYKSLEVLVADLVNAQKDSMQDESSQTSLQKEISTEEQLRRLQEEKLCKICMDRNIAIVFVPCGHLVTCKQCAEAVDKCPMCYTVITFKQKIFMS,8.045757490560675 +OC(=O)c1cnc([nH]1)-c1ccccc1,MEALMARGALTGPLRALCLLGCLLSHAAAAPSPIIKFPGDVAPKTDKELAVQYLNTFYGCPKESCNLFVLKDTLKKMQKFFGLPQTGDLDQNTIETMRKPRCGNPDVANYNFFPRKPKWDKNQITYRIIGYTPDLDPETVDDAFARAFQVWSDVTPLRFSRIHDGEADIMINFGRWEHGDGYPFDGKDGLLAHAFAPGTGVGGDSHFDDDELWTLGEGQVVRVKYGNADGEYCKFPFLFNGKEYNSCTDTGRSDGFLWCSTTYNFEKDGKYGFCPHEALFTMGGNAEGQPCKFPFRFQGTSYDSCTTEGRTDGYRWCGTTEDYDRDKKYGFCPETAMSTVGGNSEGAPCVFPFTFLGNKYESCTSAGRSDGKMWCATTANYDDDRKWGFCPDQGYSLFLVAAHEFGHAMGLEHSQDPGALMAPIYTYTKNFRLSQDDIKGIQELYGASPDIDLGTGPTPTLGPVTPEICKQDIVFDGIAQIRGEIFFFKDRFIWRTVTPRDKPMGPLLVATFWPELPEKIDAVYEAPQEEKAVFFAGNEYWIYSASTLERGYPKPLTSLGLPPDVQRVDAAFNWSKNKKTYIFAGDKFWRYNEVKKKMDPGFPKLIADAWNAIPDNLDAVVDLQGGGHSYFFKGAYYLKLENQSLKSVKFGSIKSDWLGC,3.8632794328435933 +CCCCc1ccc(NC(=O)N2CCN(CC2)c2ncccc2C(F)(F)F)cc1,MEQRASLDSEESESPPQENSCLDPPDRDPNCKPPPVKPHIFTTRSRTRLFGKGDSEEASPLDCPYEEGGLASCPIITVSSVLTIQRPGDGPASVRPSSQDSVSAGEKPPRLYDRRSIFDAVAQSNCQELESLLPFLQRSKKRLTDSEFKDPETGKTCLLKAMLNLHNGQNDTIALLLDVARKTDSLKQFVNASYTDSYYKGQTALHIAIERRNMTLVTLLVENGADVQAAANGDFFKKTKGRPGFYFGELPLSLAACTNQLAIVKFLLQNSWQPADISARDSVGNTVLHALVEVADNTVDNTKFVTSMYNEILILGAKLHPTLKLEEITNRKGLTPLALAASSGKIGVLAYILQREIHEPECRHLSRKFTEWAYGPVHSSLYDLSCIDTCEKNSVLEVIAYSSSETPNRHDMLLVEPLNRLLQDKWDRFVKRIFYFNFFVYCLYMIIFTAAAYYRPVEGLPPYKLKNTVGDYFRVTGEILSVSGGVYFFFRGIQYFLQRRPSLKSLFVDSYSEILFFVQSLFMLVSVVLYFSQRKEYVASMVFSLAMGWTNMLYYTRGFQQMGIYAVMIEKMILRDLCRFMFVYLVFLFGFSTAVVTLIEDGKNNSLPMESTPHKCRGSACKPGNSYNSLYSTCLELFKFTIGMGDLEFTENYDFKAVFIILLLAYVILTYILLLNMLIALMGETVNKIAQESKNIWKLQRAITILDTEKSFLKCMRKAFRSGKLLQVGFTPDGKDDYRWCFRVDEVNWTTWNTNVGIINEDPGNCEGVKRTLSFSLRSGRVSGRNWKNFALVPLLRDASTRDRHATQQEEVQLKHYTGSLKPEDAEVFKDSMVPGEK,5.864867348623225 +Cc1cccc2c3ccc(cc3c(=O)[nH]c12)C#N,FLDGIDKAQEEHEKYHSNWRAMASDFNLPPVVAKEIVASCDKCQLKGEAMHGQVDCSPGIWQLDCTHLEGKVILVAVHVASGYIEAEVIPAETGQETAYFLLKLAGRWPVKTVHTDNGSNFTSTTVKAACWWAGIKQEFGIPYNPQSQGVIESMNKELKKIIGQVRDQAEHLKTAVQMAVFIHNFKRKGGIGGYSAGERIVDIIATDIQTKELQKQITKIQNFRVYYRDSRDPVWKGPAKLLWKGEGAVVIQDNSDIKVVPRRKAKIIRDYGKQMAGDDCVASRQDED,3.3010299956639813 +NC1=NC2(CO1)c1cc(ccc1OCC21CCCO1)-c1cncnc1,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,4.193141970481182 +COc1cc(OC)c(c(OC)c1)-c1ccc(cc1)-c1cn(nn1)C(=O)N1CCCCC1Cc1ccncc1,MPGMVLFGRRWAIASDDLVFPGFFELVVRVLWWIGILTLYLMHRGKLDCAGGALLSSYLIVLMILLAVVICTVSAIMCVSMRGTICNPGPRKSMSKLLYIRLALFFPEMVWASLGAAWVADGVQCDRTVVNGIIATVVVSWIIIAATVVSIIIVFDPLGGKMAPYSSAGPSHLDSHDSSQLLNGLKTAATSVWETRIKLLCCCIGKDDHTRVAFSSTAELFSTYFSDTDLVPSDIAAGLALLHQQQDNIRNNQEPAQVVCHAPGSSQEADLDAELENCHHYMQFAAAAYGWPLYIYRNPLTGLCRIGGDCCRSRTTDYDLVGGDQLNCHFGSILHTTGLQYRDFIHVSFHDKVYELPFLVALDHRKESVVVAVRGTMSLQDVLTDLSAESEVLDVECEVQDRLAHKGISQAARYVYQRLINDGILSQAFSIAPEYRLVIVGHSLGGGAAALLATMLRAAYPQVRCYAFSPPRGLWSKALQEYSQSFIVSLVLGKDVIPRLSVTNLEDLKRRILRVVAHCNKPKYKILLHGLWYELFGGNPNNLPTELDGGDQEVLTQPLLGEQSLLTRWSPAYSFSSDSPLDSSPKYPPLYPPGRIIHLQEEGASGRFGCCSAAHYSAKWSHEAEFSKILIGPKMLTDHMPDILMRALDSVVSDRAACVSCPAQGVSSVDVA,5.221848749616356 +CN1CCCCC1c1c([nH]c2ccccc12)-c1ccccc1,MDILCEENTSLSSTTNSLMQLNDDTRLYSNDFNSGEANTSDAFNWTVDSENRTNLSCEGCLSPSCLSLLHLQEKNWSALLTAVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAVWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVSFFIPLTIMVITYFLTIKSLQKEATLCVSDLGTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYTGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNEDVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENKKPLQLILVNTIPALAYKSSQLQMGQKKNSKQDAKTTDNDCSMVALGKQHSEEASKDNSDGVNEKVSCV,7.853871964321762 +NC1(CCOCC1)C(=O)N[C@@H](Cc1ccc(cc1)-c1ccc(cc1)C#N)C#N,MWGLKVLLLPVVSFALYPEEILDTHWELWKKTHRKQYNNKVDEISRRLIWEKNLKYISIHNLEASLGVHTYELAMNHLGDMTSEEVVQKMTGLKVPLSHSRSNDTLYIPEWEGRAPDSVDYRKKGYVTPVKNQGQCGSCWAFSSVGALEGQLKKKTGKLLNLSPQNLVDCVSENDGCGGGYMTNAFQYVQKNRGIDSEDAYPYVGQEESCMYNPTGKAAKCRGYREIPEGNEKALKRAVARVGPVSVAIDASLTSFQFYSKGVYYDESCNSDNLNHAVLAVGYGIQKGNKHWIIKNSWGENWGNKGYILMARNKNNACGIANLASFPKM,5.0 +CCc1c(N)ncnc1N1CCN(CC1)[C@@H](CN)c1ccc(Cl)cc1,MRRRRRRDGFYPAPDFRDREAEDMAGVFDIDLDQPEDAGSEDELEEGGQLNESMDHGGVGPYELGMEHCEKFEISETSVNRGPEKIRPECFELLRVLGKGGYGKVFQVRKVTGANTGKIFAMKVLKKAMIVRNAKDTAHTKAERNILEEVKHPFIVDLIYAFQTGGKLYLILEYLSGGELFMQLEREGIFMEDTACFYLAEISMALGHLHQKGIIYRDLKPENIMLNHQGHVKLTDFGLCKESIHDGTVTHTFCGTIEYMAPEILMRSGHNRAVDWWSLGALMYDMLTGAPPFTGENRKKTIDKILKCKLNLPPYLTQEARDLLKKLLKRNAASRLGAGPGDAGEVQAHPFFRHINWEELLARKVEPPFKPLLQSEEDVSQFDSKFTRQTPVDSPDDSTLSESANQVFLGFTYVAPSVLESVKEKFSFEPKIRSPRRFIGSPRTPVSPVKFSPGDFWGRGASASTANPQTPVEYPMETSGIEQMDVTMSGEASAPLPIRQPNSGPYKKQAFPMISKRPEHLRMNL,6.721246399047171 +Cn1cc(cn1)C(NCC1CC1)c1cccc(NC(=O)c2cc(nn2-c2cccc(CN)c2)C(F)(F)F)c1,MILFKQATYFISLFATVSCGCLTQLYENAFFRGGDVASMYTPNAQYCQMRCTFHPRCLLFSFLPASSINDMEKRFGCFLKDSVTGTLPKVHRTGAVSGHSLKQCGHQISACHRDIYKGVDMRGVNFNVSKVSSVEECQKRCTNNIRCQFFSYATQTFHKAEYRNNCLLKYSPGGTPTAIKVLSNVESGFSLKPCALSEIGCHMNIFQHLAFSDVDVARVLTPDAFVCRTICTYHPNCLFFTFYTNVWKIESQRNVCLLKTSESGTPSSSTPQENTISGYSLLTCKRTLPEPCHSKIYPGVDFGGEELNVTFVKGVNVCQETCTKMIRCQFFTYSLLPEDCKEEKCKCFLRLSMDGSPTRIAYGTQGSSGYSLRLCNTGDNSVCTTKTSTRIVGGTNSSWGEWPWQVSLQVKLTAQRHLCGGSLIGHQWVLTAAHCFDGLPLQDVWRIYSGILNLSDITKDTPFSQIKEIIIHQNYKVSEGNHDIALIKLQAPLNYTEFQKPICLPSKGDTSTIYTNCWVTGWGFSKEKGEIQNILQKVNIPLVTNEECQKRYQDYKITQRMVCAGYKEGGKDACKGDSGGPLVCKHNGMWRLVGITSWGEGCARREQPGVYTKVAEYMDWILEKTQSSDGKAQMQSPA,7.600326278518962 +NC(=O)c1nnc(Nc2cnn(CC3CC3)c2)cc1NCc1cccc2ccsc12,MAPPSEETPLIPQRSCSLLSTEAGALHVLLPARGPGPPQRLSFSFGDHLAEDLCVQAAKASGILPVYHSLFALATEDLSCWFPPSHIFSVEDASTQVLLYRIRFYFPNWFGLEKCHRFGLRKDLASAILDLPVLEHLFAQHRSDLVSGRLPVGLSLKEQGECLSLAVLDLARMAREQAQRPGELLKTVSYKACLPPSLRDLIQGLSFVTRRRIRRTVRRALRRVAACQADRHSLMAKYIMDLERLDPAGAAETFHVGLPGALGGHDGLGLLRVAGDGGIAWTQGEQEVLQPFCDFPEIVDISIKQAPRVGPAGEHRLVTVTRTDNQILEAEFPGLPEALSFVALVDGYFRLTTDSQHFFCKEVAPPRLLEEVAEQCHGPITLDFAINKLKTGGSRPGSYVLRRSPQDFDSFLLTVCVQNPLGPDYKGCLIRRSPTGTFLLVGLSRPHSSLRELLATCWDGGLHVDGVAVTLTSCCIPRPKEKSNLIVVQRGHSPPTSSLVQPQSQYQLSQMTFHKIPADSLEWHENLGHGSFTKIYRGCRHEVVDGEARKTEVLLKVMDAKHKNCMESFLEAASLMSQVSYRHLVLLHGVCMAGDSTMVQEFVHLGAIDMYLRKRGHLVPASWKLQVVKQLAYALNYLEDKGLPHGNVSARKVLLAREGADGSPPFIKLSDPGVSPAVLSLEMLTDRIPWVAPECLREAQTLSLEADKWGFGATVWEVFSGVTMPISALDPAKKLQFYEDRQQLPAPKWTELALLIQQCMAYEPVQRPSFRAVIRDLNSLISSDYELLSDPTPGALAPRDGLWNGAQLYACQDPTIFEERHLKYISQLGKGNFGSVELCRYDPLGDNTGALVAVKQLQHSGPDQQRDFQREIQILKALHSDFIVKYRGVSYGPGRQSLRLVMEYLPSGCLRDFLQRHRARLDASRLLLYSSQICKGMEYLGSRRCVHRDLAARNILVESEAHVKIADFGLAKLLPLDKDYYVVREPGQSPIFWYAPESLSDNIFSRQSDVWSFGVVLYELFTYCDKSCSPSAEFLRMMGCERDVPALCRLLELLEEGQRLPAPPACPAEVHELMKLCWAPSPQDRPSFSALGPQLDMLWSGSRGCETHAFTAHPEGKHHSLSFS,7.259637310505756 +Cc1nc2CCCCn2c(=O)c1CCN1CCC(CC1)c1noc2cc(F)ccc12,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,8.346787486224656 +C[C@H]([C@H]([NH3+])C(=O)N1CC[C@H](F)C1)c1ccccc1F,MATTGTPTADRGDAAATDDPAARFQVQKHSWDGLRSIIHGSRKYSGLIVNKAPHDFQFVQKTDESGPHSHRLYYLGMPYGSRENSLLYSEIPKKVRKEALLLLSWKQMLDHFQATPHHGVYSREEELLRERKRLGVFGITSYDFHSESGLFLFQASNSLFHCRDGGKNGFMVSPMKPLEIKTQCSGPRMDPKICPADPAFFSFINNSDLWVANIETGEERRLTFCHQGLSNVLDDPKSAGVATFVIQEEFDRFTGYWWCPTASWEGSEGLKTLRILYEEVDESEVEVIHVPSPALEERKTDSYRYPRTGSKNPKIALKLAEFQTDSQGKIVSTQEKELVQPFSSLFPKVEYIARAGWTRDGKYAWAMFLDRPQQWLQLVLLPPALFIPSTENEEQRLASARAVPRNVQPYVVYEEVTNVWINVHDIFYPFPQSEGEDELCFLRANECKTGFCHLYKVTAVLKSQGYDWSEPFSPGEDEFKCPIKEEIALTSGEWEVLARHGSKIWVNEETKLVYFQGTKDTPLEHHLYVVSYEAAGEIVRLTTPGFSHSCSMSQNFDMFVSHYSSVSTPPCVHVYKLSGPDDDPLHKQPRFWASMMEAASCPPDYVPPEIFHFHTRSDVRLYGMIYKPHALQPGKKHPTVLFVYGGPQVQLVNNSFKGIKYLRLNTLASLGYAVVVIDGRGSCQRGLRFEGALKNQMGQVEIEDQVEGLQFVAEKYGFIDLSRVAIHGWSYGGFLSLMGLIHKPQVFKVAIAGAPVTVWMAYDTGYTERYMDVPENNQHGYEAGSVALHVEKLPNEPNRLLILHGFLDENVHFFHTNFLVSQLIRAGKPYQLQIYPNERHSIRCPESGEHYEVTLLHFLQEYL,4.0 +Fc1ccccc1Cn1nc(cc1-c1ccon1)-c1ncc(F)c(NC2CCOC2)n1,MFCTKLKDLKITGECPFSLLAPGQVPNESSEEAAGSSESCKATVPICQDIPEKNIQESLPQRKTSRSRVYLHTLAESICKLIFPEFERLNVALQRTLAKHKIKESRKSLEREDFEKTIAEQAVAAGVPVEVIKESLGEEVFKICYEEDENILGVVGGTLKDFLNSFSTLLKQSSHCQEAGKRGRLEDASILCLDKEDDFLHVYYFFPKRTTSLILPGIIKAAAHVLYETEVEVSLMPPCFHNDCSEFVNQPYLLYSVHMKSTKPSLSPSKPQSSLVIPTSLFCKTFPFHFMFDKDMTILQFGNGIRRLMNRRDFQGKPNFEEYFEILTPKINQTFSGIMTMLNMQFVVRVRRWDNSVKKSSRVMDLKGQMIYIVESSAILFLGSPCVDRLEDFTGRGLYLSDIPIHNALRDVVLIGEQARAQDGLKKRLGKLKATLEQAHQALEEEKKKTVDLLCSIFPCEVAQQLWQGQVVQAKKFSNVTMLFSDIVGFTAICSQCSPLQVITMLNALYTRFDQQCGELDVYKVETIGDAYCVAGGLHKESDTHAVQIALMALKMMELSDEVMSPHGEPIKMRIGLHSGSVFAGVVGVKMPRYCLFGNNVTLANKFESCSVPRKINVSPTTYRLLKDCPGFVFTPRSREELPPNFPSEIPGICHFLDAYQQGTNSKPCFQKKDVEDGNANFLGKASGID,7.0 +Nc1nnc(s1)S(N)(=O)=O,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,7.221848749616356 +CC[N+](CC)(CC)CCOc1ccc(\C=C\c2ccccc2)cc1,MRCSPGGVWLALAASLLHVSLQGEFQRKLYKELVKNYNPLERPVANDSQPLTVYFSLSLLQIMDVDEKNQVLTTNIWLQMSWTDHYLQWNVSEYPGVKTVRFPDGQIWKPDILLYNSADERFDATFHTNVLVNSSGHCQYLPPGIFKSSCYIDVRWFPFDVQHCKLKFGSWSYGGWSLDLQMQEADISGYIPNGEWDLVGIPGKRSERFYECCKEPYPDVTFTVTMRRRTLYYGLNLLIPCVLISALALLVFLLPADSGEKISLGITVLLSLTVFMLLVAEIMPATSDSVPLIAQYFASTMIIVGLSVVVTVIVLQYHHHDPDGGKMPKWTRVILLNWCAWFLRMKRPGEDKVRPACQHKQRRCSLASVEMSAVAPPPASNGNLLYIGFRGLDGVHCVPTPDSGVVCGRMACSPTHDEHLLHGGQPPEGDPDLAKILEEVRYIANRFRCQDESEAVCSEWKFAACVVDRLCLMAFSVFTIICTIGILMSAPNFVEAVSKDFA,7.3872161432802645 +COc1ccc(cc1)C1CCN(CC1)c1[nH]c(=O)[nH]c(=O)c1Cc1ccccc1,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,7.346787486224656 +CN1CCc2c(C1)sc1nc([nH]c(=O)c21)-c1cc(C)c(O)c(C)c1,MSAESGPGTRLRNLPVMGDGLETSQMSTTQAQAQPQPANAASTNPPPPETSNPNKPKRQTNQLQYLLRVVLKTLWKHQFAWPFQQPVDAVKLNLPDYYKIIKTPMDMGTIKKRLENNYYWNAQECIQDFNTMFTNCYIYNKPGDDIVLMAEALEKLFLQKINELPTEETEIMIVQAKGRGRGRKETGTAKPGVSTVPNTTQASTPPQTQTPQPNPPPVQATPHPFPAVTPDLIVQTPVMTVVPPQPLQTPPPVPPQPQPPPAPAPQPVQSHPPIIAATPQPVKTKKGVKRKADTTTPTTIDPIHEPPSLPPEPKTTKLGQRRESSRPVKPPKKDVPDSQQHPAPEKSSKVSEQLKCCSGILKEMFAKKHAAYAWPFYKPVDVEALGLHDYCDIIKHPMDMSTIKSKLEAREYRDAQEFGADVRLMFSNCYKYNPPDHEVVAMARKLQDVFEMRFAKMPDEPEEPVVAVSSPAVPPPTKVVAPPSSSDSSSDSSSDSDSSTDDSEEERAQRLAELQEQLKAVHEQLAALSQPQQNKPKKKEKDKKEKKKEKHKRKEEVEENKKSKAKEPPPKKTKKNNSSNSNVSKKEPAPMKSKPPPTYESEEEDKCKPMSYEEKRQLSLDINKLPGEKLGRVVHIIQSREPSLKNSNPDEIEIDFETLKPSTLRELERYVTSCLRKKRKPQAEKVDVIAGSSKMKGFSSSESESSSESSSSDSEDSETEMAPKSKKKGHPGREQKKHHHHHHQQMQQAPAPVPQQPPPPPQQPPPPPPPQQQQQPPPPPPPPSMPQQAAPAMKSSPPPFIATQVPVLEPQLPGSVFDPIGHFTQPILHLPQPELPPHLPQPPEHSTPPHLNQHAVVSPPALHNALPQQPSRPSNRAAALPPKPARPPAVSPALTQTPLLPQPPMAQPPQVLLEDEEPPAPPLTSMQMQLYLQQLQKVQPPTPLLPSVKVQSQPPPPLPPPPHPSVQQQLQQQPPPPPPPQPQPPPQQQHQPPPRPVHLQPMQFSTHIQQPPPPQGQQPPHPPPGQQPPPPQPAKPQQVIQHHHSPRHHKSDPYSTGHLREAPSPLMIHSPQMSQFQSLTHQSPPQQNVQPKKQELRAASVVQPQPLVVVKEEKIHSPIIRSEPFSPSLRPEPPKHPESIKAPVHLPQRPEMKPVDVGRPVIRPPEQNAPPPGAPDKDKQKQEPKTPVAPKKDLKIKNMGSWASLVQKHPTTPSSTAKSSSDSFEQFRRAAREKEEREKALKAQAEHAEKEKERLRQERMRSREDEDALEQARRAHEEARRRQEQQQQQRQEQQQQQQQQAAAVAAAATPQAQSSQPQSMLDQQRELARKREQERRRREAMAATIDMNFQSDLLSIFEENLF,6.327902142064283 +C[C@H](Nc1ncc(F)c(n1)N1[C@@H](CF)COC1=O)c1cn(c(C)n1)-c1ccc(Cl)cc1,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,6.406713932979542 +CNCC(O)COc1cccc(c1)-c1nc(OCC2CCN(CC2)S(C)(=O)=O)c(C)c(n1)-c1c(C)noc1C,MAAAAAAVGPGAGGAGSAVPGGAGPCATVSVFPGARLLTIGDANGEIQRHAEQQALRLEVRAGPDSAGIALYSHEDVCVFKCSVSRETECSRVGKQSFIITLGCNSVLIQFATPNDFCSFYNILKTCRGHTLERSVFSERTEESSAVQYFQFYGYLSQQQNMMQDYVRTGTYQRAILQNHTDFKDKIVLDVGCGSGILSFFAAQAGARKIYAVEASTMAQHAEVLVKSNNLTDRIVVIPGKVEEVSLPEQVDIIISEPMGYMLFNERMLESYLHAKKYLKPSGNMFPTIGDVHLAPFTDEQLYMEQFTKANFWYQPSFHGVDLSALRGAAVDEYFRQPVVDTFDIRILMAKSVKYTVNFLEAKEGDLHRIEIPFKFHMLHSGLVHGLAFWFDVAFIGSIMTVWLSTAPTEPLTHWYQVRCLFQSPLFAKAGDTLSGTCLLIANKRQSYDISIVAQVDQTGSKSSNLLDLKNPFFRYTGTTPSPPPGSHYTSPSENMWNTGSTYNLSSGMAVAGMPTAYDLSSVIASGSSVGHNNLIPLANTGIVNHTHSRMGSIMSTGIVQGSSGAQGSGGGSTSAHYAVNSQFTMGGPAISMASPMSIPTNTMHYGS,7.0 +COc1ccc(cc1)C(=NNC(N)=S)c1cccc(c1)C(=O)c1ccc(O)cc1,MWGLKVLLLPVVSFALYPEEILDTHWELWKKTHRKQYNNKVDEISRRLIWEKNLKYISIHNLEASLGVHTYELAMNHLGDMTSEEVVQKMTGLKVPLSHSRSNDTLYIPEWEGRAPDSVDYRKKGYVTPVKNQGQCGSCWAFSSVGALEGQLKKKTGKLLNLSPQNLVDCVSENDGCGGGYMTNAFQYVQKNRGIDSEDAYPYVGQEESCMYNPTGKAAKCRGYREIPEGNEKALKRAVARVGPVSVAIDASLTSFQFYSKGVYYDESCNSDNLNHAVLAVGYGIQKGNKHWIIKNSWGENWGNKGYILMARNKNNACGIANLASFPKM,5.210278306019078 +COc1ccc(cc1)-c1nc2cnc(NCc3ccc(Cl)c(Cl)c3)cc2n(CCNC(C)=O)c1=O,MAPDPVQTPDPASAQLRQMRYFTWEEVAQRSGREKERWLVIDRKVYNISDFSRRHPGGSRVISHYAGQDATDPFVAFHINKGLVRKYMNSLLIGELAPEQPSFEPTKNKALTDEFRELRATVERMGLMKANHLFFLFYLLHILLLDVAAWLTLWIFGTSLVPFTLCAVLLSTVQAQAGWLQHDFGHLSVFSTSTWNHLVHHFVIGHLKGAPASWWNHMHFQHHAKPNCFRKDPDINMHPLFFALGKVLSVELGKEKKKHMPYNHQHKYFFLIGPPALLPLYFQWYIFYFVVQRKKWVDLAWMLSFYVRVFFTYMPLLGLKGLLCLFFIVRFLESNWFVWVTQMNHIPMHIDHDRNVDWVSTQLQATCNVHQSAFNNWFSGHLNFQIEHHLFPTMPRHNYHKVAPLVQSLCAKYGIKYESKPLLTAFADIVYSLKESGQLWLDAYLHQ,7.522878745280337 +OCCOc1cc2N=C(CC(=O)Nc2cc1C#Cc1ccccc1)c1cccc(c1)-n1ccnc1,MGSLLALLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEDCGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHGDAPTAITGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAASQRLNASFTWVASDGWGALESVVAGSEGAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEQRFRCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTRLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTHNEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSLIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFIFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVVAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAARASSSLGQGSGSQFVPTVCNGREVVDSTTSSL,7.1938200260161125 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+Cc1nc(OC[C@@H]2CN(CCO2)C(=O)OC(C)(C)C)sc1S(=O)(=O)NC(=O)c1ccc(cc1Oc1cnc2[nH]ccc2c1)N1CCN(CC2=C(CC(C)(C)CC2)c2ccc(Cl)cc2)CC1,MPPYTVVYFPVRGRCAALRMLLADQGQSWKEEVVTVETWQEGSLKASCLYGQLPKFQDGDLTLYQSNTILRHLGRTLGLYGKDQQEAALVDMVNDGVEDLRCKYISLIYTNYEAGKDDYVKALPGQLKPFETLLSQNQGGKTFIVGDQISFADYNLLDLLLIHEVLAPGCLDAFPLLSAYVGRLSARPKLKAFLASPEYVNLPINGNGKQ,7.332575067012756 +CCOc1ccccc1C(=O)N(CC)CCN(C)c1cccc(n1)C(C)(C)O,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,5.0 +ONC(=O)c1nc2n(n1)c1ccc(Cl)cc1[nH]c2=O,MSTMHLLTFALLFSCSFARAACDPKIVNIGAVLSTRKHEQMFREAVNQANKRHGSWKIQLNATSVTHKPNAIQMALSVCEDLISSQVYAILVSHPPTPNDHFTPTPVSYTAGFYRIPVLGLTTRMSIYSDKSIHLSFLRTVPPYSHQSSVWFEMMRVYNWNHIILLVSDDHEGRAAQKRLETLLEERESKAEKVLQFDPGTKNVTALLMEARELEARVIILSASEDDAATVYRAAAMLNMTGSGYVWLVGEREISGNALRYAPDGIIGLQLINGKNESAHISDAVGVVAQAVHELLEKENITDPPRGCVGNTNIWKTGPLFKRVLMSSKYADGVTGRVEFNEDGDRKFANYSIMNLQNRKLVQVGIYNGTHVIPNDRKIIWPGGETEKPRGYQMSTRLKIVTIHQEPFVYVKPTMSDGTCKEEFTVNGDPVKKVICTGPNDTSPGSPRHTVPQCCYGFCIDLLIKLARTMNFTYEVHLVADGKFGTQERVNNSNKKEWNGMMGELLSGQADMIVAPLTINNERAQYIEFSKPFKYQGLTILVKKEIPRSTLDSFMQPFQSTLWLLVGLSVHVVAVMLYLLDRFSPFGRFKVNSEEEEEDALTLSSAMWFSWGVLLNSGIGEGAPRSFSARILGMVWAGFAMIIVASYTANLAAFLVLDRPEERITGINDPRLRNPSDKFIYATVKQSSVDIYFRRQVELSTMYRHMEKHNYESAAEAIQAVRDNKLHAFIWDSAVLEFEASQKCDLVTTGELFFRSGFGIGMRKDSPWKQNVSLSILKSHENGFMEDLDKTWVRYQECDSRSNAPATLTFENMAGVFMLVAGGIVAGIFLIFIEIAYKRHKDARRKQMQLAFAAVNVWRKNLQDRKSGRAEPDPKKKATFRAITSTLASSFKRRRSSKDTSTGGGRGALQNQKDTVLPRRAIEREEGQLQLCSRHRES,5.958607314841775 +[Na+].[Na+].[Na+].[Na+].[O-]P([O-])(=O)CCOCC(COCP([O-])([O-])=O)Cn1ccc2c1nc[nH]c2=O,MATRSPGVVISDDEPGYDLDLFCIPNHYAEDLERVFIPHGLIMDRTERLARDVMKEMGGHHIVALCVLKGGYKFFADLLDYIKALNRNSDRSIPMTVDFIRLKSYCNDQSTGDIKVIGGDDLSTLTGKNVLIVEDIIDTGKTMQTLLSLVRQYNPKMVKVASLLVKRTPRSVGYKPDFVGFEIPDKFVVGYALDYNEYFRDLNHVCVISETGKAKYKA,5.337242168318426 +CCc1c2Cn3c(cc4c(COC(=O)[C@]4(O)CC)c3=O)-c2nc2ccc(OC(=O)N3CCN(CC3)C(=O)c3ccc(COC(=O)N[C@@H](CCC(=O)N4CCN(CC4)c4cccc(c4)N=C4NCCCN4)C(O)=O)cc3)cc12,MRARPRPRPLWATVLALGALAGVGVGGPNICTTRGVSSCQQCLAVSPMCAWCSDEALPLGSPRCDLKENLLKDNCAPESIEFPVSEARVLEDRPLSDKGSGDSSQVTQVSPQRIALRLRPDDSKNFSIQVRQVEDYPVDIYYLMDLSYSMKDDLWSIQNLGTKLATQMRKLTSNLRIGFGAFVDKPVSPYMYISPPEALENPCYDMKTTCLPMFGYKHVLTLTDQVTRFNEEVKKQSVSRNRDAPEGGFDAIMQATVCDEKIGWRNDASHLLVFTTDAKTHIALDGRLAGIVQPNDGQCHVGSDNHYSASTTMDYPSLGLMTEKLSQKNINLIFAVTENVVNLYQNYSELIPGTTVGVLSMDSSNVLQLIVDAYGKIRSKVELEVRDLPEELSLSFNATCLNNEVIPGLKSCMGLKIGDTVSFSIEAKVRGCPQEKEKSFTIKPVGFKDSLIVQVTFDCDCACQAQAEPNSHRCNNGNGTFECGVCRCGPGWLGSQCECSEEDYRPSQQDECSPREGQPVCSQRGECLCGQCVCHSSDFGKITGKYCECDDFSCVRYKGEMCSGHGQCSCGDCLCDSDWTGYYCNCTTRTDTCMSSNGLLCSGRGKCECGSCVCIQPGSYGDTCEKCPTCPDACTFKKECVECKKFDRGALHDENTCNRYCRDEIESVKELKDTGKDAVNCTYKNEDDCVVRFQYYEDSSGKSILYVVEEPECPKGPDILVVLLSVMGAILLIGLAALLIWKLLITIHDRKEFAKFEEERARAKWDTANNPLYKEATSTFTNITYRGT,7.431798275933005 +Clc1ccccc1C(c1ccccc1)(c1ccccc1)n1ccnc1,MALSQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKNPHLALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDGQSLTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELMAGPGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFPILRYLPNPALQRFKAFNQRFLWFLQKTVQEHYQDFDKNSVRDITGALFKHSKKGPRASGNLIPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLSDRPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPELWEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLEFSVPPGVKVDLTPIYGLTMKHARCEHVQARRFSIN,5.903089986991944 +CC(C)(O)COc1cc(-c2ccc(nc2)N2CCC(C)(CC2)NC(=O)c2[nH]c(=O)ccc2F)c2c(cnn2c1)C#N,HCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIMEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,7.675717544702307 +OC(=O)c1ccc(CNC(=O)c2ccc3ccccc3c2)cc1,MVMQFQGLENPIQISPHCSCTPSGFFMEMMSMKPAKGVLTEQVAGPLGQNLEVEPYSQYSNVQFPQVQPQISSSSYYSNLGFYPQQPEEWYSPGIYELRRMPAETLYQGETEVAEMPVTKKPRMGASAGRIKGDELCVVCGDRASGYHYNALTCEGCKGFFRRSITKNAVYKCKNGGNCVMDMYMRRKCQECRLRKCKEMGMLAECMYTGLLTEIQCKSKRLRKNVKQHADQTVNEDSEGRDLRQVTSTTKSCREKTELTPDQQTLLHFIMDSYNKQRMPQEITNKILKEEFSAEENFLILTEMATNHVQVLVEFTKKLPGFQTLDHEDQIALLKGSAVEAMFLRSAEIFNKKLPSGHSDLLEERIRNSGISDEYITPMFSFYKSIGELKMTQEEYALLTAIVILSPDRQYIKDREAVEKLQEPLLDVLQKLCKIHQPENPQHFACLLGRLTELRTFNHHHAEMLMSWRVNDHKFTPLLCEIWDVQ,5.866461091629782 +CCCCCCCC\C=C/CCCCCCCCNC(=O)c1nn(c(c1C)-c1ccccc1)-c1ccccc1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,4.3979400086720375 +CCOC(=O)c1cnc(N2CCN(CC2)C(=O)NS(=O)(=O)c2ccc(F)cc2)c(Cl)c1,MQAVDNLTSAPGNTSLCTRDYKITQVLFPLLYTVLFFVGLITNGLAMRIFFQIRSKSNFIIFLKNTVISDLLMILTFPFKILSDAKLGTGPLRTFVCQVTSVIFYFTMYISISFLGLITIDRYQKTTRPFKTSNPKNLLGAKILSVVIWAFMFLLSLPNMILTNRQPRDKNVKKCSFLKSEFGLVWHEIVNYICQVIFWINFLIVIVCYTLITKELYRSYVRTRGVGKVPRKKVNVKVFIIIAVFFICFVPFHFARIPYTLSQTRDVFDCTAENTLFYVKESTLWLTSLNACLDPFIYFFLCKSFRNSLISMLKCPNSATSLSQDNRKKEQDGGDPNEETPM,6.327902142064283 +Cc1ccc(cc1)-c1noc2CCNCCc12,MMDVNSSGRPDLYGHLRSFLLPEVGRGLPDLSPDGGADPVAGSWAPHLLSEVTASPAPTWDAPPDNASGCGEQINYGRVEKVVIGSILTLITLLTIAGNCLVVISVCFVKKLRQPSNYLIVSLALADLSVAVAVMPFVSVTDLIGGKWIFGHFFCNVFIAMDVMCCTASIMTLCVISIDRYLGITRPLTYPVRQNGKCMAKMILSVWLLSASITLPPLFGWAQNVNDDKVCLISQDFGYTIYSTAVAFYIPMSVMLFMYYQIYKAARKSAAKHKFPGFPRVEPDSVIALNGIVKLQKEVEECANLSRLLKHERKNISIFKREQKAATTLGIIVGAFTVCWLPFFLLSTARPFICGTSCSCIPLWVERTFLWLGYANSLINPFIYAFFNRDLRTTYRSLLQCQYRNINRKLSAAGMHEALKLAERPERPEFVLRACTRRVLLRPEKRPPVSVWVLQSPDHHNWLADKMLTTVEKKVMIHD,6.070070439915412 +FC(F)(F)c1ccc(Nc2cc(=O)[nH]c3ccc(cc23)C(c2ccc(Cl)cc2)c2ccc(Cl)cc2)cc1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,8.154901959985743 +FC(F)Oc1ccccc1CC(N1CCNCC1)c1ccccc1F,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,5.187086643357144 +ClCC(=O)c1ccccc1,MKRSLRKMWRPGEKKEPQGVVYEDVPDDTEDFKESLKVVFEGSAYGLQNFNKQKKLKRCDDMDTFFLHYAAAEGQIELMEKITRDSSLEVLHEMDDYGNTPLHCAVEKNQIESVKFLLSRGANPNLRNFNMMAPLHIAVQGMNNEVMKVLLEHRTIDVNLEGENGNTAVIIACTTNNSEALQILLKKGAKPCKSNKWGCFPIHQAAFSGSKECMEIILRFGEEHGYSRQLHINFMNNGKATPLHLAVQNGDLEMIKMCLDNGAQIDPVEKGRCTAIHFAATQGATEIVKLMISSYSGSVDIVNTTDGCHETMLHRASLFDHHELADYLISVGADINKIDSEGRSPLILATASASWNIVNLLLSKGAQVDIKDNFGRNFLHLTVQQPYGLKNLRPEFMQMQQIKELVMDEDNDGCTPLHYACRQGGPGSVNNLLGFNVSIHSKSKDKKSPLHFAASYGRINTCQRLLQDISDTRLLNEGDLHGMTPLHLAAKNGHDKVVQLLLKKGALFLSDHNGWTALHHASMGGYTQTMKVILDTNLKCTDRLDEDGNTALHFAAREGHAKAVALLLSHNADIVLNKQQASFLHLALHNKRKEVVLTIIRSKRWDECLKIFSHNSPGNKCPITEMIEYLPECMKVLLDFCMLHSTEDKSCRDYYIEYNFKYLQCPLEFTKKTPTQDVIYEPLTALNAMVQNNRIELLNHPVCKEYLLMKWLAYGFRAHMMNLGSYCLGLIPMTILVVNIKPGMAFNSTGIINETSDHSEILDTTNSYLIKTCMILVFLSSIFGYCKEAGQIFQQKRNYFMDISNVLEWIIYTTGIIFVLPLFVEIPAHLQWQCGAIAVYFYWMNFLLYLQRFENCGIFIVMLEVILKTLLRSTVVFIFLLLAFGLSFYILLNLQDPFSSPLLSIIQTFSMMLGDINYRESFLEPYLRNELAHPVLSFAQLVSFTIFVPIVLMNLLIGLAVGDIAEVQKHASLKRIAMQVELHTSLEKKLPLWFLRKVDQKSTIVYPNKPRSGGMLFHIFCFLFCTGEIRQEIPNADKSLEMEILKQKYRLKDLTFLLEKQHELIKLIIQKMEIISETEDDDSHCSFQDRFKKEQMEQRNSRWNTVLRAVKAKTHHLEP,7.698970004336019 +CO\N=C(/COCc1cc(cc(c1)C(F)(F)F)C(F)(F)F)C(CCN1CCN(CC(=O)N(C(C)C)C(C)C)CC1)c1ccc(Cl)c(Cl)c1,MDNVLPVDSDLSPNISTNTSEPNQFVQPAWQIVLWAAAYTVIVVTSVVGNVVVMWIILAHKRMRTVTNYFLVNLAFAEASMAAFNTVVNFTYAVHNEWYYGLFYCKFHNFFPIAAVFASIYSMTAVAFDRYMAIIHPLQPRLSATATKVVICVIWVLALLLAFPQGYYSTTETMPSRVVCMIEWPEHPNKIYEKVYHICVTVLIYFLPLLVIGYAYTVVGITLWASEIPGDSSDRYHEQVSAKRKVVKMMIVVVCTFAICWLPFHIFFLLPYINPDLYLKKFIQQVYLAIMWLAMSSTMYNPIIYCCLNDRFRLGFKHAFRCCPFISAGDYEGLEMKSTRYLQTQGSVYKVSRLETTISTVVGAHEEEPEDGPKATPSSLDLTSNCSSRSDSKTMTESFSFSSNVLS,7.086186147616283 +CCN(CC)C(=O)c1ccc2NC(=O)OC[C@H](C)c3ccc(cc3C)[C@@H](Nc3ccc4c(N)nccc4c3)C(=O)N(C)Cc1c2,MGRPLHLVLLSASLAGLLLLGESLFIRREQANNILARVTRANSFLEEMKKGHLERECMEETCSYEEAREVFEDSDKTNEFWNKYKDGDQCETSPCQNQGKCKDGLGEYTCTCLEGFEGKNCELFTRKLCSLDNGDCDQFCHEEQNSVVCSCARGYTLADNGKACIPTGPYPCGKQTLERRKRSVAQATSSSGEAPDSITWKPYDAADLDPTENPFDLLDFNQTQPERGDNNLTRIVGGQECKDGECPWQALLINEENEGFCGGTILSEFYILTAAHCLYQAKRFKVRVGDRNTEQEEGGEAVHEVEVVIKHNRFTKETYDFDIAVLRLKTPITFRMNVAPACLPERDWAESTLMTQKTGIVSGFGRTHEKGRQSTRLKMLEVPYVDRNSCKLSSSFIITQNMFCAGYDTKQEDACQGDSGGPHVTRFKDTYFVTGIVSWGEGCARKGKYGIYTKVTAFLKWIDRSMKTRGLPKAKSHAPEVITSSPLK,5.366531544420414 +CN1CC[C@@]23[C@H]4Oc5c2c(C[C@@H]1[C@@H]3C=C[C@@H]4O)ccc5O,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,6.9083330424043154 +C[C@H](NC(=O)[C@H](Cc1ccc(OCc2ccccc2)cc1)NC(=O)OC(C)(C)C)C(=O)N[C@@H](C[C@]1(O)C(=O)Nc2ccccc12)C(=O)NC(c1ccccc1)c1ccccc1,MLRAGAPTGDLPRAGEVHTGTTIMAVEFDGGVVMGSDSRVSAGEAVVNRVFDKLSPLHERIYCALSGSAADAQAVADMAAYQLELHGIELEEPPLVLAAANVVRNISYKYREDLSAHLMVAGWDQREGGQVYGTLGGMLTRQPFAIGGSGSTFIYGYVDAAYKPGMSPEECRRFTTDAIALAMSRDGSSGGVIYLVTITAAGVDHRVILGNELPKFYDE,5.3979400086720375 +COC1=C(OC)C(O)(CCn2cnc3c(N)ncnc23)OC1=O,MAQTPAFNKPKVELHVHLDGAIKPETILYYGRKRGIALPADTPEELQNIIGMDKPLSLPEFLAKFDYYMPAIAGCREAVKRIAYEFVEMKAKDGVVYVEVRYSPHLLANSKVEPIPWNQAEGDLTPDEVVSLVNQGLQEGERDFGVKVRSILCCMRHQPSWSSEVVELCKKYREQTVVAIDLAGDETIEGSSLFPGHVKAYAEAVKSGVHRTVHAGEVGSANVVKEAVDTLKTERLGHGYHTLEDATLYNRLRQENMHFEVCPWSSYLTGAWKPDTEHPVVRFKNDQVNYSLNTDDPLIFKSTLDTDYQMTKNEMGFTEEEFKRLNINAAKSSFLPEDEKKELLDLLYKAYGMPSPASAEQCL,3.0969100130080562 +Cc1cccc(c1)C#Cc1ccc(CCC(O)=O)c(F)c1,MDLPPQLSFGLYVAAFALGFPLNVLAIRGATAHARLRLTPSLVYALNLGCSDLLLTVSLPLKAVEALASGAWPLPASLCPVFAVAHFFPLYAGGGFLAALSAGRYLGAAFPLGYQAFRRPCYSWGVCAAIWALVLCHLGLVFGLEAPGGWLDHSNTSLGINTPVNGSPVCLEAWDPASAGPARFSLSLLLFFLPLAITAFCYVGCLRALARSGLTHRRKLRAAWVAGGALLTLLLCVGPYNASNVASFLYPNLGGSWRKLGLITGAWSVVLNPLVTGYLGRGPGLKTVCAARTQGGKSQK,7.657577319177793 +CSc1sc(cc1-c1csc(Nc2ccc(cc2)C2CCCCC2)n1)C(N)=N,MRALLARLLLCVLVVSDSKGSNELHQVPSNCDCLNGGTCVSNKYFSNIHWCNCPKKFGGQHCEIDKSKTCYEGNGHFYRGKASTDTMGRPCLPWNSATVLQQTYHAHRSDALQLGLGKHNYCRNPDNRRRPWCYVQVGLKPLVQECMVHDCADGKKPSSPPEELKFQCGQKTLRPRFKIIGGEFTTIENQPWFAAIYRRHRGGSVTYVCGGSLISPCWVISATHCFIDYPKKEDYIVYLGRSRLNSNTQGEMKFEVENLILHKDYSADTLAHHNDIALLKIRSKEGRCAQPSRTIQTICLPSMYNDPQFGTSCEITGFGKENSTDYLYPEQLKMTVVKLISHRECQQPHYYGSEVTTKMLCAADPQWKTDSCQGDSGGPLVCSLQGRMTLTGIVSWGRGCALKDKPGVYTRVSHFLPWIRSHTKEENGLAL,6.958607314841775 +Cn1c(nnc1C1(CCC1)c1ccc(Cl)cc1)-c1ccc(cc1)C(=O)N1CCCC1,MERWPWPSGGAWLLVAARALLQLLRSDLRLGRPLLAALALLAALDWLCQRLLPPPAALAVLAAAGWIALSRLARPQRLPVATRAVLITGCDSGFGKETAKKLDSMGFTVLATVLELNSPGAIELRTCCSPRLRLLQMDLTKPGDISRVLEFTKAHTTSTGLWGLVNNAGHNEVVADAELSPVATFRSCMEVNFFGALELTKGLLPLLRSSRGRIVTVGSPAGDMPYPCLGAYGTSKAAVALLMDTFSCELLPWGVKVSIIQPGCFKTESVRNVGQWEKRKQLLLANLPQELLQAYGKDYIEHLHGQFLHSLRLAMSDLTPVVDAITDALLAARPRRRYYPGQGLGLMYFIHYYLPEGLRRRFLQAFFISHCLPRALQPGQPGTTPPQDAAQDPNLSPGPSPAVAR,5.3979400086720375 +CN1CCN(CC1)c1cc(Nc2cc(C)n[nH]2)nc(C=Cc2ccccc2)n1,MRGARGAWDFLCVLLLLLRVQTGSSQPSVSPGEPSPPSIHPGKSDLIVRVGDEIRLLCTDPGFVKWTFEILDETNENKQNEWITEKAEATNTGKYTCTNKHGLSNSIYVFVRDPAKLFLVDRSLYGKEDNDTLVRCPLTDPEVTNYSLKGCQGKPLPKDLRFIPDPKAGIMIKSVKRAYHRLCLHCSVDQEGKSVLSEKFILKVRPAFKAVPVVSVSKASYLLREGEEFTVTCTIKDVSSSVYSTWKRENSQTKLQEKYNSWHHGDFNYERQATLTISSARVNDSGVFMCYANNTFGSANVTTTLEVVDKGFINIFPMINTTVFVNDGENVDLIVEYEAFPKPEHQQWIYMNRTFTDKWEDYPKSENESNIRYVSELHLTRLKGTEGGTYTFLVSNSDVNAAIAFNVYVNTKPEILTYDRLVNGMLQCVAAGFPEPTIDWYFCPGTEQRCSASVLPVDVQTLNSSGPPFGKLVVQSSIDSSAFKHNGTVECKAYNDVGKTSAYFNFAFKGNNKEQIHPHTLFTPLLIGFVIVAGMMCIIVMILTYKYLQKPMYEVQWKVVEEINGNNYVYIDPTQLPYDHKWEFPRNRLSFGKTLGAGAFGKVVEATAYGLIKSDAAMTVAVKMLKPSAHLTEREALMSELKVLSYLGNHMNIVNLLGACTIGGPTLVITEYCCYGDLLNFLRRKRDSFICSKQEDHAEAALYKNLLHSKESSCSDSTNEYMDMKPGVSYVVPTKADKRRSVRIGSYIERDVTPAIMEDDELALDLEDLLSFSYQVAKGMAFLASKNCIHRDLAARNILLTHGRITKICDFGLARDIKNDSNYVVKGNARLPVKWMAPESIFNCVYTFESDVWSYGIFLWELFSLGSSPYPGMPVDSKFYKMIKEGFRMLSPEHAPAEMYDIMKTCWDADPLKRPTFKQIVQLIEKQISESTNHIYSNLANCSPNRQKPVVDHSVRINSVGSTASSSQPLLVHDDV,6.920818753952375 +Clc1ccc2[nH]cc([C@H]3CC(=O)NC3=O)c2c1,MAHAMENSWTISKEYHIDEEVGFALPNPQENLPDFYNDWMFIAKHLPDLIESGQLRERVEKLNMLSIDHLTDHKSQRLARLVLGCITMAYVWGKGHGDVRKVLPRNIAVPYCQLSKKLELPPILVYADCVLANWKKKDPNKPLTYENMDVLFSFRDGDCSKGFFLVSLLVEIAAASAIKVIPTVFKAMQMQERDTLLKALLEIASCLEKALQVFHQIHDHVNPKAFFSVLRIYLSGWKGNPQLSDGLVYEGFWEDPKEFAGGSAGQSSVFQCFDVLLGIQQTAGGGHAAQFLQDMRRYMPPAHRNFLCSLESNPSVREFVLSKGDAGLREAYDACVKALVSLRSYHLQIVTKYILIPASQQPKENKTSEDPSKLEAKGTGGTDLMNFLKTVRSTTEKSLLKEG,5.657577319177793 +CCCCCC(=O)N1CCC[C@H]1C(=O)N(C)[C@@H](C(C)CC)C(=O)N[C@@H](CCNC(=O)c1ccccc1)C(=O)NO,MRLTVLCAVCLLPGSLALPLPQEAGGMSELQWEQAQDYLKRFYLYDSETKNANSLEAKLKEMQKFFGLPITGMLNSRVIEIMQKPRCGVPDVAEYSLFPNSPKWTSKVVTYRIVSYTRDLPHITVDRLVSKALNMWGKEIPLHFRKVVWGTADIMIGFARGAHGDSYPFDGPGNTLAHAFAPGTGLGGDAHFDEDERWTDGSSLGINFLYAATHELGHSLGMGHSSDPNAVMYPTYGNGDPQNFKLSQDDIKGIQKLYGKRSNSRKK,1.3851027839668653 +CCn1c(=O)n(Cc2ccccc2)c2nc(Cc3cccs3)n(C)c2c1=O,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,6.119998611678231 +Cc1cnccc1C(=O)N[C@@H]1CC[C@@]2(O)[C@H]3Cc4ccc(O)c5O[C@@H]1[C@]2(CCN3CC1CC1)c45,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,8.823908740944319 +C[C@H]1CC[C@@H](CC1)C(=O)N(CC(=O)N1CCOCC1)c1cc(sc1C(O)=O)C#CC(C)(C)C,SGSWLRDVWDWICTVLTDFKTWLQSKLLPRIPGVPFLSCQRGYKGVWRGDGIMHTTCPCGAQITGHVKNGSMRIVGPKTCSNTWHGTFPINTYTTGPCTPSPAPNYSRALWRVAAEEYVEVTRVGDFHYVTGMTTDNVKCPCQVPAPEFFTEVDGVRLHRYAPACKPLLREEVTFMVGLNQYLVGSQLPCEPEPDVTVLTSMLTDPSHITAETAGRRLARGSPPSLASSSASQLSAPSLKATCTTRHDSPDADLIEANLLWRQEMGGNITRVESENKVVILDSFDPLQAEEDEREVSVPAEILRKSRKFPRAMPIWARPDYNPPLLESWKDPDYVPPVVHGCPLPPAKAPPIPPPRRKRTVVLTESTVSSALAELATKTFGSSGSSAVDSGTATAPPDQLPGDGDSGSDVESYSSMPPLEGEPGDPDLSDGSWSTMSEEASEDVVCC,5.318758762624412 +C[C@@H](Oc1cc(sc1C(N)=O)-n1cnc2ccc(CN3CCN(C)CC3)cc12)c1ccccc1C(F)(F)F,MSAIQAAWPSGTECIAKYNFHGTAEQDLPFCKGDVLTIVAVTKDPNWYKAKNKVGREGIIPANYVQKREGVKAGTKLSLMPWFHGKITREQAERLLYPPETGLFLVRESTNYPGDYTLCVSCDGKVEHYRIMYHASKLSIDEEVYFENLMQLVEHYTSDADGLCTRLIKPKVMEGTVAAQDEFYRSGWALNMKELKLLQTIGKGEFGDVMLGDYRGNKVAVKCIKNDATAQAFLAEASVMTQLRHSNLVQLLGVIVEEKGGLYIVTEYMAKGSLVDYLRSRGRSVLGGDCLLKFSLDVCEAMEYLEGNNFVHRDLAARNVLVSEDNVAKVSDFGLTKEASSTQDTGKLPVKWTAPEALREKKFSTKSDVWSFGILLWEIYSFGRVPYPRIPLKDVVPRVEKGYKMDAPDGCPPAVYEVMKNCWHLDAAMRPSFLQLREQLEHIKTHELHL,5.0 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+COc1ccc(F)cc1-c1ccnc(Nc2ccc(cc2)S(=O)(=O)Nc2nnc(C)s2)n1,MAKQYDSVECPFCDEVSKYEKLAKIGQGTFGEVFKARHRKTGQKVALKKVLMENEKEGFPITALREIKILQLLKHENVVNLIEICRTKASPYNRCKGSIYLVFDFCEHDLAGLLSNVLVKFTLSEIKRVMQMLLNGLYYIHRNKILHRDMKAANVLITRDGVLKLADFGLARAFSLAKNSQPNRYTNRVVTLWYRPPELLLGERDYGPPIDLWGAGCIMAEMWTRSPIMQGNTEQHQLALISQLCGSITPEVWPNVDNYELYEKLELVKGQKRKVKDRLKAYVRDPYALDLIDKLLVLDPAQRIDSDDALNHDFFWSDPMPSDLKGMLSTHLTSMFEYLAPPRRKGSQITQQSTNQSRNPATTNQTEFERVF,8.045757490560675 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+CC(C)=CCC\C(C)=C/COC(=O)c1cccc(C)c1,MKRSLRRVLRPEERKEVQGVVYRGVGKDMDCSKESFKVDIEGDMCRLEAFIKNRRKLSKYEDENLCLLHHAAAEGQVELMQLIINGSSCEALNVMDDYGNTPLHWAAEKNQVESVKFLLSQGANPNLRNRNMMAPLHIAVQGMYNEVIKVLTEHKATNINLEGENGNTALMSTCAKDNSEALQILLEKGAKLCKSNKWGDYPVHQAAFSGAKRCMELILAYGEKTGYSREAHINFVNHKKASPLHLAVQSGDLDMIKMCLDSGAHIDMMENAKCMALHFAATQGATDIVKLMISSYTGSSDIVNAVDGNQETLLHRASLFDHHDLADYLISVGADINSTDSEGRSPLILATASASWNIVNLLLSKGAKVDIKDHLGRNFLHLTVQQPYGLRNLRPEFLQMQHIKELVMDEDNDGCTPLHYACRQGAPVSVNNLLRFNVSVHSKSKDKKSPLHFAASYGRINTCQRLLQDISDTRLLNEGDLHGMTPLHLAAKNGHDKVVQLLLKKGALFLSDHNGWTALHHASMGGYTQTMKVILDTNLKCTDRLDEEGNTALHFAAREGHAKAVAMLLSYNADILLNKKQASFLHIALHNKRKEVVLTTIRSKRWDECLQVFTHDSPSNRCPIMEMVEYLPECMKVLLDFCMIPSTEDKSCQDYHIEYNFKYLQCPLSMTKKVTPTQDVIYEPLTILNVMVQHNRIELLNHPVCREYLLMKWCAYGFRAHMMNLGSYCLGLIPMTLLVVKIQPGMAFNSTGIINETISTHEERINTLNSFPLKICMILVFLSSIFGYCKEVVQIFQQKRNYFLDYNNALEWVIYTTSMIFVLPLFLDIPAYMQWQCGAIAIFFYWMNFLLYLQRFENCGIFIVMLEVIFKTLLRSTGVFIFLLLAFGLSFYVLLNFQDAFSTPLLSLIQTFSMMLGDINYRDAFLEPLFRNELAYPVLTFGQLIAFTMFVPIVLMNLLIGLAVGDIAEVQKHASLKRIAMQVELHTNLEKKLPFWYLRKVDQRSTIVYPNRPRHGRMLRFFHYFLSMQETRQEAPNIDTCLEMEILKQKYRLKDLTSLLEKQHELIKLIIQKMEIISETEDEDNHCSFQDRFKKERLEQMHSKWNFVLNAVKTKTHCSISHPDI,6.853871964321762 +Oc1c2[C@H]3CC[C@H](C3)n2c(=O)n1-c1ccc([N+]([O-])=O)c2ccccc12,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAPPGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLVLDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGPTFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGTSTISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAECKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYKSGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYGDLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGGGGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMDSYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASSTTSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,5.886056647693163 +CCCCS(=O)(=O)N1CCC(CC1)[C@@H](NS(=O)(=O)c1ccc(s1)-c1ccc(OCC)cc1)C(O)=O,MHPGVLAAFLFLSWTHCRALPLPSGGDEDDLSEEDLQFAERYLRSYYHPTNLAGILKENAASSMTERLREMQSFFGLEVTGKLDDNTLDVMKKPRCGVPDVGEYNVFPRTLKWSKMNLTYRIVNYTPDMTHSEVEKAFKKAFKVWSDVTPLNFTRLHDGIADIMISFGIKEHGDFYPFDGPSGLLAHAFPPGPNYGGDAHFDDDETWTSSSKGYNLFLVAAHEFGHSLGLDHSKDPGALMFPIYTYTGKSHFMLPDDDVQGIQSLYGPGDEDPNPKHPKTPDKCDPSLSLDAITSLRGETMIFKDRFFWRLHPQQVDAELFLTKSFWPELPNRIDAAYEHPSHDLIFIFRGRKFWALNGYDILEGYPKKISELGLPKEVKKISAAVHFEDTGKTLLFSGNQVWRYDDTNHIMDKDYPRLIEEDFPGIGDKVDAVYEKNGYIYFFNGPIQFEYSIWSNRIVRVMPANSILWC,8.397940008672037 +CCC1C2CC(Oc3ccc(cn3)C(F)(F)F)C(C2)N1C(=O)c1nc(C)ccc1-n1nccn1,MSGTKLEDSPPCRNWSSASELNETQEPFLNPTDYDDEEFLRYLWREYLHPKEYEWVLIAGYIIVFVVALIGNVLVCVAVWKNHHMRTVTNYFIVNLSLADVLVTITCLPATLVVDITETWFFGQSLCKVIPYLQTVSVSVSVLTLSCIALDRWYAICHPLMFKSTAKRARNSIVIIWIVSCIIMIPQAIVMECSTVFPGLANKTTLFTVCDERWGGEIYPKMYHICFFLVTYMAPLCLMVLAYLQIFRKLWCRQIPGTSSVVQRKWKPLQPVSQPRGPGQPTKSRMSAVAAEIKQIRARRKTARMLMIVLLVFAICYLPISILNVLKRVFGMFAHTEDRETVYAWFTFSHWLVYANSAANPIIYNFLSGKFREEFKAAFSCCCLGVHHRQEDRLTRGRTSTESRKSLTTQISNFDNISKLSEQVVLTSISTLPAANGAGPLQNW,6.286509456906058 +CC(C)C[C@H](NC(=O)[C@@H](N)CCC(N)=O)C(=O)N[C@@H](CC(O)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C)C(=O)N[C@@H](CC(O)=O)C(=O)NCC(O)=O,MMFSGFNADYEASSSRCSSASPAGDSLSYYHSPADSFSSMGSPVNAQDFCTDLAVSSANFIPTVTAISTSPDLQWLVQPALVSSVAPSQTRAPHPFGVPAPSAGAYSRAGVVKTMTGGRAQSIGRRGKVEQLSPEEEEKRRIRRERNKMAAAKCRNRRRELTDTLQAETDQLEDEKSALQTEIANLLKEKEKLEFILAAHRPACKIPDDLGFPEEMSVASLDLTGGLPEVATPESEEAFTLPLLNDPEPKPSVEPVKSISSMELKTEPFDDFLFPASSRPSGSETARSVPDMDLSGSFYAADWEPLHSGSLGMGPMATELEPLCTPVVTCTPSCTAYTSSFVFTYPEADSFPSCAAAHRKGSSSNEPSSDSLSSPTLLAL,4.0 +CCOc1ccc(cc1-c1cc(C(=O)NCc2c(C)cc(C)[nH]c2=O)c2cnn(C3CCCC3)c2c1)S(=O)(=O)N1CCN(C)CC1,MGQTGKKSEKGPVCWRKRVKSEYMRLRQLKRFRRADEVKSMFSSNRQKILERTEILNQEWKQRRIQPVHILTSVSSLRGTRECSVTSDLDFPTQVIPLKTLNAVASVPIMYSWSPLQQNFMVEDETVLHNIPYMGDEVLDQDGTFIEELIKNYDGKVHGDRECGFINDEIFVELVNALGQYNDDDDDDDGDDPEEREEKQKDLEDHRDDKESRPPRKFPSDKIFEAISSMFPDKGTAEELKEKYKELTEQQLPGALPPECTPNIDGPNAKSVQREQSLHSFHTLFCRRCFKYDCFLHPFHATPNTYKRKNTETALDNKPCGPQCYQHLEGAKEFAAALTAERIKTPPKRPGGRRRGRLPNNSSRPSTPTINVLESKDTDSDREAGTETGGENNDKEEEEKKDETSSSSEANSRCQTPIKMKPNIEPPENVEWSGAEASMFRVLIGTYYDNFCAIARLIGTKTCRQVYEFRVKESSIIAPAPAEDVDTPPRKKKRKHRLWAAHCRKIQLKKDGSSNHVYNYQPCDHPRQPCDSSCPCVIAQNFCEKFCQCSSECQNRFPGCRCKAQCNTKQCPCYLAVRECDPDLCLTCGAADHWDSKNVSCKNCSIQRGSKKHLLLAPSDVAGWGIFIKDPVQKNEFISEYCGEIISQDEADRRGKVYDKYMCSFLFNLNNDFVVDATRKGNKIRFANHSVNPNCYAKVMMVNGDHRIGIFAKRAIQTGEELFFDYRYSQADALKYVGIEREMEIP,6.522878745280337 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+COc1ccc(cc1)C(=O)NCCCNc1nc2cc(C)cc(C)c2cc1C#N,MQRSPLEKASVVSKLFFSWTRPILRKGYRQRLELSDIYQIPSVDSADNLSEKLEREWDRELASKKNPKLINALRRCFFWRFMFYGIFLYLGEVTKAVQPLLLGRIIASYDPDNKEERSIAIYLGIGLCLLFIVRTLLLHPAIFGLHHIGMQMRIAMFSLIYKKTLKLSSRVLDKISIGQLVSLLSNNLNKFDEGLALAHFVWIAPLQVALLMGLIWELLQASAFCGLGFLIVLALFQAGLGRMMMKYRDQRAGKISERLVITSEMIENIQSVKAYCWEEAMEKMIENLRQTELKLTRKAAYVRYFNSSAFFFSGFFVVFLSVLPYALIKGIILRKIFTTISFCIVLRMAVTRQFPWAVQTWYDSLGAINKIQDFLQKQEYKTLEYNLTTTEVVMENVTAFWEEGFGELFEKAKQNNNNRKTSNGDDSLFFSNFSLLGTPVLKDINFKIERGQLLAVAGSTGAGKTSLLMVIMGELEPSEGKIKHSGRISFCSQFSWIMPGTIKENIIFGVSYDEYRYRSVIKACQLEEDISKFAEKDNIVLGEGGITLSGGQRARISLARAVYKDADLYLLDSPFGYLDVLTEKEIFESCVCKLMANKTRILVTSKMEHLKKADKILILHEGSSYFYGTFSELQNLQPDFSSKLMGCDSFDQFSAERRNSILTETLHRFSLEGDAPVSWTETKKQSFKQTGEFGEKRKNSILNPINSIRKFSIVQKTPLQMNGIEEDSDEPLERRLSLVPDSEQGEAILPRISVISTGPTLQARRRQSVLNLMTHSVNQGQNIHRKTTASTRKVSLAPQANLTELDIYSRRLSQETGLEISEEINEEDLKECFFDDMESIPAVTTWNTYLRYITVHKSLIFVLIWCLVIFLAEVAASLVVLWLLGNTPLQDKGNSTHSRNNSYAVIITSTSSYYVFYIYVGVADTLLAMGFFRGLPLVHTLITVSKILHHKMLHSVLQAPMSTLNTLKAGGILNRFSKDIAILDDLLPLTIFDFIQLLLIVIGAIAVVAVLQPYIFVATVPVIVAFIMLRAYFLQTSQQLKQLESEGRSPIFTHLVTSLKGLWTLRAFGRQPYFETLFHKALNLHTANWFLYLSTLRWFQMRIEMIFVIFFIAVTFISILTTGEGEGRVGIILTLAMNIMSTLQWAVNSSIDVDSLMRSVSRVFKFIDMPTEGKPTKSTKPYKNGQLSKVMIIENSHVKKDDIWPSGGQMTVKDLTAKYTEGGNAILENISFSISPGQRVGLLGRTGSGKSTLLSAFLRLLNTEGEIQIDGVSWDSITLQQWRKAFGVIPQKVFIFSGTFRKNLDPYEQWSDQEIWKVADEVGLRSVIEQFPGKLDFVLVDGGCVLSHGHKQLMCLARSVLSKAKILLLDEPSAHLDPVTYQIIRRTLKQAFADCTVILCEHRIEAMLECQQFLVIEENKVRQYDSIQKLLNERSLFRQAISPSDRVKLFPHRNSSKCKSKPQIAALKEETEEEVQDTRL,5.36997914888659 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+OS([O-])=O,MASPDWGYDDKNGPEQWSKLYPIANGNNQSPVDIKTSETKHDTSLKPISVSYNPATAKEIINVGHSFHVNFEDNDNRSVLKGGPFSDSYRLFQFHFHWGSTNEHGSEHTVDGVKYSAELHVAHWNSAKYSSLAEAASKADGLAVIGVLMKVGEANPKLQKVLDALQAIKTKGKRAPFTNFDPSTLLPSSLDFWTYPGSLTHPPLYESVTWIICKESISVSSEQLAQFRSLLSNVEGDNAVPMQHNNRPTQPLKGRTVRASF,1.7447274948966938 +COc1ccc(cc1)-n1c(O)c2C3CCCN3C(C(=O)c3ccccc3)c2c1O,MDDIADRMRMDAGEVTLVNHNSVFKTHLLPQTGFPEDQLSLSDQQILSSRQGHLDRSFTCSTRSAAYNPSYYSDNPSSDSFLGSGDLRTFGQSANGQWRNSTPSSSSSLQKSRNSRSLYLETRKTSSGLSNSFAGKSNHHCHVSAYEKSFPIKPVPSPSWSGSCRRSLLSPKKTQRRHVSTAEETVQEEEREIYRQLLQMVTGKQFTIAKPTTHFPLHLSRCLSSSKNTLKDSLFKNGNSCASQIIGSDTSSSGSASILTNQEQLSHSVYSLSSYTPDVAFGSKDSGTLHHPHHHHSVPHQPDNLAASNTQSEGSDSVILLKVKDSQTPTPSSTFFQAELWIKELTSVYDSRARERLRQIEEQKALALQLQNQRLQEREHSVHDSVELHLRVPLEKEIPVTVVQETQKKGHKLTDSEDEFPEITEEMEKEIKNVFRNGNQDEVLSEAFRLTITRKDIQTLNHLNWLNDEIINFYMNMLMERSKEKGLPSVHAFNTFFFTKLKTAGYQAVKRWTKKVDVFSVDILLVPIHLGVHWCLAVVDFRKKNITYYDSMGGINNEACRILLQYLKQESIDKKRKEFDTNGWQLFSKKSQEIPQQMNGSDCGMFACKYADCITKDRPINFTQQHMPYFRKRMVWEILHRKLL,4.958607314841775 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+CC(C)COc1cccc(c1)-c1cc(COC(C)(C)C(O)=O)nn1Cc1ccccc1Cl,MPPAVGGPVGYTPPDGGWGWAVVIGAFISIGFSYAFPKSITVFFKEIEGIFHATTSEVSWISSIMLAVMYGGGPISSILVNKYGSRIVMIVGGCLSGCGLIAASFCNTVQQLYVCIGVIGGLGLAFNLNPALTMIGKYFYKRRPLANGLAMAGSPVFLCTLAPLNQVFFGIFGWRGSFLILGGLLLNCCVAGALMRPIGPKPTKAGKDKSKASLEKAGKSGVKKDLHDANTDLIGRHPKQEKRSVFQTINQFLDLTLFTHRGFLLYLSGNVIMFFGLFAPLVFLSSYGKSQHYSSEKSAFLLSILAFVDMVARPSMGLVANTKPIRPRIQYFFAASVVANGVCHMLAPLSTTYVGFCVYAGFFGFAFGWLSSVLFETLMDLVGPQRFSSAVGLVTIVECCPVLLGPPLLGRLNDMYGDYKYTYWACGVVLIISGIYLFIGMGINYRLLAKEQKANEQKKESKEEETSIDVAGKPNEVTKAAESPDQKDTDGGPKEEESPV,6.519993057042849 +C[C@@H](Oc1ccccc1)[C@@H]1NC(=O)[C@H](CCCCN)NC(=O)[C@@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](Cc2ccccc2)NCCCCCCNC1=O,MDMLHPSSVSTTSEPENASSAWPPDATLGNVSAGPSPAGLAVSGVLIPLVYLVVCVVGLLGNSLVIYVVLRHTASPSVTNVYILNLALADELFMLGLPFLAAQNALSYWPFGSLMCRLVMAVDGINQFTSIFCLTVMSVDRYLAVVHPTRSARWRTAPVARTVSAAVWVASAVVVLPVVVFSGVPRGMSTCHMQWPEPAAAWRAGFIIYTAALGFFGPLLVICLCYLLIVVKVRSAGRRVWAPSCQRRRRSERRVTRMVVAVVALFVLCWMPFYVLNIVNVVCPLPEEPAFFGLYFLVVALPYANSCANPILYGFLSYRFKQGFRRVLLRPSRRVRSQEPTVGPPEKTEEEDEEEEDGEESREGGKGKEMNGRVSQITQPGTSGQERPPSRVASKEQQLLPQEASTGEKSSTMRISYL,6.880018692695846 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+Clc1cccc(c1)S(=O)(=O)NC(=O)N1CCC(CC1)N1CCC(CC1)Oc1ccc(Cl)c(Cl)c1,MTTSLDTVETFGTTSYYDDVGLLCEKADTRALMAQFVPPLYSLVFTVGLLGNVVVVMILIKYRRLRIMTNIYLLNLAISDLLFLVTLPFWIHYVRGHNWVFGHGMCKLLSGFYHTGLYSEIFFIILLTIDRYLAIVHAVFALRARTVTFGVITSIVTWGLAVLAALPEFIFYETEELFEETLCSALYPEDTVYSWRHFHTLRMTIFCLVLPLLVMAICYTGIIKTLLRCPSKKKYKAIRLIFVIMAVFFIFWTPYNVAILLSSYQSILFGNDCERSKHLDLVMLVTEVIAYSHCCMNPVIYAFVGERFRKYLRHFFHRHLLMHLGRYIPFLPSEKLERTSSVSPSTAEPELSIVF,8.199970640755865 +Cn1c2nc[nH]c2c(=O)n(C)c1=O,MPPSISAFQAAYIGIEVLIALVSVPGNVLVIWAVKVNQALRDATFCFIVSLAVADVAVGALVIPLAILINIGPRTYFHTCLKVACPVLILTQSSILALLAIAVDRYLRVKIPLRYKTVVTPRRAVVAITGCWILSFVVGLTPMFGWNNLSAVERDWLANGSVGEPVIECQFEKVISMEYMVYFNFFVWVLPPLLLMVLIYMEVFYLIRKQLNKKVSASSGDPQKYYGKELKIAKSLALILFLFALSWLPLHILNCITLFCPSCHMPRILIYIAIFLSHGNSAMNPIVYAFRIQKFRVTFLKIWNDHFRCQPAPPVDEDAPAERPDD,5.614393726401688 +CN[C@]1(CC[C@]2(CN(CC(=O)NCCOCCOCCOCCOCCOCCOCCOC)C(=O)N2CC2CCC2)CC1)c1ccccc1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,5.920818753952375 +OCCCNC(=O)Nc1ccc2ncc(nc2n1)-c1ccccc1,MSQERPTFYRQELNKTIWEVPERYQNLSPVGSGAYGSVCAAFDTKTGLRVAVKKLSRPFQSIIHAKRTYRELRLLKHMKHENVIGLLDVFTPARSLEEFNDVYLVTHLMGADLNNIVKCQKLTDDHVQFLIYQILRGLKYIHSADIIHRDLKPSNLAVNEDCELKILDFGLARHTDDEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLTGRTLFPGTDHIDQLKLILRLVGTPGAELLKKISSESARNYIQSLTQMPKMNFANVFIGANPLAVDLLEKMLVLDSDKRITAAQALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES,4.0 +CC(C)(O)COc1cc(-c2ccc(nc2)N2C[C@@H]3C[C@H](C2)[C@@H]3Nc2ccccn2)c2c(cnn2c1)C#N,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIMEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,7.07727454200674 +Nc1ccc(cc1)-c1nc2c(ncnc2o1)N1CC2CCN(Cc3ccccc3)C2C1,MAAAEEEPKPKKLKVEAPQALRENILFGMGNPLLDISAVVDKDFLDKYSLKPNDQILAEDKHKELFDELVKKFKVEYHAGGSTQNSIKVAQWMIQQPHKAATFFGCIGIDKFGEILKRKAAEAHVDAHYYEQNEQPTGTCAACITGDNRSLIANLAAANCYKKEKHLDLEKNWMLVEKARVCYIAGFFLTVSPESVLKVAHHASENNRIFTLNLSAPFISQFYKESLMKVMPYVDILFGNETEAATFAREQGFETKDIKEIAKKTQALPKMNSKRQRIVIFTQGRDDTIMATESEVTAFAVLDQDQKEIIDTNGAGDAFVGGFLSQLVSDKPLTECIRAGHYAASIIIRRTGCTFPEKPDFH,7.301029995663981 +Fc1cc(N[C@H]2CCCC[C@@H]2N2CCCC2)c(Cl)cc1S(=O)(=O)Nc1ccncn1,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,6.703334809738469 +COc1ccc(Cl)cc1NC(=O)NC1CCCCC1,MAPPGMRLRSGRSTGAPLTRGSCRKRNRSPERCDLGDDLHLQPRRKHVADSVDGRECGPHTLPIPGSPTVFTSGLPAFVSSPTLPVAPIPSPAPATPLPPPALLPPVTTSSSPIPPSHPVSPGTTDTHSPSPALPPTQSPESSQRPPLSSPTGRPDSSTPMRPPPSQQTTPPHSPTTPPPEPPSKSSPDSLAPSTLRSLRKRRLSSPQGPSTLNPICQSPPVSPPRCDFANRSVYPPWATESPIYVGSSSDGDTPPRQPPTSPISIGSSSPSEGSWGDDTAMLVLLAEIAEEASKNEKECSENNQAGEDNGDNEISKESQVDKDDNDNKDDEEEQETDEEDEEDDEEDDEEDDEEDDEEDDEEDDEEDDEEEDEEEDEEEDEEEDEEEEEDEEDDDDEDNEDEEDDEEEDKKEDEEDGGDGNKTLSIQSSQQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQREPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQEPQQQDEQQQDEQQQDEQQQDEQQQDEQQQDEQQQDEQQQDEQEQQDEQQQDEQQQQDEQEQQEEQEQQEEQQQDEQQQDEQQQDEQQQDEQEQQDEQQQDEQQQQDEQEQQEEQEQQEEQEQQEEQEQQEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQELEEQEQEQELEEVEEQEQEQEEQELEEVEEQEQEQEEQEEQELEEVEEQEEQELEEVEEQEEQELEEVEEQEQQGVEQQEQETVEEPIILHGSSSEDEMEVDYPVVSTHEQIASSPPGDNTPDDDPQPGPSREYRYVLRTSPPHRPGVRMRRVPVTHPKKPHPRYQQPPVPYRQIDDCPAKARPQHIFYRRFLGKDGRRDPKCQWKFAVIFWGNDPYGLKKLSQAFQFGGVKAGPVSCLPHPGPDQSPITYCVYVYCQNKDTSKKVQMARLAWEASHPLAGNLQSSIVKFKKPLPLTQPGENQGPGDSPQEMT,4.1249387366083 +CCOC(=O)CCCN1CCC(CC1)n1cc(NC(=O)c2c(N)nn3cccnc23)c(n1)-c1cc(Cl)ccc1OC(F)F,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,9.886056647693163 +CN(CC1CCN(CC1)C(=O)OCc1ccc(C)cc1)c1ncccn1,MKPRAECCSPKFWLVLAVLAVSGSRARSQKSPPSIGIAVILVGTSDEVAIKDAHEKDDFHHLSVVPRVELVAMNETDPKSIITRICDLMSDRKIQGVVFADDTDQEAIAQILDFISAQTLTPILGIHGGSSMIMADKDESSMFFQFGPSIEQQASVMLNIMEEYDWYIFSIVTTYFPGYQDFVNKIRSTIENSFVGWELEEVLLLDMSLDDGDSKIQNQLKKLQSPIILLYCTKEEATYIFEVANSVGLTGYGYTWIVPSLVAGDTDTVPAEFPTGLISVSYDEWDYGLPARVRDGIAIITTAASDMLSEHSFIPEPKSSCYNTHEKRIYQSNMLNRYLINVTFEGRNLSFSEDGYQMHPKLVIILLNKERKWERVGKWKDKSLQMKYYVWPRMCPETEEQEDDHLSIVTLEEAPFVIVESVDPLSGTCMRNTVPCQKRIVTENKTDEEPGYIKKCCKGFCIDILKKISKSVKFTYDLYLVTNGKHGKKINGTWNGMIGEVVMKRAYMAVGSLTINEERSEVVDFSVPFIETGISVMVSRSNGTVSPSAFLEPFSADVWVMMFVMLLIVSAVAVFVFEYFSPVGYNRCLADGREPGGPSFTIGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANLAAFMIQEEYVDQVSGLSDKKFQRPNDFSPPFRFGTVPNGSTERNIRNNYAEMHAYMGKFNQRGVDDALLSLKTGKLDAFIYDAAVLNYMAGRDEGCKLVTIGSGKVFASTGYGIAIQKDSGWKRQVDLAILQLFGDGEMEELEALWLTGICHNEKNEVMSSQLDIDNMAGVFYMLGAAMALSLITFICEHLFYWQFRHCFMGVCSGKPGMVFSISRGIYSCIHGVAIEERQSVMNSPTATMNNTHSNILRLLRTAKNMANLSGVNGSPQSALDFIRRESSVYDISEHRRSFTHSDCKSYNNPPCEENLFSDYISEVERTFGNLQLKDSNVYQDHYHHHHRPHSIGSASSIDGLYDCDNPPFTTQSRSISKKPLDIGLPSSKHSQLSDLYGKFSFKSDRYSGHDDLIRSDVSDISTHTVTYGNIEGNAAKRRKQQYKDSLKKRPASAKSRREFDEIELAYRRRPPRSPDHKRYFRDKEGLRDFYLDQFRTKENSPHWEHVDLTDIYKERSDDFKRDSVSGGGPCTNRSHIKHGTGDKHGVVSGVPAPWEKNLTNVEWEDRSGGNFCRSCPSKLHNYSTTVTGQNSGRQACIRCEACKKAGNLYDISEDNSLQELDQPAAPVAVTSNASTTKYPQSPTNSKAQKKNRNKLRRQHSYDTFVDLQKEEAALAPRSVSLKDKGRFMDGSPYAHMFEMSAGESTFANNKSSVPTAGHHHHNNPGGGYMLSKSLYPDRVTQNPFIPTFGDDQCLLHGSKSYFFRQPTVAGASKARPDFRALVTNKPVVSALHGAVPARFQKDICIGNQSNPCVPNNKNPRAFNGSSNGHVYEKLSSIESDV,5.6777807052660805 +Cc1cc(O)cc(C)c1C[C@H](N)C(=O)N1Cc2ccccc2C[C@H]1C(O)=O,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,5.866461091629782 +CN1CCC(CNC(=O)[C@@H](N)CCCNC(N)=N)(CC1)Nc1ccccc1,MNSFFGTPAASWCLLESDVSSAPDKEAGRERRALSVQQRGGPAWSGSLEWSRQSAGDRRRLGLSRQTAKSSWSRSRDRTCCCRRAWWILVPAADRARRERFIMNEKWDTNSSENWHPIWNVNDTKHHLYSDINITYVNYYLHQPQVAAIFIISYFLIFFLCMMGNTVVCFIVMRNKHMHTVTNLFILNLAISDLLVGIFCMPITLLDNIIAGWPFGNTMCKISGLVQGISVAASVFTLVAIAVDRFQCVVYPFKPKLTIKTAFVIIMIIWVLAITIMSPSAVMLHVQEEKYYRVRLNSQNKTSPVYWCREDWPNQEMRKIYTTVLFANIYLAPLSLIVIMYGRIGISLFRAAVPHTGRKNQEQWHVVSRKKQKIIKMLLIVALLFILSWLPLWTLMMLSDYADLSPNELQIINIYIYPFAHWLAFGNSSVNPIIYGFFNENFRRGFQEAFQLQLCQKRAKPMEAYALKAKSHVLINTSNQLVQESTFQNPHGETLLYRKSAEKPQQELVMEELKETTNSSEI,5.301029995663981 +COc1cc(ccc1C)-c1cc(cnc1N)-c1ccc(cc1)N1CCNCC1,MVDGVMILPVLMMMAFPSPSVEDEKPKVNQKLYMCVCEGLSCGNEDHCEGQQCFSSLSINDGFHVYQKGCFQVYEQGKMTCKTPPSPGQAVECCQGDWCNRNITAQLPTKGKSFPGTQNFHLEVGLIILSVVFAVCLLACILGVALRKFKRRNQERLNPRDVEYGTIEGLITTNVGDSTLAELLDHSCTSGSGSGLPFLVQRTVARQITLLECVGKGRYGEVWRGSWQGENVAVKIFSSRDEKSWFRETELYNTVMLRHENILGFIASDMTSRHSSTQLWLITHYHEMGSLYDYLQLTTLDTVSCLRIVLSIASGLAHLHIEIFGTQGKSAIAHRDLKSKNILVKKNGQCCIADLGLAVMHSQSTNQLDVGNNPRVGTKRYMAPEVLDETIQVDCFDSYKRVDIWAFGLVLWEVARRMVSNGIVEDYKPPFYDVVPNDPSFEDMRKVVCVDQQRPNIPNRWFSDPTLTSLAKLMKECWYQNPSARLTALRIKKTLTKIDNSLDKLKTDC,6.075720713938118 +O=C(COc1ccc2oc(cc(=O)c2c1)-c1ccco1)N1CCCCC1,MASPRTRKVLKEVRAQDENNVCFECGAFNPQWVSVTYGIWICLECSGRHRGLGVHLSFVRSVTMDKWKDIELEKMKAGGNAKFREFLEAQDDYEPSWSLQDKYSSRAAALFRDKVATLAEGKEWSLESSPAQNWTPPQPKTLQFTAHRPAGQPQNVTTSGDKAFEDWLNDDLGSYQGAQENRYVGFGNTVPPQKREDDFLNSAMSSLYSGWSSFTTGASKFASAAKEGATKFGSQASQKASELGHSLNENVLKPAQEKVKEGRIFDDVSSGVSQLASKVQGVGSKGWRDVTTFFSGKAEDTSDRPLEGHSYQNSSGDNSQNSTIDQSFWETFGSAEPPKAKSPSSDSWTCADASTGRRSSDSWDIWGSGSASNNKNSNSDGWESWEGASGEGRAKATKKAAPSTAADEGWDNQNW,4.545277064327468 +COc1cc(OC)c(Cl)c(c1Cl)-c1ccc2c(NC(=O)c3ccc(cc3)N3CCN(CC3)S(C)(=O)=O)n[nH]c2n1,MWSWKCLLFWAVLVTATLCTARPSPTLPEQAQPWGAPVEVESFLVHPGDLLQLRCRLRDDVQSINWLRDGVQLAESNRTRITGEEVEVQDSVPADSGLYACVTSSPSGSDTTYFSVNVSDALPSSEDDDDDDDSSSEEKETDNTKPNRMPVAPYWTSPEKMEKKLHAVPAAKTVKFKCPSSGTPNPTLRWLKNGKEFKPDHRIGGYKVRYATWSIIMDSVVPSDKGNYTCIVENEYGSINHTYQLDVVERSPHRPILQAGLPANKTVALGSNVEFMCKVYSDPQPHIQWLKHIEVNGSKIGPDNLPYVQILKTAGVNTTDKEMEVLHLRNVSFEDAGEYTCLAGNSIGLSHHSAWLTVLEALEERPAVMTSPLYLEIIIYCTGAFLISCMVGSVIVYKMKSGTKKSDFHSQMAVHKLAKSIPLRRQVTVSADSSASMNSGVLLVRPSRLSSSGTPMLAGVSEYELPEDPRWELPRDRLVLGKPLGEGCFGQVVLAEAIGLDKDKPNRVTKVAVKMLKSDATEKDLSDLISEMEMMKMIGKHKNIINLLGACTQDGPLYVIVEYASKGNLREYLQARRPPGLEYCYNPSHNPEEQLSSKDLVSCAYQVARGMEYLASKKCIHRDLAARNVLVTEDNVMKIADFGLARDIHHIDYYKKTTNGRLPVKWMAPEALFDRIYTHQSDVWSFGVLLWEIFTLGGSPYPGVPVEELFKLLKEGHRMDKPSNCTNELYMMMRDCWHAVPSQRPTFKQLVEDLDRIVALTSNQEYLDLSMPLDQYSPSFPDTRSSTCSSGEDSVFSHEPLPEEPCLPRHPAQLANGGLKRR,9.698970004336019 +Cc1ccccc1N=C(N)NC12CC3CC(C)(CC(C)(C3)C1)C2,MQWAVGRRWAWAALLLAVAAVLTQVVWLWLGTQSFVFQREEIAQLARQYAGLDHELAFSRLIVELRRLHPGHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSRGHSGRYWAEISDTIISGTFHQWREGTTKSEVFYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLAFALADTVFSTQDFLTLFYTLRSYARGLRLELTTYLFGQDP,7.823908740944319 +OC(=O)C(O)=O.CN(C)[C@H]1C[C@@H]1COC(=O)N(C)C,MRGTPLLLVSLFSLLQDGDCRLANAEEKLMDDLLNKTRYNNLIRPATSSSQLISIRLELSLSQLISVNEREQIMTTSIWLKQEWTDYRLAWNSSCYEGVNILRIPAKRVWLPDIVLYNNADGTYEVSVYTNVIVRSNGSIQWLPPAIYKSACKIEVKHFPFDQQNCTLKFRSWTYDHTEIDMVLKSPTAIMDDFTPSGEWDIVALPGRRTVNPQDPSYVDVTYDFIIKRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTFFLLLISKIVPPTSLDIPLIGKYLLFTMVLVTFSIVTTVCVLNVHHRSPSTHTMASWVKECFLHKLPTFLFMKRPGLEVSLVRVPHPSQLHLATADTAATSALGPTSPSNLYGSSMYFVNPVPAAPKSAVSSHTAGLPRDARLRSSGRFREDLQEALEGVSFIAQHLESDDRDQSVIEDWKFVAMVVDRLFLWVFVFVCILGTMGLFLPPLFQIHAPSKDS,3.0 +COC(=O)CN1C(Nc2ccccc2C1=O)c1ccc2OCOc2c1,MESLQKTSDAGQMFDVVVIGGGISGLSAAKLLAEHEVNVLVLEARERVGGRTYTVRNEHVDYVDVGGAYVGPTQNRILRLSKQLGLETYKVNVNERLVHYVKGKTYPFRGAFPPVWNPIAYLDYNNLWRTMDNMGKEIPADAPWEAPHAVEWDKMTMKDLIEKICWTKTARQFASLFVNINVTSEPHEVSALWFLWYVKQCGGTTRIFSITNGGQERKFVGGSGQVSERIMQLLGDRVKLRSPVTYVDQSSENITVETLNRELYECRYVISAIPPTLTAKIHFRPELPSERNQLIQRLPMGAVIKCMMYYKEAFWKKKDYCGCMIIEDEEAPISITLDDTKPDGSLPAIMGFILARKADRLAKVHKDIRKRKICELYAKVLGSQEALHPVHYEEKNWCQEQYSGGCYTAYFPPGIMTQYGRVIRQPVGRIYFAGTETATQWSGYMEGAVEAGERAAREVLNALGKLSAKDIWIQEPEAEDVPAVEITPSFWERNLPSVSGLLKIVGFSTSITALWFVMYRFRLLSRS,8.214670164989233 +Clc1ccc(s1)C(=O)NC[C@@H]1OC(=O)N2[C@H]1CSc1cc(ccc21)N1CCOCC1=O,MNPLLILTFVAAALAAPFDDDDKIVGGYNCEENSVPYQVSLNSGYHFCGGSLINEQWVVSAGHCYKSRIQVRLGEHNIEVLEGNEQFINAAKIIRHPQYDRKTLNNDIMLIKLSSRAVINARVSTISLPTAPPATGTKCLISGWGNTASSGADYPDELQCLDAPVLSQAKCEASYPGKITSNMFCVGFLEGGKDSCQGDSGGPVVCNGQLQGVVSWGDGCAQKNKPGVYTKVYNYVKWIKNTIAANS,4.0 +CCN1CCN(Cc2ccc(Nc3ncc4N(C)C(=O)c5ccc(C)cc5N(C)c4n3)cc2C(F)(F)F)CC1,MAQKENSYPWPYGRQTAPSGLSTLPQRVLRKEPVTPSALVLMSRSNVQPTAAPGQKVMENSSGTPDILTRHFTIDDFEIGRPLGKGKFGNVYLAREKKSHFIVALKVLFKSQIEKEGVEHQLRREIEIQAHLHHPNILRLYNYFYDRRRIYLILEYAPRGELYKELQKSCTFDEQRTATIMEELADALMYCHGKKVIHRDIKPENLLLGLKGELKIADFGWSVHAPSLRRKTMCGTLDYLPPEMIEGRMHNEKVDLWCIGVLCYELLVGNPPFESASHNETYRRIVKVDLKFPASVPMGAQDLISKLLRHNPSERLPLAQVSAHPWVRANSRRVLPPSALQSVA,6.638272163982407 +OC(=O)c1ccc(cc1)-c1cccc(c1)-c1nc(cc(n1)C(F)(F)F)-c1ccc(nc1)C(F)(F)F,MESLLGFLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEECGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHSDAPTAVTGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAATQRLNASFTWVASDGWGALESVVAGSERAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEERFHCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTHLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTDDEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSFIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFVFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVAAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAPRASANLGQGSGSQFVPTVCNGREVVDSTTSSL,5.0 +C[n+]1cn([C@@H]2O[C@H](COP(S)(=O)OP(O)(O)=O)[C@@H](O)[C@H]2O)c2nc(N)nc([O-])c12,MATVEPETTPTTNPPPAEEEKTESNQEVANPEHYIKHPLQNRWALWFFKNDKSKTWQANLRLISKFDTVEDFWALYNHIQLSSNLMPGCDYSLFKDGIEPMWEDEKNKRGGRWLITLNKQQRRSDLDRFWLETLLCLIGESFDDYSDDVCGAVVNVRAKGDKIAIWTTECENRDAVTHIGRVYKERLGLPPKIVIGYQSHADTATKSGSTTKNRFVV,7.7447274948966935 +CC(C)(C)NC[C@H](O)CON=C(C1CC1)C1CC1,MGAGVLALGASEPCNLSSTAPLPDGAATAARLLVPASPPASLLPPTSEGSEPLSPQWTAGMGLLMVLIVLLIVAGNVLVIVAIAKTPRLQTLTNLFIMSLASADLVMGLLVVPFGATIVVWGRWEYGSFFCELWTSVDVLCVTASIETLCVIALDRYLAITSPFRYQSLLTRARARVLVCTVWAISALVSFLPILMHWWRAEGDEARRCYNDPKCCDFVTNRAYAIASSVVSFYVPLCIMAFVYLRVFREAQKQVKKIDSCERRFLGGPGRPPSPVPSPTPGSPRAATDPLANGRTSKRRPSRLVALREQKALKTLGIIMGVFTLCWLPFFLANVVKAFHRDLVPDRLFVFFNWLGYANSAFNPIIYCRSPDFRKAFQRLLCCARRAARRRHTAHGGRPRASGCLARSGPPPSPGAASDEDEDAVGAAPPARLLEPWAGCNGGAATADSDWSLDEPGRAGFASESKV,7.920818753952375 +NCC1(CCC(O)CC1)c1ccc(Cl)c(Cl)c1,METTPLNSQKQLSACEDGEDCQENGVLQKVVPTPGDKVESGQISNGYSAVPSPGAGDDTRHSIPATTTTLVAELHQGERETWGKKVDFLLSVIGYAVDLGNVWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIMAWALYYLISSFTDQLPWTSCKNSWNTGNCTNYFSEDNITWTLHSTSPAEEFYTRHVLQIHRSKGLQDLGGISWQLALCIMLIFTVIYFSIWKGVKTSGKVVWVTATFPYIILSVLLVRGATLPGAWRGVLFYLKPNWQKLLETGVWIDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHVWAKRRERFVLAVVITCFFGSLVTLTFGGAYVVKLLEEYATGPAVLTVALIEAVAVSWFYGITQFCRDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPYWSIILGYCIGTSSFICIPTYIAYRLIITPGTFKERIIKSITPETPTEIPCGDIRLNAV,5.0 +FC(F)c1nnc(o1)-c1cnc(NC2(CC2)c2ccc(cc2F)C(F)(F)F)nc1,MAQTQGTRRKVCYYYDGDVGNYYYGQGHPMKPHRIRMTHNLLLNYGLYRKMEIYRPHKANAEEMTKYHSDDYIKFLRSIRPDNMSEYSKQMQRFNVGEDCPVFDGLFEFCQLSTGGSVASAVKLNKQQTDIAVNWAGGLHHAKKSEASGFCYVNDIVLAILELLKYHQRVLYIDIDIHHGDGVEEAFYTTDRVMTVSFHKYGEYFPGTGDLRDIGAGKGKYYAVNYPLRDGIDDESYEAIFKPVMSKVMEMFQPSAVVLQCGSDSLSGDRLGCFNLTIKGHAKCVEFVKSFNLPMLMLGGGGYTIRNVARCWTYETAVALDTEIPNELPYNDYFEYFGPDFKLHISPSNMTNQNTNEYLEKIKQRLFENLRMLPHAPGVQMQAIPEDAIPEESGDEDEDDPDKRISICSSDKRIACEEEFSDSEEEGEGGRKNSSNFKKAKRVKTEDEKEKDPEEKKEVTEEEKTKEEKPEAKGVKEEVKLA,4.522878745280337 +CC(C)[C@H]1CC[C@H](CC1)N1CCC(CC1)n1ccc2ccccc12,MEPLFPAPFWEVIYGSHLQGNLSLLSPNHSLLPPHLLLNASHGAFLPLGLKVTIVGLYLAVCVGGLLGNCLVMYVILRHTKMKTATNIYIFNLALADTLVLLTLPFQGTDILLGFWPFGNALCKTVIAIDYYNMFTSTFTLTAMSVDRYVAICHPIRALDVRTSSKAQAVNVAIWALASVVGVPVAIMGSAQVEDEEIECLVEIPTPQDYWGPVFAICIFLFSFIVPVLVISVCYSLMIRRLRGVRLLSGSREKDRNLRRITRLVLVVVAVFVGCWTPVQVFVLAQGLGVQPSSETAVAILRFCTALGYVNSCLNPILYAFLDENFKACFRKFCCASALRRDVQVSDRVRSIAKDVALACKTSETVPRPA,6.795880017344075 +Cn1ccc(n1)-c1cnc(nc1NCCO)-c1cccc(c1)-c1cnn(C)c1,RPFPFCWPLCEISRGTHNFSEELKIGEGGFGCVYRAVMRNTVYAVKRLKENADLEWTAVKQSFLTEVEQLSRFRHPNIVDFAGYCAQNGFYCLVYGFLPNGSLEDRLHCQTQACPPLSWPQRLDILLGTARAIQFLHQDSPSLIHGDIKSSNVLLDERLTPKLGDFGLARFSRFAGSSPSQSSMVARTQTVRGTLAYLPEEYIKTGRLAVDTDTFSFGVVVLETLAGQRAVKTHGARTKYLKDLVEEEAEEAGVALRSTQSTLQAGLAADAWAAPIAMQIYKKHLDPRPGPCPPELGLGLGQLACCCLHRRAKRRPPMTQVYERLEKLQAVVAGVPGHSEAASCIPPSPQENSYVSSTGRAHSGAAPWQPLAAPSGASAQAAEQLQRGPNQPVESDESLGGLSAALRSWHLTPSCPLDPAPLREAGCPQGDTAGESSWGSGPGSRPTAVEGLALGSSASSSSEPPQIIINPARQKMVQKLALYEDGALDSLQLLSSSSLPGLGLEQDRQGPEESDEFQS,5.522878745280337 +Cc1cccc(NC(=O)CN2CCN(CC2)c2ccc(Cc3ccccc3)cc2)c1,MGNRSTADADGLLAGRGPAAGASAGASAGLAGQGAAALVGGVLLIGAVLAGNSLVCVSVATERALQTPTNSFIVSLAAADLLLALLVLPLFVYSEVQGGAWLLSPRLCDALMAMDVMLCTASIFNLCAISVDRFVAVAVPLRYNRQGGSRRQLLLIGATWLLSAAVAAPVLCGLNDVRGRDPAVCRLEDRDYVVYSSVCSFFLPCPLMLLLYWATFRGLQRWEVARRAKLHGRAPRRPSGPGPPSPTPPAPRLPQDPCGPDCAPPAPGLPRGPCGPDCAPAAPGLPPDPCGPDCAPPAPGLPQDPCGPDCAPPAPGLPRGPCGPDCAPPAPGLPQDPCGPDCAPPAPGLPPDPCGSNCAPPDAVRAAALPPQTPPQTRRRRRAKITGRERKAMRVLPVVVGAFLLCWTPFFVVHITQALCPACSVPPRLVSAVTWLGYVNSALNPVIYTVFNAEFRNVFRKALRACC,5.0 +Cc1ccc(F)c(c1)-c1cc(Nc2ccnc3cn(C)nc23)c(C)cn1,MEAAVAAPRPRLLLLVLAAAAAAAAALLPGATALQCFCHLCTKDNFTCVTDGLCFVSVTETTDKVIHNSMCIAEIDLIPRDRPFVCAPSSKTGSVTTTYCCNQDHCNKIELPTTVKSSPGLGPVELAAVIAGPVCFVCISLMLMVYICHNRTVIHHRVPNEEDPSLDRPFISEGTTLKDLIYDMTTSGSGSGLPLLVQRTIARTIVLQESIGKGRFGEVWRGKWRGEEVAVKIFSSREERSWFREAEIYQTVMLRHENILGFIAADNKDNGTWTQLWLVSDYHEHGSLFDYLNRYTVTVEGMIKLALSTASGLAHLHMEIVGTQGKPAIAHRDLKSKNILVKKNGTCCIADLGLAVRHDSATDTIDIAPNHRVGTKRYMAPEVLDDSINMKHFESFKRADIYAMGLVFWEIARRCSIGGIHEDYQLPYYDLVPSDPSVEEMRKVVCEQKLRPNIPNRWQSCEALRVMAKIMRECWYANGAARLTALRIKKTLSQLSQQEGIKM,6.5003129173815966 +COc1ccc(CCc2ccc(cn2)C2CCCN2C)cc1,MAGHSNSMALFSFSLLWLCSGVLGTDTEERLVEHLLDPSRYNKLIRPATNGSELVTVQLMVSLAQLISVHEREQIMTTNVWLTQEWEDYRLTWKPEDFDNMKKVRLPSKHIWLPDVVLYNNADGMYEVSFYSNAVVSYDGSIFWLPPAIYKSACKIEVKHFPFDQQNCTMKFRSWTYDRTEIDLVLKSDVASLDDFTPSGEWDIIALPGRRNENPDDSTYVDITYDFIIRRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTVFLLLISKIVPPTSLDVPLVGKYLMFTMVLVTFSIVTSVCVLNVHHRSPTTHTMAPWVKVVFLEKLPTLLFLQQPRHRCARQRLRLRRRQREREGAGALFFREGPAADPCTCFVNPASVQGLAGAFRAEPTAAGPGRSVGPCSCGLREAVDGVRFIADHMRSEDDDQSVREDWKYVAMVIDRLFLWIFVFVCVFGTVGMFLQPLFQNYTATTFLHPDHSAPSSK,8.0 +Cn1nc(nc1C1(CC1)c1ccccc1)-c1cnc(N)c(n1)C#N,MSAEGYQYRALYDYKKEREEDIDLHLGDILTVNKGSLVALGFSDGQEARPEEIGWLNGYNETTGERGDFPGTYVEYIGRKKISPPTPKPRPPRPLPVAPGSSKTEADVEQQALTLPDLAEQFAPPDIAPPLLIKLVEAIEKKGLECSTLYRTQSSSNLAELRQLLDCDTPSVDLEMIDVHVLADAFKRYLLDLPNPVIPAAVYSEMISLAPEVQSSEEYIQLLKKLIRSPSIPHQYWLTLQYLLKHFFKLSQTSSKNLLNARVLSEIFSPMLFRFSAASSDNTENLIKVIEILISTEWNERQPAPALPPKPPKPTTVANNGMNNNMSLQDAEWYWGDISREEVNEKLRDTADGTFLVRDASTKMHGDYTLTLRKGGNNKLIKIFHRDGKYGFSDPLTFSSVVELINHYRNESLAQYNPKLDVKLLYPVSKYQQDQVVKEDNIEAVGKKLHEYNTQFQEKSREYDRLYEEYTRTSQEIQMKRTAIEAFNETIKIFEEQCQTQERYSKEYIEKFKREGNEKEIQRIMHNYDKLKSRISEIIDSRRRLEEDLKKQAAEYREIDKRMNSIKPDLIQLRKTRDQYLMWLTQKGVRQKKLNEWLGNENTEDQYSLVEDDEDLPHHDEKTWNVGSSNRNKAENLLRGKRDGTFLVRESSKQGCYACSVVVDGEVKHCVINKTATGYGFAEPYNLYSSLKELVLHYQHTSLVQHNDSLNVTLAYPVYAQQRR,4.499996931948306 +CCOC(=O)N1CCc2cc(F)c(cc2C1)C(=O)Nc1cccc(n1)-c1nnnn1C(C)C,MSTEADEGITFSVPPFAPSGFCTIPEGGICRRGGAAAVGEGEEHQLPPPPPGSFWNVESAAAPGIGCPAATSSSSATRGRGSSVGGGSRRTTVAYVINEASQGQLVVAESEALQSLREACETVGATLETLHFGKLDFGETTVLDRFYNADIAVVEMSDAFRQPSLFYHLGVRESFSMANNIILYCDTNSDSLQSLKEIICQKNTMCTGNYTFVPYMITPHNKVYCCDSSFMKGLTELMQPNFELLLGPICLPLVDRFIQLLKVAQASSSQYFRESILNDIRKARNLYTGKELAAELARIRQRVDNIEVLTADIVINLLLSYRDIQDYDSIVKLVETLEKLPTFDLASHHHVKFHYAFALNRRNLPGDRAKALDIMIPMVQSEGQVASDMYCLVGRIYKDMFLDSNFTDTESRDHGASWFKKAFESEPTLQSGINYAVLLLAAGHQFESSFELRKVGVKLSSLLGKKGNLEKLQSYWEVGFFLGASVLANDHMRVIQASEKLFKLKTPAWYLKSIVETILIYKHFVKLTTEQPVAKQELVDFWMDFLVEATKTDVTVVRFPVLILEPTKIYQPSYLSINNEVEEKTISIWHVLPDDKKGIHEWNFSASSVRGVSISKFEERCCFLYVLHNSDDFQIYFCTELHCKKFFEMVNTITEEKGRSTEEGDCESDLLEYDYEYDENGDRVVLGKGTYGIVYAGRDLSNQVRIAIKEIPERDSRYSQPLHEEIALHKHLKHKNIVQYLGSFSENGFIKIFMEQVPGGSLSALLRSKWGPLKDNEQTIGFYTKQILEGLKYLHDNQIVHRDIKGDNVLINTYSGVLKISDFGTSKRLAGINPCTETFTGTLQYMAPEIIDKGPRGYGKAADIWSLGCTIIEMATGKPPFYELGEPQAAMFKVGMFKVHPEIPESMSAEAKAFILKCFEPDPDKRACANDLLVDEFLKVSSKKKKTQPKLSALSAGSNEYLRSISLPVPVLVEDTSSSSEYGSVSPDTELKVDPFSFKTRAKSCGERDVKGIRTLFLGIPDENFEDHSAPPSPEEKDSGFFMLRKDSERRATLHRILTEDQDKIVRNLMESLAQGAEEPKLKWEHITTLIASLREFVRSTDRKIIATTLSKLKLELDFDSHGISQVQVVLFGFQDAVNKVLRNHNIKPHWMFALDSIIRKAVQTAITILVPELRPHFSLASESDTADQEDLDVEDDHEEQPSNQTVRRPQAVIEDAVATSGVSTLSSTVSHDSQSAHRSLNVQLGRMKIETNRLLEELVRKEKELQALLHRAIEEKDQEIKHLKLKSQPIEIPELPVFHLNSSGTNTEDSELTDWLRVNGADEDTISRFLAEDYTLLDVLYYVTRDDLKCLRLRGGMLCTLWKAIIDFRNKQT,7.259637310505756 +CCCC[C@H](NC(C)=O)C(=O)N[C@H]1CC(=O)NCCCC[C@H](NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CCCN=C(N)N)NC(=O)[C@@H](Cc2ccccc2)NC(=O)[C@H](Cc2cnc[nH]2)NC1=O)C(N)=O,MVNSTHRGMHTSLHLWNRSSYRLHSNASESLGKGYSDGGCYEQLFVSPEVFVTLGVISLLENILVIVAIAKNKNLHSPMYFFICSLAVADMLVSVSNGSETIVITLLNSTDTDAQSFTVNIDNVIDSVICSSLLASICSLLSIAVDRYFTIFYALQYHNIMTVKRVGIIISCIWAACTVSGILFIIYSDSSAVIICLITMFFTMLALMASLYVHMFLMARLHIKRIAVLPGTGAIRQGANMKGAITLTILIGVFVVCWAPFFLHLIFYISCPQNPYCVCFMSHFNLYLILIMCNSIIDPLIYALRSQELRKTFKEIICCYPLGGLCDLSSRY,8.958607314841775 +Cc1nnc(NC(=O)C2C3OC(C=C3)C2C(O)=O)s1,MAEGERTECAEPPRDEPPADGALKRAEELKTQANDYFKAKDYENAIKFYSQAIELNPSNAIYYGNRSLAYLRTECYGYALGDATRAIELDKKYIKGYYRRAASNMALGKFRAALRDYETVVKVKPHDKDAKMKYQECNKIVKQKAFERAIAGDEHKRSVVDSLDIESMTIEDEYSGPKLEDGKVTISFMKELMQWYKDQKKLHRKCAYQILVQVKEVLSKLSTLVETTLKETEKITVCGDTHGQFYDLLNIFELNGLPSETNPYIFNGDFVDRGSFSVEVILTLFGFKLLYPDHFHLLRGNHETDNMNQIYGFEGEVKAKYTAQMYELFSEVFEWLPLAQCINGKVLIMHGGLFSEDGVTLDDIRKIERNRQPPDSGPMCDLLWSDPQPQNGRSISKRGVSCQFGPDVTKAFLEENNLDYIIRSHEVKAEGYEVAHGGRCVTVFSAPNYCDQMGNKASYIHLQGSDLRPQFHQFTAVGRPSSGS,4.173620649767548 +CCC(C(=O)Nc1ccc2[nH]c(=O)[nH]c2c1)n1cc(OC)c(cc1=O)-c1cc(Cl)ccc1C#N,MIFLYQVVHFILFTSVSGECVTQLLKDTCFEGGDITTVFTPSAKYCQVVCTYHPRCLLFTFTAESPSEDPTRWFTCVLKDSVTETLPRVNRTAAISGYSFKQCSHQISACNKDIYVDLDMKGINYNSSVAKSAQECQERCTDDVHCHFFTYATRQFPSLEHRNICLLKHTQTGTPTRITKLDKVVSGFSLKSCALSNLACIRDIFPNTVFADSNIDSVMAPDAFVCGRICTHHPGCLFFTFFSQEWPKESQRNLCLLKTSESGLPSTRIKKSKALSGFSLQSCRHSIPVFCHSSFYHDTDFLGEELDIVAAKSHEACQKLCTNAVRCQFFTYTPAQASCNEGKGKCYLKLSSNGSPTKILHGRGGISGYTLRLCKMDNECTTKIKPRIVGGTASVRGEWPWQVTLHTTSPTQRHLCGGSIIGNQWILTAAHCFYGVESPKILRVYSGILNQSEIKEDTSFFGVQEIIIHDQYKMAESGYDIALLKLETTVNYTDSQRPICLPSKGDRNVIYTDCWVTGWGYRKLRDKIQNTLQKAKIPLVTNEECQKRYRGHKITHKMICAGYREGGKDACKGDSGGPLSCKHNEVWHLVGITSWGEGCAQRERPGVYTNVVEYVDWILEKTQAV,7.494850021680094 +CCC[C@@H](CCO)Nc1nc(N)nc(C)c1Cc1ccc(CN(CC)CCC(O)=O)cc1OC,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,5.0 +C[C@H](O)[C@H](NC(=O)[C@H](CCc1ccccc1)NC(=O)CCc1ccccc1)C(=O)N[C@@H](CCCNC(N)=N)C(=O)c1nc2ccccc2s1,MGSDRARKGGGGPKDFGAGLKYNSRHEKVNGLEEGVEFLPVNNVKKVEKHGPGRWVVLAAVLIGLLLVLLGIGFLVWHLQYRDVRVQKVFNGYMRITNENFVDAYENSNSTEFVSLASKVKDALKLLYSGVPFLGPYHKESAVTAFSEGSVIAYYWSEFSIPQHLVEEAERVMAEERVVMLPPRARSLKSFVVTSVVAFPTDSKTVQRTQDNSCSFGLHARGVELMRFTTPGFPDSPYPAHARCQWALRGDADSVLSLTFRSFDLASCDERGSDLVTVYNTLSPMEPHALVQLCGTYPPSYNLTFHSSQNVLLITLITNTERRHPGFEATFFQLPRMSSCGGRLRKAQGTFNSPYYPGHYPPNIDCTWNIEVPNNQHVKVRFKFFYLLEPGVPAGTCPKDYVEINGEKYCGERSQFVVTSNSNKITVRFHSDQSYTDTGFLAEYLSYDSSDPCPGQFTCRTGRCIRKELRCDGWADCTDHSDELNCSCDAGHQFTCKNKFCKPLFWVCDSVNDCGDNSDEQGCSCPAQTFRCSNGKCLSKSQQCNGKDDCGDGSDEASCPKVNVVTCTKHTYRCLNGLCLSKGNPECDGKEDCSDGSDEKDCDCGLRSFTRQARVVGGTDADEGEWPWQVSLHALGQGHICGASLISPNWLVSAAHCYIDDRGFRYSDPTQWTAFLGLHDQSQRSAPGVQERRLKRIISHPFFNDFTFDYDIALLELEKPAEYSSMVRPICLPDASHVFPAGKAIWVTGWGHTQYGGTGALILQKGEIRVINQTTCENLLPQQITPRMMCVGFLSGGVDSCQGDSGGPLSSVEADGRIFQAGVVSWGDGCAQRNKPGVYTRLPLFRDWIKENTGV,6.698970004336019 +COc1cc(Nc2cc(Oc3ccc(NC(=O)Nc4cc(cc(NS(C)(=O)=O)c4OC)C(C)(C)C)c4ccccc34)ccn2)ccc1C(=O)NCCN1CCCCC1,MASSGMADSANHLPFFFGNITREEAEDYLVQGGMSDGLYLLRQSRNYLGGFALSVAHGRKAHHYTIERELNGTYAIAGGRTHASPADLCHYHSQESDGLVCLLKKPFNRPQGVQPKTGPFEDLKENLIREYVKQTWNLQGQALEQAIISQKPQLEKLIATTAHEKMPWFHGKISREESEQIVLIGSKTNGKFLIRARDNNGSYALCLLHEGKVLHYRIDKDKTGKLSIPEGKKFDTLWQLVEHYSYKADGLLRVLTVPCQKIGTQGNVNFGGRPQLPGSHPATWSAGGIISRIKSYSFPKPGHRKSSPAQGNRQESTVSFNPYEPELAPWAADKGPQREALPMDTEVYESPYADPEEIRPKEVYLDRKLLTLEDKELGSGNFGTVKKGYYQMKKVVKTVAVKILKNEANDPALKDELLAEANVMQQLDNPYIVRMIGICEAESWMLVMEMAELGPLNKYLQQNRHVKDKNIIELVHQVSMGMKYLEESNFVHRDLAARNVLLVTQHYAKISDFGLSKALRADENYYKAQTHGKWPVKWYAPECINYYKFSSKSDVWSFGVLMWEAFSYGQKPYRGMKGSEVTAMLEKGERMGCPAGCPREMYDLMNLCWTYDVENRPGFAAVELRLRNYYYDVVN,6.764471553092451 +Fc1cccc(c1)N(C(C(=O)NC1CC(F)(F)C1)c1ccccc1Cl)C(=O)[C@@H]1CCC(=O)N1c1cccnc1,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,6.522878745280337 +NC(=N)c1ccc2cc(ccc2c1)C(=O)Nc1ccc(CO)cc1,MDAMKRGLCCVLLLCGAVFVSPSQEIHARFRRGARSYQVICRDEKTQMIYQQHQSWLRPVLRSNRVEYCWCNSGRAQCHSVPVKSCSEPRCFNGGTCQQALYFSDFVCQCPEGFAGKCCEIDTRATCYEDQGISYRGTWSTAESGAECTNWNSSALAQKPYSGRRPDAIRLGLGNHNYCRNPDRDSKPWCYVFKAGKYSSEFCSTPACSEGNSDCYFGNGSAYRGTHSLTESGASCLPWNSMILIGKVYTAQNPSAQALGLGKHNYCRNPDGDAKPWCHVLKNRRLTWEYCDVPSCSTCGLRQYSQPQFRIKGGLFADIASHPWQAAIFAKHRRSPGERFLCGGILISSCWILSAAHCFQERFPPHHLTVILGRTYRVVPGEEEQKFEVEKYIVHKEFDDDTYDNDIALLQLKSDSSRCAQESSVVRTVCLPPADLQLPDWTECELSGYGKHEALSPFYSERLKEAHVRLYPSSRCTSQHLLNRTVTDNMLCAGDTRSGGPQANLHDACQGDSGGPLVCLNDGRMTLVGIISWGLGCGQKDVPGVYTKVTNYLDWIRDNMRP,5.078313524516398 +COCc1ccc(cn1)-c1cc2c3n([C@H]4CC[C@@H](CC4)OC)c(=O)n(C)c3cnc2cc1F,MSLVLNDLLICCRQLEHDRATERKKEVEKFKRLIRDPETIKHLDRHSDSKQGKYLNWDAVFRFLQKYIQKETECLRIAKPNVSASTQASRQKKMQEISSLVKYFIKCANRRAPRLKCQELLNYIMDTVKDSSNGAIYGADCSNILLKDILSVRKYWCEISQQQWLELFSVYFRLYLKPSQDVHRVLVARIIHAVTKGCCSQTDGLNSKFLDFFSKAIQCARQEKSSSGLNHILAALTIFLKTLAVNFRIRVCELGDEILPTLLYIWTQHRLNDSLKEVIIELFQLQIYIHHPKGAKTQEKGAYESTKWRSILYNLYDLLVNEISHIGSRGKYSSGFRNIAVKENLIELMADICHQVFNEDTRSLEISQSYTTTQRESSDYSVPCKRKKIELGWEVIKDHLQKSQNDFDLVPWLQIATQLISKYPASLPNCELSPLLMILSQLLPQQRHGERTPYVLRCLTEVALCQDKRSNLESSQKSDLLKLWNKIWCITFRGISSEQIQAENFGLLGAIIQGSLVEVDREFWKLFTGSACRPSCPAVCCLTLALTTSIVPGTVKMGIEQNMCEVNRSFSLKESIMKWLLFYQLEGDLENSTEVPPILHSNFPHLVLEKILVSLTMKNCKAAMNFFQSVPECEHHQKDKEELSFSEVEELFLQTTFDKMDFLTIVRECGIEKHQSSIGFSVHQNLKESLDRCLLGLSEQLLNNYSSEITNSETLVRCSRLLVGVLGCYCYMGVIAEEEAYKSELFQKAKSLMQCAGESITLFKNKTNEEFRIGSLRNMMQLCTRCLSNCTKKSPNKIASGFFLRLLTSKLMNDIADICKSLASFIKKPFDRGEVESMEDDTNGNLMEVEDQSSMNLFNDYPDSSVSDANEPGESQSTIGAINPLAEEYLSKQDLLFLDMLKFLCLCVTTAQTNTVSFRAADIRRKLLMLIDSSTLEPTKSLHLHMYLMLLKELPGEEYPLPMEDVLELLKPLSNVCSLYRRDQDVCKTILNHVLHVVKNLGQSNMDSENTRDAQGQFLTVIGAFWHLTKERKYIFSVRMALVNCLKTLLEADPYSKWAILNVMGKDFPVNEVFTQFLADNHHQVRMLAAESINRLFQDTKGDSSRLLKALPLKLQQTAFENAYLKAQEGMREMSHSAENPETLDEIYNRKSVLLTLIAVVLSCSPICEKQALFALCKSVKENGLEPHLVKKVLEKVSETFGYRRLEDFMASHLDYLVLEWLNLQDTEYNLSSFPFILLNYTNIEDFYRSCYKVLIPHLVIRSHFDEVKSIANQIQEDWKSLLTDCFPKILVNILPYFAYEGTRDSGMAQQRETATKVYDMLKSENLLGKQIDHLFISNLPEIVVELLMTLHEPANSSASQSTDLCDFSGDLDPAPNPPHFPSHVIKATFAYISNCHKTKLKSILEILSKSPDSYQKILLAICEQAAETNNVYKKHRILKIYHLFVSLLLKDIKSGLGGAWAFVLRDVIYTLIHYINQRPSCIMDVSLRSFSLCCDLLSQVCQTAVTYCKDALENHLHVIVGTLIPLVYEQVEVQKQVLDLLKYLVIDNKDNENLYITIKLLDPFPDHVVFKDLRITQQKIKYSRGPFSLLEEINHFLSVSVYDALPLTRLEGLKDLRRQLELHKDQMVDIMRASQDNPQDGIMVKLVVNLLQLSKMAINHTGEKEVLEAVGSCLGEVGPIDFSTIAIQHSKDASYTKALKLFEDKELQWTFIMLTYLNNTLVEDCVKVRSAAVTCLKNILATKTGHSFWEIYKMTTDPMLAYLQPFRTSRKKFLEVPRFDKENPFEGLDDINLWIPLSENHDIWIKTLTCAFLDSGGTKCEILQLLKPMCEVKTDFCQTVLPYLIHDILLQDTNESWRNLLSTHVQGFFTSCLRHFSQTSRSTTPANLDSESEHFFRCCLDKKSQRTMLAVVDYMRRQKRPSSGTIFNDAFWLDLNYLEVAKVAQSCAAHFTALLYAEIYADKKSMDDQEKRSLAFEEGSQSTTISSLSEKSKEETGISLQDLLLEIYRSIGEPDSLYGCGGGKMLQPITRLRTYEHEAMWGKALVTYDLETAIPSSTRQAGIIQALQNLGLCHILSVYLKGLDYENKDWCPELEELHYQAAWRNMQWDHCTSVSKEVEGTSYHESLYNALQSLRDREFSTFYESLKYARVKEVEEMCKRSLESVYSLYPTLSRLQAIGELESIGELFSRSVTHRQLSEVYIKWQKHSQLLKDSDFSFQEPIMALRTVILEILMEKEMDNSQRECIKDILTKHLVELSILARTFKNTQLPERAIFQIKQYNSVSCGVSEWQLEEAQVFWAKKEQSLALSILKQMIKKLDASCAANNPSLKLTYTECLRVCGNWLAETCLENPAVIMQTYLEKAVEVAGNYDGESSDELRNGKMKAFLSLARFSDTQYQRIENYMKSSEFENKQALLKRAKEEVGLLREHKIQTNRYTVKVQRELELDELALRALKEDRKRFLCKAVENYINCLLSGEEHDMWVFRLCSLWLENSGVSEVNGMMKRDGMKIPTYKFLPLMYQLAARMGTKMMGGLGFHEVLNNLISRISMDHPHHTLFIILALANANRDEFLTKPEVARRSRITKNVPKQSSQLDEDRTEAANRIICTIRSRRPQMVRSVEALCDAYIILANLDATQWKTQRKGINIPADQPITKLKNLEDVVVPTMEIKVDHTGEYGNLVTIQSFKAEFRLAGGVNLPKIIDCVGSDGKERRQLVKGRDDLRQDAVMQQVFQMCNTLLQRNTETRKRKLTICTYKVVPLSQRSGVLEWCTGTVPIGEFLVNNEDGAHKRYRPNDFSAFQCQKKMMEVQKKSFEEKYEVFMDVCQNFQPVFRYFCMEKFLDPAIWFEKRLAYTRSVATSSIVGYILGLGDRHVQNILINEQSAELVHIDLGVAFEQGKILPTPETVPFRLTRDIVDGMGITGVEGVFRRCCEKTMEVMRNSQETLLTIVEVLLYDPLFDWTMNPLKALYLQQRPEDETELHPTLNADDQECKRNLSDIDQSFNKVAERVLMRLQEKLKGVEEGTVLSVGGQVNLLIQQAIDPKNLSRLFPGWKAWV,6.619788758288394 +COc1cc(cc(OC)c1OC)C(=O)c1sc2ccccc2c1N,MREIVSCQAGQCGNQIGSKFWEVIADEHGVDPTGSYQGDSDLQ,5.376750709602099 +COc1ccc(cc1)C1=C(c2ccc(OCCN(C)C)cc2)c2ccccc2OCC1,MDIKNSPSSLNSPSSYNCSQSILPLEHGSIYIPSSYVDSHHEYPAMTFYSPAVMNYSIPSNVTNLEGGPGRQTTSPNVLWPTPGHLSPLVVHRQLSHLYAEPQKSPWCEARSLEHTLPVNRETLKRKVSGNRCASPVTGPGSKRDAHFCAVCSDYASGYHYGVWSCEGCKAFFKRSIQGHNDYICPATNQCTIDKNRRKSCQACRLRKCYEVGMVKCGSRRERCGYRLVRRQRSADEQLHCAGKAKRSGGHAPRVRELLLDALSPEQLVLTLLEAEPPHVLISRPSAPFTEASMMMSLTKLADKELVHMISWAKKIPGFVELSLFDQVRLLESCWMEVLMMGLMWRSIDHPGKLIFAPDLVLDRDEGKCVEGILEIFDMLLATTSRFRELKLQHKEYLCVKAMILLNSSMYPLVTATQDADSSRKLAHLLNAVTDALVWVIAKSGISSQQQSMRLANLLMLLSHVRHASNKGMEHLLNMKCKNVVPVYDLLLEMLNAHVLRGCKSSITGSECSPAEDSKSKEGSQNPQSQ,4.954677021213342 +CC(=O)c1nn(CC(=O)N2C3CCC(C3)[C@H]2C(=O)Nc2cccc(Br)n2)c2ccc(cc12)-c1cnc(C)nc1,MHSWERLAVLVLLGAAACAAPPRGRILGGREAEAHARPYMASVQLNGAHLCGGVLVAEQWVLSAAHCLEDAADGKVQVLLGAHSLSQPEPSKRLYDVLRAVPHPDSQPDTIDHDLLLLQLSEKATLGPAVRPLPWQRVDRDVAPGTLCDVAGWGIVNHAGRRPDSLQHVLLPVLDRATCNRRTHHDGAITERLMCAESNRRDSCKGDSGGPLVCGGVLEGVVTSGSRVCGNRKKPGIYTRVASYAAWIDSVLA,6.0 +CCCOc1cc(N2CCC(C2)Oc2ccc(cc2)[C@H](C)NC(C)=O)c(F)cn1,MVLLLCLSCLIFSCLTFSWLKIWGKMTDSKPITKSKSEANLIPSQEPFPASDNSGETPQRNGEGHTLPKTPSQAEPASHKGPKDAGRRRNSLPPSHQKPPRNPLSSSDAAPSPELQANGTGTQGLEATDTNGLSSSARPQGQQAGSPSKEDKKQANIKRQLMTNFILGSFDDYSSDEDSVAGSSRESTRKGSRASLGALSLEAYLTTGEAETRVPTMRPSMSGLHLVKRGREHKKLDLHRDFTVASPAEFVTRFGGDRVIEKVLIANNGIAAVKCMRSIRRWAYEMFRNERAIRFVVMVTPEDLKANAEYIKMADHYVPVPGGPNNNNYANVELIVDIAKRIPVQAVWAGWGHASENPKLPELLCKNGVAFLGPPSEAMWALGDKIASTVVAQTLQVPTLPWSGSGLTVEWTEDDLQQGKRISVPEDVYDKGCVKDVDEGLEAAERIGFPLMIKASEGGGGKGIRKAESAEDFPILFRQVQSEIPGSPIFLMKLAQHARHLEVQILADQYGNAVSLFGRDCSIQRRHQKIVEEAPATIAPLAIFEFMEQCAIRLAKTVGYVSAGTVEYLYSQDGSFHFLELNPRLQVEHPCTEMIADVNLPAAQLQIAMGVPLHRLKDIRLLYGESPWGVTPISFETPSNPPLARGHVIAARITSENPDEGFKPSSGTVQELNFRSSKNVWGYFSVAATGGLHEFADSQFGHCFSWGENREEAISNMVVALKELSIRGDFRTTVEYLINLLETESFQNNDIDTGWLDYLIAEKVQAEKPDIMLGVVCGALNVADAMFRTCMTDFLHSLERGQVLPADSLLNLVDVELIYGGVKYILKVARQSLTMFVLIMNGCHIEIDAHRLNDGGLLLSYNGNSYTTYMKEEVDSYRITIGNKTCVFEKENDPTVLRSPSAGKLTQYTVEDGGHVEAGSSYAEMEVMKMIMTLNVQERGRVKYIKRPGAVLEAGCVVARLELDDPSKVHPAEPFTGELPAQQTLPILGEKLHQVFHSVLENLTNVMSGFCLPEPVFSIKLKEWVQKLMMTLRHPSLPLLELQEIMTSVAGRIPAPVEKSVRRVMAQYASNITSVLCQFPSQQIATILDCHAATLQRKADREVFFINTQSIVQLVQRYRSGIRGYMKTVVLDLLRRYLRVEHHFQQAHYDKCVINLREQFKPDMSQVLDCIFSHAQVAKKNQLVIMLIDELCGPDPSLSDELISILNELTQLSKSEHCKVALRARQILIASHLPSYELRHNQVESIFLSAIDMYGHQFCPENLKKLILSETTIFDVLPTFFYHANKVVCMASLEVYVRRGYIAYELNSLQHRQLPDGTCVVEFQFMLPSSHPNRMTVPISITNPDLLRHSTELFMDSGFSPLCQRMGAMVAFRRFEDFTRNFDEVISCFANVPKDTPLFSEARTSLYSEDDCKSLREEPIHILNVSIQCADHLEDEALVPILRTFVQSKKNILVDYGLRRITFLIAQEKEFPKFFTFRARDEFAEDRIYRHLEPALAFQLELNRMRNFDLTAVPCANHKMHLYLGAAKVKEGVEVTDHRFFIRAIIRHSDLITKEASFEYLQNEGERLLLEAMDELEVAFNNTSVRTDCNHIFLNFVPTVIMDPFKIEESVRYMVMRYGSRLWKLRVLQAEVKINIRQTTTGSAVPIRLFITNESGYYLDISLYKEVTDSRSGNIMFHSFGNKQGPQHGMLINTPYVTKDLLQAKRFQAQTLGTTYIYDFPEMFRQALFKLWGSPDKYPKDILTYTELVLDSQGQLVEMNRLPGGNEVGMVAFKMRFKTQEYPEGRDVIVIGNDITFRIGSFGPGEDLLYLRASEMARAEGIPKIYVAANSGARIGMAEEIKHMFHVAWVDPEDPHKGFKYLYLTPQDYTRISSLNSVHCKHIEEGGESRYMITDIIGKDDGLGVENLRGSGMIAGESSLAYEEIVTISLVTCRAIGIGAYLVRLGQRVIQVENSHIILTGASALNKVLGREVYTSNNQLGGVQIMHYNGVSHITVPDDFEGVYTILEWLSYMPKDNHSPVPIITPTDPIDREIEFLPSRAPYDPRWMLAGRPHPTLKGTWQSGFFDHGSFKEIMAPWAQTVVTGRARLGGIPVGVIAVETRTVEVAVPADPANLDSEAKIIQQAGQVWFPDSAYKTAQAVKDFNREKLPLMIFANWRGFSGGMKDMYDQVLKFGAYIVDGLRQYKQPILIYIPPYAELRGGSWVVIDATINPLCIEMYADKESRGGVLEPEGTVEIKFRKKDLIKSMRRIDPAYKKLMEQLGEPDLSDKDRKDLEGRLKAREDLLLPIYHQVAVQFADFHDTPGRMLEKGVISDILEWKTARTFLYWRLRRLLLEDQVKQEILQASGELSHVHIQSMLRRWFVETEGAVKAYLWDNNQVVVQWLEQHWQAGDGPRSTIRENITYLKHDSVLKTIRGLVEENPEVAVDCVIYLSQHISPAERAQVVHLLSTMDSPAST,7.154901959985743 +CN(Cc1ccncc1N(CC=C)S(C)(=O)=O)c1nc(Nc2ccc(N3CCOCC3)c(Br)c2)ncc1C(F)(F)F,MAAAYLDPNLNHTPNSSTKTHLGTGMERSPGAMERVLKVFHYFESNSEPTTWASIIRHGDATDVRGIIQKIVDSHKVKHVACYGFRLSHLRSEEVHWLHVDMGVSSVREKYELAHPPEEWKYELRIRYLPKGFLNQFTEDKPTLNFFYQQVKSDYMLEIADQVDQEIALKLGCLEIRRSYWEMRGNALEKKSNYEVLEKDVGLKRFFPKSLLDSVKAKTLRKLIQQTFRQFANLNREESILKFFEILSPVYRFDKECFKCALGSSWIISVELAIGPEEGISYLTDKGCNPTHLADFTQVQTIQYSNSEDKDRKGMLQLKIAGAPEPLTVTAPSLTIAENMADLIDGYCRLVNGTSQSFIIRPQKEGERALPSIPKLANSEKQGMRTHAVSVSETDDYAEIIDEEDTYTMPSTRDYEIQRERIELGRCIGEGQFGDVHQGIYMSPENPALAVAIKTCKNCTSDSVREKFLQEALTMRQFDHPHIVKLIGVITENPVWIIMELCTLGELRSFLQVRKYSLDLASLILYAYQLSTALAYLESKRFVHRDIAARNVLVSSNDCVKLGDFGLSRYMEDSTYYKASKGKLPIKWMAPESINFRRFTSASDVWMFGVCMWEILMHGVKPFQGVKNNDVIGRIENGERLPMPPNCPPTLYSLMTKCWAYDPSRRPRFTELKAQLSTILEEEKAQQEERMRMESRRQATVSWDSGGSDEAPPKPSRPGYPSPRSSEGFYPSPQHMVQTNHYQVSGYPGSHGITAMAGSIYPGQASLLDQTDSWNHRPQEIAMWQPNVEDSTVLDLRGIGQVLPTHLMEERLIRQQQEMEEDQRWLEKEERFLKPDVRLSRGSIDREDGSLQGPIGNQHIYQPVGKPDPAAPPKKPPRPGAPGHLGSLASLSSPADSYNEGVKLQPQEISPPPTANLDRSNDKVYENVTGLVKAVIEMSSKIQPAPPEEYVPMVKEVGLALRTLLATVDETIPLLPASTHREIEMAQKLLNSDLGELINKMKLAQQYVMTSLQQEYKKQMLTAAHALAVDAKNLLDVIDQARLKMLGQTRPH,5.125170422120278 +CCC(=O)NCCc1c2-c3ccccc3Cn2c2ccc(OC)cc12,MQGNGSALPNASQPVLRGDGARPSWLASALACVLIFTIVVDILGNLLVILSVYRNKKLRNAGNIFVVSLAVADLVVAIYPYPLVLMSIFNNGWNLGYLHCQVSGFLMGLSVIGSIFNITGIAINRYCYICHSLKYDKLYSSKNSLCYVLLIWLLTLAAVLPNLRAGTLQYDPRIYSCTFAQSVSSAYTIAVVVFHFLVPMIIVIFCYLRIWILVLQVRQRVKPDRKPKLKPQDFRNFVTMFVVFVLFAICWAPLNFIGLAVASDPASMVPRIPEWLFVASYYMAYFNSCLNAIIYGLLNQNFRKEYRRIIVSLCTARVFFVDSSNDVADRVKWKPSPLMTNNNVVKVDSV,8.359518563029578 +CC(=O)N1CCc2c(CC1)c1ccc(cc1n2C)-n1ccc(cc1=O)-c1ccc(nc1)C(F)(F)F,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,7.327902142064282 +O=C(Nc1ccc(Cc2ccc(NC(=O)c3ccc4OCOc4c3)cc2)cc1)c1ccc2OCOc2c1,MTLQEQIMKALHVQPVIDPKAEIRKRVDFLKDYVKKTGAKGFVLGISGGQDSTLAGRLAQLAVEEIRNEGGNATFIAVRLPYKVQKDEDDAQLALQFIQADQSVAFDIASTVDAFSNQYENLLDESLTDFNKGNVKARIRMVTQYAIGGQKGLLVIGTDHAAEAVTGFFTKFGDGGADLLPLTGLTKRQGRALLQELGADERLYLKMPTADLLDEKPGQADETELGITYDQLDDYLEGKTVPADVAEKIEKRYTVSEHKRQVPASMFDDWWK,4.182434630440219 +CNC[C@@H]1OCc2ccccc2[C@@H]1Oc1cc(F)ccc1C,MLLARMNPQVQPENNGADTGPEQPLRARKTAELLVVKERNGVQCLLAPRDGDAQPRETWGKKIDFLLSVVGFAVDLANVWRFPYLCYKNGGGAFLIPYTLFLIIAGMPLFYMELALGQYNREGAATVWKICPFFKGVGYAVILIALYVGFYYNVIIAWSLYYLFSSFTLNLPWTDCGHTWNSPNCTDPKLLNGSVLGNHTKYSKYKFTPAAEFYERGVLHLHESSGIHDIGLPQWQLLLCLMVVVIVLYFSLWKGVKTSGKVVWITATLPYFVLFVLLVHGVTLPGASNGINAYLHIDFYRLKEATVWIDAATQIFFSLGAGFGVLIAFASYNKFDNNCYRDALLTSSINCITSFVSGFAIFSILGYMAHEHKVNIEDVATEGAGLVFILYPEAISTLSGSTFWAVVFFVMLLALGLDSSMGGMEAVITGLADDFQVLKRHRKLFTFGVTFSTFLLALFCITKGGIYVLTLLDTFAAGTSILFAVLMEAIGVSWFYGVDRFSNDIQQMMGFRPGLYWRLCWKFVSPAFLLFVVVVSIINFKPLTYDDYIFPPWANWVGWGIALSSMVLVPIYVIYKFLSTQGSLWERLAYGITPENEHHLVAQRDIRQFQLQHWLAI,7.958607314841775 +O=C(Nc1cc2cnc(nc2cc1N1CCCCC1)N1CCOCC1)c1cnn2cccnc12,MAGGPGPGEPAAPGAQHFLYEVPPWVMCRFYKVMDALEPADWCQFAALIVRDQTELRLCERSGQRTASVLWPWINRNARVADLVHILTHLQLLRARDIITAWHPPAPLPSPGTTAPRPSSIPAPAEAEAWSPRKLPSSASTFLSPAFPGSQTHSGPELGLVPSPASLWPPPPSPAPSSTKPGPESSVSLLQGARPFPFCWPLCEISRGTHNFSEELKIGEGGFGCVYRAVMRNTVYAVKRLKENADLEWTAVKQSFLTEVEQLSRFRHPNIVDFAGYCAQNGFYCLVYGFLPNGSLEDRLHCQTQACPPLSWPQRLDILLGTARAIQFLHQDSPSLIHGDIKSSNVLLDERLTPKLGDFGLARFSRFAGSSPSQSSMVARTQTVRGTLAYLPEEYIKTGRLAVDTDTFSFGVVVLETLAGQRAVKTHGARTKYLKDLVEEEAEEAGVALRSTQSTLQAGLAADAWAAPIAMQIYKKHLDPRPGPCPPELGLGLGQLACCCLHRRAKRRPPMTQVYERLEKLQAVVAGVPGHSEAASCIPPSPQENSYVSSTGRAHSGAAPWQPLAAPSGASAQAAEQLQRGPNQPVESDESLGGLSAALRSWHLTPSCPLDPAPLREAGCPQGDTAGESSWGSGPGSRPTAVEGLALGSSASSSSEPPQIIINPARQKMVQKLALYEDGALDSLQLLSSSSLPGLGLEQDRQGPEESDEFQS,5.267606240177032 +CCCCCCCCCCCCCCCNC(=O)c1ccc2ccccc2c1,MRTADREARPGLPSLLLLLLAGAGLSAASPPAAPRFNVSLDSVPELRWLPVLRHYDLDLVRAAMAQVIGDRVPKWVHVLIGKVVLELERFLPQPFTGEIRGMCDFMNLSLADCLLVNLAYESSVFCTSIVAQDSRGHIYHGRNLDYPFGNVLRKLTVDVQFLKNGQIAFTGTTFIGYVGLWTGQSPHKFTVSGDERDKGWWWENAIAALFRRHIPVSWLIRATLSESENFEAAVGKLAKTPLIADVYYIVGGTSPREGVVITRNRDGPADIWPLDPLNGAWFRVETNYDHWKPAPKEDDRRTSAIKALNATGQANLSLEALFQILSVVPVYNNFTIYTTVMSAGSPDKYMTRIRNPSRK,4.0 +CC(c1ccccc1)c1cc2cc3c(n[nH]c3cc2[nH]c1=O)N1CCOCC1,MAAAAAAGAGPEMVRGQVFDVGPRYTNLSYIGEGAYGMVCSAYDNVNKVRVAIKKISPFEHQTYCQRTLREIKILLRFRHENIIGINDIIRAPTIEQMKDVYIVQDLMETDLYKLLKTQHLSNDHICYFLYQILRGLKYIHSANVLHRDLKPSNLLLNTTCDLKICDFGLARVADPDHDHTGFLTEYVATRWYRAPEIMLNSKGYTKSIDIWSVGCILAEMLSNRPIFPGKHYLDQLNHILGILGSPSQEDLNCIINLKARNYLLSLPHKNKVPWNRLFPNADSKALDLLDKMLTFNPHKRIEVEQALAHPYLEQYYDPSDEPIAEAPFKFDMELDDLPKEKLKELIFEETARFQPGYRS,7.301029995663981 +OC(=O)c1csc(n1)-c1ccc2CCCC(=NNc3nc4ccccc4s3)c2c1,MSQSNRELVVDFLSYKLSQKGYSWSQFSDVEENRTEAPEGTESEMETPSAINGNPSWHLADSPAVNGATAHSSSLDAREVIPMAAVKQALREAGDEFELRYRRAFSDLTSQLHITPGTAYQSFEQVVNELFRDGVNWGRIVAFFSFGGALCVESVDKEMQVLVSRIAAWMATYLNDHLEPWIQENGGWDTFVELYGNNAAAESRKGQERFNRWFLTGMTVAGVVLLGSLFSRK,7.886056647693163 +CNC(=O)Cn1c2ccccc2n(C2CCN(Cc3ccc(C)c4ccccc34)CC2)c1=O,MEPLFPAPFWEVIYGSHLQGNLSLLSPNHSLLPPHLLLNASHGAFLPLGLKVTIVGLYLAVCVGGLLGNCLVMYVILRHTKMKTATNIYIFNLALADTLVLLTLPFQGTDILLGFWPFGNALCKTVIAIDYYNMFTSTFTLTAMSVDRYVAICHPIRALDVRTSSKAQAVNVAIWALASVVGVPVAIMGSAQVEDEEIECLVEIPTPQDYWGPVFAICIFLFSFIVPVLVISVCYSLMIRRLRGVRLLSGSREKDRNLRRITRLVLVVVAVFVGCWTPVQVFVLAQGLGVQPSSETAVAILRFCTALGYVNSCLNPILYAFLDENFKACFRKFCCASALRRDVQVSDRVRSIAKDVALACKTSETVPRPA,8.568636235841012 +Cc1ccc(cc1)-c1ccc2c3nc([nH]c3c(=O)[nH]c2c1)-c1c(F)cccc1Cl,MGLEALVPLAVIVAIFLLLVDLMHRRQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQLRRRFGDVFSLQLAWTPVVVLNGLAAVREALVTHGEDTADRPPVPITQILGFGPRSQGVFLARYGPAWREQRRFSVSTLRNLGLGKKSLEQWVTEEAACLCAAFANHSGRPFRPNGLLDKAVSNVIASLTCGRRFEYDDPRFLRLLDLAQEGLKEESGFLREVLNAVPVLLHIPALAGKVLRFQKAFLTQLDELLTEHRMTWDPAQPPRDLTEAFLAEMEKAKGNPESSFNDENLRIVVADLFSAGMVTTSTTLAWGLLLMILHPDVQRRVQQEIDDVIGQVRRPEMGDQAHMPYTTAVIHEVQRFGDIVPLGVTHMTSRDIEVQGFRIPKGTTLITNLSSVLKDEAVWEKPFRFHPEHFLDAQGHFVKPEAFLPFSAGRRACLGEPLARMELFLFFTSLLQHFSFSVPTGQPRPSHHGVFAFLVSPSPYELCAVPR,4.522878745280337 +CN1[C@@H](C[C@H](O)c2ccccc2)CCC[C@H]1CC(=O)c1ccccc1,MALSDLVLLRWLRDSRHSRKLILFIVFLALLLDNMLLTVVVPIIPSYLYSIKHEKNSTEIQTTRPELVVSTSESIFSYYNNSTVLITGNATGTLPGGQSHKATSTQHTVANTTVPSDCPSEDRDLLNENVQVGLLFASKATVQLLTNPFIGLLTNRIGYPIPMFAGFCIMFISTVMFAFSSSYAFLLIARSLQGIGSSCSSVAGMGMLASVYTDDEERGKPMGIALGGLAMGVLVGPPFGSVLYEFVGKTAPFLVLAALVLLDGAIQLFVLQPSRVQPESQKGTPLTTLLKDPYILIAAGSICFANMGIAMLEPALPIWMMETMCSRKWQLGVAFLPASISYLIGTNIFGILAHKMGRWLCALLGMVIVGISILCIPFAKNIYGLIAPNFGVGFAIGMVDSSMMPIMGYLVDLRHVSVYGSVYAIADVAFCMGYAIGPSAGGAIAKAIGFPWLMTIIGIIDIAFAPLCFFLRSPPAKEEKMAILMDHNCPIKRKMYTQNNVQSYPIGDDEESESD,6.327902142064283 +CCCc1c(Sc2cc(OC)ccc2OC)[nH]c2nc(N)nc(N)c12,MPVAGSELPRRPLPPAAQERDAEPRPPHGELQYLGQIQHILRCGVRKDDRTGTGTLSVFGMQARYSLRDEFPLLTTKRVFWKGVLEELLWFIKGSTNAKELSSKGVKIWDANGSRDFLDSLGFSTREEGDLGPVYGFQWRHFGAEYRDMESDYSGQGVDQLQRVIDTIKTNPDDRRIIMCAWNPRDLPLMALPPCHALCQFYVVNSELSCQLYQRSGDMGLGVPFNIASYALLTYMIAHITGLKPGDFIHTLGDAHIYLNHIEPLKIQLQREPRPFPKLRILRKVEKIDDFKAEDFQIEGYNPHPTIKMEMAV,4.920818753952375 +CSC[C@@H](CO)NCc1c[nH]c2c(N)ncnc12,MASGTTTTAVKIGIIGGTGLDDPEILEGRTEKYVDTPFGKPSDALILGKIKNVDCVLLARHGRQHTIMPSKVNYQANIWALKEEGCTHVIVTTACGSLREEIQPGDIVIIDQFIDRTTMRPQSFYDGSHSCARGVCHIPMAEPFCPKTREVLIETAKKLGLRCHSKGTMVTIEGPRFSSRAESFMFRTWGADVINMTTVPEVVLAKEAGICYASIAMATDYDCWKEHEEAVSVDRVLKTLKENANKAKSLLLTTIPQIGSTEWSETLHNLKNMAQFSVLLPRH,8.356547323513812 +COC(=O)CCc1cc2nc(Nc3ccc(OC(F)(F)F)cc3)n([C@H]3C[C@@H](C)CC(C)(C)C3)c2cc1C,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,6.356547323513812 +Clc1ccc2ncc(-c3ccc4[nH]ccc4c3)n2n1,MHTGGETSACKPSSVRLAPSFSFHAAGLQMAGQMPHSHQYSDRRQPNISDQQVSALSYSDQIQQPLTNQVMPDIVMLQRRMPQTFRDPATAPLRKLSVDLIKTYKHINEVYYAKKKRRHQQGQGDDSSHKKERKVYNDGYDDDNYDYIVKNGEKWMDRYEIDSLIGKGSFGQVVKAYDRVEQEWVAIKIIKNKKAFLNQAQIEVRLLELMNKHDTEMKYYIVHLKRHFMFRNHLCLVFEMLSYNLYDLLRNTNFRGVSLNLTRKFAQQMCTALLFLATPELSIIHCDLKPENILLCNPKRSAIKIVDFGSSCQLGQRIYQYIQSRFYRSPEVLLGMPYDLAIDMWSLGCILVEMHTGEPLFSGANEVDQMNKIVEVLGIPPAHILDQAPKARKFFEKLPDGTWNLKKTKDGKREYKPPGTRKLHNILGVETGGPGGRRAGESGHTVADYLKFKDLILRMLDYDPKTRIQPYYALQHSFFKKTADEGTNTSNSVSTSPAMEQSQSSGTTSSTSSSSGGSSGTSNSGRARSDPTHQHRHSGGHFTAAVQAMDCETHSPQVRQQFPAPLGWSGTEAPTQVTVETHPVQETTFHVAPQQNALHHHHGNSSHHHHHHHHHHHHHGQQALGNRTRPRVYNSPTNSSSTQDSMEVGHSHHSMTSLSSSTTSSSTSSSSTGNQGNQAYQNRPVAANTLDFGQNGAMDVNLTVYSNPRQETGIAGHPTYQFSANTGPAHYMTEGHLTMRQGADREESPMTGVCVQQSPVASS,5.619788758288394 +CC(=O)Nc1ccc(NC2=CC(=NS(=O)(=O)c3cccs3)c3ccccc3C2=O)cc1,MDAKARNCLLQHREALEKDIKTSYIMDHMISDGFLTISEEEKVRNEPTQQQRAAMLIKMILKKDNDSYVSFYNALLHEGYKDLAALLHDGIPVVSSSSGKDSVSGITSYVRTVLCEGGVPQRPVVFVTRKKLVNAIQQKLSKLKGEPGWVTIHGMAGCGKSVLAAEAVRDHSLLEGCFPGGVHWVSVGKQDKSGLLMKLQNLCTRLDQDESFSQRLPLNIEEAKDRLRILMLRKHPRSLLILDDVWDSWVLKAFDSQCQILLTTRDKSVTDSVMGPKYVVPVESSLGKEKGLEILSLFVNMKKADLPEQAHSIIKECKGSPLVVSLIGALLRDFPNRWEYYLKQLQNKQFKRIRKSSSYDYEALDEAMSISVEMLREDIKDYYTDLSILQKDVKVPTKVLCILWDMETEEVEDILQEFVNKSLLFCDRNGKSFRYYLHDLQVDFLTEKNCSQLQDLHKKIITQFQRYHQPHTLSPDQEDCMYWYNFLAYHMASAKMHKELCALMFSLDWIKAKTELVGPAHLIHEFVEYRHILDEKDCAVSENFQEFLSLNGHLLGRQPFPNIVQLGLCEPETSEVYQQAKLQAKQEVDNGMLYLEWINKKNITNLSRLVVRPHTDAVYHACFSEDGQRIASCGADKTLQVFKAETGEKLLEIKAHEDEVLCCAFSTDDRFIATCSVDKKVKIWNSMTGELVHTYDEHSEQVNCCHFTNSSHHLLLATGSSDCFLKLWDLNQKECRNTMFGHTNSVNHCRFSPDDKLLASCSADGTLKLWDATSANERKSINVKQFFLNLEDPQEDMEVIVKCCSWSADGARIMVAAKNKIFLFDIHTSGLLGEIHTGHHSTIQYCDFSPQNHLAVVALSQYCVELWNTDSRSKVADCRGHLSWVHGVMFSPDGSSFLTSSDDQTIRLWETKKVCKNSAVMLKQEVDVVFQENEVMVLAVDHIRRLQLINGRTGQIDYLTEAQVSCCCLSPHLQYIAFGDENGAIEILELVNNRIFQSRFQHKKTVWHIQFTADEKTLISSSDDAEIQVWNWQLDKCIFLRGHQETVKDFRLLKNSRLLSWSFDGTVKVWNIITGNKEKDFVCHQGTVLSCDISHDATKFSSTSADKTAKIWSFDLLLPLHELRGHNGCVRCSAFSVDSTLLATGDDNGEIRIWNVSNGELLHLCAPLSEEGAATHGGWVTDLCFSPDGKMLISAGGYIKWWNVVTGESSQTFYTNGTNLKKIHVSPDFKTYVTVDNLGILYILQTLE,4.0 +COc1cc(Nc2ncc3CCN(c3n2)c2ccccn2)cc(OC)c1OC,MAAAYLDPNLNHTPNSSTKTHLGTGMERSPGAMERVLKVFHYFESNSEPTTWASIIRHGDATDVRGIIQKIVDSHKVKHVACYGFRLSHLRSEEVHWLHVDMGVSSVREKYELAHPPEEWKYELRIRYLPKGFLNQFTEDKPTLNFFYQQVKSDYMLEIADQVDQEIALKLGCLEIRRSYWEMRGNALEKKSNYEVLEKDVGLKRFFPKSLLDSVKAKTLRKLIQQTFRQFANLNREESILKFFEILSPVYRFDKECFKCALGSSWIISVELAIGPEEGISYLTDKGCNPTHLADFTQVQTIQYSNSEDKDRKGMLQLKIAGAPEPLTVTAPSLTIAENMADLIDGYCRLVNGTSQSFIIRPQKEGERALPSIPKLANSEKQGMRTHAVSVSETDDYAEIIDEEDTYTMPSTRDYEIQRERIELGRCIGEGQFGDVHQGIYMSPENPALAVAIKTCKNCTSDSVREKFLQEALTMRQFDHPHIVKLIGVITENPVWIIMELCTLGELRSFLQVRKYSLDLASLILYAYQLSTALAYLESKRFVHRDIAARNVLVSSNDCVKLGDFGLSRYMEDSTYYKASKGKLPIKWMAPESINFRRFTSASDVWMFGVCMWEILMHGVKPFQGVKNNDVIGRIENGERLPMPPNCPPTLYSLMTKCWAYDPSRRPRFTELKAQLSTILEEEKAQQEERMRMESRRQATVSWDSGGSDEAPPKPSRPGYPSPRSSEGFYPSPQHMVQTNHYQVSGYPGSHGITAMAGSIYPGQASLLDQTDSWNHRPQEIAMWQPNVEDSTVLDLRGIGQVLPTHLMEERLIRQQQEMEEDQRWLEKEERFLKPDVRLSRGSIDREDGSLQGPIGNQHIYQPVGKPDPAAPPKKPPRPGAPGHLGSLASLSSPADSYNEGVKLQPQEISPPPTANLDRSNDKVYENVTGLVKAVIEMSSKIQPAPPEEYVPMVKEVGLALRTLLATVDETIPLLPASTHREIEMAQKLLNSDLGELINKMKLAQQYVMTSLQQEYKKQMLTAAHALAVDAKNLLDVIDQARLKMLGQTRPH,7.0 +COc1ccc2n(Cc3ccc(F)cc3)c(C)c(CC(NS(=O)(=O)c3ccc(OCC#CC)cc3)C(O)=O)c2c1,MRQSLLFLTSVVPFVLAPRPPDDPGFGPHQRLEKLDSLLSDYDILSLSNIQQHSVRKRDLQTSTHVETLLTFSALKRHFKLYLTSSTERFSQNFKVVVVDGKNESEYTVKWQDFFTGHVVGEPDSRVLAHIRDDDVIIRINTDGAEYNIEPLWRFVNDTKDKRMLVYKSEDIKNVSRLQSPKVCGYLKVDNEELLPKGLVDREPPEELVHRVKRRADPDPMKNTCKLLVVADHRFYRYMGRGEESTTTNYLIELIDRVDDIYRNTSWDNAGFKGYGIQIEQIRILKSPQEVKPGEKHYNMAKSYPNEEKDAWDVKMLLEQFSFDIAEEASKVCLAHLFTYQDFDMGTLGLAYVGSPRANSHGGVCPKAYYSPVGKKNIYLNSGLTSTKNYGKTILTKEADLVTTHELGHNFGAEHDPDGLAECAPNEDQGGKYVMYPIAVSGDHENNKMFSNCSKQSIYKTIESKAQECFQERSNKVCGNSRVDEGEECDPGIMYLNNDTCCNSDCTLKEGVQCSDRNSPCCKNCQFETAQKKCQEAINATCKGVSYCTGNSSECPPPGNAEDDTVCLDLGKCKDGKCIPFCEREQQLESCACNETDNSCKVCCRDLSGRCVPYVDAEQKNLFLRKGKPCTVGFCDMNGKCEKRVQDVIERFWDFIDQLSINTFGKFLADNIVGSVLVFSLIFWIPFSILVHCVDKKLDKQYESLSLFHPSNVEMLSSMDSASVRIIKPFPAPQTPGRLQPAPVIPSAPAAPKLDHQRMDTIQEDPSTDSHMDEDGFEKDPFPNSSTAAKSFEDLTDHPVTRSEKAASFKLQRQNRVDSKETEC,6.494850021680094 +COc1ccc(COc2ccc(Cc3cnc(N)nc3N)cc2OC)cc1,MELQAARACFALLWGCALAAAAAAQGKEVVLLDFAAAGGELGWLTHPYGKGWDLMQNIMNDMPIYMYSVCNVMSGDQDNWLRTNWVYRGEAERIFIELKFTVRDCNSFPGGASSCKETFNLYYAESDLDYGTNFQKRLFTKIDTIAPDEITVSSDFEARHVKLNVEERSVGPLTRKGFYLAFQDIGACVALLSVRVYYKKCPELLQGLAHFPETIAGSDAPSLATVAGTCVDHAVVPPGGEEPRMHCAVDGEWLVPIGQCLCQAGYEKVEDACQACSPGFFKFEASESPCLECPEHTLPSPEGATSCECEEGFFRAPQDPASMPCTRPPSAPHYLTAVGMGAKVELRWTPPQDSGGREDIVYSVTCEQCWPESGECGPCEASVRYSEPPHGLTRTSVTVSDLEPHMNYTFTVEARNGVSGLVTSRSFRTASVSINQTEPPKVRLEGRSTTSLSVSWSIPPPQQSRVWKYEVTYRKKGDSNSYNVRRTEGFSVTLDDLAPDTTYLVQVQALTQEGQGAGSKVHEFQTLSPEGSGNLAVIGGVAVGVVLLLVLAGVGFFIHRRRKNQRARQSPEDVYFSKSEQLKPLKTYVDPHTYEDPNQAVLKFTTEIHPSCVTRQKVIGAGEFGEVYKGMLKTSSGKKEVPVAIKTLKAGYTEKQRVDFLGEAGIMGQFSHHNIIRLEGVISKYKPMMIITEYMENGALDKFLREKDGEFSVLQLVGMLRGIAAGMKYLANMNYVHRDLAARNILVNSNLVCKVSDFGLSRVLEDDPEATYTTSGGKIPIRWTAPEAISYRKFTSASDVWSFGIVMWEVMTYGERPYWELSNHEVMKAINDGFRLPTPMDCPSAIYQLMMQCWQQERARRPKFADIVSILDKLIRAPDSLKTLADFDPRVSIRLPSTSGSEGVPFRTVSEWLESIKMQQYTEHFMAAGYTAIEKVVQMTNDDIKRIGVRLPGHQKRIAYSLLGLKDQVNTVGIPI,5.0 +CC(C)=CC(=O)c1cccc(Nc2nc(Nc3cccc(OC(F)(F)F)c3)ncc2F)c1,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,5.259637310505756 +FC(F)(F)c1ccc(cn1)-c1cnc2nc(COc3ccccn3)cn2c1,MVLLLILSVLLLKEDVRGSAQSSERRVVAHMPGDIIIGALFSVHHQPTVDKVHERKCGAVREQYGIQRVEAMLHTLERINSDPTLLPNITLGCEIRDSCWHSAVALEQSIEFIRDSLISSEEEEGLVRCVDGSSSSFRSKKPIVGVIGPGSSSVAIQVQNLLQLFNIPQIAYSATSMDLSDKTLFKYFMRVVPSDAQQARAMVDIVKRYNWTYVSAVHTEGNYGESGMEAFKDMSAKEGICIAHSYKIYSNAGEQSFDKLLKKLTSHLPKARVVACFCEGMTVRGLLMAMRRLGLAGEFLLLGSDGWADRYDVTDGYQREAVGGITIKLQSPDVKWFDDYYLKLRPETNHRNPWFQEFWQHRFQCRLEGFPQENSKYNKTCNSSLTLKTHHVQDSKMGFVINAIYSMAYGLHNMQMSLCPGYAGLCDAMKPIDGRKLLESLMKTNFTGVSGDTILFDENGDSPGRYEIMNFKEMGKDYFDYINVGSWDNGELKMDDDEVWSKKSNIIRSVCSEPCEKGQIKVIRKGEVSCCWTCTPCKENEYVFDEYTCKACQLGSWPTDDLTGCDLIPVQYLRWGDPEPIAAVVFACLGLLATLFVTVVFIIYRDTPVVKSSSRELCYIILAGICLGYLCTFCLIAKPKQIYCYLQRIGIGLSPAMSYSALVTKTNRIARILAGSKKKICTKKPRFMSACAQLVIAFILICIQLGIIVALFIMEPPDIMHDYPSIREVYLICNTTNLGVVTPLGYNGLLILSCTFYAFKTRNVPANFNEAKYIAFTMYTTCIIWLAFVPIYFGSNYKIITMCFSVSLSATVALGCMFVPKVYIILAKPERNVRSAFTTSTVVRMHVGDGKSSSAASRSSSLVNLWKRRGSSGETLRYKDRRLAQHKSEIECFTPKGSMGNGGRATMSSSNGKSVTWAQNEKSSRGQHLWQRLSIHINKKENPNQTAVIKPFPKSTESRGLGAGAGAGGSAGGVGATGGAGCAGAGPGGPESPDAGPKALYDVAEAEEHFPAPARPRSPSPISTLSHRAGSASRTDDDVPSLHSEPVARSSSSQGSLMEQISSVVTRFTANISELNSMMLSTAAPSPGVGAPLCSSYLIPKEIQLPTTMTTFAEIQPLPAIEVTGGAQPAAGAQAAGDAARESPAAGPEAAAAKPDLEELVALTPPSPFRDSVDSGSTTPNSPVSESALCIPSSPKYDTLIIRDYTQSSSSL,6.522878745280337 +COc1cccc([C@H]2O[C@H](CC(O)=O)c3nnc(n3-c3ccc(Cl)cc23)C(F)(F)F)c1C,MEFVKCLGHPEEFYNLLRFRMGGRRNFIPKMDRNSLSNSLKTCYKYLDQTSRSFAAVIQALDGDIRHAVCVFYLILRAMDTVEDDMAISVEKKIPLLRNFHTFLYEPEWRFTESKEKHRVVLEDFPTISLEFRNLAEKYQTVIADICHRMGCGMAEFLNKDVTSKQDWDKYCHYVAGLVGIGLSRLFSASEFEDPIVGEDTECANSMGLFLQKTNIIRDYLEDQQEGRQFWPQEVWGKYVKKLEDFVKPENVDVAVKCLNELITNALQHIPDVITYLSRLRNQSVFNFCAIPQVMAIATLAACYNNHQVFKGVVKIRKGQAVTLMMDATNMPAVKAIIYQYIEEIYHRVPNSDPSASKAKQLISNIRTQSLPNCQLISRSHYSPIYLSFIMLLAALSWQYLSTLSQVTEDYVQREH,9.070581074285707 +CCCOc1ccc(C2CNC(=O)N2c2ccc3[nH]cnc3c2)c(F)c1,MAGGRHRRVVGTLHLLLLVAALPWASRGVSPSASAWPEEKNYHQPAILNSSALRQIAEGTSISEMWQNDLQPLLIERYPGSPGSYAARQHIMQRIQRLQADWVLEIDTFLSQTPYGYRSFSNIISTLNPTAKRHLVLACHYDSKYFSHWNNRVFVGATDSAVPCAMMLELARALDKKLLSLKTVSDSKPDLSLQLIFFDGEEAFLHWSPQDSLYGSRHLAAKMASTPHPPGARGTSQLHGMDLLVLLDLIGAPNPTFPNFFPNSARWFERLQAIEHELHELGLLKDHSLEGRYFQNYSYGGVIQDDHIPFLRRGVPVLHLIPSPFPEVWHTMDDNEENLDESTIDNLNKILQVFVLEYLHL,5.0 +COCC[C@@H]1[C@@H](C)C\C=C\[C@@](CN2CCN(CC2)C(C)(C)C)(OC)[C@@H]2CC[C@H]2CN2C[C@@]3(CCCc4cc(Cl)ccc34)COc3ccc(cc23)C(=O)NS1(=O)=O,EDELYRQSLEIISRYLREQATGAKDTKPMGRSGATSRKALETLRRVGDGVQRNHETAFQGMLRKLDIKNEDDVKSLSRVMIHVFSDGVTNWGRIVTLISFGAFVAKHLKTINQESCIEPLAESITDVLVRTKRDWLVKQRGWDGFVEFFHVEDLEGGIRNVLLAFAG,10.075720713938118 +CNCCCCOc1ccccc1Cc1ccccc1,MFDGYDSCSEDTSSSSSSEESEEEVAPLPSNLPIIKNNGQVYTYPDGKSGMATCEMCGMVGVRDAFYSKTKRFCSVSCSRSYSSNSKKASILARLQGKPPTKKAKVLQKQPLVAKLAAYAQYQATLQNQAKTKAAVSMEGFSWGNYINSNSFIAAPVTCFKHAPMGTCWGDISENVRVEVPNTDCSLPTKVFWIAGIVKLAGYNALLRYEGFENDSGLDFWCNICGSDIHPVGWCAASGKPLVPPRTIQHKYTNWKAFLVKRLTGAKTLPPDFSQKVSESMQYPFKPCMRVEVVDKRHLCRTRVAVVESVIGGRLRLVYEESEDRTDDFWCHMHSPLIHHIGWSRSIGHRFKRSDITKKQDGHFDTPPHLFAKVKEVDQSGEWFKEGMKLEAIDPLNLSTICVATIRKVLADGFLMIGIDGSEAADGSDWFCYHATSPSIFPVGFCEINMIELTPPRGYTKLPFKWFDYLRETGSIAAPVKLFNKDVPNHGFRVGMKLEAVDLMEPRLICVATVTRIIHRLLRIHFDGWEEEYDQWVDCESPDLYPVGWCQLTGYQLQPPASQSSRENQSASSKQKKKAKSQQYKGHKKMTTLQLKEELLDGEDYNFLQGASDQESNGSANFYIKQEP,4.0 +OC(=O)CCC(=O)N1N=C(CC1c1ccc(Cl)cc1)c1c(-c2ccc(Cl)cc2)c2ccccc2[nH]c1=O,MGRLGYWTLLVLPALLVWRDPAQNAAAEKGPPALNIAVLLGHSHDVTERELRNLWGPEQATGLPLDVNVVALLMNRTDPKSLITHVCDLMSGARIHGLVFGDDTDQEAVAQMLDFISSQTFIPILGIHGGASMIMADKDPTSTFFQFGASIQQQATVMLKIMQDYDWHVFSLVTTIFPGYRDFISFIKTTVDNSFVGWDMQNVITLDTSFEDAKTQVQLKKIHSSVILLYCSKDEAVLILSEARSLGLTGYDFFWIVPSLVSGNTELIPKEFPSGLISVSYDDWDYSLEARVRDGLGILTTAASSMLEKFSYIPEAKASCYGQAEKPETPLHTLHQFMVNVTWDGKDLSFTEEGYQVHPRLVVIVLNKDREWEKVGKWENQTLSLRHAVWPRYKSFSDCEPDDNHLSIVTLEEAPFVIVEDIDPLTETCVRNTVPCRKFVKINNSTNEGMNVKKCCKGFCIDILKKLSRTVKFTYDLYLVTNGKHGKKVNNVWNGMIGEVVYQRAVMAVGSLTINEERSEVVDFSVPFVETGISVMVSRSNGTVSPSAFLEPFSASVWVMMFVMLLIVSAIAVFVFEYFSPVGYNRNLAKGKAPHGPSFTIGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANLAAFMIQEEFVDQVTGLSDKKFQRPHDYSPPFRFGTVPNGSTERNIRNNYPYMHQYMTRFNQRGVEDALVSLKTGKLDAFIYDAAVLNYKAGRDEGCKLVTIGSGYIFASTGYGIALQKGSPWKRQIDLALLQFVGDGEMEELETLWLTGICHNEKNEVMSSQLDIDNMAGVFYMLAAAMALSLITFIWEHLFYWKLRFCFTGVCSDRPGLLFSISRGIYSCIHGVHIEEKKKSPDFNLTGSQSNMLKLLRSAKNISNMSNMNSSRMDSPKRATDFIQRGSLIVDMVSDKGNLIYSDNRSFQGKDSIFGDNMNELQTFVANRHKDNLSNYVFQGQHPLTLNESNPNTVEVAVSTESKGNSRPRQLWKKSMESLRQDSLNQNPVSQRDEKTAENRTHSLKSPRYLPEEVAHSDISETSSRATCHREPDNNKNHKTKDNFKRSMASKYPKDCSDVDRTYMKTKASSPRDKIYTIDGEKEPSFHLDPPQFVENITLPENVGFPDTYQDHNENFRKGDSTLPMNRNPLHNEDGLPNNDQYKLYAKHFTLKDKGSPHSEGSDRYRQNSTHCRSCLSNLPTYSGHFTMRSPFKCDACLRMGNLYDIDEDQMLQETGNPATREEVYQQDWSQNNALQFQKNKLRINRQHSYDNILDKPREIDLSRPSRSISLKDRERLLEGNLYGSLFSVPSSKLLGNKSSLFPQGLEDSKRSKSLLPDHASDNPFLHTYGDDQRLVIGRCPSDPYKHSLPSQAVNDSYLRSSLRSTASYCSRDSRGHSDVYISEHVMPYAANKNTMYSTPRVLNSCSNRRVYKKMPSIESDV,4.6777807052660805 +Oc1ccc2C(=O)N(Cc3ccc(Cl)c(F)c3)C(=O)c2c1O,FLDGIDKAQEEHEKYHSNWRAMASDFNLPPVVAKEIVASCDKCQLKGEAMHGQVDCSPGIWQLDCTHLEGKVILVAVHVASGYIEAEVIPAETGQETAYFLLKLAGRWPVKTVHTDNGSNFTSTTVKAACWWAGIKQEFGIPYNPQSQGVIESMNKELKKIIGQVRDQAEHLKTAVQMAVFIHNFKRKGGIGGYSAGERIVDIIATDIQTKELQKQITKIQNFRVYYRDSRDPVWKGPAKLLWKGEGAVVIQDNSDIKVVPRRKAKIIRDYGKQMAGDDCVASRQDED,6.045757490560675 +CCCc1cc(N)c2cc(NC(=O)NCc3ccc(cc3)C(F)(F)F)ccc2n1,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,7.42021640338319 +CN(c1ccc(cc1)C1=CCOCC1)c1ccc2[C@H](CNc3cnccc3C(O)=O)CCOc2c1,MEVAEVESPLNPSCKIMTFRPSMEEFREFNKYLAYMESKGAHRAGLAKVIPPKEWKPRQCYDDIDNLLIPAPIQQMVTGQSGLFTQYNIQKKAMTVKEFRQLANSGKYCTPRYLDYEDLERKYWKNLTFVAPIYGADINGSIYDEGVDEWNIARLNTVLDVVEEECGISIEGVNTPYLYFGMWKTTFAWHTEDMDLYSINYLHFGEPKSWYAIPPEHGKRLERLAQGFFPSSSQGCDAFLRHKMTLISPSVLKKYGIPFDKITQEAGEFMITFPYGYHAGFNHGFNCAESTNFATVRWIDYGKVAKLCTCRKDMVKISMDIFVRKFQPDRYQLWKQGKDIYTIDHTKPTPASTPEVKAWLQRRRKVRKASRSFQCARSTSKRPKADEEEEVSDEVDGAEVPNPDSVTDDLKVSEKSEAAVKLRNTEASSEEESSASRMQVEQNLSDHIKLSGNSCLSTSVTEDIKTEDDKAYAYRSVPSISSEADDSIPLSSGYEKPEKSDPSELSWPKSPESCSSVAESNGVLTEGEESDVESHGNGLEPGEIPAVPSGERNSFKVPSIAEGENKTSKSWRHPLSRPPARSPMTLVKQQAPSDEELPEVLSIEEEVEETESWAKPLIHLWQTKSPNFAAEQEYNATVARMKPHCAICTLLMPYHKPDSSNEENDARWETKLDEVVTSEGKTKPLIPEMCFIYSEENIEYSPPNAFLEEDGTSLLISCAKCCVRVHASCYGIPSHEICDGWLCARCKRNAWTAECCLCNLRGGALKQTKNNKWAHVMCAVAVPEVRFTNVPERTQIDVGRIPLQRLKLKCIFCRHRVKRVSGACIQCSYGRCPASFHVTCAHAAGVLMEPDDWPYVVNITCFRHKVNPNVKSKACEKVISVGQTVITKHRNTRYYSCRVMAVTSQTFYEVMFDDGSFSRDTFPEDIVSRDCLKLGPPAEGEVVQVKWPDGKLYGAKYFGSNIAHMYQVEFEDGSQIAMKREDIYTLDEELPKRVKARFSTASDMRFEDTFYGADIIQGERKRQRVLSSRFKNEYVADPVYRTFLKSSFQKKCQKRQ,6.259637310505756 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+Oc1c(ncc2cccnc12)C(=O)c1ccc(Oc2ccccc2)cc1,MGIQGLAKLIADVAPSAIRENDIKSYFGRKVAIDASMSIYQFLIAVRQGGDVLQNEEGETTSHLMGMFYRTIRMMENGIKPVYVFDGKPPQLKSGELAKRSERRAEAEKQLQQAQAAGAEQEVEKFTKRLVKVTKQHNDECKHLLSLMGIPYLDAPSEAEASCAALVKAGKVYAAATEDMDCLTFGSPVLMRHLTASEAKKLPIQEFHLSRILQELGLNQEQFVDLCILLGSDYCESIRGIGPKRAVDLIQKHKSIEEIVRRLDPNKYPVPENWLHKEAHQLFLEPEVLDPESVELKWSEPNEEELIKFMCGEKQFSEERIRSGVKRLSKSRQGSTQGRLDDFFKVTGSLSSAKRKEPEPKGSTKKKAKTGAAGKFKRGK,4.5376020021010435 +[O-]C(=O)c1cccc(Cc2cc(Cl)ccc2OCc2ccc(F)cc2Cl)n1,MGLEALVPLAVIVAIFLLLVDLMHRRQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQLRRRFGDVFSLQLAWTPVVVLNGLAAVREALVTHGEDTADRPPVPITQILGFGPRSQGVFLARYGPAWREQRRFSVSTLRNLGLGKKSLEQWVTEEAACLCAAFANHSGRPFRPNGLLDKAVSNVIASLTCGRRFEYDDPRFLRLLDLAQEGLKEESGFLREVLNAVPVLLHIPALAGKVLRFQKAFLTQLDELLTEHRMTWDPAQPPRDLTEAFLAEMEKAKGNPESSFNDENLRIVVADLFSAGMVTTSTTLAWGLLLMILHPDVQRRVQQEIDDVIGQVRRPEMGDQAHMPYTTAVIHEVQRFGDIVPLGVTHMTSRDIEVQGFRIPKGTTLITNLSSVLKDEAVWEKPFRFHPEHFLDAQGHFVKPEAFLPFSAGRRACLGEPLARMELFLFFTSLLQHFSFSVPTGQPRPSHHGVFAFLVSPSPYELCAVPR,4.0 +OC(=O)C(=O)Nc1cc(sc1C(O)=O)-c1ccc(F)cc1,MAPEPAPGRTMVPLVPALVMLGLVAGAHGDSKPVFIKVPEDQTGLSGGVASFVCQATGEPKPRITWMKKGKKVSSQRFEVIEFDDGAGSVLRIQPLRVQRDEAIYECTATNSLGEINTSAKLSVLEEEQLPPGFPSIDMGPQLKVVEKARTATMLCAAGGNPDPEISWFKDFLPVDPATSNGRIKQLRSGALQIESSEESDQGKYECVATNSAGTRYSAPANLYVRVRRVAPRFSIPPSSQEVMPGGSVNLTCVAVGAPMPYVKWMMGAEELTKEDEMPVGRNVLELSNVVRSANYTCVAISSLGMIEATAQVTVKALPKPPIDLVVTETTATSVTLTWDSGNSEPVTYYGIQYRAAGTEGPFQEVDGVATTRYSIGGLSPFSEYAFRVLAVNSIGRGPPSEAVRARTGEQAPSSPPRRVQARMLSASTMLVQWEPPEEPNGLVRGYRVYYTPDSRRPPNAWHKHNTDAGLLTTVGSLLPGITYSLRVLAFTAVGDGPPSPTIQVKTQQGVPAQPADFQAEVESDTRIQLSWLLPPQERIIMYELVYWAAEDEDQQHKVTFDPTSSYTLEDLKPDTLYRFQLAARSDMGVGVFTPTIEARTAQSTPSAPPQKVMCVSMGSTTVRVSWVPPPADSRNGVITQYSVAYEAVDGEDRGRHVVDGISREHSSWDLVGLEKWTEYRVWVRAHTDVGPGPESSPVLVRTDEDVPSGPPRKVEVEPLNSTAVHVYWKLPVPSKQHGQIRGYQVTYVRLENGEPRGLPIIQDVMLAEAQWRPEESEDYETTISGLTPETTYSVTVAAYTTKGDGARSKPKIVTTTGAVPGRPTMMISTTAMNTALLQWHPPKELPGELLGYRLQYCRADEARPNTIDFGKDDQHFTVTGLHKGTTYIFRLAAKNRAGLGEEFEKEIRTPEDLPSGFPQNLHVTGLTTSTTELAWDPPVLAERNGRIISYTVVFRDINSQQELQNITTDTRFTLTGLKPDTTYDIKVRAWTSKGSGPLSPSIQSRTMPVEQVFAKNFRVAAAMKTSVLLSWEVPDSYKSAVPFKILYNGQSVEVDGHSMRKLIADLQPNTEYSFVLMNRGSSAGGLQHLVSIRTAPDLLPHKPLPASAYIEDGRFDLSMPHVQDPSLVRWFYIVVVPIDRVGGSMLTPRWSTPEELELDELLEAIEQGGEEQRRRRRQAERLKPYVAAQLDVLPETFTLGDKKNYRGFYNRPLSPDLSYQCFVLASLKEPMDQKRYASSPYSDEIVVQVTPAQQQEEPEMLWVTGPVLAVILIILIVIAILLFKRKRTHSPSSKDEQSIGLKDSLLAHSSDPVEMRRLNYQTPGMRDHPPIPITDLADNIERLKANDGLKFSQEYESIDPGQQFTWENSNLEVNKPKNRYANVIAYDHSRVILTSIDGVPGSDYINANYIDGYRKQNAYIATQGPLPETMGDFWRMVWEQRTATVVMMTRLEEKSRVKCDQYWPARGTETCGLIQVTLLDTVELATYTVRTFALHKSGSSEKRELRQFQFMAWPDHGVPEYPTPILAFLRRVKACNPLDAGPMVVHCSAGVGRTGCFIVIDAMLERMKHEKTVDIYGHVTCMRSQRNYMVQTEDQYVFIHEALLEAATCGHTEVPARNLYAHIQKLGQVPPGESVTAMELEFKLLASSKAHTSRFISANLPCNKFKNRLVNIMPYELTRVCLQPIRGVEGSDYINASFLDGYRQQKAYIATQGPLAESTEDFWRMLWEHNSTIIVMLTKLREMGREKCHQYWPAERSARYQYFVVDPMAEYNMPQYILREFKVTDARDGQSRTIRQFQFTDWPEQGVPKTGEGFIDFIGQVHKTKEQFGQDGPITVHCSAGVGRTGVFITLSIVLERMRYEGVVDMFQTVKTLRTQRPAMVQTEDQYQLCYRAALEYLGSFDHYAT,3.958607314841775 +COCc1ccc(NC(=O)c2c(C#Cc3cccnc3)n(c3ncnc(N)c23)C2(C)CC2)cc1,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,9.522878745280337 +CCC[C@@H]([C@@H](CC(C)C)C(=O)N[C@H]1N=C(c2ccccc2)c2ccccc2N(C)C1=O)C(N)=O,MPPLLAPLLCLALLPALAARGPRCSQPGETCLNGGKCEAANGTEACVCGGAFVGPRCQDPNPCLSTPCKNAGTCHVVDRRGVADYACSCALGFSGPLCLTPLDNACLTNPCRNGGTCDLLTLTEYKCRCPPGWSGKSCQQADPCASNPCANGGQCLPFEASYICHCPPSFHGPTCRQDVNECGQKPGLCRHGGTCHNEVGSYRCVCRATHTGPNCERPYVPCSPSPCQNGGTCRPTGDVTHECACLPGFTGQNCEENIDDCPGNNCKNGGACVDGVNTYNCRCPPEWTGQYCTEDVDECQLMPNACQNGGTCHNTHGGYNCVCVNGWTGEDCSENIDDCASAACFHGATCHDRVASFYCECPHGRTGLLCHLNDACISNPCNEGSNCDTNPVNGKAICTCPSGYTGPACSQDVDECSLGANPCEHAGKCINTLGSFECQCLQGYTGPRCEIDVNECVSNPCQNDATCLDQIGEFQCICMPGYEGVHCEVNTDECASSPCLHNGRCLDKINEFQCECPTGFTGHLCQYDVDECASTPCKNGAKCLDGPNTYTCVCTEGYTGTHCEVDIDECDPDPCHYGSCKDGVATFTCLCRPGYTGHHCETNINECSSQPCRHGGTCQDRDNAYLCFCLKGTTGPNCEINLDDCASSPCDSGTCLDKIDGYECACEPGYTGSMCNINIDECAGNPCHNGGTCEDGINGFTCRCPEGYHDPTCLSEVNECNSNPCVHGACRDSLNGYKCDCDPGWSGTNCDINNNECESNPCVNGGTCKDMTSGYVCTCREGFSGPNCQTNINECASNPCLNQGTCIDDVAGYKCNCLLPYTGATCEVVLAPCAPSPCRNGGECRQSEDYESFSCVCPTGWQGQTCEVDINECVLSPCRHGASCQNTHGGYRCHCQAGYSGRNCETDIDDCRPNPCHNGGSCTDGINTAFCDCLPGFRGTFCEEDINECASDPCRNGANCTDCVDSYTCTCPAGFSGIHCENNTPDCTESSCFNGGTCVDGINSFTCLCPPGFTGSYCQHDVNECDSQPCLHGGTCQDGCGSYRCTCPQGYTGPNCQNLVHWCDSSPCKNGGKCWQTHTQYRCECPSGWTGLYCDVPSVSCEVAAQRQGVDVARLCQHGGLCVDAGNTHHCRCQAGYTGSYCEDLVDECSPSPCQNGATCTDYLGGYSCKCVAGYHGVNCSEEIDECLSHPCQNGGTCLDLPNTYKCSCPRGTQGVHCEINVDDCNPPVDPVSRSPKCFNNGTCVDQVGGYSCTCPPGFVGERCEGDVNECLSNPCDARGTQNCVQRVNDFHCECRAGHTGRRCESVINGCKGKPCKNGGTCAVASNTARGFICKCPAGFEGATCENDARTCGSLRCLNGGTCISGPRSPTCLCLGPFTGPECQFPASSPCLGGNPCYNQGTCEPTSESPFYRCLCPAKFNGLLCHILDYSFGGGAGRDIPPPLIEEACELPECQEDAGNKVCSLQCNNHACGWDGGDCSLNFNDPWKNCTQSLQCWKYFSDGHCDSQCNSAGCLFDGFDCQRAEGQCNPLYDQYCKDHFSDGHCDQGCNSAECEWDGLDCAEHVPERLAAGTLVVVVLMPPEQLRNSSFHFLRELSRVLHTNVVFKRDAHGQQMIFPYYGREEELRKHPIKRAAEGWAAPDALLGQVKASLLPGGSEGGRRRRELDPMDVRGSIVYLEIDNRQCVQASSQCFQSATDVAAFLGALASLGSLNIPYKIEAVQSETVEPPPPAQLHFMYVAAAAFVLLFFVGCGVLLSRKRRRQHGQLWFPEGFKVSEASKKKRREPLGEDSVGLKPLKNASDGALMDDNQNEWGDEDLETKKFRFEEPVVLPDLDDQTDHRQWTQQHLDAADLRMSAMAPTPPQGEVDADCMDVNVRGPDGFTPLMIASCSGGGLETGNSEEEEDAPAVISDFIYQGASLHNQTDRTGETALHLAARYSRSDAAKRLLEASADANIQDNMGRTPLHAAVSADAQGVFQILIRNRATDLDARMHDGTTPLILAARLAVEGMLEDLINSHADVNAVDDLGKSALHWAAAVNNVDAAVVLLKNGANKDMQNNREETPLFLAAREGSYETAKVLLDHFANRDITDHMDRLPRDIAQERMHHDIVRLLDEYNLVRSPQLHGAPLGGTPTLSPPLCSPNGYLGSLKPGVQGKKVRKPSSKGLACGSKEAKDLKARRKKSQDGKGCLLDSSGMLSPVDSLESPHGYLSDVASPPLLPSPFQQSPSVPLNHLPGMPDTHLGIGHLNVAAKPEMAALGGGGRLAFETGPPRLSHLPVASGTSTVLGSSSGGALNFTVGGSTSLNGQCEWLSRLQSGMVPNQYNPLRGSVAPGPLSTQAPSLQHGMVGPLHSSLAASALSQMMSYQGLPSTRLATQPHLVQTQQVQPQNLQMQQQNLQPANIQQQQSLQPPPPPPQPHLGVSSAASGHLGRSFLSGEPSQADVQPLGPSSLAVHTILPQESPALPTSLPSSLVPPVTAAQFLTPPSQHSYSSPVDNTPSHQLQVPEHPFLTPSPESPDQWSSSSPHSNVSDWSEGVSSPPTSMQSQIARIPEAFK,7.193141970481182 +FC(F)(F)c1cccc(C(=O)N2CCc3c(C2)ncnc3-c2ccccn2)c1Cl,MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY,7.229147988357855 +CCCCCCCCCCCCC1CC(C(=O)Nc2c(cccc2C(C)C)C(C)C)C(=O)N1,PLFLKEVGSHFDDFVTNLIEKSASLDNGGCALTTFSILKEMKNNHRAKDLRAPPEQGKIFVARRSLLDELFEVDHIRTIYHMFIALLILFILSTLVVDYIDEGRLVLEFNLLSYAFGKLPTVVWTWWTMFLSTLSIPYFLFQHWANGYSKSSHPLMYSLFHGLLFMVFQLGILGFGPTYIVLAYTLPPASRFIVILEQIRLIMKAHSFVRENVPRVLNSAKEKSSTVPIPTVNQYLYFLFAPTLIYRDSYPRTPTVRWGYVAMQFAQVFGCLFYVYYIFERLCAPLFRNIKQEPFSARVLVLCIF,7.275724130399211 +CC(C)(C)OC(=O)N1CCN(CC1)C(=O)CCCc1c[nH]c2ccccc12,MPSYTVTVATGSQWFAGTDDYIYLSLIGSAGCSEKHLLDKAFYNDFERGGRDSYDVTVDEELGEIYLVKIEKRKYRLHDDWYLKYITLKTPHDYIEFPCYRWITGEGEIVLRDGCAKLARDDQIHILKQHRRKELETRQKQYRWMEWNPGFPLSIDAKCHKDLPRDIQFDSEKGVDFVLNYSKAMENLFINRFMHMFQSSWHDFADFEKIFVKISNTISERVKNHWQEDLMFGYQFLNGCNPVLIKRCTELPKKLPVTTEMVECSLERQLSLEQEVQEGNIFIVDYELLDGIDANKTDPCTHQFLAAPICLLYKNLANKIVPIAIQLNQTPGEKNPIFLPTDSKYDWLLAKIWVRSSDFHIHQTITHLLRTHLVSEVFGIAMYRQLPAVHPLFKLLVAHVRFTIAINTKAREQLNCEYGLFDKANATGGGGHVQMVQRAVQDLTYSSLCFPEAIKARGMDNTEDIPYYFYRDDGLLVWEAIQSFTTEVVSIYYEDDQVVEEDQELQDFVKDVYVYGMRGRKASGFPKSIKSREKLSEYLTVVIFTASAQHAAVNFGQYDWCSWIPNAPPTMRAPPPTAKGVVTIEQIVDTLPDRGRSCWHLGAVWALSQFQENELFLGMYPEEHFIEKPVKEAMIRFRKNLEAIVSVIAERNKNKKLPYYYLSPDRIPNSVAI,6.130768280269024 +O=C1CC2(CCCC2)CC(=O)N1CCN1CCN(CC1)c1ccccc1,MTFRDILSVTFEGPRSSSSTGGSGAGGGAGTVGPEGGAVGGVPGATGGGAVVGTGSGEDNQSSTGEPGAAASGEVNGSAAVGGLVVSAQGVGVGVFLAAFILTAVAGNLLVILSVACNRHLQTVTNYFIVNLAVADLLLSAAVLPFSATMEVLGFWAFGRTFCDVWAAVDVLCCTASILSLCTISVDRYVGVRHSLKYPAIMTERKAAAILALLWAVALVVSVGPLLGWKEPVPPDERFCGITEEVGYAIFSSVCSFYLPMAVIVVMYCRVYVVARSTTRSLEAGIKREPGKASEVVLRIHCRGAATSAKGYPGTQSSKGHTLRSSLSVRLLKFSREKKAAKTLAIVVGVFVLCWFPFFFVLPLGSLFPQLKPSEGVFKVIFWLGYFNSCVNPLIYPCSSREFKRAFLRLLRCQCRRRRRRLWAVYGHHWRASTGDARSDCAPSPRIAPPGAPLALTAHPGAGSADTPETQDSVSSSRKPASALREWRLLGPLQRPTTQLRAKVSSLSHKIRSGARRAETACALRSEVEAVSLNVPQDGAEAVICQAYEPGDYSNLRETDI,8.364516253185087 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+CCCc1c(OCCCN2C(=O)Cc3cc(ccc23)C(O)=O)ccc2c(noc12)C(F)(F)F,MSSPTTSSLDTPLPGNGPPQPGAPSSSPTVKEEGPEPWPGGPDPDVPGTDEASSACSTDWVIPDPEEEPERKRKKGPAPKMLGHELCRVCGDKASGFHYNVLSCEGCKGFFRRSVVRGGARRYACRGGGTCQMDAFMRRKCQQCRLRKCKEAGMREQCVLSEEQIRKKKIRKQQQESQSQSQSPVGPQGSSSSASGPGASPGGSEAGSQGSGEGEGVQLTAAQELMIQQLVAAQLQCNKRSFSDQPKVTPWPLGADPQSRDARQQRFAHFTELAIISVQEIVDFAKQVPGFLQLGREDQIALLKASTIEIMLLETARRYNHETECITFLKDFTYSKDDFHRAGLQVEFINPIFEFSRAMRRLGLDDAEYALLIAINIFSADRPNVQEPGRVEALQQPYVEALLSYTRIKRPQDQLRFPRMLMKLVSLRTLSSVHSEQVFALRLQDKKLPPLLSEIWDVHE,5.356547323513812 +O=C(Nc1ccc(cc1)C12CC3CC(C1)CC(C3)(C2)c1ccc(cc1)C#N)c1ccccc1,MTELKAKGPRAPHVAGGPPSPEVGSPLLCRPAAGPFPGSQTSDTLPEVSAIPISLDGLLFPRPCQGQDPSDEKTQDQQSLSDVEGAYSRAEATRGAGGSSSSPPEKDSGLLDSVLDTLLAPSGPGQSQPSPPACEVTSSWCLFGPELPEDPPAAPATQRVLSPLMSRSGCKVGDSSGTAAAHKVLPRGLSPARQLLLPASESPHWSGAPVKPSPQAAAVEVEEEDGSESEESAGPLLKGKPRALGGAAAGGGAAAVPPGAAAGGVALVPKEDSRFSAPRVALVEQDAPMAPGRSPLATTVMDFIHVPILPLNHALLAARTRQLLEDESYDGGAGAASAFAPPRSSPCASSTPVAVGDFPDCAYPPDAEPKDDAYPLYSDFQPPALKIKEEEEGAEASARSPRSYLVAGANPAAFPDFPLGPPPPLPPRATPSRPGEAAVTAAPASASVSSASSSGSTLECILYKAEGAPPQQGPFAPPPCKAPGASGCLLPRDGLPSTSASAAAAGAAPALYPALGLNGLPQLGYQAAVLKEGLPQVYPPYLNYLRPDSEASQSPQYSFESLPQKICLICGDEASGCHYGVLTCGSCKVFFKRAMEGQHNYLCAGRNDCIVDKIRRKNCPACRLRKCCQAGMVLGGRKFKKFNKVRVVRALDAVALPQPVGVPNESQALSQRFTFSPGQDIQLIPPLINLLMSIEPDVIYAGHDNTKPDTSSSLLTSLNQLGERQLLSVVKWSKSLPGFRNLHIDDQITLIQYSWMSLMVFGLGWRSYKHVSGQMLYFAPDLILNEQRMKESSFYSLCLTMWQIPQEFVKLQVSQEEFLCMKVLLLLNTIPLEGLRSQTQFEEMRSSYIRELIKAIGLRQKGVVSSSQRFYQLTKLLDNLHDLVKQLHLYCLNTFIQSRALSVEFPEMMSEVIAAQLPKILAGMVKPLLFHKK,6.393618634889395 +Cc1ccc2nc(SCc3ccc(cc3)[N+]([O-])=O)[nH]c2c1,MTEGARAADEVRVPLGAPPPGPAALVGASPESPGAPGREAERGSELGVSPSESPAAERGAELGADEEQRVPYPALAATVFFCLGQTTRPRSWCLRLVCNPWFEHVSMLVIMLNCVTLGMFRPCEDVECGSERCNILEAFDAFIFAFFAVEMVIKMVALGLFGQKCYLGDTWNRLDFFIVVAGMMEYSLDGHNVSLSAIRTVRVLRPLRAINRVPSMRILVTLLLDTLPMLGNVLLLCFFVFFIFGIVGVQLWAGLLRNRCFLDSAFVRNNNLTFLRPYYQTEEGEENPFICSSRRDNGMQKCSHIPGRRELRMPCTLGWEAYTQPQAEGVGAARNACINWNQYYNVCRSGDSNPHNGAINFDNIGYAWIAIFQVITLEGWVDIMYYVMDAHSFYNFIYFILLIIVGSFFMINLCLVVIATQFSETKQRESQLMREQRARHLSNDSTLASFSEPGSCYEELLKYVGHIFRKVKRRSLRLYARWQSRWRKKVDPSAVQGQGPGHRQRRAGRHTASVHHLVYHHHHHHHHHYHFSHGSPRRPGPEPGACDTRLVRAGAPPSPPSPGRGPPDAESVHSIYHADCHIEGPQERARVAHAAATAAASLRLATGLGTMNYPTILPSGVGSGKGSTSPGPKGKWAGGPPGTGGHGPLSLNSPDPYEKIPHVVGEHGLGQAPGHLSGLSVPCPLPSPPAGTLTCELKSCPYCTRALEDPEGELSGSESGDSDGRGVYEFTQDVRHGDRWDPTRPPRATDTPGPGPGSPQRRAQQRAAPGEPGWMGRLWVTFSGKLRRIVDSKYFSRGIMMAILVNTLSMGVEYHEQPEELTNALEISNIVFTSMFALEMLLKLLACGPLGYIRNPYNIFDGIIVVISVWEIVGQADGGLSVLRTFRLLRVLKLVRFLPALRRQLVVLVKTMDNVATFCTLLMLFIFIFSILGMHLFGCKFSLKTDTGDTVPDRKNFDSLLWAIVTVFQILTQEDWNVVLYNGMASTSSWAALYFVALMTFGNYVLFNLLVAILVEGFQAEGDANRSDTDEDKTSVHFEEDFHKLRELQTTELKMCSLAVTPNGHLEGRGSLSPPLIMCTAATPMPTPKSSPFLDAAPSLPDSRRGSSSSGDPPLGDQKPPASLRSSPCAPWGPSGAWSSRRSSWSSLGRAPSLKRRGQCGERESLLSGEGKGSTDDEAEDGRAAPGPRATPLRRAESLDPRPLRPAALPPTKCRDRDGQVVALPSDFFLRIDSHREDAAELDDDSEDSCCLRLHKVLEPYKPQWCRSREAWALYLFSPQNRFRVSCQKVITHKMFDHVVLVFIFLNCVTIALERPDIDPGSTERVFLSVSNYIFTAIFVAEMMVKVVALGLLSGEHAYLQSSWNLLDGLLVLVSLVDIVVAMASAGGAKILGVLRVLRLLRTLRPLRVISRAPGLKLVVETLISSLRPIGNIVLICCAFFIIFGILGVQLFKGKFYYCEGPDTRNISTKAQCRAAHYRWVRRKYNFDNLGQALMSLFVLSSKDGWVNIMYDGLDAVGVDQQPVQNHNPWMLLYFISFLLIVSFFVLNMFVGVVVENFHKCRQHQEAEEARRREEKRLRRLERRRRSTFPSPEAQRRPYYADYSPTRRSIHSLCTSHYLDLFITFIICVNVITMSMEHYNQPKSLDEALKYCNYVFTIVFVFEAALKLVAFGFRRFFKDRWNQLDLAIVLLSLMGITLEEIEMSAALPINPTIIRIMRVLRIARVLKLLKMATGMRALLDTVVQALPQVGNLGLLFMLLFFIYAALGVELFGRLECSEDNPCEGLSRHATFSNFGMAFLTLFRVSTGDNWNGIMKDTLRECSREDKHCLSYLPALSPVYFVTFVLVAQFVLVNVVVAVLMKHLEESNKEAREDAELDAEIELEMAQGPGSARRVDADRPPLPQESPGARDAPNLVARKVSVSRMLSLPNDSYMFRPVVPASAPHPRPLQEVEMETYGAGTPLGSVASVHSPPAESCASLQIPLAVSSPARSGEPLHALSPRGTARSPSLSRLLCRQEAVHTDSLEGKIDSPRDTLDPAEPGEKTPVRPVTQGGSLQSPPRSPRPASVRTRKHTFGQRCVSSRPAAPGGEEAEASDPADEEVSHITSSACPWQPTAEPHGPEASPVAGGERDLRRLYSVDAQGFLDKPGRADEQWRPSAELGSGEPGEAKAWGPEAEPALGARRKKKMSPPCISVEPPAEDEGSARPSAAEGGSTTLRRRTPSCEATPHRDSLEPTEGSGAGGDPAAKGERWGQASCRAEHLTVPSFAFEPLDLGVPSGDPFLDGSHSVTPESRASSSGAIVPLEPPESEPPMPVGDPPEKRRGLYLTVPQCPLEKPGSPSATPAPGGGADDPV,5.355561410532161 +Cc1cc(COc2ccc(cc2)C(=O)NCC2(C3CCN(CC3)S(C)(=O)=O)C(=O)NC(=O)NC2=O)c2ccccc2n1,MKFLLILLLQATASGALPLNSSTSLEKNNVLFGERYLEKFYGLEINKLPVTKMKYSGNLMKEKIQEMQHFLGLKVTGQLDTSTLEMMHAPRCGVPDVHHFREMPGGPVWRKHYITYRINNYTPDMNREDVDYAIRKAFQVWSNVTPLKFSKINTGMADILVVFARGAHGDFHAFDGKGGILAHAFGPGSGIGGDAHFDEDEFWTTHSGGTNLFLTAVHEIGHSLGLGHSSDPKAVMFPTYKYVDINTFRLSADDIRGIQSLYGDPKENQRLPNPDNSEPALCDPNLSFDAVTTVGNKIFFFKDRFFWLKVSERPKTSVNLISSLWPTLPSGIEAAYEIEARNQVFLFKDDKYWLISNLRPEPNYPKSIHSFGFPNFVKKIDAAVFNPRFYRTYFFVDNQYWRYDERRQMMDPGYPKLITKNFQGIGPKIDAVFYSKNKYYYFFQGSNQFEYDFLLQRITKTLKSNSWFGC,5.220403508742176 +C[C@@H](Oc1ccccc1-c1cccc(c1)[N+]([O-])=O)C1=NCCN1,MASPALAAALAVAAAAGPNASGAGERGSGGVANASGASWGPPRGQYSAGAVAGLAAVVGFLIVFTVVGNVLVVIAVLTSRALRAPQNLFLVSLASADILVATLVMPFSLANELMAYWYFGQVWCGVYLALDVLFCTSSIVHLCAISLDRYWSVTQAVEYNLKRTPRRVKATIVAVWLISAVISFPPLVSLYRQPDGAAYPQCGLNDETWYILSSCIGSFFAPCLIMGLVYARIYRVAKLRTRTLSEKRAPVGPDGASPTTENGLGAAAGAGENGHCAPPPADVEPDESSAAAERRRRRGALRRGGRRRAGAEGGAGGADGQGAGPGAAESGALTASRSPGPGGRLSRASSRSVEFFLSRRRRARSSVCRRKVAQAREKRFTFVLAVVMGVFVLCWFPFFFSYSLYGICREACQVPGPLFKFFFWIGYCNSSLNPVIYTVFNQDFRRSFKHILFRRRRRGFRQ,6.590066876668706 +CCOc1cc(-c2ccc(nc2)N2CCN(CC2)C(=O)C(N(C)C)c2ccc(F)cc2)c2c(cnn2c1)C#N,HCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYRSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,6.059483515067432 +COCCOCCOCCNc1nc2ccc3C[C@@H]4[C@@H]5CCCC[C@]5(CCN4C)c3c2s1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,6.0 +CN(C)Cc1ccncc1NC(=O)c1nc(cnc1N)-c1ccc(cc1)S(=O)(=O)N1CCCC1,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASTPTNATAASDANTGDRGQTNNAASASASNST,9.318758762624412 +CCCCCCC(Sc1nc(Cl)cc(Nc2ccc3ncccc3c2)n1)C(O)=O,MPSYTVTVATGSQWFAGTDDYIYLSLVGSAGCSEKHLLDKPFYNDFERGAVDSYDVTVDEELGEIQLVRIEKRKYWLNDDWYLKYITLKTPHGDYIEFPCYRWITGDVEVVLRDGRAKLARDDQIHILKQHRRKELETRQKQYRWMEWNPGFPLSIDAKCHKDLPRDIQFDSEKGVDFVLNYSKAMENLFINRFMHMFQSSWNDFADFEKIFVKISNTISERVMNHWQEDLMFGYQFLNGCNPVLIRRCTELPEKLPVTTEMVECSLERQLSLEQEVQQGNIFIVDFELLDGIDANKTDPCTLQFLAAPICLLYKNLANKIVPIAIQLNQIPGDENPIFLPSDAKYDWLLAKIWVRSSDFHVHQTITHLLRTHLVSEVFGIAMYRQLPAVHPIFKLLVAHVRFTIAINTKAREQLICECGLFDKANATGGGGHVQMVQRAMKDLTYASLCFPEAIKARGMESKEDIPYYFYRDDGLLVWEAIRTFTAEVVDIYYEGDQVVEEDPELQDFVNDVYVYGMRGRKSSGFPKSVKSREQLSEYLTVVIFTASAQHAAVNFGQYDWCSWIPNAPPTMRAPPPTAKGVVTIEQIVDTLPDRGRSCWHLGAVWALSQFQENELFLGMYPEEHFIEKPVKEAMARFRKNLEAIVSVIAERNKKKQLPYYYLSPDRIPNSVAI,4.468521082957745 +[I-].CCCCCCCCCCCCCCCC[N+]1=C(C)N(Cc2ccccc2)CC1,MADEDLIFRLEGVDGGQSPRAGHDGDSDGDSDDEEGYFICPITDDPSSNQNVNSKVNKYYSNLTKSERYSSSGSPANSFHFKEAWKHAIQKAKHMPDPWAEFHLEDIATERATRHRYNAVTGEWLDDEVLIKMASQPFGRGAMRECFRTKKLSNFLHAQQWKGASNYVAKRYIEPVDRDVYFEDVRLQMEAKLWGEEYNRHKPPKQVDIMQMCIIELKDRPGKPLFHLEHYIEGKYIKYNSNSGFVRDDNIRLTPQAFSHFTFERSGHQLIVVDIQGVGDLYTDPQIHTETGTDFGDGNLGVRGMALFFYSHACNRICESMGLAPFDLSPRERDAVNQNTKLLQSAKTILRGTEEKCGSPQVRTLSGSRPPLLRPLSENSGDENMSDVTFDSLPSSPSSATPHSQKLDHLHWPVFSDLDNMASRDHDHLDNHRESENSGDSGYPSEKRGELDDPEPREHGHSYSNRKYESDEDSLGSSGRVCVEKWNLLNSSRLHLPRASAVALEVQRLNALDLEKKIGKSILGKVHLAMVRYHEGGRFCEKGEEWDQESAVFHLEHAANLGELEAIVGLGLMYSQLPHHILADVSLKETEENKTKGFDYLLKAAEAGDRQSMILVARAFDSGQNLSPDRCQDWLEALHWYNTALEMTDCDEGGEYDGMQDEPRYMMLAREAEMLFTGGYGLEKDPQRSGDLYTQAAEAAMEAMKGRLANQYYQKAEEAWAQMEE,7.221848749616356 +OCc1ccc(o1)C(=O)NN=Cc1cc(C(O)=O)c(Nc2ccc(I)cc2F)c(F)c1F,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,5.522878745280337 +CCCN1CCC[C@H](C1)c1cccc(CC#N)c1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,6.66354026615147 +CCN(C(=O)c1ccccc1)c1ccc2n(CCC(N)=O)c(NC(=O)c3ccc(cc3)C#N)nc2c1,MATGGRRGAAAAPLLVAVAALLLGAAGHLYPGEVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNNELCYLATIDWSRILDSVEDNYIVLNKDDNEECGDICPGTAKGKTNCPATVINGQFVERCWTHSHCQKVCPTICKSHGCTAEGLCCHSECLGNCSQPDDPTKCVACRNFYLDGRCVETCPPPYYHFQDWRCVNFSFCQDLHHKCKNSRRQGCHQYVIHNNKCIPECPSGYTMNSSNLLCTPCLGPCPKVCHLLEGEKTIDSVTSAQELRGCTVINGSLIINIRGGNNLAAELEANLGLIEEISGYLKIRRSYALVSLSFFRKLRLIRGETLEIGNYSFYALDNQNLRQLWDWSKHNLTITQGKLFFHYNPKLCLSEIHKMEEVSGTKGRQERNDIALKTNGDQASCENELLKFSYIRTSFDKILLRWEPYWPPDFRDLLGFMLFYKEAPYQNVTEFDGQDACGSNSWTVVDIDPPLRSNDPKSQNHPGWLMRGLKPWTQYAIFVKTLVTFSDERRTYGAKSDIIYVQTDATNPSVPLDPISVSNSSSQIILKWKPPSDPNGNITHYLVFWERQAEDSELFELDYCLKGLKLPSRTWSPPFESEDSQKHNQSEYEDSAGECCSCPKTDSQILKELEESSFRKTFEDYLHNVVFVPRKTSSGTGAEDPRPSRKRRSLGDVGNVTVAVPTVAAFPNTSSTSVPTSPEEHRPFEKVVNKESLVISGLRHFTGYRIELQACNQDTPEERCSVAAYVSARTMPEAKADDIVGPVTHEIFENNVVHLMWQEPKEPNGLIVLYEVSYRRYGDEELHLCVSRKHFALERGCRLRGLSPGNYSVRIRATSLAGNGSWTEPTYFYVTDYLDVPSNIAKIIIGPLIFVFLFSVVIGSIYLFLRKRQPDGPLGPLYASSNPEYLSASDVFPCSVYVPDEWEVSREKITLLRELGQGSFGMVYEGNARDIIKGEAETRVAVKTVNESASLRERIEFLNEASVMKGFTCHHVVRLLGVVSKGQPTLVVMELMAHGDLKSYLRSLRPEAENNPGRPPPTLQEMIQMAAEIADGMAYLNAKKFVHRDLAARNCMVAHDFTVKIGDFGMTRDIYETDYYRKGGKGLLPVRWMAPESLKDGVFTTSSDMWSFGVVLWEITSLAEQPYQGLSNEQVLKFVMDGGYLDQPDNCPERVTDLMRMCWQFNPKMRPTFLEIVNLLKDDLHPSFPEVSFFHSEENKAPESEELEMEFEDMENVPLDRSSHCQREEAGGRDGGSSLGFKRSYEEHIPYTHMNGGKKNGRILTLPRSNPS,5.0 +CCN(CC)CCNC(=O)c1c(C)[nH]c(\C=C2/C(=O)Nc3ccc(F)cc23)c1C,MFQASMRSPNMEPFKQQKVEDFYDIGEELGSGQFAIVKKCREKSTGLEYAAKFIKKRQSRASRRGVSREEIEREVSILRQVLHHNVITLHDVYENRTDVVLILELVSGGELFDFLAQKESLSEEEATSFIKQILDGVNYLHTKKIAHFDLKPENIMLLDKNIPIPHIKLIDFGLAHEIEDGVEFKNIFGTPEFVAPEIVNYEPLGLEADMWSIGVITYILLSGASPFLGDTKQETLANITAVSYDFDEEFFSQTSELAKDFIRKLLVKETRKRLTIQEALRHPWITPVDNQQAMVRRESVVNLENFRKQYVRRRWKLSFSIVSLCNHLTRSLMKKVHLRPDEDLRNCESDTEEDIARRKALHPRRRSSTS,6.823908740944319 +COc1cc2ncnc(Oc3cccc(NC(=O)Nc4cc(nn4-c4ccc(C)nc4)C(C)(C)C)c3)c2cc1OC,MEHIQGAWKTISNGFGFKDAVFDGSSCISPTIVQQFGYQRRASDDGKLTDPSKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARLDWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPTMCVDWSNIRQLLLFPNSTIGDSGVPALPSLTMRRMRESVSRMPVSSQHRYSTPHAFTFNTSSPSSEGSLSQRQRSTSTPNVHMVSTTLPVDSRMIEDAIRSHSESASPSALSSSPNNLSPTGWSQPKTPVPAQRERAPVSGTQEKNKIRPRGQRDSSYYWEIEASEVMLSTRIGSGSFGTVYKGKWHGDVAVKILKVVDPTPEQFQAFRNEVAVLRKTRHVNILLFMGYMTKDNLAIVTQWCEGSSLYKHLHVQETKFQMFQLIDIARQTAQGMDYLHAKNIIHRDMKSNNIFLHEGLTVKIGDFGLATVKSRWSGSQQVEQPTGSVLWMAPEVIRMQDNNPFSFQSDVYSYGIVLYELMTGELPYSHINNRDQIIFMVGRGYASPDLSKLYKNCPKAMKRLVADCVKKVKEERPLFPQILSSIELLQHSLPKINRSASEPSLHRAAHTEDINACTLTTSPRLPVF,6.425968732272281 +CC(C1CN(C)C1)c1cc(Cl)c2CCN(Cc3c(C)cc(C)[nH]c3=O)C(=O)c2c1Cl,GQTGKKSEKGPVCWRKRVKSEYMRLRQLKRFRRADEVKSMFSSNRQKILERTEILNQEWKQRRIQPVHILTSVSSLRGTRECSVTSDLDFPTQVIPLKTLNAVASVPIMYSWSPLQQNFMVEDETVLHNIPYMGDEVLDQDGTFIEELIKNYDGKVHGDRECGFINDEIFVELVNALGQYNDDDDDDDGDDPEEREEKQKDLEDHRDDKESRPPRKFPSDKIFEAISSMFPDKGTAEELKEKYKELTEQQLPGALPPECTPNIDGPNAKSVQREQSLHSFHTLFCRRCFKYDCFLHPFHATPNTYKRKNTETALDNKPCGPQCYQHLEGAKEFAAALTAERIKTPPKRPGGRRRGRLPNNSSRPSTPTINVLESKDTDSDREAGTETGGENNDKEEEEKKDETSSSSEANSRCQTPIKMKPNIEPPENVEWSGAEASMFRVLIGTYYDNFCAIARLIGTKTCRQVYEFRVKESSIIAPAPAEDVDTPPRKKKRKHRLWAAHCRKIQLKKDGSSNHVYNYQPCDHPRQPCDSSCPCVIAQNFCEKFCQCSSECQNRFPGCRCKAQCNTKQCPCYLAVRECDPDLCLTCGAADHWDSKNVSCKNCSIQRGSKKHLLLAPSDVAGWGIFIKDPVQKNEFISENCGEIISQDEADRRGKVYDKYMCSFLFNLNNDFVVDATRKGNKIRFANHSVNPNCYAKVMMVNGDHRIGIFAKRAIQTGEELFFDYRYSQADALKYVGIEREMEIP,6.82102305270683 +C[C@@]1(N=C(N)S[C@]2(C[C@@H]12)C(=O)N1CCOCC1)c1cc(\C=C(/F)c2ccc(cn2)C2COC2)ccc1F,MQPSSLLPLALCLLAAPASALVRIPLHKFTSIRRTMSEVGGSVEDLIAKGPVSKYSQAVPAVTEGPIPEVLKNYMDAQYYGEIGIGTPPQCFTVVFDTGSSNLWVPSIHCKLLDIACWIHHKYNSDKSSTYVKNGTSFDIHYGSGSLSGYLSQDTVSVPCQSASSASALGGVKVERQVFGEATKQPGITFIAAKFDGILGMAYPRISVNNVLPVFDNLMQQKLVDQNIFSFYLSRDPDAQPGGELMLGGTDSKYYKGSLSYLNVTRKAYWQVHLDQVEVASGLTLCKEGCEAIVDTGTSLMVGPVDEVRELQKAIGAVPLIQGEYMIPCEKVSTLPAITLKLGGKGYKLSPEDYTLKVSQAGKTLCLSGFMGMDIPPPSGPLWILGDVFIGRYYTVFDRDNNRVGFAEAARL,3.525201181199369 +Oc1ccc(cc1)N(C(=O)c1cc(-c2cc3OCOc3cc2C(=O)N2Cc3ccccc3C[C@H]2CN2CCOCC2)n2CCCCc12)c1ccc(OC(F)(F)F)cc1,MAQAGRTGYDNREIVMKYIHYKLSQRGYEWDAGDADAAPLGAAPTPGIFSFQPESNPMPAVHRDMAARTSPLRPLVATAGPALSPVPPVVHLTLRRAGDDFSRRYRRDFAEMSSQLHLTPFTARGRFATVVEELFRDGVNWGRIVAFFEFGGVMCVESVNREMSPLVDNIALWMTEYLNRHLHTWIQDNGGWDAFVELYGPSMRPLFDFSWLSLKTLLSLALVGACITLGAYLGHK,7.292429823902063 +COc1ccc(Cn2c3ncc(CN4CCN(CC5CCOC5)CC4)cc3c3ncnn3c2=O)cc1,MELSPRSPPEMLEESDCPSPLELKSAPSKKMWIKLRSLLRYMVKQLENGEINIEELKKNLEYTASLLEAVYIDETRQILDTEDELQELRSDAVPSEVRDWLASTFTQQARAKGRRAEEKPKFRSIVHAVQAGIFVERMFRRTYTSVGPTYSTAVLNCLKNLDLWCFDVFSLNQAADDHALRTIVFELLTRHNLISRFKIPTVFLMSFLDALETGYGKYKNPYHNQIHAADVTQTVHCFLLRTGMVHCLSEIELLAIIFAAAIHDYEHTGTTNSFHIQTKSECAIVYNDRSVLENHHISSVFRLMQDDEMNIFINLTKDEFVELRALVIEMVLATDMSCHFQQVKTMKTALQQLERIDKPKALSLLLHAADISHPTKQWLVHSRWTKALMEEFFRQGDKEAELGLPFSPLCDRTSTLVAQSQIGFIDFIVEPTFSVLTDVAEKSVQPLADEDSKSKNQPSFQWRQPSLDVEVGDPNPDVVSFRSTWVKRIQENKQKWKERAASGITNQMSIDELSPCEEEAPPSPAEDEHNQNGNLD,5.259637310505756 +CC[N+](C)(C)CCCCCC[N+](C)(C)CCCN1C(=O)c2ccccc2C1=O,MNNSTNSSNSGLALTSPYKTFEVVFIVLVAGSLSLVTIIGNILVMVSIKVNRHLQTVNNYFLFSLACADLIIGVFSMNLYTLYTVIGYWPLGPVVCDLWLALDYVVSNASVMNLLIISFDRYFCVTKPLTYPVKRTTKMAGMMIAAAWVLSFILWAPAILFWQFIVGVRTVEDGECYIQFFSNAAVTFGTAIAAFYLPVIIMTVLYWHISRASKSRIKKDKKEPVANQEPVSPSLVQGRIVKPNNNNMPGSDEALEHNKIQNGKAPRDAVTENCVQGEEKESSNDSTSVSAVASNMRDDEITQDENTVSTSLGHSKDENSKQTCIKIVTKTQKSDSCTPANTTVELVGSSGQNGDEKQNIVARKIVKMTKQPAKKKPPPSREKKVTRTILAILLAFIITWAPYNVMVLINTFCAPCIPNTVWTIGYWLCYINSTINPACYALCNATFKKTFKHLLMCHYKNIGATR,5.0 +CN(C)Cc1ccc(cc1)S(=O)(=O)n1ccc(\C=C\C(=O)NO)c1,MTSTGQDSTTTRQRRSRQNPQSPPQDSSVTSKRNIKKGAVPRSIPNLAEVKKKGKMKKLGQAMEEDLIVGLQGMDLNLEAEALAGTGLVLDEQLNEFHCLWDDSFPEGPERLHAIKEQLIQEGLLDRCVSFQARFAEKEELMLVHSLEYIDLMETTQYMNEGELRVLADTYDSVYLHPNSYSCACLASGSVLRLVDAVLGAEIRNGMAIIRPPGHHAQHSLMDGYCMFNHVAVAARYAQQKHRIRRVLIVDWDVHHGQGTQFTFDQDPSVLYFSIHRYEQGRFWPHLKASNWSTTGFGQGQGYTINVPWNQVGMRDADYIAAFLHVLLPVALEFQPQLVLVAAGFDALQGDPKGEMAATPAGFAQLTHLLMGLAGGKLILSLEGGYNLRALAEGVSASLHTLLGDPCPMLESPGAPCRSAQASVSCALEALEPFWEVLVRSTETVERDNMEEDNVEESEEEGPWEPPVLPILTWPVLQSRTGLVYDQNMMNHCNLWDSHHPEVPQRILRIMCRLEELGLAGRCLTLTPRPATEAELLTCHSAEYVGHLRATEKMKTRELHRESSNFDSIYICPSTFACAQLATGAACRLVEAVLSGEVLNGAAVVRPPGHHAEQDAACGFCFFNSVAVAARHAQTISGHALRILIVDWDVHHGNGTQHMFEDDPSVLYVSLHRYDHGTFFPMGDEGASSQIGRAAGTGFTVNVAWNGPRMGDADYLAAWHRLVLPIAYEFNPELVLVSAGFDAARGDPLGGCQVSPEGYAHLTHLLMGLASGRIILILEGGYNLTSISESMAACTRSLLGDPPPLLTLPRPPLSGALASITETIQVHRRYWRSLRVMKVEDREGPSSSKLVTKKAPQPAKPRLAERMTTREKKVLEAGMGKVTSASFGEESTPGQTNSETAVVALTQDQPSEAATGGATLAQTISEAAIGGAMLGQTTSEEAVGGATPDQTTSEETVGGAILDQTTSEDAVGGATLGQTTSEEAVGGATLAQTTSEAAMEGATLDQTTSEEAPGGTELIQTPLASSTDHQTPPTSPVQGTTPQISPSTLIGSLRTLELGSESQGASESQAPGEENLLGEAAGGQDMADSMLMQGSRGLTDQAIFYAVTPLPWCPHLVAVCPIPAAGLDVTQPCGDCGTIQENWVCLSCYQVYCGRYINGHMLQHHGNSGHPLVLSYIDLSAWCYYCQAYVHHQALLDVKNIAHQNKFGEDMPHPH,7.142667503568731 +CN(C)C(=O)Cn1cc(C)c2ncc(cc12)-c1cccc(c1)C(F)(F)F,MKPRAECCSPKFWLVLAVLAVSGSRARSQKSPPSIGIAVILVGTSDEVAIKDAHEKDDFHHLSVVPRVELVAMNETDPKSIITRICDLMSDRKIQGVVFADDTDQEAIAQILDFISAQTLTPILGIHGGSSMIMADKDESSMFFQFGPSIEQQASVMLNIMEEYDWYIFSIVTTYFPGYQDFVNKIRSTIENSFVGWELEEVLLLDMSLDDGDSKIQNQLKKLQSPIILLYCTKEEATYIFEVANSVGLTGYGYTWIVPSLVAGDTDTVPAEFPTGLISVSYDEWDYGLPARVRDGIAIITTAASDMLSEHSFIPEPKSSCYNTHEKRIYQSNMLNRYLINVTFEGRNLSFSEDGYQMHPKLVIILLNKERKWERVGKWKDKSLQMKYYVWPRMCPETEEQEDDHLSIVTLEEAPFVIVESVDPLSGTCMRNTVPCQKRIVTENKTDEEPGYIKKCCKGFCIDILKKISKSVKFTYDLYLVTNGKHGKKINGTWNGMIGEVVMKRAYMAVGSLTINEERSEVVDFSVPFIETGISVMVSRSNGTVSPSAFLEPFSADVWVMMFVMLLIVSAVAVFVFEYFSPVGYNRCLADGREPGGPSFTIGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANLAAFMIQEEYVDQVSGLSDKKFQRPNDFSPPFRFGTVPNGSTERNIRNNYAEMHAYMGKFNQRGVDDALLSLKTGKLDAFIYDAAVLNYMAGRDEGCKLVTIGSGKVFASTGYGIAIQKDSGWKRQVDLAILQLFGDGEMEELEALWLTGICHNEKNEVMSSQLDIDNMAGVFYMLGAAMALSLITFICEHLFYWQFRHCFMGVCSGKPGMVFSISRGIYSCIHGVAIEERQSVMNSPTATMNNTHSNILRLLRTAKNMANLSGVNGSPQSALDFIRRESSVYDISEHRRSFTHSDCKSYNNPPCEENLFSDYISEVERTFGNLQLKDSNVYQDHYHHHHRPHSIGSASSIDGLYDCDNPPFTTQSRSISKKPLDIGLPSSKHSQLSDLYGKFSFKSDRYSGHDDLIRSDVSDISTHTVTYGNIEGNAAKRRKQQYKDSLKKRPASAKSRREFDEIELAYRRRPPRSPDHKRYFRDKEGLRDFYLDQFRTKENSPHWEHVDLTDIYKERSDDFKRDSVSGGGPCTNRSHIKHGTGDKHGVVSGVPAPWEKNLTNVEWEDRSGGNFCRSCPSKLHNYSTTVTGQNSGRQACIRCEACKKAGNLYDISEDNSLQELDQPAAPVAVTSNASTTKYPQSPTNSKAQKKNRNKLRRQHSYDTFVDLQKEEAALAPRSVSLKDKGRFMDGSPYAHMFEMSAGESTFANNKSSVPTAGHHHHNNPGGGYMLSKSLYPDRVTQNPFIPTFGDDQCLLHGSKSYFFRQPTVAGASKARPDFRALVTNKPVVSALHGAVPARFQKDICIGNQSNPCVPNNKNPRAFNGSSNGHVYEKLSSIESDV,7.100179497572904 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+CCOC(=O)c1nc2c3c(cn(-c4ccc(cc4)S(N)(=O)=O)c3ncn2n1)-c1ccc(Br)cc1,MPRRSLHAAAVLLLVILKEQPSSPAPVNGSKWTYFGPDGENSWSKKYPSCGGLLQSPIDLHSDILQYDASLTPLEFQGYNLSANKQFLLTNNGHSVKLNLPSDMHIQGLQSRYSATQLHLHWGNPNDPHGSEHTVSGQHFAAELHIVHYNSDLYPDASTASNKSEGLAVLAVLIEMGSFNPSYDKIFSHLQHVKYKGQEAFVPGFNIEELLPERTAEYYRYRGSLTTPPCNPTVLWTVFRNPVQISQEQLLALETALYCTHMDDPSPREMINNFRQVQKFDERLVYTSFSQVQVCTAAGLSLGIILSLALAGILGICIVVVVSIWLFRRKSIKKGDNKGVIYKPATKMETEAHA,6.437707135543525 +Cc1ccc(CC(=O)Nc2ccc(NC(=O)CCc3ccccc3)cc2C(=O)c2ccccc2)cc1,MEEYDYSDVKPLPIETDLQDELCRIMYTEDYKRLMGLARALISLNELSPRALQLTAEIIDVAPAFYTIWNYRFNIVRHMMSESEDTVLYLNKELDWLDEVTLNNPKNYQIWSYRQSLLKLHPSPSFKRELPILKLMIDDDSKNYHVWSYRKWCCLFFSDFQHELAYASDLIETDIYNNSAWTHRMFYWVNAKDVISKVELADELQFIMDKIQLVPQNISPWTYLRGFQELFHDRLQWDSKVVDFATTFIGDVLSLPIGSPEDLPEIESSYALEFLAYHWGADPCTRDNAVKAYSLLAIKYDPIRKNLWHHKINNLN,5.698970004336019 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+CC(O)c1cncc(c1)-c1cnc2N(CCCc2c1)C(N)=O,MALRAKAEVCMAAPWLSLQRAQALSTRAARAPSTVLPFEAIPQRPGSRWLRLLQIWREQGYEHLHLEVHQTFQELGPIFRNGPEWRFNRLRLNPDVLSPKAVQRFLPMVDAVARDFSQALRNKVVQNARGSLTLDVQPSIFHYTIEASNLALFGERLGLVGHSPSSASLSFLHALEVMFKSTVQLMFMPRSLSRWTSPKVWKEHFEAWDCIFQYGDNCIQKIYQELALSRPQQYTGIVAELLLNAELSLEAIKANSMELTAGSVDTTAFPLLMTLFELARNPDVQQALRQESLAAAASISEHPQKATTELPLMRAALKETLRLYPVGLFLERVVSSDLVLQNYHIPAGTLVQVFLYSLGRNPALFPRPERYNPQRWLDIRGSGKNFHNVPFGFGMRQCLGRRLAEAEMLLLLHHVLKHLQVETLTQEDIKMVYSFILRPSTFPLLTFRAIN,8.0 +SCCCCCCOc1ccccc1,MNSPNESDGMSGREPSLEILPRTSLHSIPVTVEVKPVLPRAMPSSMGGGGGGSPSPVELRGALVGSVDPTLREQQLQQELLALKQQQQLQKQLLFAEFQKQHDHLTRQHEVQLQKHLKQQQEMLAAKQQQEMLAAKRQQELEQQRQREQQRQEELEKQRLEQQLLILRNKEKSKESAIASTEVKLRLQEFLLSKSKEPTPGGLNHSLPQHPKCWGAHHASLDQSSPPQSGPPGTPPSYKLPLPGPYDSRDDFPLRKTASEPNLKVRSRLKQKVAERRSSPLLRRKDGTVISTFKKRAVEITGAGPGASSVCNSAPGSGPSSPNSSHSTIAENGFTGSVPNIPTEMLPQHRALPLDSSPNQFSLYTSPSLPNISLGLQATVTVTNSHLTASPKLSTQQEAERQALQSLRQGGTLTGKFMSTSSIPGCLLGVALEGDGSPHGHASLLQHVLLLEQARQQSTLIAVPLHGQSPLVTGERVATSMRTVGKLPRHRPLSRTQSSPLPQSPQALQQLVMQQQHQQFLEKQKQQQLQLGKILTKTGELPRQPTTHPEETEEELTEQQEVLLGEGALTMPREGSTESESTQEDLEEEDEEDDGEEEEDCIQVKDEEGESGAEEGPDLEEPGAGYKKLFSDAQPLQPLQVYQAPLSLATVPHQALGRTQSSPAAPGGMKSPPDQPVKHLFTTGVVYDTFMLKHQCMCGNTHVHPEHAGRIQSIWSRLQETGLLSKCERIRGRKATLDEIQTVHSEYHTLLYGTSPLNRQKLDSKKLLGPISQKMYAVLPCGGIGVDSDTVWNEMHSSSAVRMAVGCLLELAFKVAAGELKNGFAIIRPPGHHAEESTAMGFCFFNSVAITAKLLQQKLNVGKVLIVDWDIHHGNGTQQAFYNDPSVLYISLHRYDNGNFFPGSGAPEEVGGGPGVGYNVNVAWTGGVDPPIGDVEYLTAFRTVVMPIAHEFSPDVVLVSAGFDAVEGHLSPLGGYSVTARCFGHLTRQLMTLAGGRVVLALEGGHDLTAICDASEACVSALLSVELQPLDEAVLQQKPNINAVATLEKVIEIQSKHWSCVQKFAAGLGRSLREAQAGETEEAETVSAMALLSVGAEQAQAAAAREHSPRPAEEPMEQEPAL,4.958607314841775 +COc1ccc(cc1OC1CCCC1)C1(CCC(=O)CC1)C#N,MEPPTVPSERSLSLSLPGPREGQATLKPPPQHLWRQPRTPIRIQQRGYSDSAERAERERQPHRPIERADAMDTSDRPGLRTTRMSWPSSFHGTGTGSGGAGGGSSRRFEAENGPTPSPGRSPLDSQASPGLVLHAGAATSQRRESFLYRSDSDYDMSPKTMSRNSSVTSEAHAEDLIVTPFAQVLASLRSVRSNFSLLTNVPVPSNKRSPLGGPTPVCKATLSEETCQQLARETLEELDWCLEQLETMQTYRSVSEMASHKFKRMLNRELTHLSEMSRSGNQVSEYISTTFLDKQNEVEIPSPTMKEREKQQAPRPRPSQPPPPPVPHLQPMSQITGLKKLMHSNSLNNSNIPRFGVKTDQEELLAQELENLNKWGLNIFCVSDYAGGRSLTCIMYMIFQERDLLKKFRIPVDTMVTYMLTLEDHYHADVAYHNSLHAADVLQSTHVLLATPALDAVFTDLEILAALFAAAIHDVDHPGVSNQFLINTNSELALMYNDESVLENHHLAVGFKLLQEDNCDIFQNLSKRQRQSLRKMVIDMVLATDMSKHMTLLADLKTMVETKKVTSSGVLLLDNYSDRIQVLRNMVHCADLSNPTKPLELYRQWTDRIMAEFFQQGDRERERGMEISPMCDKHTASVEKSQVGFIDYIVHPLWETWADLVHPDAQEILDTLEDNRDWYYSAIRQSPSPPPEEESRGPGHPPLPDKFQFELTLEEEEEEEISMAQIPCTAQEALTAQGLSGVEEALDATIAWEASPAQESLEVMAQEASLEAELEAVYLTQQAQSTGSAPVAPDEFSSREEFVVAVSHSSPSALALQSPLLPAWRTLSVSEHAPGLPGLPSTAAEVEAQREHQAAKRACSACAGTFGEDTSALPAPGGGGSGGDPT,7.356547323513812 +CCCC[C@H](NC(=O)CCCCCNC(=O)[C@H]1CC[C@@H]2N(CCc3c2[nH]c2ccccc32)C1)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCCN)C(N)=O,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,5.200659450546418 +COc1ccc2CN(CCCc3c[nH]c4ccc(F)cc34)CCc2c1,MSKSKCSVGLMSSVVAPAKEPNAVGPKEVELILVKEQNGVQLTSSTLTNPRQSPVEAQDRETWGKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPILKGVGFTVILISLYVGFFYNVIIAWALHYLFSSFTTELPWIHCNNSWNSPNCSDAHPGDSSGDSSGLNDTFGTTPAAEYFERGVLHLHQSHGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAIDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIVTTSINSLTSFSSGFVVFSFLGYMAQKHSVPIGDVAKDGPGLIFIIYPEAIATLPLSSAWAVVFFIMLLTLGIDSAMGGMESVITGLIDEFQLLHRHRELFTLFIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVGQFSDDIQQMTGQRPSLYWRLCWKLVSPCFLLFVVVVSIVTFRPPHYGAYIFPDWANALGWVIATSSMAMVPIYAAYKFCSLPGSFREKLAYAIAPEKDRELVDRGEVRQFTLRHWLKV,5.603800652904264 +Fc1ccc(cc1)C(NC(=O)CCN1CCC(CC1)c1ccccc1)c1ccncc1,MGRRALLLLLLSFLAPWATIALRPALRALGSLHLPTNPTSLPAVAKNYSVLYFQQKVDHFGFNTVKTFNQRYLVADKYWKKNGGSILFYTGNEGDIIWFCNNTGFMWDVAEELKAMLVFAEHRYYGESLPFGDNSFKDSRHLNFLTSEQALADFAELIKHLKRTIPGAENQPVIAIGGSYGGMLAAWFRMKYPHMVVGALAASAPIWQFEDLVPCGVFMKIVTTDFRKSGPHCSESIHRSWDAINRLSNTGSGLQWLTGALHLCSPLTSQDIQHLKDWISETWVNLAMVDYPYASNFLQPLPAWPIKVVCQYLKNPNVSDSLLLQNIFQALNVYYNYSGQVKCLNISETATSSLGTLGWSYQACTEVVMPFCTNGVDDMFEPHSWNLKELSDDCFQQWGVRPRPSWITTMYGGKNISSHTNIVFSNGELDPWSGGGVTKDITDTLVAVTISEGAHHLDLRTKNALDPMSVLLARSLEVRHMKNWIRDFYDSAGKQH,8.42021640338319 +CCCN(C)c1nc(NC2COC2)cc(n1)C(=O)NC[C@H](O)CN1CCc2ccccc2C1,MHHHHHHRKETPPPLVPPAAREWNLPPNAPACMERQLEAARYRSDGALLLGASSLSGRCWAGSLWLFKDPCAAPNEGFCSAGVQTEAGVADLTWVGERGILVASDSGAVELWELDENETLIVSKFCKYEHDDIVSTVSVLSSGTQAVSGSKDICIKVWDLAQQVVLSSYRAHAAQVTCVAASPHKDSVFLSCSEDNRILLWDTRCPKPASQIGCSAPGYLPTSLAWHPQQSEVFVFGDENGTVSLVDTKSTSCVLSSAVHSQCVTGLVFSPHSVPFLASLSEDCSLAVLDSSLSELFRSQAHRDFVRDATWSPLNHSLLTTVGWDHQVVHHVVPTEPLPAPGPASVTE,7.0 +CN(Cc1ccc(cc1)[N+]([O-])=O)c1ncnc2n(cnc12)[C@@H]1O[C@H](CO)[C@@H](O)[C@H]1O,MTTSHQPQDRYKAVWLIFFMLGLGTLLPWNFFMTATQYFTNRLDMSQNVSLVTAELSKDAQASAAPAAPLPERNSLSAIFNNVMTLCAMLPLLLFTYLNSFLHQRIPQSVRILGSLVAILLVFLITAILVKVQLDALPFFVITMIKIVLINSFGAILQGSLFGLAGLLPASYTAPIMSGQGLAGFFASVAMICAIASGSELSESAFGYFITACAVIILTIICYLGLPRLEFYRYYQQLKLEGPGEQETKLDLISKGEEPRAGKEESGVSVSNSQPTNESHSIKAILKNISVLAFSVCFIFTITIGMFPAVTVEVKSSIAGSSTWERYFIPVSCFLTFNIFDWLGRSLTAVFMWPGKDSRWLPSLVLARLVFVPLLLLCNIKPRRYLTVVFEHDAWFIFFMAAFAFSNGYLASLCMCFGPKKVKPAEAETAGAIMAFFLCLGLALGAVFSFLFRAIV,6.509999358109048 +C[C@@H](NC(=O)c1cc(OCC2(C)COC2)cc(c1)-c1ncc(C)s1)c1cnc(nc1)C(F)(F)F,MAAAQPKYPAGATARRLARGCWSALWDYETPKVIVVRNRRLGVLYRAVQLLILLYFVWYVFIVQKSYQESETGPESSIITKVKGITTSEHKVWDVEEYVKPPEGGSVFSIITRVEATHSQTQGTCPESIRVHNATCLSDADCVAGELDMLGNGLRTGRCVPYYQGPSKTCEVFGWCPVEDGASVSQFLGTMAPNFTILIKNSIHYPKFHFSKGNIADRTDGYLKRCTFHEASDLYCPIFKLGFIVEKAGESFTELAHKGGVIGVIINWDCDLDLPASECNPKYSFRRLDPKHVPASSGYNFRFAKYYKINGTTTRTLIKAYGIRIDVIVHGQAGKFSLIPTIINLATALTSVGVGSFLCDWILLTFMNKNKVYSHKKFDKVCTPSHPSGSWPVTLARVLGQAPPEPGHRSEDQHPSPPSGQEGQQGAECGPAFPPLRPCPISAPSEQMVDTPASEPAQASTPTDPKGLAQL,6.621602099051862 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+CC(C)[C@H](NS(=O)(=O)c1ccc(cc1)-c1ccc(C)cc1)P(O)(O)=O,MEALMARGALTGPLRALCLLGCLLSHAAAAPSPIIKFPGDVAPKTDKELAVQYLNTFYGCPKESCNLFVLKDTLKKMQKFFGLPQTGDLDQNTIETMRKPRCGNPDVANYNFFPRKPKWDKNQITYRIIGYTPDLDPETVDDAFARAFQVWSDVTPLRFSRIHDGEADIMINFGRWEHGDGYPFDGKDGLLAHAFAPGTGVGGDSHFDDDELWTLGEGQVVRVKYGNADGEYCKFPFLFNGKEYNSCTDTGRSDGFLWCSTTYNFEKDGKYGFCPHEALFTMGGNAEGQPCKFPFRFQGTSYDSCTTEGRTDGYRWCGTTEDYDRDKKYGFCPETAMSTVGGNSEGAPCVFPFTFLGNKYESCTSAGRSDGKMWCATTANYDDDRKWGFCPDQGYSLFLVAAHEFGHAMGLEHSQDPGALMAPIYTYTKNFRLSQDDIKGIQELYGASPDIDLGTGPTPTLGPVTPEICKQDIVFDGIAQIRGEIFFFKDRFIWRTVTPRDKPMGPLLVATFWPELPEKIDAVYEAPQEEKAVFFAGNEYWIYSASTLERGYPKPLTSLGLPPDVQRVDAAFNWSKNKKTYIFAGDKFWRYNEVKKKMDPGFPKLIADAWNAIPDNLDAVVDLQGGGHSYFFKGAYYLKLENQSLKSVKFGSIKSDWLGC,8.638272163982407 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+COc1ccc(CNCCc2c[nH]c3ccc(OC)cc23)cc1,MVNLGNAVRSLLMHLIGLLVWQFDISISPVAAIVTDTFNSSDGGRLFQFPDGVQNWPALSIVVIIIMTIGGNILVIMAVSMEKKLHNATNYFLMSLAIADMLVGLLVMPLSLLAILYDYVWPLPRYLCPVWISLDVLFSTASIMHLCAISLDRYVAIRNPIEHSRFNSRTKAIMKIAIVWAISIGVSVPIPVIGLRDESKVFVNNTTCVLNDPNFVLIGSFVAFFIPLTIMVITYFLTIYVLRRQTLMLLRGHTEEELANMSLNFLNCCCKKNGGEEENAPNPNPDQKPRRKKKEKRPRGTMQAINNEKKASKVLGIVFFVFLIMWCPFFITNILSVLCGKACNQKLMEKLLNVFVWIGYVCSGINPLVYTLFNKIYRRAFSKYLRCDYKPDKKPPVRQIPRVAATALSGRELNVNIYRHTNERVARKANDPEPGIEMQVENLELPVNPSNVVSERISSV,5.928117992693874 +CN(C)c1ccc(cc1)[C@H]1C[C@@]2(C)[C@@H](CC[C@@]2(O)C#Cc2ccccc2Cl)[C@@H]2OCC3=CC(=O)CCC3=C12,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,7.188424994129407 +Cn1cnc(c1)N1CCN2C(=O)N(C(=O)CC2(C)C1=O)c1c(F)cc(cc1F)C#Cc1ccccc1,MPGKRGLGWWWARLPLCLLLSLYGPWMPSSLGKPKGHPHMNSIRIDGDITLGGLFPVHGRGSEGKPCGELKKEKGIHRLEAMLFALDRINNDPDLLPNITLGARILDTCSRDTHALEQSLTFVQALIEKDGTEVRCGSGGPPIITKPERVVGVIGASGSSVSIMVANILRLFKIPQISYASTAPDLSDNSRYDFFSRVVPSDTYQAQAMVDIVRALKWNYVSTVASEGSYGESGVEAFIQKSREDGGVCIAQSVKIPREPKAGEFDKIIRRLLETSNARAVIIFANEDDIRRVLEAARRANQTGHFFWMGSDSWGSKIAPVLHLEEVAEGAVTILPKRMSVRGFDRYFSSRTLDNNRRNIWFAEFWEDNFHCKLSRHALKKGSHVKKCTNRERIGQDSAYEQEGKVQFVIDAVYAMGHALHAMHRDLCPGRVGLCPRMDPVDGTQLLKYIRNVNFSGIAGNPVTFNENGDAPGRYDIYQYQLRNDSAEYKVIGSWTDHLHLRIERMHWPGSGQQLPRSICSLPCQPGERKKTVKGMPCCWHCEPCTGYQYQVDRYTCKTCPYDMRPTENRTGCRPIPIIKLEWGSPWAVLPLFLAVVGIAATLFVVITFVRYNDTPIVKASGRELSYVLLAGIFLCYATTFLMIAEPDLGTCSLRRIFLGLGMSISYAALLTKTNRIYRIFEQGKRSVSAPRFISPASQLAITFSLISLQLLGICVWFVVDPSHSVVDFQDQRTLDPRFARGVLKCDISDLSLICLLGYSMLLMVTCTVYAIKTRGVPETFNEAKPIGFTMYTTCIVWLAFIPIFFGTSQSADKLYIQTTTLTVSVSLSASVSLGMLYMPKVYIILFHPEQNVPKRKRSLKAVVTAATMSNKFTQKGNFRPNGEAKSELCENLEAPALATKQTYVTYTNHAI,6.669586226650809 +[O-][N+](=O)c1cccc(c1)S(=O)(=O)NC(=O)[C@H](Cc1ccccc1)N1C(=O)N[C@@H](Cc2ccc(cc2)-c2ccc(Cl)cc2)C1=O,MFGLKRNAVIGLNLYCGGAGLGAGSGGATRPGGRLLATEKEASARREIGGGEAGAVIGGSAGASPPSTLTPDSRRVARPPPIGAEVPDVTATPARLLFFAPTRRAAPLEEMEAPAADAIMSPEEELDGYEPEPLGKRPAVLPLLELVGESGNNTSTDGSLPSTPPPAEEEEDELYRQSLEIISRYLREQATGAKDTKPMGRSGATSRKALETLRRVGDGVQRNHETAFQGMLRKLDIKNEDDVKSLSRVMIHVFSDGVTNWGRIVTLISFGAFVAKHLKTINQESCIEPLAESITDVLVRTKRDWLVKQRGWDGFVEFFHVEDLEGGIRNVLLAFAGVAGVGAGLAYLIR,4.301029995663981 +Fc1cc(Cl)cc(c1)N1CCN(CCN2Cc3ccccc3C2)C1=O,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,7.50003813440381 +C[C@@H]1COCCN1c1cc(N=S2(=O)CCOCC2)nc(n1)-c1ccnc2[nH]ccc12,MAGTSAPGSKRRSEPPAPRPGPPPGTGHPPSKRARGFSAAAAPDPDDPFGAHGDFTADDLEELDTLASQALSQCPAAARDVSSDHKVHRLLDGMSKNPSGKNRETVPIKDNFELEVLQAQYKELKEKMKVMEEEVLIKNGEIKILRDSLHQTESVLEEQRRSHFLLEQEKTQALSDKEKEFSKKLQSLQSELQFKDAEMNELRTKLQTSERANKLAAPSVSHVSPRKNPSVVIKPEACSPQFGKTSFPTKESFSANMSLPHPCQTESGYKPLVGREDSKPHSLRGDSIKQEEAQKSFVDSWRQRSNTQGSILINLLLKQPLIPGSSLSLCHLLSSSSESPAGTPLQPPGFGSTLAGMSGLRTTGSYDGSFSLSALREAQNLAFTGLNLVARNECSRDGDPAEGGRRAFPLCQLPGAVHFLPLVQFFIGLHCQALQDLAAAKRSGAPGDSPTHSSCVSSGVETNPEDSVCILEGFSVTALSILQHLVCHSGAVVSLLLSGVGADSAAGEGNRSLVHRLSDGDMTSALRGVADDQGQHPLLKMLLHLLAFSSAATGHLQASVLTQCLKVLVKLAENTSCDFLPRFQCVFQVLPKCLSPETPLPSVLLAVELLSLLADHDQLAPQLCSHSEGCLLLLLYMYITSRPDRVALETQWLQLEQEVVWLLAKLGVQSPLPPVTGSNCQCNVEVVRALTVMLHRQWLTVRRAGGPPRTDQQRRTVRCLRDTVLLLHGLSQKDKLFMMHCVEVLHQFDQVMPGVSMLIRGLPDVTDCEEAALDDLCAAETDVEDPEVECG,8.522878745280337 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+COc1ccccc1N1CCN(Cc2ccn(c2)-c2ccccc2C)CC1,MDVFSFGQGNNTTASQEPFGTGGNVTSISDVTFSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVRKVEKKGAGTSLGTSSAPPPKKSLNGQPGSGDWRRCAENRAVGTPCTNGAVRQGDDEATLEVIEVHRVGNSKEHLPLPSESGSNSYAPACLERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPALLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRR,8.00436480540245 +COc1cc2CCN=C(c3ccc(cc3)S(N)(=O)=O)c2cc1OC,MLFSALLLEVIWILAADGGQHWTYEGPHGQDHWPASYPECGNNAQSPIDIQTDSVTFDPDLPALQPHGYDQPGTEPLDLHNNGHTVQLSLPSTLYLGGLPRKYVAAQLHLHWGQKGSPGGSEHQINSEATFAELHIVHYDSDSYDSLSEAAERPQGLAVLGILIEVGETKNIAYEHILSHLHEVRHKDQKTSVPPFNLRELLPKQLGQYFRYNGSLTTPPCYQSVLWTVFYRRSQISMEQLEKLQGTLFSTEEEPSKLLVQNYRALQPLNQRMVFASFIQAGSSYTTGEMLSLGVGILVGCLCLLLAVYFIARKIRKKRLENRKSVVFTSAQATTEA,6.987162775294828 +Cc1[nH]c(nc1-c1ccc(cc1)C(F)(F)F)N1CCN(CC1)c1ncccc1C(F)(F)F,MEQRASLDSEESESPPQENSCLDPPDRDPNCKPPPVKPHIFTTRSRTRLFGKGDSEEASPLDCPYEEGGLASCPIITVSSVLTIQRPGDGPASVRPSSQDSVSAGEKPPRLYDRRSIFDAVAQSNCQELESLLPFLQRSKKRLTDSEFKDPETGKTCLLKAMLNLHNGQNDTIALLLDVARKTDSLKQFVNASYTDSYYKGQTALHIAIERRNMTLVTLLVENGADVQAAANGDFFKKTKGRPGFYFGELPLSLAACTNQLAIVKFLLQNSWQPADISARDSVGNTVLHALVEVADNTVDNTKFVTSMYNEILILGAKLHPTLKLEEITNRKGLTPLALAASSGKIGVLAYILQREIHEPECRHLSRKFTEWAYGPVHSSLYDLSCIDTCEKNSVLEVIAYSSSETPNRHDMLLVEPLNRLLQDKWDRFVKRIFYFNFFVYCLYMIIFTAAAYYRPVEGLPPYKLKNTVGDYFRVTGEILSVSGGVYFFFRGIQYFLQRRPSLKSLFVDSYSEILFFVQSLFMLVSVVLYFSQRKEYVASMVFSLAMGWTNMLYYTRGFQQMGIYAVMIEKMILRDLCRFMFVYLVFLFGFSTAVVTLIEDGKNNSLPMESTPHKCRGSACKPGNSYNSLYSTCLELFKFTIGMGDLEFTENYDFKAVFIILLLAYVILTYILLLNMLIALMGETVNKIAQESKNIWKLQRAITILDTEKSFLKCMRKAFRSGKLLQVGFTPDGKDDYRWCFRVDEVNWTTWNTNVGIINEDPGNCEGVKRTLSFSLRSGRVSGRNWKNFALVPLLRDASTRDRHATQQEEVQLKHYTGSLKPEDAEVFKDSMVPGEK,6.2020403562628035 +Cn1ccc(COc2ccc3nc([C@@H]4[C@@H](C(O)=O)C4(C)C)n(Cc4ccc(Br)cc4)c3c2)n1,MDQETVGNVVLLAIVTLISVVQNGFFAHKVEHESRTQNGRSFQRTGTLAFERVYTANQNCVDAYPTFLAVLWSAGLLCSQVPAAFAGLMYLFVRQKYFVGYLGERTQSTPGYIFGKRIILFLFLMSVAGIFNYYLIFFFGSDFENYIKTISTTISPLLLIP,5.72584215073632 +OC(=O)c1ccc(Nc2ncc3CN=C(c4cc(Cl)ccc4-c3n2)c2c(F)cccc2F)cc1,MAQKENSYPWPYGRQTAPSGLSTLPQRVLRKEPVTPSALVLMSRSNVQPTAAPGQKVMENSSGTPDILTRHFTIDDFEIGRPLGKGKFGNVYLAREKKSHFIVALKVLFKSQIEKEGVEHQLRREIEIQAHLHHPNILRLYNYFYDRRRIYLILEYAPRGELYKELQKSCTFDEQRTATIMEELADALMYCHGKKVIHRDIKPENLLLGLKGELKIADFGWSVHAPSLRRKTMCGTLDYLPPEMIEGRMHNEKVDLWCIGVLCYELLVGNPPFESASHNETYRRIVKVDLKFPASVPMGAQDLISKLLRHNPSERLPLAQVSAHPWVRANSRRVLPPSALQSVA,5.2441251443275085 +Fc1cc(F)cc(NC(=O)c2cncc(n2)N2C[C@@H]3CNC[C@@H]3C2)c1,MAGHSNSMALFSFSLLWLCSGVLGTDTEERLVEHLLDPSRYNKLIRPATNGSELVTVQLMVSLAQLISVHEREQIMTTNVWLTQEWEDYRLTWKPEDFDNMKKVRLPSKHIWLPDVVLYNNADGMYEVSFYSNAVVSYDGSIFWLPPAIYKSACKIEVKHFPFDQQNCTMKFRSWTYDRTEIDLVLKSDVASLDDFTPSGEWDIIALPGRRNENPDDSTYVDITYDFIIRRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTVFLLLISKIVPPTSLDVPLVGKYLMFTMVLVTFSIVTSVCVLNVHHRSPTTHTMAPWVKVVFLEKLPTLLFLQQPRHRCARQRLRLRRRQREREGAGALFFREGPAADPCTCFVNPASVQGLAGAFRAEPTAAGPGRSVGPCSCGLREAVDGVRFIADHMRSEDDDQSVREDWKYVAMVIDRLFLWIFVFVCVFGTVGMFLQPLFQNYTATTFLHPDHSAPSSK,4.0 +O=C1CC2CCc3cc(OC4CCN(CC4)C4CCC4)ccc3C2=NN1,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,4.7447274948966935 +CC(C)(O)C(O)CC[C@@](C)(C=C)\C=C\c1ccc(O)cc1,MTADKEKKRSSSERRKEKSRDAARCRRSKETEVFYELAHELPLPHSVSSHLDKASIMRLAISFLRTHKLLSSVCSENESEAEADQQMDNLYLKALEGFIAVVTQDGDMIFLSENISKFMGLTQVELTGHSIFDFTHPCDHEEIRENLSLKNGSGFGKKSKDMSTERDFFMRMKCTVTNRGRTVNLKSATWKVLHCTGQVKVYNNCPPHNSLCGYKEPLLSCLIIMCEPIQHPSHMDIPLDSKTFLSRHSMDMKFTYCDDRITELIGYHPEELLGRSAYEFYHALDSENMTKSHQNLCTKGQVVSGQYRMLAKHGGYVWLETQGTVIYNPRNLQPQCIMCVNYVLSEIEKNDVVFSMDQTESLFKPHLMAMNSIFDSSGKGAVSEKSNFLFTKLKEEPEELAQLAPTPGDAIISLDFGNQNFEESSAYGKAILPPSQPWATELRSHSTQSEAGSLPAFTVPQAAAPGSTTPSATSSSSSCSTPNSPEDYYTSLDNDLKIEVIEKLFAMDTEAKDQCSTQTDFNELDLETLAPYIPMDGEDFQLSPICPEERLLAENPQSTPQHCFSAMTNIFQPLAPVAPHSPFLLDKFQQQLESKKTEPEHRPMSSIFFDAGSKASLPPCCGQASTPLSSMGGRSNTQWPPDPPLHFGPTKWAVGDQRTEFLGAAPLGPPVSPPHVSTFKTRSAKGFGARGPDVLSPAMVALSNKLKLKRQLEYEEQAFQDLSGGDPPGGSTSHLMWKRMKNLRGGSCPLMPDKPLSANVPNDKFTQNPMRGLGHPLRHLPLPQPPSAISPGENSKSRFPPQCYATQYQDYSLSSAHKVSGMASRLLGPSFESYLLPELTRYDCEVNVPVLGSSTLLQGGDLLRALDQAT,4.301029995663981 +Cn1nc(cc1OC(F)F)C(=O)Nc1ccc(cc1)-c1n[nH]c(=O)c2ccccc12,MSRPPPTGKMPGAPETAPGDGAGASRQRKLEALIRDPRSPINVESLLDGLNSLVLDLDFPALRKNKNIDNFLNRYEKIVKKIRGLQMKAEDYDVVKVIGRGAFGEVQLVRHKASQKVYAMKLLSKFEMIKRSDSAFFWEERDIMAFANSPWVVQLFYAFQDDRYLYMVMEYMPGGDLVNLMSNYDVPEKWAKFYTAEVVLALDAIHSMGLIHRDVKPDNMLLDKHGHLKLADFGTCMKMDETGMVHCDTAVGTPDYISPEVLKSQGGDGFYGRECDWWSVGVFLYEMLVGDTPFYADSLVGTYSKIMDHKNSLCFPEDAEISKHAKNLICAFLTDREVRLGRNGVEEIRQHPFFKNDQWHWDNIRETAAPVVPELSSDIDSSNFDDIEDDKGDVETFPIPKAFVGNQLPFIGFTYYRENLLLSDSPSCRETDSIQSRKNEESQEIQKKLYTLEEHLSNEMQAKEELEQKCKSVNTRLEKTAKELEEEITLRKSVESALRQLEREKALLQHKNAEYQRKADHEADKKRNLENDVNSLKDQLEDLKKRNQNSQISTEKVNQLQRQLDETNALLRTESDTAARLRKTQAESSKQIQQLESNNRDLQDKNCLLETAKLKLEKEFINLQSALESERRDRTHGSEIINDLQGRICGLEEDLKNGKILLAKVELEKRQLQERFTDLEKEKSNMEIDMTYQLKVIQQSLEQEEAEHKATKARLADKNKIYESIEEAKSEAMKEMEKKLLEERTLKQKVENLLLEAEKRCSLLDCDLKQSQQKINELLKQKDVLNEDVRNLTLKIEQETQKRCLTQNDLKMQTQQVNTLKMSEKQLKQENNHLMEMKMNLEKQNAELRKERQDADGQMKELQDQLEAEQYFSTLYKTQVRELKEECEEKTKLGKELQQKKQELQDERDSLAAQLEITLTKADSEQLARSIAEEQYSDLEKEKIMKELEIKEMMARHKQELTEKDATIASLEETNRTLTSDVANLANEKEELNNKLKDVQEQLSRLKDEEISAAAIKAQFEKQLLTERTLKTQAVNKLAEIMNRKEPVKRGNDTDVRRKEKENRKLHMELKSEREKLTQQMIKYQKELNEMQAQIAEESQIRIELQMTLDSKDSDIEQLRSQLQALHIGLDSSSIGSGPGDAEADDGFPESRLEGWLSLPVRNNTKKFGWVKKYVIVSSKKILFYDSEQDKEQSNPYMVLDIDKLFHVRPVTQTDVYRADAKEIPRIFQILYANEGESKKEQEFPVEPVGEKSNYICHKGHEFIPTLYHFPTNCEACMKPLWHMFKPPPALECRRCHIKCHKDHMDKKEEIIAPCKVYYDISTAKNLLLLANSTEEQQKWVSRLVKKIPKKPPAPDPFARSSPRTSMKIQQNQSIRRPSRQLAPNKPS,7.0 +CN(C)Cc1nnc(o1)-c1c(C)[nH]c2c1c(cn(C)c2=O)C#CC(C)(O)C1CC1,QVAFSFILDNIVTQKMMAVPDSWPFHHPVNKKFVPDYYKVIVNPMDLETIRKNISKHKYQSRESFLDDVNLILANSVKYNGPESQYTKTAQEIVNVCYQTLTEYDEHLTQLEKDICTAKEAALEEAELESLD,7.511449283499555 +COc1ccc(cc1)-c1cc(nn1-c1ccc(Cl)cc1)C(F)(F)F,MLARALLLCAVLALSHTANPCCSHPCQNRGVCMSVGFDQYKCDCTRTGFYGENCSTPEFLTRIKLFLKPTPNTVHYILTHFKGFWNVVNNIPFLRNAIMSYVLTSRSHLIDSPPTYNADYGYKSWEAFSNLSYYTRALPPVPDDCPTPLGVKGKKQLPDSNEIVEKLLLRRKFIPDPQGSNMMFAFFAQHFTHQFFKTDHKRGPAFTNGLGHGVDLNHIYGETLARQRKLRLFKDGKMKYQIIDGEMYPPTVKDTQAEMIYPPQVPEHLRFAVGQEVFGLVPGLMMYATIWLREHNRVCDVLKQEHPEWGDEQLFQTSRLILIGETIKIVIEDYVQHLSGYHFKLKFDPELLFNKQFQYQNRIAAEFNTLYHWHPLLPDTFQIHDQKYNYQQFIYNNSILLEHGITQFVESFTRQIAGRVAGGRNVPPAVQKVSQASIDQSRQMKYQSFNEYRKRFMLKPYESFEELTGEKEMSAELEALYGDIDAVELYPALLVEKPRPDAIFGETMVEVGAPFSLKGLMGNVICSPAYWKPSTFGGEVGFQIINTASIQSLICNNVKGCPFTSFSVPDPELIKTVTINASSSRSGLDDINPTVLLKERSTEL,6.1249387366083 +COc1ncc(F)cc1[C@H]1CCCN1c1ccn2ncc(C(=O)NC[C@@H](C)O)c2n1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,6.0 +CC\C=C\CC=CCC=CC=CC=CC1OC1CCCC(=O)OC,MNTTSSAAPPSLGVEFISLLAIILLSVALAVGLPGNSFVVWSILKRMQKRSVTALMVLNLALADLAVLLTAPFFLHFLAQGTWSFGLAGCRLCHYVCGVSMYASVLLITAMSLDRSLAVARPFVSQKLRTKAMARRVLAGIWVLSFLLATPVLAYRTVVPWKTNMSLCFPRYPSEGHRAFHLIFEAVTGFLLPFLAVVASYSDIGRRLQARRFRRSRRTGRLVVLIILTFAAFWLPYHVVNLAEAGRALAGQAAGLGLVGKRLSLARNVLIALAFLSSSVNPVLYACAGGGLLRSAGVGFVAKLLEGTGSEASSTRRGGSLGQTARSGPAALEPGPSESLTASSPLKLNELN,5.0 +C[C@H](CCC(=O)NCCS(O)(=O)=O)[C@H]1CC[C@H]2[C@@H]3C[C@H](O)[C@@H]4C[C@H](O)CC[C@]4(C)[C@H]3CC[C@]12C,MTPNSTGEVPSPIPKGALGLSLALASLIITANLLLALGIAWDRRLRSPPAGCFFLSLLLAGLLTGLALPTLPGLWNQSRRGYWSCLLVYLAPNFSFLSLLANLLLVHGERYMAVLRPLQPPGSIRLALLLTWAGPLLFASLPALGWNHWTPGANCSSQAIFPAPYLYLEVYGLLLPAVGAAAFLSVRVLATAHRQLQDICRLERAVCRDEPSALARALTWRQARAQAGAMLLFGLCWGPYVATLLLSVLAYEQRPPLGPGTLLSLLSLGSASAAAVPVAMGLGDQRYTAPWRAAAQRCLQGLWGRASRDSPGPSIAYHPSSQSSVDLDLN,4.616184634019569 +OC1CCc2oc3c(Cl)cc(cc3c2C1)S(=O)(=O)c1ccccc1,MVPEPGPTANSTPAWGAGPPSAPGGSGWVAAALCVVIALTAAANSLLIALICTQPALRNTSNFFLVSLFTSDLMVGLVVMPPAMLNALYGRWVLARGLCLLWTAFDVMCCSASILNLCLISLDRYLLILSPLRYKLRMTPLRALALVLGAWSLAALASFLPLLLGWHELGHARPPVPGQCRLLASLPFVLVASGLTFFLPSGAICFTYCRILLAARKQAVQVASLTTGMASQASETLQVPRTPRPGVESADSRRLATKHSRKALKASLTLGILLGMFFVTWLPFFVANIVQAVCDCISPGLFDVLTWLGYCNSTMNPIIYPLFMRDFKRALGRFLPCPRCPRERQASLASPSLRTSHSGPRPGLSLQQVLPLPLPPDSDSDSDAGSGGSSGLRLTAQLLLPGEATQDPPLPTRAAAAVNFFNIDPAEPELRPHPLGIPTN,9.0 +C[C@@H](C[C@H]1COC(N)=N1)Oc1cccc(Cl)c1,MHLCHAITNISHRNSDWSREVQASLYSLMSLIILATLVGNLIVIISISHFKQLHTPTNWLLHSMAIVDFLLGCLIMPCSMVRTVERCWYFGEILCKVHTSTDIMLSSASIFHLAFISIDRYCAVCDPLRYKAKINISTILVMILVSWSLPAVYAFGMIFLELNLKGVEELYRSQVSDLGGCSPFFSKVSGVLAFMTSFYIPGSVMLFVYYRIYFIAKGQARSINRTNVQVGLEGKSQAPQSKETKAAKTLGIMVGVFLVCWCPFFLCTVLDPFLGYVIPPSLNDALYWFGYLNSALNPMVYAFFYPWFRRALKMVLLGKIFQKDSSRSKLFL,8.920818753952375 +COC(=O)C[C@H](NC(=O)CN1C(=O)CC[C@H](NC(=O)c2cc(OC)c(OC)c(OC)c2)C1=O)C(=O)OC,MEALMARGALTGPLRALCLLGCLLSHAAAAPSPIIKFPGDVAPKTDKELAVQYLNTFYGCPKESCNLFVLKDTLKKMQKFFGLPQTGDLDQNTIETMRKPRCGNPDVANYNFFPRKPKWDKNQITYRIIGYTPDLDPETVDDAFARAFQVWSDVTPLRFSRIHDGEADIMINFGRWEHGDGYPFDGKDGLLAHAFAPGTGVGGDSHFDDDELWTLGEGQVVRVKYGNADGEYCKFPFLFNGKEYNSCTDTGRSDGFLWCSTTYNFEKDGKYGFCPHEALFTMGGNAEGQPCKFPFRFQGTSYDSCTTEGRTDGYRWCGTTEDYDRDKKYGFCPETAMSTVGGNSEGAPCVFPFTFLGNKYESCTSAGRSDGKMWCATTANYDDDRKWGFCPDQGYSLFLVAAHEFGHAMGLEHSQDPGALMAPIYTYTKNFRLSQDDIKGIQELYGASPDIDLGTGPTPTLGPVTPEICKQDIVFDGIAQIRGEIFFFKDRFIWRTVTPRDKPMGPLLVATFWPELPEKIDAVYEAPQEEKAVFFAGNEYWIYSASTLERGYPKPLTSLGLPPDVQRVDAAFNWSKNKKTYIFAGDKFWRYNEVKKKMDPGFPKLIADAWNAIPDNLDAVVDLQGGGHSYFFKGAYYLKLENQSLKSVKFGSIKSDWLGC,6.301029995663981 +CCN(CC)CCOc1ccc2C(=O)c3c([nH]c4cc(ccc34)C#N)C(C)(C)c2c1,MGAIGLLWLLPLLLSTAAVGSGMGTGQRAGSPAAGPPLQPREPLSYSRLQRKSLAVDFVVPSLFRVYARDLLLPPSSSELKAGRPEARGSLALDCAPLLRLLGPAPGVSWTAGSPAPAEARTLSRVLKGGSVRKLRRAKQLVLELGEEAILEGCVGPPGEAAVGLLQFNLSELFSWWIRQGEGRLRIRLMPEKKASEVGREGRLSAAIRASQPRLLFQIFGTGHSSLESPTNMPSPSPDYFTWNLTWIMKDSFPFLSHRSRYGLECSFDFPCELEYSPPLHDLRNQSWSWRRIPSEEASQMDLLDGPGAERSKEMPRGSFLLLNTSADSKHTILSPWMRSSSEHCTLAVSVHRHLQPSGRYIAQLLPHNEAAREILLMPTPGKHGWTVLQGRIGRPDNPFRVALEYISSGNRSLSAVDFFALKNCSEGTSPGSKMALQSSFTCWNGTVLQLGQACDFHQDCAQGEDESQMCRKLPVGFYCNFEDGFCGWTQGTLSPHTPQWQVRTLKDARFQDHQDHALLLSTTDVPASESATVTSATFPAPIKSSPCELRMSWLIRGVLRGNVSLVLVENKTGKEQGRMVWHVAAYEGLSLWQWMVLPLLDVSDRFWLQMVAWWGQGSRAIVAFDNISISLDCYLTISGEDKILQNTAPKSRNLFERNPNKELKPGENSPRQTPIFDPTVHWLFTTCGASGPHGPTQAQCNNAYQNSNLSVEVGSEGPLKGIQIWKVPATDTYSISGYGAAGGKGGKNTMMRSHGVSVLGIFNLEKDDMLYILVGQQGEDACPSTNQLIQKVCIGENNVIEEEIRVNRSVHEWAGGGGGGGGATYVFKMKDGVPVPLIIAAGGGGRAYGAKTDTFHPERLENNSSVLGLNGNSGAAGGGGGWNDNTSLLWAGKSLQEGATGGHSCPQAMKKWGWETRGGFGGGGGGCSSGGGGGGYIGGNAASNNDPEMDGEDGVSFISPLGILYTPALKVMEGHGEVNIKHYLNCSHCEVDECHMDPESHKVICFCDHGTVLAEDGVSCIVSPTPEPHLPLSLILSVVTSALVAALVLAFSGIMIVYRRKHQELQAMQMELQSPEYKLSKLRTSTIMTDYNPNYCFAGKTSSISDLKEVPRKNITLIRGLGHGAFGEVYEGQVSGMPNDPSPLQVAVKTLPEVCSEQDELDFLMEALIISKFNHQNIVRCIGVSLQSLPRFILLELMAGGDLKSFLRETRPRPSQPSSLAMLDLLHVARDIACGCQYLEENHFIHRDIAARNCLLTCPGPGRVAKIGDFGMARDIYRASYYRKGGCAMLPVKWMPPEAFMEGIFTSKTDTWSFGVLLWEIFSLGYMPYPSKSNQEVLEFVTSGGRMDPPKNCPGPVYRIMTQCWQHQPEDRPNFAIILERIEYCTQDPDVINTALPIEYGPLVEEEEKVPVRPKDPEGVPPLLVSQQAKREEERSPAAPPPLPTTSSGKAAKKPTAAEISVRVPRGPAVEGGHVNMAFSQSNPPSELHKVHGSRNKPTSLWNPTYGSWFTEKPTKKNNPIAKKEPHDRGNLGLEGSCTVPPNVATGRLPGASLLLEPSSLTANMKEVPLFRLRHFPCGNVNYGYQQQGLPLEAATAPGAGHYEDTILKSKNSMNQPGP,8.119186407719209 +COc1ccc(COc2ccc(Cc3cnc(N)nc3N)cc2OC)cc1,MERPPGLRPGAGGPWEMRERLGTGGFGNVCLYQHRELDLKIAIKSCRLELSTKNRERWCHEIQIMKKLNHANVVKACDVPEELNILIHDVPLLAMEYCSGGDLRKLLNKPENCCGLKESQILSLLSDIGSGIRYLHENKIIHRDLKPENIVLQDVGGKIIHKIIDLGYAKDVDQGSLCTSFVGTLQYLAPELFENKPYTATVDYWSFGTMVFECIAGYRPFLHHLQPFTWHEKIKKKDPKCIFACEEMSGEVRFSSHLPQPNSLCSLVVEPMENWLQLMLNWDPQQRGGPVDLTLKQPRCFVLMDHILNLKIVHILNMTSAKIISFLLPPDESLHSLQSRIERETGINTGSQELLSETGISLDPRKPASQCVLDGVRGCDSYMVYLFDKSKTVYEGPFASRSLSDCVNYIVQDSKIQLPIIQLRKVWAEAVHYVSGLKEDYSRLFQGQRAAMLSLLRYNANLTKMKNTLISASQQLKAKLEFFHKSIQLDLERYSEQMTYGISSEKMLKAWKEMEEKAIHYAEVGVIGYLEDQIMSLHAEIMELQKSPYGRRQGDLMESLEQRAIDLYKQLKHRPSDHSYSDSTEMVKIIVHTVQSQDRVLKELFGHLSKLLGCKQKIIDLLPKVEVALSNIKEADNTVMFMQGKRQKEIWHLLKIACTQSSARSLVGSSLEGAVTPQTSAWLPPTSAEHDHSLSCVVTPQDGETSAQMIEENLNCLGHLSTIIHEANEEQGNSMMNLDWSWLTE,5.0 +Cc1cccc(c1)C1(CCCCC1)N1CCC=CC1,MGGALGPALLLTSLLGAWARLGAGQGEQAVTVAVVFGSSGPLQTQARTRLTSQNFLDLPLEIQPLTVGVNNTNPSSILTQICGLLGAARVHGIVFEDNVDTEAVAQLLDFVSSQTHVPILSISGGSAVVLTPKEPGSAFLQLGVSLEQQLQVLFKVLEEYDWSAFAVITSLHPGHALFLEGVRAVADASYLSWRLLDVLTLELGPGGPRARTQRLLRQVDAPVLVAYCSREEAEVLFAEAAQAGLVGPGHVWLVPNLALGSTDAPPAAFPVGLISVVTESWRLSLRQKVRDGVAILALGAHSYRRQYGTLPAPAGDCRSHPGPVSPAREAFYRHLLNVTWEGRDFSFSPGGYLVRPTMVVIALNRHRLWEMVGRWDHGVLYMKYPVWPRYSTSLQPVVDSRHLTVATLEERPFVIVESPDPGTGGCVPNTVPCRRQSNHTFSSGDLTPYTKLCCKGFCIDILKKLAKVVKFSYDLYLVTNGKHGKRVRGVWNGMIGEVYYKRADMAIGSLTINEERSEIIDFSVPFVETGISVMVSRSNGTVSPSAFLEPYSPAVWVMMFVMCLTVVAITVFMFEYFSPVSYNQNLTKGKKPGGPSFTIGKSVWLLWALVFNNSVPIENPRGTTSKIMVLVWAFFAVIFLASYTANLAAFMIQEQYIDTVSGLSDKKFQRPQDQYPPFRFGTVPNGSTERNIRSNYRDMHTHMVKFNQRSVEDALTSLKMGKLDAFIYDAAVLNYMAGKDEGCKLVTIGSGKVFATTGYGIAMQKDSHWKRAIDLALLQLLGDGETQKLETVWLSGICQNEKNEVMSSKLDIDNMAGVFYMLLVAMGLALLVFAWEHLVYWKLRHSVPNSSQLDFLLAFSRGIYSCFNGVQSLPSPARPPSPDLTADSAQANVLKMLQAARDMVNTADVSSSLDRATRTIENWGNNRRVPAPTASGPRSSTPGPPGQPSPSGWGPPGGGRTPLARRAPQPPARPATCGPPLPDVSRPSCRHASDARWPVRVGHQGPHVSASERRALPERSLLPAHCHYSSFPRAERSGRPYLPLFPEPPEPDDLPLLGPEQLARREAMLRAAWARGPRPRHASLPSSVAEAFTRSNPLPARCTGHACACPCPQSRPSCRHLAQAQSLRLPSYPEACVEGVPAGVATWQPRQHVCLHAHTRLPFCWGTVCRHPPPCTSHSPWLIGTWEPPAHRVRTLGLGTGYRDSGVLEEVSREACGTQGFPRSCTWRRVSSLESEV,7.0915149811213505 +OC(=O)c1ccc(cc1)-n1c(\C=C\c2cccc(c2)C(F)(F)F)nc2ccccc2c1=O,MSTMHLLTFALLFSCSFARAACDPKIVNIGAVLSTRKHEQMFREAVNQANKRHGSWKIQLNATSVTHKPNAIQMALSVCEDLISSQVYAILVSHPPTPNDHFTPTPVSYTAGFYRIPVLGLTTRMSIYSDKSIHLSFLRTVPPYSHQSSVWFEMMRVYNWNHIILLVSDDHEGRAAQKRLETLLEERESKAEKVLQFDPGTKNVTALLMEARELEARVIILSASEDDAATVYRAAAMLNMTGSGYVWLVGEREISGNALRYAPDGIIGLQLINGKNESAHISDAVGVVAQAVHELLEKENITDPPRGCVGNTNIWKTGPLFKRVLMSSKYADGVTGRVEFNEDGDRKFANYSIMNLQNRKLVQVGIYNGTHVIPNDRKIIWPGGETEKPRGYQMSTRLKIVTIHQEPFVYVKPTMSDGTCKEEFTVNGDPVKKVICTGPNDTSPGSPRHTVPQCCYGFCIDLLIKLARTMNFTYEVHLVADGKFGTQERVNNSNKKEWNGMMGELLSGQADMIVAPLTINNERAQYIEFSKPFKYQGLTILVKKEIPRSTLDSFMQPFQSTLWLLVGLSVHVVAVMLYLLDRFSPFGRFKVNSEEEEEDALTLSSAMWFSWGVLLNSGIGEGAPRSFSARILGMVWAGFAMIIVASYTANLAAFLVLDRPEERITGINDPRLRNPSDKFIYATVKQSSVDIYFRRQVELSTMYRHMEKHNYESAAEAIQAVRDNKLHAFIWDSAVLEFEASQKCDLVTTGELFFRSGFGIGMRKDSPWKQNVSLSILKSHENGFMEDLDKTWVRYQECDSRSNAPATLTFENMAGVFMLVAGGIVAGIFLIFIEIAYKRHKDARRKQMQLAFAAVNVWRKNLQDRKSGRAEPDPKKKATFRAITSTLASSFKRRRSSKDTSTGGGRGALQNQKDTVLPRRAIEREEGQLQLCSRHRES,4.886056647693163 +CCOC(=O)c1nc(nc(N2CCOCC2)c1OCC)-c1ccc(NC(=O)Nc2ccc(cc2)N2CCN(C)CC2)cc1,MLGTGPAAATTAATTSSNVSVLQQFASGLKSRNEETRAKAAKELQHYVTMELREMSQEESTRFYDQLNHHIFELVSSSDANERKGGILAIASLIGVEGGNATRIGRFANYLRNLLPSNDPVVMEMASKAIGRLAMAGDTFTAEYVEFEVKRALEWLGADRNEGRRHAAVLVLRELAISVPTFFFQQVQPFFDNIFVAVWDPKQAIREGAVAALRACLILTTQREPKEMQKPQWYRHTFEEAEKGFDETLAKEKGMNRDDRIHGALLILNELVRISSMEGERLREEMEEITQQQLVHDKYCKDLMGFGTKPRHITPFTSFQAVQPQQSNALVGLLGYSSHQGLMGFGTSPSPAKSTLVESRCCRDLMEEKFDQVCQWVLKCRNSKNSLIQMTILNLLPRLAAFRPSAFTDTQYLQDTMNHVLSCVKKEKERTAAFQALGLLSVAVRSEFKVYLPRVLDIIRAALPPKDFAHKRQKAMQVDATVFTCISMLARAMGPGIQQDIKELLEPMLAVGLSPALTAVLYDLSRQIPQLKKDIQDGLLKMLSLVLMHKPLRHPGMPKGLAHQLASPGLTTLPEASDVGSITLALRTLGSFEFEGHSLTQFVRHCADHFLNSEHKEIRMEAARTCSRLLTPSIHLISGHAHVVSQTAVQVVADVLSKLLVVGITDPDPDIRYCVLASLDERFDAHLAQAENLQALFVALNDQVFEIRELAICTVGRLSSMNPAFVMPFLRKMLIQILTELEHSGIGRIKEQSARMLGHLVSNAPRLIRPYMEPILKALILKLKDPDPDPNPGVINNVLATIGELAQVSGLEMRKWVDELFIIIMDMLQDSSLLAKRQVALWTLGQLVASTGYVVEPYRKYPTLLEVLLNFLKTEQNQGTRREAIRVLGLLGALDPYKHKVNIGMIDQSRDASAVSLSESKSSQDSSDYSTSEMLVNMGNLPLDEFYPAVSMVALMRIFRDQSLSHHHTMVVQAITFIFKSLGLKCVQFLPQVMPTFLNVIRVCDGAIREFLFQQLGMLVSFVKSHIRPYMDEIVTLMREFWVMNTSIQSTIILLIEQIVVALGGEFKLYLPQLIPHMLRVFMHDNSPGRIVSIKLLAAIQLFGANLDDYLHLLLPPIVKLFDAPEAPLPSRKAALETVDRLTESLDFTDYASRIIHPIVRTLDQSPELRSTAMDTLSSLVFQLGKKYQIFIPMVNKVLVRHRINHQRYDVLICRIVKGYTLADEEEDPLIYQHRMLRSGQGDALASGPVETGPMKKLHVSTINLQKAWGAARRVSKDDWLEWLRRLSLELLKDSSSPSLRSCWALAQAYNPMARDLFNAAFVSCWSELNEDQQDELIRSIELALTSQDIAEVTQTLLNLAEFMEHSDKGPLPLRDDNGIVLLGERAAKCRAYAKALHYKELEFQKGPTPAILESLISINNKLQQPEAAAGVLEYAMKHFGELEIQATWYEKLHEWEDALVAYDKKMDTNKDDPELMLGRMRCLEALGEWGQLHQQCCEKWTLVNDETQAKMARMAAAAAWGLGQWDSMEEYTCMIPRDTHDGAFYRAVLALHQDLFSLAQQCIDKARDLLDAELTAMAGESYSRAYGAMVSCHMLSELEEVIQYKLVPERREIIRQIWWERLQGCQRIVEDWQKILMVRSLVVSPHEDMRTWLKYASLCGKSGRLALAHKTLVLLLGVDPSRQLDHPLPTVHPQVTYAYMKNMWKSARKIDAFQHMQHFVQTMQQQAQHAIATEDQQHKQELHKLMARCFLKLGEWQLNLQGINESTIPKVLQYYSAATEHDRSWYKAWHAWAVMNFEAVLHYKHQNQARDEKKKLRHASGANITNATTAATTAATATTTASTEGSNSESEAESTENSPTPSPLQKKVTEDLSKTLLMYTVPAVQGFFRSISLSRGNNLQDTLRVLTLWFDYGHWPDVNEALVEGVKAIQIDTWLQVIPQLIARIDTPRPLVGRLIHQLLTDIGRYHPQALIYPLTVASKSTTTARHNAANKILKNMCEHSNTLVQQAMMVSEELIRVAILWHEMWHEGLEEASRLYFGERNVKGMFEVLEPLHAMMERGPQTLKETSFNQAYGRDLMEAQEWCRKYMKSGNVKDLTQAWDLYYHVFRRISKQLPQLTSLELQYVSPKLLMCRDLELAVPGTYDPNQPIIRIQSIAPSLQVITSKQRPRKLTLMGSNGHEFVFLLKGHEDLRQDERVMQLFGLVNTLLANDPTSLRKNLSIQRYAVIPLSTNSGLIGWVPHCDTLHALIRDYREKKKILLNIEHRIMLRMAPDYDHLTLMQKVEVFEHAVNNTAGDDLAKLLWLKSPSSEVWFDRRTNYTRSLAVMSMVGYILGLGDRHPSNLMLDRLSGKILHIDFGDCFEVAMTREKFPEKIPFRLTRMLTNAMEVTGLDGNYRITCHTVMEVLREHKDSVMAVLEAFVYDPLLNWRLMDTNTKGNKRSRTRTDSYSAGQSVEILDGVELGEPAHKKTGTTVPESIHSFIGDGLVKPEALNKKAIQIINRVRDKLTGRDFSHDDTLDVPTQVELLIKQATSHENLCQCYIGWCPFW,6.978810700930062 +CC(C)C(=O)N1CCC(CC1)c1cc(-c2ccc(NC(=O)c3cc(nn(-c4ccccc4)c3=O)C3CC3)cc2)c2c(N)ncnn12,MALRRSMGRPGLPPLPLPPPPRLGLLLAALASLLLPESAAAGLKLMGAPVKLTVSQGQPVKLNCSVEGMEEPDIQWVKDGAVVQNLDQLYIPVSEQHWIGFLSLKSVERSDAGRYWCQVEDGGETEISQPVWLTVEGVPFFTVEPKDLAVPPNAPFQLSCEAVGPPEPVTIVWWRGTTKIGGPAPSPSVLNVTGVTQSTMFSCEAHNLKGLASSRTATVHLQALPAAPFNITVTKLSSSNASVAWMPGADGRALLQSCTVQVTQAPGGWEVLAVVVPVPPFTCLLRDLVPATNYSLRVRCANALGPSPYADWVPFQTKGLAPASAPQNLHAIRTDSGLILEWEEVIPEAPLEGPLGPYKLSWVQDNGTQDELTVEGTRANLTGWDPQKDLIVRVCVSNAVGCGPWSQPLVVSSHDRAGQQGPPHSRTSWVPVVLGVLTALVTAAALALILLRKRRKETRFGQAFDSVMARGEPAVHFRAARSFNRERPERIEATLDSLGISDELKEKLEDVLIPEQQFTLGRMLGKGEFGSVREAQLKQEDGSFVKVAVKMLKADIIASSDIEEFLREAACMKEFDHPHVAKLVGVSLRSRAKGRLPIPMVILPFMKHGDLHAFLLASRIGENPFNLPLQTLIRFMVDIACGMEYLSSRNFIHRDLAARNCMLAEDMTVCVADFGLSRKIYSGDYYRQGCASKLPVKWLALESLADNLYTVQSDVWAFGVTMWEIMTRGQTPYAGIENAEIYNYLIGGNRLKQPPECMEDVYDLMYQCWSADPKQRPSFTCLRMELENILGQLSVLSASQDPLYINIERAEEPTAGGSLELPGRDQPYSGAGDGSGMGAVGGTPSDCRYILTPGGLAEQPGQAEHQPESPLNETQRLLLLQQGLLPHSSC,7.0 +OC(C1CCOCC1)C(=O)N1CC[C@@]2([C@H]1CCc1cc(ccc21)C(F)(C(F)(F)F)C(F)(F)F)S(=O)(=O)c1ccc(F)cc1,APYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFS,7.6777807052660805 +OC(=O)c1ccncc1NC[C@H]1CCCc2ccccc12,MAGVGPGGYAAEFVPPPECPVFEPSWEEFTDPLSFIGRIRPLAEKTGICKIRPPKDWQPPFACEVKSFRFTPRVQRLNELEAMTRVRLDFLDQLAKFWELQGSTLKIPVVERKILDLYALSKIVASKGGFEMVTKEKKWSKVGSRLGYLPGKGTGSLLKSHYERILYPYELFQSGVSLMGVQMPNLDLKEKVEPEVLSTDTQTSPEPGTRMNILPKRTRRVKTQSESGDVSRNTELKKLQIFGAGPKVVGLAMGTKDKEDEVTRRRKVTNRSDAFNMQMRQRKGTLSVNFVDLYVCMFCGRGNNEDKLLLCDGCDDSYHTFCLIPPLPDVPKGDWRCPKCVAEECSKPREAFGFEQAVREYTLQSFGEMADNFKSDYFNMPVHMVPTELVEKEFWRLVSSIEEDVIVEYGADISSKDFGSGFPVKDGRRKILPEEEEYALSGWNLNNMPVLEQSVLAHINVDISGMKVPWLYVGMCFSSFCWHIEDHWSYSINYLHWGEPKTWYGVPSHAAEQLEEVMRELAPELFESQPDLLHQLVTIMNPNVLMEHGVPVYRTNQCAGEFVVTFPRAYHSGFNQGYNFAEAVNFCTADWLPIGRQCVNHYRRLRRHCVFSHEELIFKMAADPECLDVGLAAMVCKELTLMTEEETRLRESVVQMGVLMSEEEVFELVPDDERQCSACRTTCFLSALTCSCNPERLVCLYHPTDLCPCPMQKKCLRYRYPLEDLPSLLYGVKVRAQSYDTWVSRVTEALSANFNHKKDLIELRVMLEDAEDRKYPENDLFRKLRDAVKEAETCASVAQLLLSKKQKHRQSPDSGRTRTKLTVEELKAFVQQLFSLPCVISQARQVKNLLDDVEEFHERAQEAMMDETPDSSKLQMLIDMGSSLYVELPELPRLKQELQQARWLDEVRLTLSDPQQVTLDVMKKLIDSGVGLAPHHAVEKAMAELQELLTVSERWEEKAKVCLQARPRHSVASLESIVNEAKNIPAFLPNVLSLKEALQKAREWTAKVEAIQSGSNYAYLEQLESLSAKGRPIPVRLEALPQVESQVAAARAWRERTGRTFLKKNSSHTLLQVLSPRTDIGVYGSGKNRRKKVKELIEKEKEKDLDLEPLSDLEEGLEETRDTAMVVAVFKEREQKEIEAMHSLRAANLAKMTMVDRIEEVKFCICRKTASGFMLQCELCKDWFHNSCVPLPKSSSQKKGSSWQAKEVKFLCPLCMRSRRPRLETILSLLVSLQKLPVRLPEGEALQCLTERAMSWQDRARQALATDELSSALAKLSVLSQRMVEQAAREKTEKIISAELQKAAANPDLQGHLPSFQQSAFNRVVSSVSSSPRQTMDYDDEETDSDEDIRETYGYDMKDTASVKSSSSLEPNLFCDEEIPIKSEEVVTHMWTAPSFCAEHAYSSASKSCSQGSSTPRKQPRKSPLVPRSLEPPVLELSPGAKAQLEELMMVGDLLEVSLDETQHIWRILQATHPPSEDRFLHIMEDDSMEEKPLKVKGKDSSEKKRKRKLEKVEQLFGEGKQKSKELKKMDKPRKKKLKLGADKSKELNKLAKKLAKEEERKKKKEKAAAAKVELVKESTEKKREKKVLDIPSKYDWSGAEESDDENAVCAAQNCQRPCKDKVDWVQCDGGCDEWFHQVCVGVSPEMAENEDYICINCAKKQGPVSPGPAPPPSFIMSYKLPMEDLKETS,7.0 +Cc1cn(Cc2cn3ccccc3n2)c2c(\C=C\C(=O)NS(=O)(=O)c3cc(Cl)c(Cl)s3)cc(F)cc12,MKETRGYGGDAPFCTRLNHSYTGMWAPERSAEARGNLTRPPGSGEDCGSVSVAFPITMLLTGFVGNALAMLLVSRSYRRRESKRKKSFLLCIGWLALTDLVGQLLTTPVVIVVYLSKQRWEHIDPSGRLCTFFGLTMTVFGLSSLFIASAMAVERALAIRAPHWYASHMKTRATRAVLLGVWLAVLAFALLPVLGVGQYTVQWPGTWCFISTGRGGNGTSSSHNWGNLFFASAFAFLGLLALTVTFSCNLATIKALVSRCRAKATASQSSAQWGRITTETAIQLMGIMCVLSVCWSPLLIMMLKMIFNQTSVEHCKTHTEKQKECNFFLIAVRLASLNQILDPWVYLLLRKILLRKFCQIRYHTNNYASSSTSLPCQCSSTLMWSDHLER,6.166215625343521 +O[C@H]1CC[C@@]2(O)[C@H]3Cc4ccc(O)c5O[C@@H]1[C@]2(CCN3CC1CC1)c45,YTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKTVNVCNWI,8.958607314841775 +COCc1ccc(C(C)=O)c2sc(C(=O)Nc3cc(Cl)c4ccccc4n3)c(C)c12,MEDGPSNNASCFRRLTECFLSPSLTDEKVKAYLSLHPQVLDEFVSESVSAETVEKWLKRKNNKSEDESAPKEVSRYQDTNMQGVVYELNSYIEQRLDTGGDNQLLLYELSSIIKIATKADGFALYFLGECNNSLCIFTPPGIKEGKPRLIPAGPITQGTTVSAYVAKSRKTLLVEDILGDERFPRGTGLESGTRIQSVLCLPIVTAIGDLIGILELYRHWGKEAFCLSHQEVATANLAWASVAIHQVQVCRGLAKQTELNDFLLDVSKTYFDNIVAIDSLLEHIMIYAKNLVNADRCALFQVDHKNKELYSDLFDIGEEKEGKPVFKKTKEIRFSIEKGIAGQVARTGEVLNIPDAYADPRFNREVDLYTGYTTRNILCMPIVSRGSVIGVVQMVNKISGSAFSKTDENNFKMFAVFCALALHCANMYHRIRHSECIYRVTMEKLSYHSICTSEEWQGLMQFTLPVRLCKEIELFHFDIGPFENMWPGIFVYMVHRSCGTSCFELEKLCRFIMSVKKNYRRVPYHNWKHAVTVAHCMYAILQNNHTLFTDLERKGLLIACLCHDLDHRGFSNSYLQKFDHPLAALYSTSTMEQHHFSQTVSILQLEGHNIFSTLSSSEYEQVLEIIRKAIIATDLALYFGNRKQLEEMYQTGSLNLNNQSHRDRVIGLMMTACDLCSVTKLWPVTKLTANDIYAEFWAEGDEMKKLGIQPIPMMDRDKKDEVPQGQLGFYNAVAIPCYTTLTQILPPTEPLLKACRDNLSQWEKVIRGEETATWISSPSVAQKAAASED,7.7447274948966935 +OC(=O)[C@@]12CC3CC(C1)[C@H](Oc1ccc(cc1)C(=O)NCCNC(=O)c1ccc(cc1)-c1ccccc1)C(C3)C2,MGDRGGAGSSRRRRTGSRVSVQGGSGPKVEEDEVRDAAVSPDLGAGGDAPAPAPAPAHTRDKDGRTSVGDGYWDLRCHRLQDSLFSSDSGFSNYRGILNWCVVMLILSNARLFLENLIKYGILVDPIQVVSLFLKDPYSWPAPCVIIASNIFVVAAFQIEKRLAVGALTEQMGLLLHVVNLATIICFPAAVALLVESITPVGSVFALASYSIMFLKLYSYRDVNLWCRQRRVKAKAVSTGKKVSGAAAQQAVSYPDNLTYRDLYYFIFAPTLCYELNFPRSPRIRKRFLLRRVLEMLFFTQLQVGLIQQWMVPTIQNSMKPFKDMDYSRIIERLLKLAVPNHLIWLIFFYWFFHSCLNAVAELLQFGDREFYRDWWNAESVTYFWQNWNIPVHKWCIRHFYKPMLRHGSSKWVARTGVFLTSAFFHEYLVSVPLRMFRLWAFTAMMAQVPLAWIVGRFFQGNYGNAAVWVTLIIGQPVAVLMYVHDYYVLNYDAPVGV,8.301029995663981 +COc1ccc(cc1)-c1c(C)sc(NC(=O)c2ccnn2C)c1C#N,MSTNENANTPAARLHRFKNKGKDSTEMRRRRIEVNVELRKAKKDDQMLKRRNVSSFPDDATSPLQENRNNQGTVNWSVDDIVKGINSSNVENQLQATQAARKLLSREKQPPIDNIIRAGLIPKFVSFLGRTDCSPIQFESAWALTNIASGTSEQTKAVVDGGAIPAFISLLASPHAHISEQAVWALGNIAGDGSVFRDLVIKYGAVDPLLALLAVPDMSSLACGYLRNLTWTLSNLCRNKNPAPPIDAVEQILPTLVRLLHHDDPEVLADTCWAISYLTDGPNERIGMVVKTGVVPQLVKLLGASELPIVTPALRAIGNIVTGTDEQTQVVIDAGALAVFPSLLTNPKTNIQKEATWTMSNITAGRQDQIQQVVNHGLVPFLVSVLSKADFKTQKEAVWAVTNYTSGGTVEQIVYLVHCGIIEPLMNLLTAKDTKIILVILDAISNIFQAAEKLGETEKLSIMIEECGGLDKIEALQNHENESVYKASLSLIEKYFSVEEEEDQNVVPETTSEGYTFQVQDGAPGTFNF,3.3010299956639813 +CCCCC#Cc1cncc(OC[C@@H]2CCCN2)c1,MANSGTGAPPPLLLLPLLLLLGTGLLPASSHIETRAHAEERLLKRLFSGYNKWSRPVANISDVVLVRFGLSIAQLIDVDEKNQMMTTNVWVKQEWHDYKLRWDPGDYENVTSIRIPSELIWRPDIVLYNNADGDFAVTHLTKAHLFYDGRVQWTPPAIYKSSCSIDVTFFPFDQQNCTMKFGSWTYDKAKIDLVSMHSRVDQLDFWESGEWVIVDAVGTYNTRKYECCAEIYPDITYAFIIRRLPLFYTINLIIPCLLISCLTVLVFYLPSECGEKVTLCISVLLSLTVFLLLITEIIPSPTSLVIPLIGEYLLFTMIFVTLSIVITVFVLNVHHRSPRTHTMPAWVRRVFLDIVPRLLFMKRPSVVKDNCRRLIESMHKMANAPRFWPEPVGEPGILSDICNQGLSPAPTFCNPTDTAVETQPTCRSPPLEVPDLKTSEVEKASPCPSPGSCPPPKSSSGAPMLIKARSLSVQHVPSSQEAAEDGIRCRSRSIQYCVSQDGAASLADSKPTSSPTSLKARPSQLPVSDQASPCKCTCKEPSPVSPVTVLKAGGTKAPPQHLPLSPALTRAVEGVQYIADHLKAEDTDFSVKEDWKYVAMVIDRIFLWMFIIVCLLGTVGLFLPPWLAAC,8.920818753952375 +CC[C@]1(Cc2cc(OCCCOc3ccc(OCC(F)(F)F)cc3)ccc2O1)C(O)=O,MVDTESPLCPLSPLEAGDLESPLSEEFLQEMGNIQEISQSIGEDSSGSFGFTEYQYLGSCPGSDGSVITDTLSPASSPSSVTYPVVPGSVDESPSGALNIECRICGDKASGYHYGVHACEGCKGFFRRTIRLKLVYDKCDRSCKIQKKNRNKCQYCRFHKCLSVGMSHNAIRFGRMPRSEKAKLKAEILTCEHDIEDSETADLKSLAKRIYEAYLKNFNMNKVKARVILSGKASNNPPFVIHDMETLCMAEKTLVAKLVANGIQNKEAEVRIFHCCQCTSVETVTELTEFAKAIPGFANLDLNDQVTLLKYGVYEAIFAMLSSVMNKDGMLVAYGNGFITREFLKSLRKPFCDIMEPKFDFAMKFNALELDDSDISLFVAAIICCGDRPGLLNVGHIEKMQEGIVHVLRLHLQSNHPDDIFLFPKLLQKMADLRQLVTEHAQLVQIIKKTESDAALHPLLQEIYRDMY,5.522878745280337 +CC(=O)OCC1(CCN(CCc2ccccc2)CC1)N(C(C)=O)c1ccccc1,MESPIQIFRGEPGPTCAPSACLLPNSSSWFPNWAESDSNGSVGSEDQQLEPAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSAVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLASSVGISAIVLGGTKVREDVDVIECSLQFPDDEYSWWDLFMKICVFVFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITKLVLVVVAVFIICWTPIHIFILVEALGSTSHSTAVLSSYYFCIALGYTNSSLNPVLYAFLDENFKRCFRDFCFPIKMRMERQSTNRVRNTVQDPASMRDVGGMNKPV,7.920818753952375 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+Cc1ccc(C[N+](C)(C)CCCN2c3ccccc3Sc3ccc(Cl)cc23)cc1C,MMSKIFDLVVIGAGSGGLEAAWNAATLYKKRVAVIDVQMVHGPPFFSALGGTCVNVGCVPKKLMVTGAQYMEHLRESAGFGWEFDRTTLRAEWKKLIAVKDEAVLNINKSYEEMFRDTEGLEFFLGWGSLESKNVVNVRESADPASAVKERLETENILLASGSWPHMPNIPGIEHCISSNEAFYLPEPPRRVLTVGGGFISVEFAGIFNAYKPKDGQVTLCYRGEMILRGFDHTLREELTKQLTANGIQILTKENPAKVELNADGSKSVTFESGKKMDFDLVMMAIGRSPRTKDLQLQNAGVMIKNGGVQVDEYSRTNVSNIYAIGDVTNRVMLTPVAINEAAALVDTVFGTNPRKTDHTRVASAVFSIPPIGTCGLIEEVASKRYEVVAVYLSSFTPLMHNISGSKYKTFVAKIITNHSDGTVLGVHLLGDNAPEIIQGVGICLKLNAKISDFYNTIGVHPTSAEELCSMRTPSYYYVKGEKMEKPSEASL,5.4089353929735005 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+N[C@]1(CN[C@H](C1)C(O)=O)C(O)=O,MESLLGFLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEECGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHSDAPTAVTGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAATQRLNASFTWVASDGWGALESVVAGSERAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEERFHCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTHLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTDDEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSFIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFVFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVAAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAPRASANLGQGSGSQFVPTVCNGREVVDSTTSSL,6.522878745280337 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+FC(F)(F)c1nc(no1)-c1ccc(cc1)C(=O)NC1CCNC1,MAQTQGTRRKVCYYYDGDVGNYYYGQGHPMKPHRIRMTHNLLLNYGLYRKMEIYRPHKANAEEMTKYHSDDYIKFLRSIRPDNMSEYSKQMQRFNVGEDCPVFDGLFEFCQLSTGGSVASAVKLNKQQTDIAVNWAGGLHHAKKSEASGFCYVNDIVLAILELLKYHQRVLYIDIDIHHGDGVEEAFYTTDRVMTVSFHKYGEYFPGTGDLRDIGAGKGKYYAVNYPLRDGIDDESYEAIFKPVMSKVMEMFQPSAVVLQCGSDSLSGDRLGCFNLTIKGHAKCVEFVKSFNLPMLMLGGGGYTIRNVARCWTYETAVALDTEIPNELPYNDYFEYFGPDFKLHISPSNMTNQNTNEYLEKIKQRLFENLRMLPHAPGVQMQAIPEDAIPEESGDEDEDDPDKRISICSSDKRIACEEEFSDSEEEGEGGRKNSSNFKKAKRVKTEDEKEKDPEEKKEVTEEEKTKEEKPEAKGVKEEVKLA,5.0 +O=C(NCC(=O)N1CCC[C@H]1C#N)OCc1ccccc1,MLSLQYPDVYRDETAVQDYHGHKICDPYAWLEDPDSEQTKAFVEAQNKITVPFLEQCPIRGLYKERMTELYDYPKYSCHFKKGKRYFYFYNTGLQNQRVLYVQDSLEGEARVFLDPNILSDDGTVALRGYAFSEDGEYFAYGLSASGSDWVTIKFMKVDGAKELPDVLERVKFSCMAWTHDGKGMFYNSYPQQDGKSDGTETSTNLHQKLYYHVLGTDQSEDILCAEFPDEPKWMGGAELSDDGRYVLLSIREGCDPVNRLWYCDLQQESSGIAGILKWVKLIDNFEGEYDYVTNEGTVFTFKTNRQSPNYRVINIDFRDPEESKWKVLVPEHEKDVLEWIACVRSNFLVLCYLHDVKNILQLHDLTTGALLKTFPLDVGSIVGYSGQKKDTEIFYQFTSFLSPGIIYHCDLTKEELEPRVFREVTVKGIDASDYQTVQIFYPSKDGTKIPMFIVHKKGIKLDGSHPAFLYGYGGFNISITPNYSVSRLIFVRHMGGILAVANIRGGGEYGETWHKGGILANKQNCFDDFQCAAEYLIKEGYTSPKRLTINGGSNGGLLVAACANQRPDLFGCVIAQVGVMDMLKFHKYTIGHAWTTDYGCSDSKQHFEWLVKYSPLHNVKLPEADDIQYPSMLLLTADHDDRVVPLHSLKFIATLQYIVGRSRKQSNPLLIHVDTKAGHGAGKPTAKVIEEVSDMFAFIARCLNVDWIP,7.698970004336019 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+NS(=O)(=O)Oc1ccc(NC(=O)Nc2ccc(cc2)C#N)cc1,MAPLCPSPWLPLLIPAPAPGLTVQLLLSLLLLVPVHPQRLPRMQEDSPLGGGSSGEDDPLGEEDLPSEEDSPREEDPPGEEDLPGEEDLPGEEDLPEVKPKSEEEGSLKLEDLPTVEAPGDPQEPQNNAHRDKEGDDQSHWRYGGDPPWPRVSPACAGRFQSPVDIRPQLAAFCPALRPLELLGFQLPPLPELRLRNNGHSVQLTLPPGLEMALGPGREYRALQLHLHWGAAGRPGSEHTVEGHRFPAEIHVVHLSTAFARVDEALGRPGGLAVLAAFLEEGPEENSAYEQLLSRLEEIAEEGSETQVPGLDISALLPSDFSRYFQYEGSLTTPPCAQGVIWTVFNQTVMLSAKQLHTLSDTLWGPGDSRLQLNFRATQPLNGRVIEASFPAGVDSSPRAAEPVQLNSCLAAGDILALVFGLLFAVTSVAFLVQMRRQHRRGTKGGVSYRPAEVAETGA,8.045757490560675 +COc1cccc(c1)-c1cc2cc(CCC(O)=O)ccc2[nH]1,MDLPPQLSFGLYVAAFALGFPLNVLAIRGATAHARLRLTPSLVYALNLGCSDLLLTVSLPLKAVEALASGAWPLPASLCPVFAVAHFFPLYAGGGFLAALSAGRYLGAAFPLGYQAFRRPCYSWGVCAAIWALVLCHLGLVFGLEAPGGWLDHSNTSLGINTPVNGSPVCLEAWDPASAGPARFSLSLLLFFLPLAITAFCYVGCLRALARSGLTHRRKLRAAWVAGGALLTLLLCVGPYNASNVASFLYPNLGGSWRKLGLITGAWSVVLNPLVTGYLGRGPGLKTVCAARTQGGKSQK,7.6020599913279625 +CN(O)C(=O)c1nn(C)c-2c1CCc1cnc(NC3CCCC3)nc-21,MENFQKVEKIGEGTYGVVYKARNKLTGEVVALKKIRLDTETEGVPSTAIREISLLKELNHPNIVKLLDVIHTENKLYLVFEFLHQDLKKFMDASALTGIPLPLIKSYLFQLLQGLAFCHSHRVLHRDLKPQNLLINTEGAIKLADFGLARAFGVPVRTYTHEVVTLWYRAPEILLGCKYYSTAVDIWSLGCIFAEMVTRRALFPGDSEIDQLFRIFRTLGTPDEVVWPGVTSMPDYKPSFPKWARQDFSKVVPPLDEDGRSLLSQMLHYDPNKRISAKAALAHPFFQDVTKPVPHLRL,6.756961951313706 +CC(C)[C@H](NC(=O)[C@@H](NC(=O)[C@H](CC(O)=O)NC(=O)OCc1ccccc1)C1Cc2ccccc2C1)C(=O)N[C@@H](CC(O)=O)\C=C\S(C)(=O)=O,MDEADRRLLRRCRLRLVEELQVDQLWDALLSRELFRPHMIEDIQRAGSGSRRDQARQLIIDLETRGSQALPLFISCLEDTGQDMLASFLRTNRQAAKLSKPTLENLTPVVLRPEIRKPEVLRPETPRPVDIGSGGFGDVGALESLRGNADLAYILSMEPCGHCLIINNVNFCRESGLRTRTGSNIDCEKLRRRFSSLHFMVEVKGDLTAKKMVLALLELAQQDHGALDCCVVVILSHGCQASHLQFPGAVYGTDGCPVSVEKIVNIFNGTSCPSLGGKPKLFFIQACGGEQKDHGFEVASTSPEDESPGSNPEPDATPFQEGLRTFDQLDAISSLPTPSDIFVSYSTFPGFVSWRDPKSGSWYVETLDDIFEQWAHSEDLQSLLLRVANAVSVKGIYKQMPGCFNFLRKKLFFKTS,5.47755576649368 +CC1(C)CC(=O)C2=C(C1)N(C1=C(C2c2cccc(c2)[N+]([O-])=O)C(=O)CC(C)(C)C1)c1ccc(cc1)S(N)(=O)=O,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,6.050609993355087 +NCCc1ccc(cc1)S(N)(=O)=O,MKKRFSFIFIFLVALPLYSANNVAAPLIDLGAEAKKQAQKSAATQSAVPEKESATKVAEKQKEPEEKAKPEPKKPPHWGYFGEEGPQYWGELAPEFSTCKTGKNQSPINLKPQTAVGTTSLPGFDVYYRETALKLINNGHTLQVNIPLGSYIKINGHRYELLQYHFHTPSEHQRDGFNYPMEMHLVHKDGDGNLAVIAILFQEGEENETLAKLMSFLPQTLKKQEIHESVKIHPAKFFPADKKFYKYSGSLTTPPCSEGVYWMVFKQPIQASVTQLEKMHEYLGSNARPVQRQNARTLLKSWPDRNRANTVYEFY,6.311580177997289 +CCOc1ccccc1CNc1nc(C)nc2[nH]cc(-c3ccnc(N)c3)c12,MAKQYDSVECPFCDEVSKYEKLAKIGQGTFGEVFKARHRKTGQKVALKKVLMENEKEGFPITALREIKILQLLKHENVVNLIEICRTKASPYNRCKGSIYLVFDFCEHDLAGLLSNVLVKFTLSEIKRVMQMLLNGLYYIHRNKILHRDMKAANVLITRDGVLKLADFGLARAFSLAKNSQPNRYTNRVVTLWYRPPELLLGERDYGPPIDLWGAGCIMAEMWTRSPIMQGNTEQHQLALISQLCGSITPEVWPNVDNYELYEKLELVKGQKRKVKDRLKAYVRDPYALDLIDKLLVLDPAQRIDSDDALNHDFFWSDPMPSDLKGMLSTHLTSMFEYLAPPRRKGSQITQQSTNQSRNPATTNQTEFERVF,8.0 +Cc1ccc(cc1)-c1ccnc2nnnn12,MTISDHPETEPKWWKEATIYQIYPASFKDSNNDGWGDLKGITSKLQYIKDLGVDAIWVCPFYDSPQQDMGYDISNYEKVWPTYGTNEDCFELIDKTHKLGMKFITDLVINHCSTEHEWFKESRSSKTNPKRDWFFWRPPKGYDAEGKPIPPNNWKSFFGGSAWTFDETTNEFYLRLFASRQVDLNWENEDCRRAIFESAVGFWLDHGVDGFRIDTAGLYSKRPGLPDSPIFDKTSKLQHPNWGSHNGPRIHEYHQELHRFMKNRVKDGREIMTVGEVAHGSDNALYTSAARYEVSEVFSFTHVEVGTSPFFRYNIVPFTLKQWKEAIASNFLFINGTDSWATTYIENHDQARSITRFADDSPKYRKISGKLLTLLECSLTGTLYVYQGQEIGQINFKEWPIEKYEDVDVKNNYEIIKKSFGKNSKEMKDFFKGIALLSRDHSRTPMPWTKDKPNAGFTGPDVKPWFLLNESFEQGINVEQESRDDDSVLNFWKRALQARKKYKELMIYGYDFQFIDLDSDQIFSFTKEYEDKTLFAALNFSGEEIEFSLPREGASLSFILGNYDDTDVSSRVLKPWEGRIYLVK,4.302770657240282 +OC(=O)c1ccc(NC(=O)CCCN2C(=S)S\C(=C/c3ccc4OCOc4c3)C2=O)cc1,MDRLLRLGGGMPGLGQGPPTDAPAVDTAEQVYISSLALLKMLKHGRAGVPMEVMGLMLGEFVDDYTVRVIDVFAMPQSGTGVSVEAVDPVFQAKMLDMLKQTGRPEMVVGWYHSHPGFGCWLSGVDINTQQSFEALSERAVAVVVDPIQSVKGKVVIDAFRLINANMMVLGHEPRQTTSNLGHLNKPSIQALIHGLNRHYYSITINYRKNELEQKMLLNLHKKSWMEGLTLQDYSEHCKHNESVVKEMLELAKNYNKAVEEEDKMTPEQLAIKNVGKQDPKRHLEEHVDVLMTSNIVQCLAAMLDTVVFK,4.39040559077478 +NS(=O)(=O)c1ccccc1Br,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,6.2441251443275085 +Cc1ccc(OCCC(=O)Nc2ccccc2C(=O)NC2CC2)cc1,MAKQPSDVSSECDREGRQLQPAERPPQLRPGAPTSLQTEPQGNPEGNHGGEGDSCPHGSPQGPLAPPASPGPFATRSPLFIFMRRSSLLSRSSSGYFSFDTDRSPAPMSCDKSTQTPSPPCQAFNHYLSAMASMRQAEPADMRPEIWIAQELRRIGDEFNAYYARRVFLNNYQAAEDHPRMVILRLLRYIVRLVWRMH,3.4559319556497243 +COc1nc(ccc1CN[C@H]1C[C@](C)(O)C1)-c1cccc(c1Cl)-c1cccc2[C@H](CCc12)Nc1nc(OC)c(CN[C@@H](C2CC2)C(O)=O)cc1C(F)(F)F,LDSPDRPWNPPTFSPALLVVTEGDNATFTCSFSNTSESFVLNWYRMSPSNQTDKLAAFPEDRSQPGQDCRFRVTQLPNGRDFHMSVVRARRNDSGTYLCGAISLAPKAQIKESLRAELRVTERRAEVPTAHPSPSPRPAGQFQ,10.193820026016112 +Nc1n[nH]c2nc(N3CCCCC3)c3CN(Cc4ccccc4)CCc3c12,MSQRQPQSPNQTLISITNDTETSSSAVSNDTTPKGWTGDNSPGIEALCAIYITYAVIISVGILGNAILIKVFFKTKSMQTVPNIFITSLAFGDLLLLLTCVPVDATHYLAEGWLFGKVGCKVLSFIRLTSVGVSVFTLTILSADRYKAVVKPLERQPSNAILKTCAKAGGIWIMAMIFALPEAIFSNVYTFQDPNRNVTFESCNSYPISERLLQEIHSLLCFLVFYIIPLSIISVYYSLIARTLYKSTLNIPTEEQSHARKQIESRKRIAKTVLVLVALFALCWLPNHLLYLYHSFTYESYAEPSDVPFVVTIFSRVLAFSNSCVNPFALYWLSKTFQKHFKAQLCCFKAEQPEPPLGDTPLNNLTVMGRVPATGSAHVSEISVTLFSGSTAKKGEDKV,6.42021640338319 +CC1N(CC(F)(F)F)S(=O)(=O)c2ccc(Nc3nn([C@H]4CCCC[C@@H]4C#N)c4cc[nH]c(=O)c34)cc12,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,5.585026652029182 +BrC1=C[C@]2(CCNC3=C2C2=NCCc4c[nH]c(c24)C3=O)C(SSC2=CC(=O)C(Br)=C[C@]22CCNC3=C2C2=NCCc4c[nH]c(c24)C3=O)=CC1=O,MEGAGGANDKKKISSERRKEKSRDAARSRRSKESEVFYELAHQLPLPHNVSSHLDKASVMRLTISYLRVRKLLDAGDLDIEDDMKAQMNCFYLKALDGFVMVLTDDGDMIYISDNVNKYMGLTQFELTGHSVFDFTHPCDHEEMREMLTHRNGLVKKGKEQNTQRSFFLRMKCTLTSRGRTMNIKSATWKVLHCTGHIHVYDTNSNQPQCGYKKPPMTCLVLICEPIPHPSNIEIPLDSKTFLSRHSLDMKFSYCDERITELMGYEPEELLGRSIYEYYHALDSDHLTKTHHDMFTKGQVTTGQYRMLAKRGGYVWVETQATVIYNTKNSQPQCIVCVNYVVSGIIQHDLIFSLQQTECVLKPVESSDMKMTQLFTKVESEDTSSLFDKLKKEPDALTLLAPAAGDTIISLDFGSNDTETDDQQLEEVPLYNDVMLPSPNEKLQNINLAMSPLPTAETPKPLRSSADPALNQEVALKLEPNPESLELSFTMPQIQDQTPSPSDGSTRQSSPEPNSPSEYCFYVDSDMVNEFKLELVEKLFAEDTEAKNPFSTQDTDLDLEMLAPYIPMDDDFQLRSFDQLSPLESSSASPESASPQSTVTVFQQTQIQEPTANATTTTATTDELKTVTKDRMEDIKILIASPSPTHIHKETTSATSSPYRDTQSRTASPNRAGKGVIEQTEKSHPRSPNVLSVALSQRTTVPEEELNPKILALQNAQRKRKMEHDGSLFQAVGIGTLLQQPDDHAATTSLSWKRVKGCKSSEQNGMEQKTIILIPSDLACRLLGQSMDESGLPQLTSYDCEVNAPIQGSRNLLQGEELLRALDQVN,4.0 +NS(=O)(=O)c1nc2ccc(O)cc2s1,MASPDWGYDDKNGPEQWSKLYPIANGNNQSPVDIKTSETKHDTSLKPISVSYNPATAKEIINVGHSFHVNFEDNDNRSVLKGGPFSDSYRLFQFHFHWGSTNEHGSEHTVDGVKYSAELHVAHWNSAKYSSLAEAASKADGLAVIGVLMKVGEANPKLQKVLDALQAIKTKGKRAPFTNFDPSTLLPSSLDFWTYPGSLTHPPLYESVTWIICKESISVSSEQLAQFRSLLSNVEGDNAVPMQHNNRPTQPLKGRTVRASF,7.022276394711152 +CC[n+]1cn([C@@H]2O[C@H](CO)[C@H](OC(C)C)C2OC(C)C)c2nc(N)[nH]c(=O)c12,MATVEPETTPTPNPPTTEEEKTESNQEVANPEHYIKHPLQNRWALWFFKNDKSKTWQANLRLISKFDTVEDFWALYNHIQLSSNLMPGCDYSLFKDGIEPMWEDEKNKRGGRWLITLNKQQRRSDLDRFWLETLLCLIGESFDDYSDDVCGAVVNVRAKGDKIAIWTTECENREAVTHIGRVYKERLGLPPKIVIGYQSHADTATKSGSTTKNRFVV,3.3979400086720375 +CC(C)Oc1ccc(cc1C(F)(F)F)-c1nc(no1)-c1ccc(CCC(O)=O)cc1C,MATALPPRLQPVRGNETLREHYQYVGKLAGRLKEASEGSTLTTVLFLVICSFIVLENLMVLIAIWKNNKFHNRMYFFIGNLALCDLLAGIAYKVNILMSGKKTFSLSPTVWFLREGSMFVALGASTCSLLAIAIERHLTMIKMRPYDANKRHRVFLLIGMCWLIAFTLGALPILGWNCLHNLPDCSTILPLYSKKYIAFCISIFTAILVTIVILYARIYFLVKSSSRKVANHNNSERSMALLRTVVIVVSVFIACWSPLFILFLIDVACRVQACPILFKAQWFIVLAVLNSAMNPVIYTLASKEMRRAFFRLVCNCLVRGRGARASPIQPALDPSRSKSSSSNNSSHSPKVKEDLPHTAPSSCIMDKNAALQNGIFCN,6.958607314841775 +Clc1ccc(CN2CCC2)cn1,MAGHSNSMALFSFSLLWLCSGVLGTDTEERLVEHLLDPSRYNKLIRPATNGSELVTVQLMVSLAQLISVHEREQIMTTNVWLTQEWEDYRLTWKPEDFDNMKKVRLPSKHIWLPDVVLYNNADGMYEVSFYSNAVVSYDGSIFWLPPAIYKSACKIEVKHFPFDQQNCTMKFRSWTYDRTEIDLVLKSDVASLDDFTPSGEWDIIALPGRRNENPDDSTYVDITYDFIIRRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTVFLLLISKIVPPTSLDVPLVGKYLMFTMVLVTFSIVTSVCVLNVHHRSPTTHTMAPWVKVVFLEKLPTLLFLQQPRHRCARQRLRLRRRQREREGAGALFFREGPAADPCTCFVNPASVQGLAGAFRAEPTAAGPGRSVGPCSCGLREAVDGVRFIADHMRSEDDDQSVREDWKYVAMVIDRLFLWIFVFVCVFGTVGMFLQPLFQNYTATTFLHPDHSAPSSK,7.795880017344075 +O=C(Nc1ccc(cc1)C(=O)NCC1CCCC1)N1Cc2ccncc2C1,MNPAAEAEFNILLATDSYKVTHYKQYPPNTSKVYSYFECREKKTENSKLRKVKYEETVFYGLQYILNKYLKGKVVTKEKIQEAKDVYKEHFQDDVFNEKGWNYILEKYDGHLPIEIKAVPEGFVIPRGNVLFTVENTDPECYWLTNWIETILVQSWYPITVATNSREQKKILAKYLLETSGNLDGLEYKLHDFGYRGVSSQETAGIGASAHLVNFKGTDTVAGLALIKKYYGTKDPVPGYSVPAAEHSTITAWGKDHEKDAFEHIVTQFSSVPVSVVSDSYDIYNACEKIWGEDLRHLIVSRSTQAPLIIRPDSGNPLDTVLKVLEILGKKFPVTENSKGYKLLPPYLRVIQGDGVDINTLQEIVEGMKQKMWSIENIAFGSGGGLLQKLTRDLLNCSFKCSYVVTNGLGINVFKDPVADPNKRSKKGRLSLHRTPAGNFVTLEEGKGDLEEYGQDLLHTVFKNGKVTKSYSFDEIRKNAQLNIELEAAHH,8.379863945026242 +COC(=O)[C@H](CC(C)C)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC=CS(C)(=O)=O)NC(=O)OCc1ccccc1,MSETSRTAFGGRRAVPPNNSNAAEDDLPTVELQGVVPRGVNLQEFLNVTSVHLFKERWDTNKVDHHTDKYENNKLIVRRGQSFYVQIDFSRPYDPRRDLFRVEYVIGRYPQENKGTYIPVPIVSELQSGKWGAKIVMREDRSVRLSIQSSPKCIVGKFRMYVAVWTPYGVLRTSRNPETDTYILFNPWCEDDAVYLDNEKEREEYVLNDIGVIFYGEVNDIKTRSWSYGQFEDGILDTCLYVMDRAQMDLSGRGNPIKVSRVGSAMVNAKDDEGVLVGSWDNIYAYGVPPSAWTGSVDILLEYRSSENPVRYGQCWVFAGVFNTFLRCLGIPARIVTNYFSAHDNDANLQMDIFLEEDGNVNSKLTKDSVWNYHCWNEAWMTRPDLPVGFGGWQAVDSTPQENSDGMYRCGPASVQAIKHGHVCFQFDAPFVFAEVNSDLIYITAKKDGTHVVENVDATHIGKLIVTKQIGGDGMMDITDTYKFQEGQEEERLALETALMYGAKKPLNTEGVMKSRSNVDMDFEVENAVLGKDFKLSITFRNNSHNRYTITAYLSANITFYTGVPKAEFKKETFDVTLEPLSFKKEAVLIQAGEYMGQLLEQASLHFFVTARINETRDVLAKQKSTVLTIPEIIIKVRGTQVVGSDMTVTVQFTNPLKETLRNVWVHLDGPGVTRPMKKMFREIRPNSTVQWEEVCRPWVSGHRKLIASMSSDSLRHVYGELDVQIQRRPSM,4.0 +CC(=O)NCCc1c[nH]c2ccccc12,MSENGSFANCCEAGGWAVRPGWSGAGSARPSRTPRPPWVAPALSAVLIVTTAVDVVGNLLVILSVLRNRKLRNAGNLFLVSLALADLVVAFYPYPLILVAIFYDGWALGEEHCKASAFVMGLSVIGSVFNITAIAINRYCYICHSMAYHRIYRRWHTPLHICLIWLLTVVALLPNFFVGSLEYDPRIYSCTFIQTASTQYTAAVVVIHFLLPIAVVSFCYLRIWVLVLQARRKAKPESRLCLKPSDLRSFLTMFVVFVIFAICWAPLNCIGLAVAINPQEMAPQIPEGLFVTSYLLAYFNSCLNAIVYGLLNQNFRREYKRILLALWNPRHCIQDASKGSHAEGLQSPAPPIIGVQHQADAL,7.190036478285986 +CC1N(CCn2c1nnc2-c1nc(C)ns1)C(=O)c1ccc(Cl)cc1,MDNVLPVDSDLSPNISTNTSEPNQFVQPAWQIVLWAAAYTVIVVTSVVGNVVVMWIILAHKRMRTVTNYFLVNLAFAEASMAAFNTVVNFTYAVHNEWYYGLFYCKFHNFFPIAAVFASIYSMTAVAFDRYMAIIHPLQPRLSATATKVVICVIWVLALLLAFPQGYYSTTETMPSRVVCMIEWPEHPNKIYEKVYHICVTVLIYFLPLLVIGYAYTVVGITLWASEIPGDSSDRYHEQVSAKRKVVKMMIVVVCTFAICWLPFHIFFLLPYINPDLYLKKFIQQVYLAIMWLAMSSTMYNPIIYCCLNDRFRLGFKHAFRCCPFISAGDYEGLEMKSTRYLQTQGSVYKVSRLETTISTVVGAHEEEPEDGPKATPSSLDLTSNCSSRSDSKTMTESFSFSSNVLS,4.494850021680094 +Oc1cccc(c1)-c1oc2ccc(O)cc2c(=O)c1O,MVGSLNCIVAVSQNMGIGKNGDLPWPPLRNEFRYFQRMTTTSSVEGKQNLVIMGKKTWFSIPEKNRPLKGRINLVLSRELKEPPQGAHFLSRSLDDALKLTEQPELANKVDMVWIVGGSSVYKEAMNHPGHLKLFVTRIMQDFESDTFFPEIDLEKYKLLPEYPGVLSDVQEEKGIKYKFEVYEKND,4.301029995663981 +Oc1c(Br)cccc1C(=O)Nc1ccccc1,MNIRPLHDRVIVKRKEVETKSAGGIVLTGSAAAKSTRGEVLAVGNGRILENGEVKPLDVKVGDIVIFNDGYGVKSEKIDNEEVLIMSESDILAIVEA,4.0 +COc1nc(ccc1-c1cn[nH]c1)N1CC2(CCN(CC2)C(=O)CO)N(Cc2cccc(F)c2C)C1=O,MSRPPPTGKMPGAPETAPGDGAGASRQRKLEALIRDPRSPINVESLLDGLNSLVLDLDFPALRKNKNIDNFLNRYEKIVKKIRGLQMKAEDYDVVKVIGRGAFGEVQLVRHKASQKVYAMKLLSKFEMIKRSDSAFFWEERDIMAFANSPWVVQLFYAFQDDRYLYMVMEYMPGGDLVNLMSNYDVPEKWAKFYTAEVVLALDAIHSMGLIHRDVKPDNMLLDKHGHLKLADFGTCMKMDETGMVHCDTAVGTPDYISPEVLKSQGGDGFYGRECDWWSVGVFLYEMLVGDTPFYADSLVGTYSKIMDHKNSLCFPEDAEISKHAKNLICAFLTDREVRLGRNGVEEIRQHPFFKNDQWHWDNIRETAAPVVPELSSDIDSSNFDDIEDDKGDVETFPIPKAFVGNQLPFIGFTYYRENLLLSDSPSCRETDSIQSRKNEESQEIQKKLYTLEEHLSNEMQAKEELEQKCKSVNTRLEKTAKELEEEITLRKSVESALRQLEREKALLQHKNAEYQRKADHEADKKRNLENDVNSLKDQLEDLKKRNQNSQISTEKVNQLQRQLDETNALLRTESDTAARLRKTQAESSKQIQQLESNNRDLQDKNCLLETAKLKLEKEFINLQSALESERRDRTHGSEIINDLQGRICGLEEDLKNGKILLAKVELEKRQLQERFTDLEKEKSNMEIDMTYQLKVIQQSLEQEEAEHKATKARLADKNKIYESIEEAKSEAMKEMEKKLLEERTLKQKVENLLLEAEKRCSLLDCDLKQSQQKINELLKQKDVLNEDVRNLTLKIEQETQKRCLTQNDLKMQTQQVNTLKMSEKQLKQENNHLMEMKMNLEKQNAELRKERQDADGQMKELQDQLEAEQYFSTLYKTQVRELKEECEEKTKLGKELQQKKQELQDERDSLAAQLEITLTKADSEQLARSIAEEQYSDLEKEKIMKELEIKEMMARHKQELTEKDATIASLEETNRTLTSDVANLANEKEELNNKLKDVQEQLSRLKDEEISAAAIKAQFEKQLLTERTLKTQAVNKLAEIMNRKEPVKRGNDTDVRRKEKENRKLHMELKSEREKLTQQMIKYQKELNEMQAQIAEESQIRIELQMTLDSKDSDIEQLRSQLQALHIGLDSSSIGSGPGDAEADDGFPESRLEGWLSLPVRNNTKKFGWVKKYVIVSSKKILFYDSEQDKEQSNPYMVLDIDKLFHVRPVTQTDVYRADAKEIPRIFQILYANEGESKKEQEFPVEPVGEKSNYICHKGHEFIPTLYHFPTNCEACMKPLWHMFKPPPALECRRCHIKCHKDHMDKKEEIIAPCKVYYDISTAKNLLLLANSTEEQQKWVSRLVKKIPKKPPAPDPFARSSPRTSMKIQQNQSIRRPSRQLAPNKPS,8.522878745280337 +C[C@H](F)[C@H]1COC(=O)N1c1ccnc(N[C@@H](C)c2cnn(c2)-c2ccc(Cl)cc2)n1,GPGMSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGVVVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIVVYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAVVTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,7.481486060122112 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+NC(=N)NCCCCC(=O)Nc1ccc(C[C@H](NC(=O)[C@@H]2CCCCN2S(=O)(=O)c2ccccc2)C(O)=O)cc1,MAFPPRRRLRLGPRGLPLLLSGLLLPLCRAFNLDVDSPAEYSGPEGSYFGFAVDFFVPSASSRMFLLVGAPKANTTQPGIVEGGQVLKCDWSSTRRCQPIEFDATGNRDYAKDDPLEFKSHQWFGASVRSKQDKILACAPLYHWRTEMKQEREPVGTCFLQDGTKTVEYAPCRSQDIDADGQGFCQGGFSIDFTKADRVLLGGPGSFYWQGQLISDQVAEIVSKYDPNVYSIKYNNQLATRTAQAIFDDSYLGYSVAVGDFNGDGIDDFVSGVPRAARTLGMVYIYDGKNMSSLYNFTGEQMAAYFGFSVAATDINGDDYADVFIGAPLFMDRGSDGKLQEVGQVSVSLQRASGDFQTTKLNGFEVFARFGSAIAPLGDLDQDGFNDIAIAAPYGGEDKKGIVYIFNGRSTGLNAVPSQILEGQWAARSMPPSFGYSMKGATDIDKNGYPDLIVGAFGVDRAILYRARPVITVNAGLEVYPSILNQDNKTCSLPGTALKVSCFNVRFCLKADGKGVLPRKLNFQVELLLDKLKQKGAIRRALFLYSRSPSHSKNMTISRGGLMQCEELIAYLRDESEFRDKLTPITIFMEYRLDYRTAADTTGLQPILNQFTPANISRQAHILLDCGEDNVCKPKLEVSVDSDQKKIYIGDDNPLTLIVKAQNQGEGAYEAELIVSIPLQADFIGVVRNNEALARLSCAFKTENQTRQVVCDLGNPMKAGTQLLAGLRFSVHQQSEMDTSVKFDLQIQSSNLFDKVSPVVSHKVDLAVLAAVEIRGVSSPDHVFLPIPNWEHKENPETEEDVGPVVQHIYELRNNGPSSFSKAMLHLQWPYKYNNNTLLYILHYDIDGPMNCTSDMEINPLRIKISSLQTTEKNDTVAGQGERDHLITKRDLALSEGDIHTLGCGVAQCLKIVCQVGRLDRGKSAILYVKSLLWTETFMNKENQNHSYSLKSSASFNVIEFPYKNLPIEDITNSTLVTTNVTWGIQPAPMPVPVWVIILAVLAGLLLLAVLVFVMYRMGFFKRVRPPQEEQEREQLQPHENGEGNSET,5.3979400086720375 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+CS(=O)(=O)NCc1cccc(c1)-c1cc(-c2ccnn2C2CCOCC2)c2c(N)ncnn12,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,8.0 +CC(=O)N1CCC(CC1)n1c(NC(=O)c2ccc3cc4C(=O)NCCCn4c3c2)nc2ccccc12,MDLSMKKFAVRRFFSVYLRRKSRSKSSSLSRLEEEGVVKEIDISHHVKEGFEKADPSQFELLKVLGQGSYGKVFLVRKVKGSDAGQLYAMKVLKKATLKVRDRVRSKMERDILAEVNHPFIVKLHYAFQTEGKLYLILDFLRGGDLFTRLSKEVMFTEEDVKFYLAELALALDHLHSLGIIYRDLKPENILLDEEGHIKITDFGLSKEAIDHDKRAYSFCGTIEYMAPEVVNRRGHTQSADWWSFGVLMFEMLTGSLPFQGKDRKETMALILKAKLGMPQFLSGEAQSLLRALFKRNPCNRLGAGIDGVEEIKRHPFFVTIDWNTLYRKEIKPPFKPAVGRPEDTFHFDPEFTARTPTDSPGVPPSANAHHLFRGFSFVASSLIQEPSQQDLHKVPVHPIVQQLHGNNIHFTDGYEIKEDIGVGSYSVCKRCVHKATDTEYAVKIIDKSKRDPSEEIEILLRYGQHPNIITLKDVYDDGKFVYLVMELMRGGELLDRILRQRYFSEREASDVLCTITKTMDYLHSQGVVHRDLKPSNILYRDESGSPESIRVCDFGFAKQLRAGNGLLMTPCYTANFVAPEVLKRQGYDAACDIWSLGILLYTMLAGFTPFANGPDDTPEEILARIGSGKYALSGGNWDSISDAAKDVVSKMLHVDPHQRLTAMQVLKHPWVVNREYLSPNQLSRQDVHLVKGAMAATYFALNRTPQAPRLEPVLSSNLAQRRGMKRLTSTRL,7.236572006437062 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+Fc1ccc(cc1)-c1[nH]c(nc1-c1ccncc1)-c1ccc(Br)o1,MSQERPTFYRQELNKTIWEVPERYQNLSPVGSGAYGSVCAAFDTKTGLRVAVKKLSRPFQSIIHAKRTYRELRLLKHMKHENVIGLLDVFTPARSLEEFNDVYLVTHLMGADLNNIVKCQKLTDDHVQFLIYQILRGLKYIHSADIIHRDLKPSNLAVNEDCELKILDFGLARHTDDEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLTGRTLFPGTDHIDQLKLILRLVGTPGAELLKKISSESARNYIQSLTQMPKMNFANVFIGANPLAVDLLEKMLVLDSDKRITAAQALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES,6.721246399047171 +CC1(C)CCCN(CCNc2nc3CCCC(=O)c3s2)C1,MATTSTGPLHPYWPRHLRLDHFVPNDLSAWYIVTVLFTVFGALVVTMWLLSSRASVVPLGTWRRLSVCWFAVCAFVHLVIEGWFVLYQKAILGDQAFLSQLWKEYAKGDSRYIIEDNFIICMESITVVLWGPLSLWAVIAFLRQHPSRYVLQFVISLGQIYGDLLYFLTEYRDGFQHGEMGHPIYFWFYFFFMNVLWLVIPGVLFFDSVKQFYGAQNALDTKVMKSKGK,5.0 +NC(=O)c1cnc(N)c2cc(sc12)-c1ccc(cc1)N1CCOCC1,MPLRHWGMARGSKPVGDGAQPMAAMGGLKVLLHWAGPGGGEPWVTFSESSLTAEEVCIHIAHKVGITPPCFNLFALFDAQAQVWLPPNHILEIPRDASLMLYFRIRFYFRNWHGMNPREPAVYRCGPPGTEASSDQTAQGMQLLDPASFEYLFEQGKHEFVNDVASLWELSTEEEIHHFKNESLGMAFLHLCHLALRHGIPLEEVAKKTSFKDCIPRSFRRHIRQHSALTRLRLRNVFRRFLRDFQPGRLSQQMVMVKYLATLERLAPRFGTERVPVCHLRLLAQAEGEPCYIRDSGVAPTDPGPESAAGPPTHEVLVTGTGGIQWWPVEEEVNKEEGSSGSSGRNPQASLFGKKAKAHKAVGQPADRPREPLWAYFCDFRDITHVVLKEHCVSIHRQDNKCLELSLPSRAAALSFVSLVDGYFRLTADSSHYLCHEVAPPRLVMSIRDGIHGPLLEPFVQAKLRPEDGLYLIHWSTSHPYRLILTVAQRSQAPDGMQSLRLRKFPIEQQDGAFVLEGWGRSFPSVRELGAALQGCLLRAGDDCFSLRRCCLPQPGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASDPTVFHKRYLKKIRDLGEGHFGKVSLYCYDPTNDGTGEMVAVKALKADCGPQHRSGWKQEIDILRTLYHEHIIKYKGCCEDQGEKSLQLVMEYVPLGSLRDYLPRHSIGLAQLLLFAQQICEGMAYLHAQHYIHRDLAARNVLLDNDRLVKIGDFGLAKAVPEGHEYYRVREDGDSPVFWYAPECLKEYKFYYASDVWSFGVTLYELLTHCDSSQSPPTKFLELIGIAQGQMTVLRLTELLERGERLPRPDKCPCEVYHLMKNCWETEASFRPTFENLIPILKTVHEKYQGQAPSVFSVC,4.6020599913279625 +COc1ccccc1N1CCN(CCCCNS(=O)(=O)c2ccc(F)cc2)CC1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,7.142667503568731 +CC(=N)NCC(F)(F)CC[C@H](N)C(O)=O,MEDHMFGVQQIQPNVISVRLFKRKVGGLGFLVKERVSKPPVIISDLIRGGAAEQSGLIQAGDIILAVNGRPLVDLSYDSALEVLRGIASETHVVLILRGPEGFTTHLETTFTGDGTPKTIRVTQPLGPPTKAVDLSHQPPAGKEQPLAVDGASGPGNGPQHAYDDGQEAGSLPHANGLAPRPPGQDPAKKATRVSLQGRGENNELLKEIEPVLSLLTSGSRGVKGGAPAKAEMKDMGIQVDRDLDGKSHKPLPLGVENDRVFNDLWGKGNVPVVLNNPYSEKEQPPTSGKQSPTKNGSPSKCPRFLKVKNWETEVVLTDTLHLKSTLETGCTEYICMGSIMHPSQHARRPEDVRTKGQLFPLAKEFIDQYYSSIKRFGSKAHMERLEEVNKEIDTTSTYQLKDTELIYGAKHAWRNASRCVGRIQWSKLQVFDARDCTTAHGMFNYICNHVKYATNKGNLRSAITIFPQRTDGKHDFRVWNSQLIRYAGYKQPDGSTLGDPANVQFTEICIQQGWKPPRGRFDVLPLLLQANGNDPELFQIPPELVLEVPIRHPKFEWFKDLGLKWYGLPAVSNMLLEIGGLEFSACPFSGWYMGTEIGVRDYCDNSRYNILEEVAKKMNLDMRKTSSLWKDQALVEINIAVLYSFQSDKVTIVDHHSATESFIKHMENEYRCRGGCPADWVWIVPPMSGSITPVFHQEMLNYRLTPSFEYQPDPWNTHVWKGTNGTPTKRRAIGFKKLAEAVKFSAKLMGQAMAKRVKATILYATETGKSQAYAKTLCEIFKHAFDAKVMSMEEYDIVHLEHETLVLVVTSTFGNGDPPENGEKFGCALMEMRHPNSVQEERKSYKVRFNSVSSYSDSQKSSGDGPDLRDNFESAGPLANVRFSVFGLGSRAYPHFCAFGHAVDTLLEELGGERILKMREGDELCGQEEAFRTWAKKVFKAACDVFCVGDDVNIEKANNSLISNDRSWKRNKFRLTFVAEAPELTQGLSNVHKKRVSAARLLSRQNLQSPKSSRSTIFVRLHTNGSQELQYQPGDHLGVFPGNHEDLVNALIERLEDAPPVNQMVKVELLEERNTALGVISNWTDELRLPPCTIFQAFKYYLDITTPPTPLQLQQFASLATSEKEKQRLLVLSKGLQEYEEWKWGKNPTIVEVLEEFPSIQMPATLLLTQLSLLQPRYYSISSSPDMYPDEVHLTVAIVSYRTRDGEGPIHHGVCSSWLNRIQADELVPCFVRGAPSFHLPRNPQVPCILVGPGTGIAPFRSFWQQRQFDIQHKGMNPCPMVLVFGCRQSKIDHIYREETLQAKNKGVFRELYTAYSREPDKPKKYVQDILQEQLAESVYRALKEQGGHIYVCGDVTMAADVLKAIQRIMTQQGKLSAEDAGVFISRMRDDNRYHEDIFGVTLRTYEVTNRLRSESIAFIEESKKDTDEVFSS,4.471083299722345 +CC[C@@]1(C)CCC[C@@]2(C)[C@H]1CC[C@]1(C)[C@@H]2C[C@H](OC(=O)CC(O)C(C)C)[C@]2(C)C=C([C@H](O)C[C@@H]12)C(C)=O,MAALGGDGLRLLSVSRPERPPESAALGGLGPGLCCWVSVFSCLSLACSYVGSLYVWKSELPRDHPAVIKRRFTSVLVVSSLSPLCVLLWRELTGIQPGTSLLTLMGFRLEGIFPAALLPLLLTMILFLGPLMQLSMDCPCDLADGLKVVLAPRSWARCLTDMRWLRNQVIAPLTEELVFRACMLPMLAPCMGLGPAVFTCPLFFGVAHFHHIIEQLRFRQSSVGNIFLSAAFQFSYTAVFGAYTAFLFIRTGHLIGPVLCHSFCNYMGFPAVCAALEHPQRRPLLAGYALGVGLFLLLLQPLTDPKLYGSLPLCVLLERAGDSEAPLCS,4.133712660915805 +CC(Oc1cncc(n1)-c1c[nH]c2ccc(cc12)-c1nnc(N)s1)C(F)(F)F,MLLSKINSLAHLRAAPCNDLHATKLAPGKEKEPLESQYQVGPLLGSGGFGSVYSGIRVSDNLPVAIKHVEKDRISDWGELPNGTRVPMEVVLLKKVSSGFSGVIRLLDWFERPDSFVLILERPEPVQDLFDFITERGALQEELARSFFWQVLEAVRHCHNCGVLHRDIKDENILIDLNRGELKLIDFGSGALLKDTVYTDFDGTRVYSPPEWIRYHRYHGRSAAVWSLGILLYDMVCGDIPFEHDEEIIRGQVFFRQRVSSECQHLIRWCLALRPSDRPTFEEIQNHPWMQDVLLPQETAEIHLHSLSPGPSK,7.611153106400489 +Fc1cccc2[C@@H](CCOc12)n1c2nc(ncc2[nH]c1=O)-n1cnc2ccc(cc12)C#N,MAPPSEETPLIPQRSCSLLSTEAGALHVLLPARGPGPPQRLSFSFGDHLAEDLCVQAAKASGILPVYHSLFALATEDLSCWFPPSHIFSVEDASTQVLLYRIRFYFPNWFGLEKCHRFGLRKDLASAILDLPVLEHLFAQHRSDLVSGRLPVGLSLKEQGECLSLAVLDLARMAREQAQRPGELLKTVSYKACLPPSLRDLIQGLSFVTRRRIRRTVRRALRRVAACQADRHSLMAKYIMDLERLDPAGAAETFHVGLPGALGGHDGLGLLRVAGDGGIAWTQGEQEVLQPFCDFPEIVDISIKQAPRVGPAGEHRLVTVTRTDNQILEAEFPGLPEALSFVALVDGYFRLTTDSQHFFCKEVAPPRLLEEVAEQCHGPITLDFAINKLKTGGSRPGSYVLRRSPQDFDSFLLTVCVQNPLGPDYKGCLIRRSPTGTFLLVGLSRPHSSLRELLATCWDGGLHVDGVAVTLTSCCIPRPKEKSNLIVVQRGHSPPTSSLVQPQSQYQLSQMTFHKIPADSLEWHENLGHGSFTKIYRGCRHEVVDGEARKTEVLLKVMDAKHKNCMESFLEAASLMSQVSYRHLVLLHGVCMAGDSTMVQEFVHLGAIDMYLRKRGHLVPASWKLQVVKQLAYALNYLEDKGLPHGNVSARKVLLAREGADGSPPFIKLSDPGVSPAVLSLEMLTDRIPWVAPECLREAQTLSLEADKWGFGATVWEVFSGVTMPISALDPAKKLQFYEDRQQLPAPKWTELALLIQQCMAYEPVQRPSFRAVIRDLNSLISSDYELLSDPTPGALAPRDGLWNGAQLYACQDPTIFEERHLKYISQLGKGNFGSVELCRYDPLGDNTGALVAVKQLQHSGPDQQRDFQREIQILKALHSDFIVKYRGVSYGPGRQSLRLVMEYLPSGCLRDFLQRHRARLDASRLLLYSSQICKGMEYLGSRRCVHRDLAARNILVESEAHVKIADFGLAKLLPLDKDYYVVREPGQSPIFWYAPESLSDNIFSRQSDVWSFGVVLYELFTYCDKSCSPSAEFLRMMGCERDVPALCRLLELLEEGQRLPAPPACPAEVHELMKLCWAPSPQDRPSFSALGPQLDMLWSGSRGCETHAFTAHPEGKHHSLSFS,9.0 +Oc1ccc(cc1)-c1[nH]c2nccnc2c1CC1CC1,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDMWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASPPANATAASDTNAGDRGQTNNAASASASNST,5.522878745280337 +COc1cc(OC)cc(c1)-c1nc2nc(N)nc(N)c2[nH]1,MVRPLNCIVAVSQNMGIGKNGDLPWPLLRNEFKYFQRMTTTSSVEGKQNLVIMGRKTWFSIPEKNRPLKDRINIVLSRELKEPPQGAHFLAKSLDDALKLIEQPELASKVDMVWVVGGSSVYQEAMNQPGHLRLFVTRIMQEFESDTFFPEIDLEKYKLLPEYPGVLSEIQEEKGIKYKFEVYEKKD,4.489454989793388 +CC(C)(C)n1nc(c(C(N)=O)c1N)-c1cnc2ccccc2c1,MGQQESTLGGAAGEPRSRGHAAGTSGGPGDHLHATPGMFVQHSTAIFSDRYKGQRVLGKGSFGEVILCKDKITGQECAVKVISKRQVKQKTDKESLLREVQLLKQLDHPNIMKLYEFFEDKGYFYLVGEVYTGGELFDEIISRKRFSEVDAARIIRQVLSGITYMHKNKIVHRDLKPENLLLESKSKDANIRIIDFGLSTHFEASKKMKDKIGTAYYIAPEVLHGTYDEKCDVWSTGVILYILLSGCPPFNGANEYDILKKVEKGKYTFELPQWKKVSESAKDLIRKMLTYVPSMRISARDALDHEWIQTYTKEQISVDVPSLDNAILNIRQFQGTQKLAQAALLYMGSKLTSQDETKELTAIFHKMDKNGDGQLDRAELIEGYKELMRMKGQDASMLDASAVEHEVDQVLDAVDFDKNGYIEYSEFVTVAMDRKTLLSRERLERAFRMFDSDNSGKISSTELATIFGVSDVDSETWKSVLSEVDKNNDGEVDFDEFQQMLLKLCGN,8.221848749616356 +Cc1c(\C=C2/C(=O)Nc3ccc(F)cc23)[nH]c2CCCN(CCN3CCOCC3)C(=O)c12,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,7.443697499232712 +NC(=O)c1ccc(F)c2OCC(Cc12)N(CCCCc1c[nH]c2ccc(F)cc12)C1CCC1,METTPLNSQKVLSECKDREDCQENGVLQKGVPTTADRAEPSQISNGYSAVPSTSAGDEASHSIPAATTTLVAEIRQGERETWGKKMDFLLSVIGYAVDLGNIWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIIAWALYYLISSLTDRLPWTSCTNSWNTGNCTNYFAQDNITWTLHSTSPAEEFYLRHVLQIHQSKGLQDLGTISWQLTLCIVLIFTVIYFSIWKGVKTSGKVVWVTATFPYIVLSVLLVRGATLPGAWRGVVFYLKPNWQKLLETGVWVDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHIWAKRREWFVLIVVITCVLGSLLTLTSGGAYVVTLLEEYATGPAVLTVALIEAVAVSWFYGITQFCSDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPHWSIVLGYCIGMSSVICIPTYIIYRLISTPGTLKERIIKSITPETPTEIPCGDIRMNAV,7.982966660701219 +C[C@H]1Cn2c(nnc2C(=O)N1Cc1cccc(c1Cl)C(F)(F)F)C1CCCCC1,MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY,6.115771230367396 +COc1ccc(NC(=O)Nc2nnc(SCc3cc(=O)n4cccc(C)c4n3)s2)cc1OC,MLRGGRRGQLGWHSWAAGPGSLLAWLILASAGAAPCPDACCPHGSSGLRCTRDGALDSLHHLPGAENLTELYIENQQHLQHLELRDLRGLGELRNLTIVKSGLRFVAPDAFHFTPRLSRLNLSFNALESLSWKTVQGLSLQELVLSGNPLHCSCALRWLQRWEEEGLGGVPEQKLQCHGQGPLAHMPNASCGVPTLKVQVPNASVDVGDDVLLRCQVEGRGLEQAGWILTELEQSATVMKSGGLPSLGLTLANVTSDLNRKNVTCWAENDVGRAEVSVQVNVSFPASVQLHTAVEMHHWCIPFSVDGQPAPSLRWLFNGSVLNETSFIFTEFLEPAANETVRHGCLRLNQPTHVNNGNYTLLAANPFGQASASIMAAFMDNPFEFNPEDPIPVSFSPVDTNSTSGDPVEKKDETPFGVSVAVGLAVFACLFLSTLLLVLNKCGRRNKFGINRPAVLAPEDGLAMSLHFMTLGGSSLSPTEGKGSGLQGHIIENPQYFSDACVHHIKRRDIVLKWELGEGAFGKVFLAECHNLLPEQDKMLVAVKALKEASESARQDFQREAELLTMLQHQHIVRFFGVCTEGRPLLMVFEYMRHGDLNRFLRSHGPDAKLLAGGEDVAPGPLGLGQLLAVASQVAAGMVYLAGLHFVHRDLATRNCLVGQGLVVKIGDFGMSRDIYSTDYYRVGGRTMLPIRWMPPESILYRKFTTESDVWSFGVVLWEIFTYGKQPWYQLSNTEAIDCITQGRELERPRACPPEVYAIMRGCWQREPQQRHSIKDVHARLQALAQAPPVYLDVLG,5.0 +C[C@H](Nc1ncnc(N)c1C#N)c1nc2c(Cl)ccc(Cl)c2c(=O)n1-c1cccc(NC(=O)NCCCO)c1,MAGPEGFQYRALYPFRRERPEDLELLPGDVLVVSRAALQALGVAEGGERCPQSVGWMPGLNERTRQRGDFPGTYVEFLGPVALARPGPRPRGPRPLPARPRDGAPEPGLTLPDLPEQFSPPDVAPPLLVKLVEAIERTGLDSESHYRPELPAPRTDWSLSDVDQWDTAALADGIKSFLLALPAPLVTPEASAEARRALREAAGPVGPALEPPTLPLHRALTLRFLLQHLGRVASRAPALGPAVRALGATFGPLLLRAPPPPSSPPPGGAPDGSEPSPDFPALLVEKLLQEHLEEQEVAPPALPPKPPKAKPASTVLANGGSPPSLQDAEWYWGDISREEVNEKLRDTPDGTFLVRDASSKIQGEYTLTLRKGGNNKLIKVFHRDGHYGFSEPLTFCSVVDLINHYRHESLAQYNAKLDTRLLYPVSKYQQDQIVKEDSVEAVGAQLKVYHQQYQDKSREYDQLYEEYTRTSQELQMKRTAIEAFNETIKIFEEQGQTQEKCSKEYLERFRREGNEKEMQRILLNSERLKSRIAEIHESRTKLEQQLRAQASDNREIDKRMNSLKPDLMQLRKIRDQYLVWLTQKGARQKKINEWLGIKNETEDQYALMEDEDDLPHHEERTWYVGKINRTQAEEMLSGKRDGTFLIRESSQRGCYACSVVVDGDTKHCVIYRTATGFGFAEPYNLYGSLKELVLHYQHASLVQHNDALTVTLAHPVRAPGPGPPPAAR,4.5376020021010435 +COc1ccc(c(OC)c1)-c1cnc2[nH]cc(-c3ccc(OC)c(OC)c3)c2c1,MRGARGAWDFLCVLLLLLRVQTGSSQPSVSPGEPSPPSIHPGKSDLIVRVGDEIRLLCTDPGFVKWTFEILDETNENKQNEWITEKAEATNTGKYTCTNKHGLSNSIYVFVRDPAKLFLVDRSLYGKEDNDTLVRCPLTDPEVTNYSLKGCQGKPLPKDLRFIPDPKAGIMIKSVKRAYHRLCLHCSVDQEGKSVLSEKFILKVRPAFKAVPVVSVSKASYLLREGEEFTVTCTIKDVSSSVYSTWKRENSQTKLQEKYNSWHHGDFNYERQATLTISSARVNDSGVFMCYANNTFGSANVTTTLEVVDKGFINIFPMINTTVFVNDGENVDLIVEYEAFPKPEHQQWIYMNRTFTDKWEDYPKSENESNIRYVSELHLTRLKGTEGGTYTFLVSNSDVNAAIAFNVYVNTKPEILTYDRLVNGMLQCVAAGFPEPTIDWYFCPGTEQRCSASVLPVDVQTLNSSGPPFGKLVVQSSIDSSAFKHNGTVECKAYNDVGKTSAYFNFAFKGNNKEQIHPHTLFTPLLIGFVIVAGMMCIIVMILTYKYLQKPMYEVQWKVVEEINGNNYVYIDPTQLPYDHKWEFPRNRLSFGKTLGAGAFGKVVEATAYGLIKSDAAMTVAVKMLKPSAHLTEREALMSELKVLSYLGNHMNIVNLLGACTIGGPTLVITEYCCYGDLLNFLRRKRDSFICSKQEDHAEAALYKNLLHSKESSCSDSTNEYMDMKPGVSYVVPTKADKRRSVRIGSYIERDVTPAIMEDDELALDLEDLLSFSYQVAKGMAFLASKNCIHRDLAARNILLTHGRITKICDFGLARDIKNDSNYVVKGNARLPVKWMAPESIFNCVYTFESDVWSYGIFLWELFSLGSSPYPGMPVDSKFYKMIKEGFRMLSPEHAPAEMYDIMKTCWDADPLKRPTFKQIVQLIEKQISESTNHIYSNLANCSPNRQKPVVDHSVRINSVGSTASSSQPLLVHDDV,5.262807357295262 +NC(=O)C1(CCCCC1)NC(=O)[C@H](CCCC(O)=O)NC(=O)[C@H](CCCCNC(=O)\C=C\c1cccnc1)NC(=O)CCc1ccc(Nc2nc3ccccc3[nH]2)cc1,MFPTESAWLGKRGANPGPEAAVRETVMLLLCLGVPTGRPYNVDTESALLYQGPHNTLFGYSVVLHSHGANRWLLVGAPTANWLANASVINPGAIYRCRIGKNPGQTCEQLQLGSPNGEPCGKTCLEERDNQWLGVTLSRQPGENGSIVTCGHRWKNIFYIKNENKLPTGGCYGVPPDLRTELSKRIAPCYQDYVKKFGENFASCQAGISSFYTKDLIVMGAPGSSYWTGSLFVYNITTNKYKAFLDKQNQVKFGSYLGYSVGAGHFRSQHTTEVVGGAPQHEQIGKAYIFSIDEKELNILHEMKGKKLGSYFGASVCAVDLNADGFSDLLVGAPMQSTIREEGRVFVYINSGSGAVMNAMETNLVGSDKYAARFGESIVNLGDIDNDGFEDVAIGAPQEDDLQGAIYIYNGRADGISSTFSQRIEGLQISKSLSMFGQSISGQIDADNNGYVDVAVGAFRSDSAVLLRTRPVVIVDASLSHPESVNRTKFDCVENGWPSVCIDLTLCFSYKGKEVPGYIVLFYNMSLDVNRKAESPPRFYFSSNGTSDVITGSIQVSSREANCRTHQAFMRKDVRDILTPIQIEAAYHLGPHVISKRSTEEFPPLQPILQQKKEKDIMKKTINFARFCAHENCSADLQVSAKIGFLKPHENKTYLAVGSMKTLMLNVSLFNAGDDAYETTLHVKLPVGLYFIKILELEEKQINCEVTDNSGVVQLDCSIGYIYVDHLSRIDISFLLDVSSLSRAEEDLSITVHATCENEEEMDNLKHSRVTVAIPLKYEVKLTVHGFVNPTSFVYGSNDENEPETCMVEKMNLTFHVINTGNSMAPNVSVEIMVPNSFSPQTDKLFNILDVQTTTGECHFENYQRVCALEQQKSAMQTLKGIVRFLSKTDKRLLYCIKADPHCLNFLCNFGKMESGKEASVHIQLEGRPSILEMDETSALKFEIRATGFPEPNPRVIELNKDENVAHVLLEGLHHQRPKRYFTIVIISSSLLLGLIVLLLISYVMWKAGFFKRQYKSILQEENRRDSWSYINSKSNDD,6.46344155742847 +Nc1ncnc2ccc(cc12)-c1ccc(CNc2ncccc2C(=O)NCc2cccc(F)c2F)s1,MDGTAAEPRPGAGSLQHAQPPPQPRKKRPEDFKFGKILGEGSFSTVVLARELATSREYAIKILEKRHIIKENKVPYVTRERDVMSRLDHPFFVKLYFTFQDDEKLYFGLSYAKNGELLKYIRKIGSFDETCTRFYTAEIVSALEYLHGKGIIHRDLKPENILLNEDMHIQITDFGTAKVLSPESKQARANSFVGTAQYVSPELLTEKSACKSSDLWALGCIIYQLVAGLPPFRAGNEYLIFQKIIKLEYDFPEKFFPKARDLVEKLLVLDATKRLGCEEMEGYGPLKAHPFFESVTWENLHQQTPPKLT,6.259637310505756 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+Fc1ccc(C(=O)N2[C@H]3CC[C@@H]2c2nnc(-c4cscn4)n2C3)c(Cl)c1C(F)(F)F,MPACCSWNDVLQYETNKVTRIQSTNYGTVKWVLHMIVFSYISFALVSDKLYQRKEPVISSVHTKVKGIAEVTENVTEGGVTKLGHSIFDTADYTFPLQGNSFFVMTNYVKSEGQVQTLCPEYPRRGAQCSSDRRCKKGWMDPQSKGIQTGRCVPYDKTRKTCEVSAWCPTEEEKEAPRPALLRSAENFTVLIKNNIHFPGHNYTTRNILPTMNGSCTFHKTWDPQCSIFRLGDIFQEAGENFTEVAVQGGIMGIEIYWDCNLDSWSHHCRPRYSFRRLDDKNTDESFVPGYNFRYAKYYKENNVEKRTLIKAFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLLINTYSSAFCRSGVYPYCKCCEPCTVNEYYYRKKCESIMEPKPTLKYVSFVDEPHIRMVDQQLLGKSLQVVKGQEVPRPQMDFSDLSRLSLSLHDSPLTPGQSEEIQLLHEEVAPKSGDSPSWCQCGNCLPSRLPEQRRALEELCCRRKPGRCITTSKLFHKLVLSRDTLQLLLLYQDPLLVLGEEATNSRLRHRAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKTEGQYSGFKYPY,6.882728704344236 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+Clc1ccc(COc2ccc(cc2)-c2cc([nH]n2)C(=O)N\N=C\c2c[nH]c3ccccc23)cc1,MVFLPLKWSLATMSFLLSSLLALLTVSTPSWCQSTEASPKRSDGTPFPWNKIRLPEYVIPVHYDLLIHANLTTLTFWGTTKVEITASQPTSTIILHSHHLQISRATLRKGAGERLSEEPLQVLEHPRQEQIALLAPEPLLVGLPYTVVIHYAGNLSETFHGFYKSTYRTKEGELRILASTQFEPTAARMAFPCFDEPAFKASFSIKIRREPRHLAISNMPLVKSVTVAEGLIEDHFDVTVKMSTYLVAFIISDFESVSKITKSGVKVSVYAVPDKINQADYALDAAVTLLEFYEDYFSIPYPLPKQDLAAIPDFQSGAMENWGLTTYRESALLFDAEKSSASSKLGITMTVAHELAHQWFGNLVTMEWWNDLWLNEGFAKFMEFVSVSVTHPELKVGDYFFGKCFDAMEVDALNSSHPVSTPVENPAQIREMFDDVSYDKGACILNMLREYLSADAFKSGIVQYLQKHSYKNTKNEDLWDSMASICPTDGVKGMDGFCSRSQHSSSSSHWHQEGVDVKTMMNTWTLQKGFPLITITVRGRNVHMKQEHYMKGSDGAPDTGYLWHVPLTFITSKSDMVHRFLLKTKTDVLILPEEVEWIKFNVGMNGYYIVHYEDDGWDSLTGLLKGTHTAVSSNDRASLINNAFQLVSIGKLSIEKALDLSLYLKHETEIMPVFQGLNELIPMYKLMEKRDMNEVETQFKAFLIRLLRDLIDKQTWTDEGSVSERMLRSQLLLLACVHNYQPCVQRAEGYFRKWKESNGNLSLPVDVTLAVFAVGAQSTEGWDFLYSKYQFSLSSTEKSQIEFALCRTQNKEKLQWLLDESFKGDKIKTQEFPQILTLIGRNPVGYPLAWQFLRKNWNKLVQKFELGSSSIAHMVMGTTNQFSTRTRLEEVKGFFSSLKENGSQLRCVQQTIETIEENIGWMDKNFDKIRVWLQSEKLERM,4.7447274948966935 +CC(C)[C@@H]1N(Cc2ccc(cc2)C(F)(F)F)Cc2cc(cnc12)C(=O)NCc1ccc(cc1)C#N,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,7.0 +CNC1CCN(CC1)c1nc2ccccc2n1Cc1ccc(F)cc1,MNTSAPPAVSPNITVLAPGKGPWQVAFIGITTGLLSLATVTGNLLVLISFKVNTELKTVNNYFLLSLACADLIIGTFSMNLYTTYLLMGHWALGTLACDLWLALDYVASNASVMNLLLISFDRYFSVTRPLSYRAKRTPRRAALMIGLAWLVSFVLWAPAILFWQYLVGERTVLAGQCYIQFLSQPIITFGTAMAAFYLPVTVMCTLYWRIYRETENRARELAALQGSETPGKGGGSSSSSERSQPGAEGSPETPPGRCCRCCRAPRLLQAYSWKEEEEEDEGSMESLTSSEGEEPGSEVVIKMPMVDPEAQAPTKQPPRSSPNTVKRPTKKGRDRAGKGQKPRGKEQLAKRKTFSLVKEKKAARTLSAILLAFILTWTPYNIMVLVSTFCKDCVPETLWELGYWLCYVNSTINPMCYALCNKAFRDTFRLLLLCRWDKRRWRKIPKRPGSVHRTPSRQC,6.005243055412372 +OC(=O)C(F)(F)F.OC(=O)C(F)(F)F.OC(=O)C(F)(F)F.CC[C@H](C)[C@H](NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@@H](NC(=O)[C@H](CCCN\C(N)=N\C(=O)NCCCCNC(=O)CC)NC(=O)[C@@H](N)CC(O)=O)C(C)C)C(=O)N[C@@H](Cc1cnc[nH]1)C(=O)N1CCC[C@H]1C(=O)N[C@@H](Cc1ccccc1)C(O)=O,MILNSSTEDGIKRIQDDCPKAGRHNYIFVMIPTLYSIIFVVGIFGNSLVVIVIYFYMKLKTVASVFLLNLALADLCFLLTLPLWAVYTAMEYRWPFGNYLCKIASASVSFNLYASVFLLTCLSIDRYLAIVHPMKSRLRRTMLVAKVTCIIIWLLAGLASLPAIIHRNVFFIENTNITVCAFHYESQNSTLPIGLGLTKNILGFLFPFLIILTSYTLIWKALKKAYEIQKNKPRNDDIFKIIMAIVLFFFFSWIPHQIFTFLDVLIQLGIIRDCRIADIVDTAMPITICIAYFNNCLNPLFYGFLGKKFKRYFLQLLKYIPPKAKSHSNLSTKMSTLSYRPSDNVSSSTKKPAPCFEVE,8.657577319177793 +CN1CC[C@@](O)(C#Cc2cccc(c2)-c2cccc(c2)C(N)=O)C1=O,MAVMEMACPGAPGSAVGQQKELPKAKEKTPPLGKKQSSVYKLEAVEKSPVFCGKWEILNDVITKGTAKEGSEAGPAAISIIAQAECENSQEFSPTFSERIFIAGSKQYSQSESLDQIPNNVAHATEGKMARVCWKGKRRSKARKKRKKKSSKSLAHAGVALAKPLPRTPEQESCTIPVQEDESPLGAPYVRNTPQFTKPLKEPGLGQLCFKQLGEGLRPALPRSELHKLISPLQCLNHVWKLHHPQDGGPLPLPTHPFPYSRLPHPFPFHPLQPWKPHPLESFLGKLACVDSQKPLPDPHLSKLACVDSPKPLPGPHLEPSCLSRGAHEKFSVEEYLVHALQGSVSSGQAHSLTSLAKTWAARGSRSREPSPKTEDNEGVLLTEKLKPVDYEYREEVHWATHQLRLGRGSFGEVHRMEDKQTGFQCAVKKVRLEVFRAEELMACAGLTSPRIVPLYGAVREGPWVNIFMELLEGGSLGQLVKEQGCLPEDRALYYLGQALEGLEYLHSRRILHGDVKADNVLLSSDGSHAALCDFGHAVCLQPDGLGKSLLTGDYIPGTETHMAPEVVLGRSCDAKVDVWSSCCMMLHMLNGCHPWTQFFRGPLCLKIASEPPPVREIPPSCAPLTAQAIQEGLRKEPIHRVSAAELGGKVNRALQQVGGLKSPWRGEYKEPRHPPPNQANYHQTLHAQPRELSPRAPGPRPAEETTGRAPKLQPPLPPEPPEPNKSPPLTLSKEESGMWEPLPLSSLEPAPARNPSSPERKATVPEQELQQLEIELFLNSLSQPFSLEEQEQILSCLSIDSLSLSDDSEKNPSKASQSSRDTLSSGVHSWSSQAEARSSSWNMVLARGRPTDTPSYFNGVKVQIQSLNGEHLHIREFHRVKVGDIATGISSQIPAAAFSLVTKDGQPVRYDMEVPDSGIDLQCTLAPDGSFAWSWRVKHGQLENRP,7.167491087293763 +C[C@H]1CN(C[C@@H](C)O1)C1CCN(CC1)c1cc(C)c2nc([nH]c2c1)-c1c(NC[C@@H](O)c2cccc(Cl)c2)cc[nH]c1=O,MALIPDLAMETWLLLAVSLVLLYLYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIAEDEEWKRLRSLLSPTFTSGKLKEMVPIIAQYGDVLVRNLRREAETGKPVTLKDVFGAYSMDVITSTSFGVNIDSLNNPQDPFVENTKKLLRFDFLDPFFLSITVFPFLIPILEVLNICVFPREVTNFLRKSVKRMKESRLEDTQKHRVDFLQLMIDSQNSKETESHKALSDLELVAQSIIFIFAGYETTSSVLSFIMYELATHPDVQQKLQEEIDAVLPNKAPPTYDTVLQMEYLDMVVNETLRLFPIAMRLERVCKKDVEINGMFIPKGVVVMIPSYALHRDPKYWTEPEKFLPERFSKKNKDNIDPYIYTPFGSGPRNCIGMRFALMNMKLALIRVLQNFSFKPCKETQIPLKLSLGGLLQPEKPVVLKVESRDGTVSGA,8.508638306165727 +CS(=O)(=O)c1ccc(cc1)-c1nc(NCc2ccncc2)cc(n1)C(F)(F)F,MLARALLLCAVLALSHTANPCCSHPCQNRGVCMSVGFDQYKCDCTRTGFYGENCSTPEFLTRIKLFLKPTPNTVHYILTHFKGFWNVVNNIPFLRNAIMSYVLTSRSHLIDSPPTYNADYGYKSWEAFSNLSYYTRALPPVPDDCPTPLGVKGKKQLPDSNEIVEKLLLRRKFIPDPQGSNMMFAFFAQHFTHQFFKTDHKRGPAFTNGLGHGVDLNHIYGETLARQRKLRLFKDGKMKYQIIDGEMYPPTVKDTQAEMIYPPQVPEHLRFAVGQEVFGLVPGLMMYATIWLREHNRVCDVLKQEHPEWGDEQLFQTSRLILIGETIKIVIEDYVQHLSGYHFKLKFDPELLFNKQFQYQNRIAAEFNTLYHWHPLLPDTFQIHDQKYNYQQFIYNNSILLEHGITQFVESFTRQIAGRVAGGRNVPPAVQKVSQASIDQSRQMKYQSFNEYRKRFMLKPYESFEELTGEKEMSAELEALYGDIDAVELYPALLVEKPRPDAIFGETMVEVGAPFSLKGLMGNVICSPAYWKPSTFGGEVGFQIINTASIQSLICNNVKGCPFTSFSVPDPELIKTVTINASSSRSGLDDINPTVLLKERSTEL,2.47494002533119 +COCC1(CCN(CC1)c1nccc(Nc2cc3n(C(C)C)c(C)nc3cn2)n1)OC,MELAALCRWGLLLALLPPGAASTQVCTGTDMKLRLPASPETHLDMLRHLYQGCQVVQGNLELTYLPTNASLSFLQDIQEVQGYVLIAHNQVRQVPLQRLRIVRGTQLFEDNYALAVLDNGDPLNNTTPVTGASPGGLRELQLRSLTEILKGGVLIQRNPQLCYQDTILWKDIFHKNNQLALTLIDTNRSRACHPCSPMCKGSRCWGESSEDCQSLTRTVCAGGCARCKGPLPTDCCHEQCAAGCTGPKHSDCLACLHFNHSGICELHCPALVTYNTDTFESMPNPEGRYTFGASCVTACPYNYLSTDVGSCTLVCPLHNQEVTAEDGTQRCEKCSKPCARVCYGLGMEHLREVRAVTSANIQEFAGCKKIFGSLAFLPESFDGDPASNTAPLQPEQLQVFETLEEITGYLYISAWPDSLPDLSVFQNLQVIRGRILHNGAYSLTLQGLGISWLGLRSLRELGSGLALIHHNTHLCFVHTVPWDQLFRNPHQALLHTANRPEDECVGEGLACHQLCARGHCWGPGPTQCVNCSQFLRGQECVEECRVLQGLPREYVNARHCLPCHPECQPQNGSVTCFGPEADQCVACAHYKDPPFCVARCPSGVKPDLSYMPIWKFPDEEGACQPCPINCTHSCVDLDDKGCPAEQRASPLTSIISAVVGILLVVVLGVVFGILIKRRQQKIRKYTMRRLLQETELVEPLTPSGAMPNQAQMRILKETELRKVKVLGSGAFGTVYKGIWIPDGENVKIPVAIKVLRENTSPKANKEILDEAYVMAGVGSPYVSRLLGICLTSTVQLVTQLMPYGCLLDHVRENRGRLGSQDLLNWCMQIAKGMSYLEDVRLVHRDLAARNVLVKSPNHVKITDFGLARLLDIDETEYHADGGKVPIKWMALESILRRRFTHQSDVWSYGVTVWELMTFGAKPYDGIPAREIPDLLEKGERLPQPPICTIDVYMIMVKCWMIDSECRPRFRELVSEFSRMARDPQRFVVIQNEDLGPASPLDSTFYRSLLEDDDMGDLVDAEEYLVPQQGFFCPDPAPGAGGMVHHRHRSSSTRSGGGDLTLGLEPSEEEAPRSPLAPSEGAGSDVFDGDLGMGAAKGLQSLPTHDPSPLQRYSEDPTVPLPSETDGYVAPLTCSPQPEYVNQPDVRPQPPSPREGPLPAARPAGATLERPKTLSPGKNGVVKDVFAFGGAVENPEYLTPQGGAAPQPHPPPAFSPAFDNLYYWDQDPPERGAPPSTFKGTPTAENPEYLGLDVPV,7.113509274827518 +C[C@H]([C@@H](N1CCN(CCCc2ccccc2)C1=O)C(=O)N[C@H](CCCCN)C(=O)OC(C)(C)C)c1c[nH]c2ccccc12,MEPLFPASTPSWNASSPGAASGGGDNRTLVGPAPSAGARAVLVPVLYLLVCAAGLGGNTLVIYVVLRFAKMKTVTNIYILNLAVADVLYMLGLPFLATQNAASFWPFGPVLCRLVMTLDGVNQFTSVFCLTVMSVDRYLAVVHPLSSARWRRPRVAKLASAAAWVLSLCMSLPLLVFADVQEGGTCNASWPEPVGLWGAVFIIYTAVLGFFAPLLVICLCYLLIVVKVRAAGVRVGCVRRRSERKVTRMVLVVVLVFAGCWLPFFTVNIVNLAVALPQEPASAGLYFFVVILSYANSCANPVLYGFLSDNFRQSFQKVLCLRKGSGAKDADATEPRPDRIRQQQEATPPAHRAAANGLMQTSKL,6.546681659952962 +CO[C@@H]1Cc2ccc(O)cc2C(C)(C)[C@@H]1N,MDSPIQIFRGEPGPTCAPSACLPPNSSAWFPGWAEPDSNGSAGSEDAQLEPAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSTVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLSSSVGISAIVLGGTKVREDVDVIECSLQFPDDDYSWWDLFMKICVFIFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITRLVLVVVAVFVVCWTPIHIFILVEALGSTSHSTAALSSYYFCIALGYTNSSLNPILYAFLDENFKRCFRDFCFPLKMRMERQSTSRVRNTVQDPAYLRDIDGMNKPV,6.735182176990463 +FC(F)(F)C1CCN(CCN2CCN(C2=O)c2cccc(c2)C#N)CC1,MAPLSQISTHLNSTCGAENSTGVNRARPHAYYALSYCALILAIIFGNGLVCAAVLRERALQTTTNYLVVSLAVADLLVATLVMPWVVYLEVTGGVWNFSRICCDVFVTLDVMMCTASILNLCAISIDRYTAVVMPVHYQHGTGQSSCRRVALMITAVWVLAFAVSCPLLFGFNTTGDPSICSISNPDFVIYSSVVSFYVPFGVTVLVYARIYIVLRQRQRKRILTRQNSQCISIRPGFPQQSSCLRLHPIRQFSIRARFLSDATGQMEHIEDKQYPQKCQDPLLSHLQPPSPGQTHGGLKRYYSICQDTALRHPSLEGGAGMSPVERTRNSLSPTMAPKLSLEVRKLSNGRLSTSLRLGPLQPRGVPLREKKATQMVVIVLGAFIVCWLPFFLTHVLNTHCQACHVSPELYRATTWLGYVNSALNPVIYTTFNVEFRKAFLKILSC,9.100179497572904 +CCOC(=O)c1ccccc1NC(=O)Cn1c(nc2ccccc12)-c1nonc1N,MNPTLILAAFCLGIASATLTFDHSLEAQWTKWKAMHNRLYGMNEEGWRRAVWEKNMKMIELHNQEYREGKHSFTMAMNAFGDMTSEEFRQVMNGFQNRKPRKGKVFQEPLFYEAPRSVDWREKGYVTPVKNQGQCGSCWAFSATGALEGQMFRKTGRLISLSEQNLVDCSGPQGNEGCNGGLMDYAFQYVQDNGGLDSEESYPYEATEESCKYNPKYSVANDTGFVDIPKQEKALMKAVATVGPISVAIDAGHESFLFYKEGIYFEPDCSSEDMDHGVLVVGYGFESTESDNNKYWLVKNSWGEEWGMGGYVKMAKDRRNHCGIASAASYPTV,4.301029995663981 +C[C@@H]1C[C@H](N)C[C@@H](C1)c1ccncc1NC(=O)c1ccc(F)c2cc(cnc12)N(C)CC1CC1,MLTKPLQGPPAPPGTPTPPPGGKDREAFEAEYRLGPLLGKGGFGTVFAGHRLTDRLQVAIKVIPRNRVLGWSPLSDSVTCPLEVALLWKVGAGGGHPGVIRLLDWFETQEGFMLVLERPLPAQDLFDYITEKGPLGEGPSRCFFGQVVAAIQHCHSRGVVHRDIKDENILIDLRRGCAKLIDFGSGALLHDEPYTDFDGTRVYSPPEWISRHQYHALPATVWSLGILLYDMVCGDIPFERDQEILEAELHFPAHVSPDCCALIRRCLAPKPSSRPSLEEILLDPWMQTPAEDVPLNPSKGGPAPLAWSLLP,6.259637310505756 +COc1ccc(cc1)-c1csc2nc(=O)cc(N)n12,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,5.0 +CCCCSc1c(cnc2[nH]ncc12)C(=O)c1ccccc1,MENFQKVEKIGEGTYGVVYKARNKLTGEVVALKKIRLDTETEGVPSTAIREISLLKELNHPNIVKLLDVIHTENKLYLVFEFLHQDLKKFMDASALTGIPLPLIKSYLFQLLQGLAFCHSHRVLHRDLKPQNLLINTEGAIKLADFGLARAFGVPVRTYTHEVVTLWYRAPEILLGCKYYSTAVDIWSLGCIFAEMVTRRALFPGDSEIDQLFRIFRTLGTPDEVVWPGVTSMPDYKPSFPKWARQDFSKVVPPLDEDGRSLLSQMLHYDPNKRISAKAALAHPFFQDVTKPVPHLRL,5.356547323513812 +COc1cc(ccc1OCCN1CCCC1)N1CC=C(Oc2ccc(cc2)-c2ccccc2)C1=O,MSVQTMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,9.522878745280337 +CC1(C)C(C(=O)c2cn(CC3CCOCC3)c3ccc(F)cc23)C1(C)C,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,5.91721462968355 +NCc1cccc(CC(CP(O)(=O)C(N)CCc2cccnc2)C(O)=O)c1,MVFLPLKWSLATMSFLLSSLLALLTVSTPSWCQSTEASPKRSDGTPFPWNKIRLPEYVIPVHYDLLIHANLTTLTFWGTTKVEITASQPTSTIILHSHHLQISRATLRKGAGERLSEEPLQVLEHPRQEQIALLAPEPLLVGLPYTVVIHYAGNLSETFHGFYKSTYRTKEGELRILASTQFEPTAARMAFPCFDEPAFKASFSIKIRREPRHLAISNMPLVKSVTVAEGLIEDHFDVTVKMSTYLVAFIISDFESVSKITKSGVKVSVYAVPDKINQADYALDAAVTLLEFYEDYFSIPYPLPKQDLAAIPDFQSGAMENWGLTTYRESALLFDAEKSSASSKLGITMTVAHELAHQWFGNLVTMEWWNDLWLNEGFAKFMEFVSVSVTHPELKVGDYFFGKCFDAMEVDALNSSHPVSTPVENPAQIREMFDDVSYDKGACILNMLREYLSADAFKSGIVQYLQKHSYKNTKNEDLWDSMASICPTDGVKGMDGFCSRSQHSSSSSHWHQEGVDVKTMMNTWTLQKGFPLITITVRGRNVHMKQEHYMKGSDGAPDTGYLWHVPLTFITSKSDMVHRFLLKTKTDVLILPEEVEWIKFNVGMNGYYIVHYEDDGWDSLTGLLKGTHTAVSSNDRASLINNAFQLVSIGKLSIEKALDLSLYLKHETEIMPVFQGLNELIPMYKLMEKRDMNEVETQFKAFLIRLLRDLIDKQTWTDEGSVSERMLRSQLLLLACVHNYQPCVQRAEGYFRKWKESNGNLSLPVDVTLAVFAVGAQSTEGWDFLYSKYQFSLSSTEKSQIEFALCRTQNKEKLQWLLDESFKGDKIKTQEFPQILTLIGRNPVGYPLAWQFLRKNWNKLVQKFELGSSSIAHMVMGTTNQFSTRTRLEEVKGFFSSLKENGSQLRCVQQTIETIEENIGWMDKNFDKIRVWLQSEKLERM,5.306273051076353 +C[C@]12O[C@H](C[C@]1(O)CO)n1c3ccccc3c3c4C(=O)NCc4c4c5ccccc5n2c4c13,MSDNGELEDKPPAPPVRMSSTIFSTGGKDPLSANHSLKPLPSVPEEKKPRHKIISIFSGTEKGSKKKEKERPEISPPSDFEHTIHVGFDAVTGEFTGMPEQWARLLQTSNITKLEQKKNPQAVLDVLKFYDSNTVKQKYLSFTPPEKDGFPSGTPALNAKGTEAPAVVTEEEDDDEETAPPVIAPRPDHTKSIYTRSVIDPVPAPVGDSHVDGAAKSLDKQKKKTKMTDEEIMEKLRTIVSIGDPKKKYTRYEKIGQGASGTVFTATDVALGQEVAIKQINLQKQPKKELIINEILVMKELKNPNIVNFLDSYLVGDELFVVMEYLAGGSLTDVVTETCMDEAQIAAVCRECLQALEFLHANQVIHRDIKSDNVLLGMEGSVKLTDFGFCAQITPEQSKRSTMVGTPYWMAPEVVTRKAYGPKVDIWSLGIMAIEMVEGEPPYLNENPLRALYLIATNGTPELQNPEKLSPIFRDFLNRCLEMDVEKRGSAKELLQHPFLKLAKPLSSLTPLIMAAKEAMKSNR,7.366531544420414 +NS(=O)(=O)c1cccc(-c2ncccn2)c1-c1nn[nH]n1,MSKLSVFFIFLFCSIATAAESLPDLKIEKLDEGVYVHTSFEEVNGWGVVPKHGLVVLVNAEAYLIDTPFTAKDTEKLVTWFVERGYKIKGSISSHFHSDSTGGIEWLNSRSIPTYASELTNELLKKDGKVQATNSFSGVNYWLVKNKIEVFYPGPGHTPDNVVVWLPERKILFGGCFIKPYGLGNLGDANIEAWPKSAKLLKSKYGKAKLVVPSHSEVGDASLLKLTLEQAVKGLNESKKPSKPSN,5.589391457431632 +CN1CCN(CC1)C1=c2ccccc2=Nc2ccc(Cl)cc2N1,MEEPGAQCAPPPPAGSETWVPQANLSSAPSQNCSAKDYIYQDSISLPWKVLLVMLLALITLATTLSNAFVIATVYRTRKLHTPANYLIASLAVTDLLVSILVMPISTMYTVTGRWTLGQVVCDFWLSSDITCCTASILHLCVIALDRYWAITDAVEYSAKRTPKRAAVMIALVWVFSISISLPPFFWRQAKAEEEVSECVVNTDHILYTVYSTVGAFYFPTLLLIALYGRIYVEARSRILKQTPNRTGKRLTRAQLITDSPGSTSSVTSINSRVPDVPSESGSPVYVNQVKVRVSDALLEKKKLMAARERKATKTLGIILGAFIVCWLPFFIISLVMPICKDACWFHLAIFDFFTWLGYLNSLINPIIYTMSNEDFKQAFHKLIRFKCTS,6.188424994129407 +ONC(=O)CCCCn1cc(C(=O)Nc2nccs2)c(=O)c2ccccc12,MSSQSHPDGLSGRDQPVELLNPARVNHMPSTVDVATALPLQVAPSAVPMDLRLDHQFSLPVAEPALREQQLQQELLALKQKQQIQRQILIAEFQRQHEQLSRQHEAQLHEHIKQQQEMLAMKHQQELLEHQRKLERHRQEQELEKQHREQKLQQLKNKEKGKESAVASTEVKMKLQEFVLNKKKALAHRNLNHCISSDPRYWYGKTQHSSLDQSSPPQSGVSTSYNHPVLGMYDAKDDFPLRKTASEPNLKLRSRLKQKVAERRSSPLLRRKDGPVVTALKKRPLDVTDSACSSAPGSGPSSPNNSSGSVSAENGIAPAVPSIPAETSLAHRLVAREGSAAPLPLYTSPSLPNITLGLPATGPSAGTAGQQDAERLTLPALQQRLSLFPGTHLTPYLSTSPLERDGGAAHSPLLQHMVLLEQPPAQAPLVTGLGALPLHAQSLVGADRVSPSIHKLRQHRPLGRTQSAPLPQNAQALQHLVIQQQHQQFLEKHKQQFQQQQLQMNKIIPKPSEPARQPESHPEETEEELREHQALLDEPYLDRLPGQKEAHAQAGVQVKQEPIESDEEEAEPPREVEPGQRQPSEQELLFRQQALLLEQQRIHQLRNYQASMEAAGIPVSFGGHRPLSRAQSSPASATFPVSVQEPPTKPRFTTGLVYDTLMLKHQCTCGSSSSHPEHAGRIQSIWSRLQETGLRGKCECIRGRKATLEELQTVHSEAHTLLYGTNPLNRQKLDSKKLLGSLASVFVRLPCGGVGVDSDTIWNEVHSAGAARLAVGCVVELVFKVATGELKNGFAVVRPPGHHAEESTPMGFCYFNSVAVAAKLLQQRLSVSKILIVDWDVHHGNGTQQAFYSDPSVLYMSLHRYDDGNFFPGSGAPDEVGTGPGVGFNVNMAFTGGLDPPMGDAEYLAAFRTVVMPIASEFAPDVVLVSSGFDAVEGHPTPLGGYNLSARCFGYLTKQLMGLAGGRIVLALEGGHDLTAICDASEACVSALLGNELDPLPEKVLQQRPNANAVRSMEKVMEIHSKYWRCLQRTTSTAGRSLIEAQTCENEEAETVTAMASLSVGVKPAEKRPDEEPMEEEPPL,7.376750709602099 +CC1N(Cc2ccc(Cl)cc2C1=O)C(C)(C)C,MSKSKCSVGLMSSVVAPAKEPNAVGPKEVELILVKEQNGVQLTSSTLTNPRQSPVEAQDRETWGKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPILKGVGFTVILISLYVGFFYNVIIAWALHYLFSSFTTELPWIHCNNSWNSPNCSDAHPGDSSGDSSGLNDTFGTTPAAEYFERGVLHLHQSHGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAIDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIVTTSINSLTSFSSGFVVFSFLGYMAQKHSVPIGDVAKDGPGLIFIIYPEAIATLPLSSAWAVVFFIMLLTLGIDSAMGGMESVITGLIDEFQLLHRHRELFTLFIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVGQFSDDIQQMTGQRPSLYWRLCWKLVSPCFLLFVVVVSIVTFRPPHYGAYIFPDWANALGWVIATSSMAMVPIYAAYKFCSLPGSFREKLAYAIAPEKDRELVDRGEVRQFTLRHWLKV,5.0 +Cn1nnnc1SCC1=C(N2[C@H](SC1)[C@H](NC(=O)[C@H](O)c1ccccc1)C2=O)C(O)=O,MTFSEILDRVGSMGHFQFLHVAILGLPILNMANHNLLQIFTAATPVHHCRPPHNASTGPWVLPMGPNGKPERCLRFVHPPNASLPNDTQRAMEPCLDGWVYNSTKDSIVTEWDLVCNSNKLKEMAQSIFMAGILIGGLVLGDLSDRFGRRPILTCSYLLLAASGSGAAFSPTFPIYMVFRFLCGFGISGITLSTVILNVEWVPTRMRAIMSTALGYCYTFGQFILPGLAYAIPQWRWLQLTVSIPFFVFFLSSWWTPESIRWLVLSGKSSKALKILRRVAVFNGKKEEGERLSLEELKLNLQKEISLAKAKYTASDLFRIPMLRRMTFCLSLAWFATGFAYYSLAMGVEEFGVNLYILQIIFGGVDVPAKFITILSLSYLGRHTTQAAALLLAGGAILALTFVPLDLQTVRTVLAVFGKGCLSSSFSCLFLYTSELYPTVIRQTGMGVSNLWTRVGSMVSPLVKITGEVQPFIPNIIYGITALLGGSAALFLPETLNQPLPETIEDLENWSLRAKKPKQEPEVEKASQRIPLQPHGPGLGSS,7.337242168318426 +COCC(C)(C)C(=O)n1nc(cc1NCc1ccc(Cl)s1)-c1cccn(Cc2ccccn2)c1=O,MILFKQATYFISLFATVSCGCLTQLYENAFFRGGDVASMYTPNAQYCQMRCTFHPRCLLFSFLPASSINDMEKRFGCFLKDSVTGTLPKVHRTGAVSGHSLKQCGHQISACHRDIYKGVDMRGVNFNVSKVSSVEECQKRCTNNIRCQFFSYATQTFHKAEYRNNCLLKYSPGGTPTAIKVLSNVESGFSLKPCALSEIGCHMNIFQHLAFSDVDVARVLTPDAFVCRTICTYHPNCLFFTFYTNVWKIESQRNVCLLKTSESGTPSSSTPQENTISGYSLLTCKRTLPEPCHSKIYPGVDFGGEELNVTFVKGVNVCQETCTKMIRCQFFTYSLLPEDCKEEKCKCFLRLSMDGSPTRIAYGTQGSSGYSLRLCNTGDNSVCTTKTSTRIVGGTNSSWGEWPWQVSLQVKLTAQRHLCGGSLIGHQWVLTAAHCFDGLPLQDVWRIYSGILNLSDITKDTPFSQIKEIIIHQNYKVSEGNHDIALIKLQAPLNYTEFQKPICLPSKGDTSTIYTNCWVTGWGFSKEKGEIQNILQKVNIPLVTNEECQKRYQDYKITQRMVCAGYKEGGKDACKGDSGGPLVCKHNGMWRLVGITSWGEGCARREQPGVYTKVAEYMDWILEKTQSSDGKAQMQSPA,4.259637310505756 +O[C@@H](CNCCc1ccc(NC(=O)Cc2n[nH]c3ccccc23)cc1)c1cccnc1,MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL,5.0 +COc1ccc(cc1OC)C(=O)N1CCN(CC1c1ccccc1)C(NC#N)=Nc1cccc2ncccc12,MPACCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENVTEGGVTKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSRLSLSLHHSPPIPGQPEEMQLLQIEAVPRSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY,7.522878745280337 +C[C@@H]1CN(CCN1C(=O)[C@@H]1CCCC[C@H]1C(=O)NC1(CC1)C#N)c1ccc(cc1)S(C)(=O)=O,MWQLWASLCCLLVLANARSRPSFHPLSDELVNYVNKRNTTWQAGHNFYNVDMSYLKRLCGTFLGGPKPPQRVMFTEDLKLPASFDAREQWPQCPTIKEIRDQGSCGSCWAFGAVEAISDRICIHTNAHVSVEVSAEDLLTCCGSMCGDGCNGGYPAEAWNFWTRKGLVSGGLYESHVGCRPYSIPPCEHHVNGSRPPCTGEGDTPKCSKICEPGYSPTYKQDKHYGYNSYSVSNSEKDIMAEIYKNGPVEGAFSVYSDFLLYKSGVYQHVTGEMMGGHAIRILGWGVENGTPYWLVANSWNTDWGDNGFFKILRGQDHCGIESEVVAGIPRTDQYWEKI,6.0101054362812265 +CNC(=O)[C@@H](NC(=O)[C@H](CC(C)C)[C@H](N1CCOCC1)C(=O)NO)C(C)(C)C,MHSFPPLLLLLFWGVVSHSFPATLETQEQDVDLVQKYLEKYYNLKNDGRQVEKRRNSGPVVEKLKQMQEFFGLKVTGKPDAETLKVMKQPRCGVPDVAQFVLTEGNPRWEQTHLTYRIENYTPDLPRADVDHAIEKAFQLWSNVTPLTFTKVSEGQADIMISFVRGDHRDNSPFDGPGGNLAHAFQPGPGIGGDAHFDEDERWTNNFREYNLHRVAAHELGHSLGLSHSTDIGALMYPSYTFSGDVQLAQDDIDGIQAIYGRSQNPVQPIGPQTPKACDSKLTFDAITTIRGEVMFFKDRFYMRTNPFYPEVELNFISVFWPQLPNGLEAAYEFADRDEVRFFKGNKYWAVQGQNVLHGYPKDIYSSFGFPRTVKHIDAALSEENTGKTYFFVANKYWRYDEYKRSMDPGYPKMIAHDFPGIGHKVDAVFMKDGFFYFFHGTRQYKFDPKTKRILTLQKANSWFNCRKN,8.657577319177793 +COc1ccc(cc1)C(=O)Cn1c(N)nc2ccccc12,MEEQGHSEMEIIPSESHPHIQLLKSNRELLVTHIRNTQCLVDNLLKNDYFSAEDAEIVCACPTQPDKVRKILDLVQSKGEEVSEFFLYLLQQLADAYVDLRPWLLEIGFSPSLLTQSKVVVNTDPVSRYTQQLRHHLGRDSKFVLCYAQKEELLLEEIYMDTIMELVGFSNESLGSLNSLACLLDHTTGILNEQGETIFILGDAGVGKSMLLQRLQSLWATGRLDAGVKFFFHFRCRMFSCFKESDRLCLQDLLFKHYCYPERDPEEVFAFLLRFPHVALFTFDGLDELHSDLDLSRVPDSSCPWEPAHPLVLLANLLSGKLLKGASKLLTARTGIEVPRQFLRKKVLLRGFSPSHLRAYARRMFPERALQDRLLSQLEANPNLCSLCSVPLFCWIIFRCFQHFRAAFEGSPQLPDCTMTLTDVFLLVTEVHLNRMQPSSLVQRNTRSPVETLHAGRDTLCSLGQVAHRGMEKSLFVFTQEEVQASGLQERDMQLGFLRALPELGPGGDQQSYEFFHLTLQAFFTAFFLVLDDRVGTQELLRFFQEWMPPAGAATTSCYPPFLPFQCLQGSGPAREDLFKNKDHFQFTNLFLCGLLSKAKQKLLRHLVPAAALRRKRKALWAHLFSSLRGYLKSLPRVQVESFNQVQAMPTFIWMLRCIYETQSQKVGQLAARGICANYLKLTYCNACSADCSALSFVLHHFPKRLALDLDNNNLNDYGVRELQPCFSRLTVLRLSVNQITDGGVKVLSEELTKYKIVTYLGLYNNQITDVGARYVTKILDECKGLTHLKLGKNKITSEGGKYLALAVKNSKSISEVGMWGNQVGDEGAKAFAEALRNHPSLTTLSLASNGISTEGGKSLARALQQNTSLEILWLTQNELNDEVAESLAEMLKVNQTLKHLWLIQNQITAKGTAQLADALQSNTGITEICLNGNLIKPEEAKVYEDEKRIICF,4.698970004336019 +CCC(CC)O[C@@H]1C=C(C[C@H](N)[C@H]1NC(C)=O)C(=O)NOCc1ccccc1,MNPNQKIITIGSICMAIGIISLILQIGNIISIWVSHSIQTGSQNHTGICNQRIITYENSTWVNQTYVNISNTNVVAGKDTTSMTLAGNSSLCPIRGWAIYSKDNSIRIGSKGDVFVIREPFISCSHLECRTFFLTQGALLNDKHSNGTVKDRSPYRALMSCPIGEAPSPYNSRFESVAWSASACHDGMGWLTIGISGPDDGAVAVLKYNGIITETIKSWRKQILRTQESECVCVNGSCFTIMTDGPSDGPASYRIFKIEKGKITKSIELDAPNSHYEECSCYPDTGTVMCVCRDNWHGSNRPWVSFNQNLDYQIGYICSGVFGDNPRPKDGKGSCDPVNVDGADGVKGFSYRYGNGVWIGRTKSNSSRKGFEMIWDPNGWTDTDSNFLVKQDVVAMTDWSGYSGSFVQHPELTGLDCMRPCFWVELIRGRPREKTTIWTSGSSISFCGVNSDTVNWSWPDGAELPFTIDK,7.508638306165727 +COc1ccccc1N1CCN(CCCCNC(=O)c2cc3ccccc3oc2=O)CC1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,7.638272163982407 +Cc1cc(OCc2nnc(n2-c2cccnc2)S(=O)(=O)C2CCCC=C2)ccc1C#CCO,MASGADSKGDDLSTAILKQKNRPNRLIVDEAINEDNSVVSLSQPKMDELQLFRGDTVLLKGKKRREAVCIVLSDDTCSDEKIRMNRVVRNNLRVRLGDVISIQPCPDVKYGKRIHVLPIDDTVEGITGNLFEVYLKPYFLEAYRPIRKGDIFLVRGGMRAVEFKVVETDPSPYCIVAPDTVIHCEGEPIKREDEEESLNEVGYDDIGGCRKQLAQIKEMVELPLRHPALFKAIGVKPPRGILLYGPPGTGKTLIARAVANETGAFFFLINGPEIMSKLAGESESNLRKAFEEAEKNAPAIIFIDELDAIAPKREKTHGEVERRIVSQLLTLMDGLKQRAHVIVMAATNRPNSIDPALRRFGRFDREVDIGIPDATGRLEILQIHTKNMKLADDVDLEQVANETHGHVGADLAALCSEAALQAIRKKMDLIDLEDETIDAEVMNSLAVTMDDFRWALSQSNPSALRETVVEVPQVTWEDIGGLEDVKRELQELVQYPVEHPDKFLKFGMTPSKGVLFYGPPGCGKTLLAKAIANECQANFISIKGPELLTMWFGESEANVREIFDKARQAAPCVLFFDELDSIAKARGGNIGDGGGAADRVINQILTEMDGMSTKKNVFIIGATNRPDIIDPAILRPGRLDQLIYIPLPDEKSRVAILKANLRKSPVAKDVDLEFLAKMTNGFSGADLTEICQRACKLAIRESIESEIRRERERQTNPSAMEVEEDDPVPEIRRDHFEEAMRFARRSVSDNDIRKYEMFAQTLQQSRGFGSFRFPSGNQGGAGPSQGSGGGTGGSVYTEDNDDDLYG,5.317043073698791 +COc1c(I)cc(I)cc1C(=O)Nc1ccc2ccccc2c1,MRIGAMLIPFIILGNAIIAYGYVRGCYYTNWAQYRQGEGKFLPEDIPKGLCTHILYAFAKVDQSGTSLPFEWNDEDTNWSKGMYSRVTKLKENDPEMKILLSYGGYNFGSSTFTAIRNRAEKRKHFIKSAIAFLRKNKFDGFDFDWEYPIGMAQEYAKLVNEMKVAFVEEAKKSDSEQLLLTAAVSAGKHTIDQSYNVQSLGENFDLLSLMSYDFHGSWEMNVDLHAKLHPTKGETSGTGIFNTEFAANYWLSKGMPKQKIIIGIPTYGRGWTLRDSSKTTIGAEGISPSSPSTTNPAGGTAAYWEICKYLKEGGKETIDEQGVGACMVQGSQWYGYDNEETIRMKMRWLKEKGYGGAFIWTLDFDDFKGTSCGEGPYPLLSAINHELKGEATATTRSLRTTITQSSTIGSTKFETTTTASEITKNNKIKTTTIAVEPTGESSDIKCPESFGLFRHPNDCHLFIHCAHDHPYVKLCPPNTFFNDKIKVCDHFGECDE,6.050609993355087 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+NS(=O)(=O)c1cccc(-c2ccn3cncc3c2)c1-c1nn[nH]n1,MELPNIMHPVAKLSTALAAALMLSGCMPGEIRPTIGQQMETGDQRFGDLVFRQLAPNVWQHTSYLDMPGFGAVASNGLIVRDGGRVLVVDTAWTDDQTAQILNWIKQEINLPVALAVVTHAHQDKMGGMDALHAAGIATYANALSNQLAPQEGMVAAQHSLTFAANGWVEPATAPNFGPLKVFYPGPGHTSDNITVGIDGTDIAFGGCLIKDSKAKSLGNLGDADTEHYAASARAFGAAFPKASMIVMSHSAPDSRAAITHTARMADKLR,7.835647144215563 +OC(c1ccc(F)c(c1)-c1ncnc2cc(ccc12)N1CCOCC1)c1c(Cl)cncc1Cl,MAGSGAGVRCSLLRLQETLSAADRCGAALAGHQLIRGLGQECVLSSSPAVLALQTSLVFSRDFGLLVFVRKSLNSIEFRECREEILKFLCIFLEKMGQKIAPYSVEIKNTCTSVYTKDRAAKCKIPALDLLIKLLQTFRSSRLMDEFKIGELFSKFYGELALKKKIPDTVLEKVYELLGLLGEVHPSEMINNAENLFRAFLGELKTQMTSAVREPKLPVLAGCLKGLSSLLCNFTKSMEEDPQTSREIFNFVLKAIRPQIDLKRYAVPSAGLRLFALHASQFSTCLLDNYVSLFEVLLKWCAHTNVELKKAALSALESFLKQVSNMVAKNAEMHKNKLQYFMEQFYGIIRNVDSNNKELSIAIRGYGLFAGPCKVINAKDVDFMYVELIQRCKQMFLTQTDTGDDRVYQMPSFLQSVASVLLYLDTVPEVYTPVLEHLVVMQIDSFPQYSPKMQLVCCRAIVKVFLALAAKGPVLRNCISTVVHQGLIRICSKPVVLPKGPESESEDHRASGEVRTGKWKVPTYKDYVDLFRHLLSSDQMMDSILADEAFFSVNSSSESLNHLLYDEFVKSVLKIVEKLDLTLEIQTVGEQENGDEAPGVWMIPTSDPAANLHPAKPKDFSAFINLVEFCREILPEKQAEFFEPWVYSFSYELILQSTRLPLISGFYKLLSITVRNAKKIKYFEGVSPKSLKHSPEDPEKYSCFALFVKFGKEVAVKMKQYKDELLASCLTFLLSLPHNIIELDVRAYVPALQMAFKLGLSYTPLAEVGLNALEEWSIYIDRHVMQPYYKDILPCLDGYLKTSALSDETKNNWEVSALSRAAQKGFNKVVLKHLKKTKNLSSNEAISLEEIRIRVVQMLGSLGGQINKNLLTVTSSDEMMKSYVAWDREKRLSFAVPFREMKPVIFLDVFLPRVTELALTASDRQTKVAACELLHSMVMFMLGKATQMPEGGQGAPPMYQLYKRTFPVLLRLACDVDQVTRQLYEPLVMQLIHWFTNNKKFESQDTVALLEAILDGIVDPVDSTLRDFCGRCIREFLKWSIKQITPQQQEKSPVNTKSLFKRLYSLALHPNAFKRLGASLAFNNIYREFREEESLVEQFVFEALVIYMESLALAHADEKSLGTIQQCCDAIDHLCRIIEKKHVSLNKAKKRRLPRGFPPSASLCLLDLVKWLLAHCGRPQTECRHKSIELFYKFVPLLPGNRSPNLWLKDVLKEEGVSFLINTFEGGGCGQPSGILAQPTLLYLRGPFSLQATLCWLDLLLAALECYNTFIGERTVGALQVLGTEAQSSLLKAVAFFLESIAMHDIIAAEKCFGTGAAGNRTSPQEGERYNYSKCTVVVRIMEFTTTLLNTSPEGWKLLKKDLCNTHLMRVLVQTLCEPASIGFNIGDVQVMAHLPDVCVNLMKALKMSPYKDILETHLREKITAQSIEELCAVNLYGPDAQVDRSRLAAVVSACKQLHRAGLLHNILPSQSTDLHHSVGTELLSLVYKGIAPGDERQCLPSLDLSCKQLASGLLELAFAFGGLCERLVSLLLNPAVLSTASLGSSQGSVIHFSHGEYFYSLFSETINTELLKNLDLAVLELMQSSVDNTKMVSAVLNGMLDQSFRERANQKHQGLKLATTILQHWKKCDSWWAKDSPLETKMAVLALLAKILQIDSSVSFNTSHGSFPEVFTTYISLLADTKLDLHLKGQAVTLLPFFTSLTGGSLEELRRVLEQLIVAHFPMQSREFPPGTPRFNNYVDCMKKFLDALELSQSPMLLELMTEVLCREQQHVMEELFQSSFRRIARRGSCVTQVGLLESVYEMFRKDDPRLSFTRQSFVDRSLLTLLWHCSLDALREFFSTIVVDAIDVLKSRFTKLNESTFDTQITKKMGYYKILDVMYSRLPKDDVHAKESKINQVFHGSCITEGNELTKTLIKLCYDAFTENMAGENQLLERRRLYHCAAYNCAISVICCVFNELKFYQGFLFSEKPEKNLLIFENLIDLKRRYNFPVEVEVPMERKKKYIEIRKEAREAANGDSDGPSYMSSLSYLADSTLSEEMSQFDFSTGVQSYSYSSQDPRPATGRFRRREQRDPTVHDDVLELEMDELNRHECMAPLTALVKHMHRSLGPPQGEEDSVPRDLPSWMKFLHGKLGNPIVPLNIRLFLAKLVINTEEVFRPYAKHWLSPLLQLAASENNGGEGIHYMVVEIVATILSWTGLATPTGVPKDEVLANRLLNFLMKHVFHPKRAVFRHNLEIIKTLVECWKDCLSIPYRLIFEKFSGKDPNSKDNSVGIQLLGIVMANDLPPYDPQCGIQSSEYFQALVNNMSFVRYKEVYAAAAEVLGLILRYVMERKNILEESLCELVAKQLKQHQNTMEDKFIVCLNKVTKSFPPLADRFMNAVFFLLPKFHGVLKTLCLEVVLCRVEGMTELYFQLKSKDFVQVMRHRDDERQKVCLDIIYKMMPKLKPVELRELLNPVVEFVSHPSTTCREQMYNILMWIHDNYRDPESETDNDSQEIFKLAKDVLIQGLIDENPGLQLIIRNFWSHETRLPSNTLDRLLALNSLYSPKIEVHFLSLATNFLLEMTSMSPDYPNPMFEHPLSECEFQEYTIDSDWRFRSTVLTPMFVETQASQGTLQTRTQEGSLSARWPVAGQIRATQQQHDFTLTQTADGRSSFDWLTGSSTDPLVDHTSPSSDSLLFAHKRSERLQRAPLKSVGPDFGKKRLGLPGDEVDNKVKGAAGRTDLLRLRRRFMRDQEKLSLMYARKGVAEQKREKEIKSELKMKQDAQVVLYRSYRHGDLPDIQIKHSSLITPLQAVAQRDPIIAKQLFSSLFSGILKEMDKFKTLSEKNNITQKLLQDFNRFLNTTFSFFPPFVSCIQDISCQHAALLSLDPAAVSAGCLASLQQPVGIRLLEEALLRLLPAELPAKRVRGKARLPPDVLRWVELAKLYRSIGEYDVLRGIFTSEIGTKQITQSALLAEARSDYSEAAKQYDEALNKQDWVDGEPTEAEKDFWELASLDCYNHLAEWKSLEYCSTASIDSENPPDLNKIWSEPFYQETYLPYMIRSKLKLLLQGEADQSLLTFIDKAMHGELQKAILELHYSQELSLLYLLQDDVDRAKYYIQNGIQSFMQNYSSIDVLLHQSRLTKLQSVQALTEIQEFISFISKQGNLSSQVPLKRLLNTWTNRYPDAKMDPMNIWDDIITNRCFFLSKIEEKLTPLPEDNSMNVDQDGDPSDRMEVQEQEEDISSLIRSCKFSMKMKMIDSARKQNNFSLAMKLLKELHKESKTRDDWLVSWVQSYCRLSHCRSRSQGCSEQVLTVLKTVSLLDENNVSSYLSKNILAFRDQNILLGTTYRIIANALSSEPACLAEIEEDKARRILELSGSSSEDSEKVIAGLYQRAFQHLSEAVQAAEEEAQPPSWSCGPAAGVIDAYMTLADFCDQQLRKEEENASVIDSAELQAYPALVVEKMLKALKLNSNEARLKFPRLLQIIERYPEETLSLMTKEISSVPCWQFISWISHMVALLDKDQAVAVQHSVEEITDNYPQAIVYPFIISSESYSFKDTSTGHKNKEFVARIKSKLDQGGVIQDFINALDQLSNPELLFKDWSNDVRAELAKTPVNKKNIEKMYERMYAALGDPKAPGLGAFRRKFIQTFGKEFDKHFGKGGSKLLRMKLSDFNDITNMLLLKMNKDSKPPGNLKECSPWMSDFKVEFLRNELEIPGQYDGRGKPLPEYHVRIAGFDERVTVMASLRRPKRIIIRGHDEREHPFLVKGGEDLRQDQRVEQLFQVMNGILAQDSACSQRALQLRTYSVVPMTSRLGLIEWLENTVTLKDLLLNTMSQEEKAAYLSDPRAPPCEYKDWLTKMSGKHDVGAYMLMYKGANRTETVTSFRKRESKVPADLLKRAFVRMSTSPEAFLALRSHFASSHALICISHWILGIGDRHLNNFMVAMETGGVIGIDFGHAFGSATQFLPVPELMPFRLTRQFINLMLPMKETGLMYSIMVHALRAFRSDPGLLTNTMDVFVKEPSFDWKNFEQKMLKKGGSWIQEINVAEKNWYPRQKICYAKRKLAGANPAVITCDELLLGHEKAPAFRDYVAVARGSKDHNIRAQEPESGLSEETQVKCLMDQATDPNILGRTWEGWEPWM,8.301029995663981 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+COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)CC(N)=O,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,7.698970004336019 +OC(=O)[C@@H](NC(=O)c1cc2ccccc2cc1NC(=O)Nc1c(Cl)cc(Cl)cc1Cl)C1CCCCC1,MAKPLTDQEKRRQISIRGIVGVENVAELKKSFNRHLHFTLVKDRNVATTRDYYFALAHTVRDHLVGRWIRTQQHYYDKCPKRVYYLSLEFYMGRTLQNTMINLGLQNACDEAIYQLGLDIEELEEIEEDAGLGNGGLGRLAACFLDSMATLGLAAYGYGIRYEYGIFNQKIRDGWQVEEADDWLRYGNPWEKSRPEFMLPVHFYGKVEHTNTGTKWIDTQVVLALPYDTPVPGYMNNTVNTMRLWSARAPNDFNLRDFNVGDYIQAVLDRNLAENISRVLYPNDNFFEGKELRLKQEYFVVAATLQDIIRRFKASKFGSTRGAGTVFDAFPDQVAIQLNDTHPALAIPELMRIFVDIEKLPWSKAWELTQKTFAYTNHTVLPEALERWPVDLVEKLLPRHLEIIYEINQKHLDRIVALFPKDVDRLRRMSLIEEEGSKRINMAHLCIVGSHAVNGVAKIHSDIVKTKVFKDFSELEPDKFQNKTNGITPRRWLLLCNPGLAELIAEKIGEDYVKDLSQLTKLHSFLGDDVFLRELAKVKQENKLKFSQFLETEYKVKINPSSMFDVQVKRIHEYKRQLLNCLHVITMYNRIKKDPKKLFVPRTVIIGGKAAPGYHMAKMIIKLITSVADVVNNDPMVGSKLKVIFLENYRVSLAEKVIPATDLSEQISTAGTEASGTGNMKFMLNGALTIGTMDGANVEMAEEAGEENLFIFGMRIDDVAALDKKGYEAKEYYEALPELKLVIDQIDNGFFSPKQPDLFKDIINMLFYHDRFKVFADYEAYVKCQDKVSQLYMNPKAWNTMVLKNIAASGKFSSDRTIKEYAQNIWNVEPSDLKISLSNESNKVNGN,7.187086643357144 +CC(C)c1cc(C(C)C)c(c(c1)C(C)C)S(=O)(=O)N[C@@H](Cc1cccc(c1)C(N)=N)C(=O)N1CCCN(CC1)C(=O)C1CCN(CC1)C(N)=N,MGSDRARKGGGGPKDFGAGLKYNSRHEKVNGLEEGVEFLPVNNVKKVEKHGPGRWVVLAAVLIGLLLVLLGIGFLVWHLQYRDVRVQKVFNGYMRITNENFVDAYENSNSTEFVSLASKVKDALKLLYSGVPFLGPYHKESAVTAFSEGSVIAYYWSEFSIPQHLVEEAERVMAEERVVMLPPRARSLKSFVVTSVVAFPTDSKTVQRTQDNSCSFGLHARGVELMRFTTPGFPDSPYPAHARCQWALRGDADSVLSLTFRSFDLASCDERGSDLVTVYNTLSPMEPHALVQLCGTYPPSYNLTFHSSQNVLLITLITNTERRHPGFEATFFQLPRMSSCGGRLRKAQGTFNSPYYPGHYPPNIDCTWNIEVPNNQHVKVRFKFFYLLEPGVPAGTCPKDYVEINGEKYCGERSQFVVTSNSNKITVRFHSDQSYTDTGFLAEYLSYDSSDPCPGQFTCRTGRCIRKELRCDGWADCTDHSDELNCSCDAGHQFTCKNKFCKPLFWVCDSVNDCGDNSDEQGCSCPAQTFRCSNGKCLSKSQQCNGKDDCGDGSDEASCPKVNVVTCTKHTYRCLNGLCLSKGNPECDGKEDCSDGSDEKDCDCGLRSFTRQARVVGGTDADEGEWPWQVSLHALGQGHICGASLISPNWLVSAAHCYIDDRGFRYSDPTQWTAFLGLHDQSQRSAPGVQERRLKRIISHPFFNDFTFDYDIALLELEKPAEYSSMVRPICLPDASHVFPAGKAIWVTGWGHTQYGGTGALILQKGEIRVINQTTCENLLPQQITPRMMCVGFLSGGVDSCQGDSGGPLSSVEADGRIFQAGVVSWGDGCAQRNKPGVYTRLPLFRDWIKENTGV,7.301029995663981 +[Zn++].c1cc2nc1c(-c1ccccc1)c1ccc([n-]1)c(-c1ccccc1)c1ccc(n1)c(-c1ccccc1)c1ccc([n-]1)c2-c1ccccc1,MKILDALLFPVIFIMFFIHLSIAQTDPELTIMTRLGQVQGTRLPVPDRSHVIAFLGIPFAEPPLGKMRFKPPEPKKPWNDVFDARDYPSACYQYVDTSYPGFSGTEMWNPNRMMSEDCLYLNVWVPATPRPHNLTVMVWIYGGGFYSGSSSLDVYDGRYLAHSEKVVVVSMNYRVSAFGFLALNGSAEAPGNVGLLDQRLALQWVQDNIHFFGGNPKQVTIFGESAGAASVGMHLLSPDSRPKFTRAILQSGVPNGPWRTVSFDEARRRAIKLGRLVGCPDGNDTDLIDCLRSKQPQDLIDQEWLVLPFSGLFRFSFVPVIDGVVFPDTPEAMLNSGNFKDTQILLGVNQNEGSYFLIYGAPGFSKDNESLITREDFLQGVKMSVPHANEIGLEAVILQYTDWMDEDNPIKNREAMDDIVGDHNVVCPLQHFAKMYAQYSILQGQTGTASQGNLGWGNSGSASNSGNSQVSVYLYMFDHRASNLVWPEWMGVIHGYEIEFVFGLPLEKRLNYTLEEEKLSRRMMKYWANFARTGNPNINVDGSIDSRRRWPVFTSTEQKHVGLNTDSLKVHKGLKSQFCALWNRFLPRLLNVTENIDDAERQWKAEFHRWSSYMMHWKNQFDHYSKQERCTNL,5.268411234813261 +CC(=O)N1CCN(CC1)c1ccc(CN(C2CCC2)S(=O)(=O)c2ccc(Cl)cc2)c(F)c1,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,6.721246399047171 +COCCOc1cc2ncnc(Nc3cccc(OC)c3)c2c2OCCOc12,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,6.795880017344075 +CC(=O)Nc1nnc(s1)S(N)(=O)=O,MLGRNTWKTSAFSFLVEQMWAPLWSRSMRPGRWCSQRSCAWQTSNNTLHPLWTVPVSVPGGTRQSPINIQWRDSVYDPQLKPLRVSYEAASCLYIWNTGYLFQVEFDDATEASGISGGPLENHYRLKQFHFHWGAVNEGGSEHTVDGHAYPAELHLVHWNSVKYQNYKEAVVGENGLAVIGVFLKLGAHHQTLQRLVDILPEIKHKDARAAMRPFDPSTLLPTCWDYWTYAGSLTTPPLTESVTWIIQKEPVEVAPSQLSAFRTLLFSALGEEEKMMVNNYRPLQPLMNRKVWASFQATNEGTRS,7.200659450546418 +C[C@H](NC(=O)C(C)(C)NCCCN(C)C)[C@@H](Cc1ccc(Cl)cc1)c1cccc(c1)C#N,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,5.525492360883024 +Cc1cccc(c1)C(=O)Nc1cccn2c1nc(cc2=O)N1CCOCC1,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,6.327902142064283 +CC(C)c1ccc(cc1)-c1nnc(o1)-c1cc(Cl)c(s1)[C@]1(C)CS(=O)(=O)N(C)C(=N)N1,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,6.445389714773836 +Cc1cc(Oc2cccc(CNC(=O)c3cc4cc(Cl)ccc4[nH]3)c2)ccc1CCC(O)=O,MEQPQEEAPEVREEEEKEEVAEAEGAPELNGGPQHALPSSSYTDLSRSSSPPSLLDQLQMGCDGASCGSLNMECRVCGDKASGFHYGVHACEGCKGFFRRTIRMKLEYEKCERSCKIQKKNRNKCQYCRFQKCLALGMSHNAIRFGRMPEAEKRKLVAGLTANEGSQYNPQVADLKAFSKHIYNAYLKNFNMTKKKARSILTGKASHTAPFVIHDIETLWQAEKGLVWKQLVNGLPPYKEISVHVFYRCQCTTVETVRELTEFAKSIPSFSSLFLNDQVTLLKYGVHEAIFAMLASIVNKDGLLVANGSGFVTREFLRSLRKPFSDIIEPKFEFAVKFNALELDDSDLALFIAAIILCGDRPGLMNVPRVEAIQDTILRALEFHLQANHPDAQYLFPKLLQKMADLRQLVTEHAQMMQRIKKTETETSLHPLLQEIYKDMY,8.522878745280337 +CC(C)n1c(C)ncc1-c1ccnc(Nc2ccc(cc2)C(=O)NC2CCN(C)CC2)n1,MEDYTKIEKIGEGTYGVVYKGRHKTTGQVVAMKKIRLESEEEGVPSTAIREISLLKELRHPNIVSLQDVLMQDSRLYLIFEFLSMDLKKYLDSIPPGQYMDSSLVKSYLYQILQGIVFCHSRRVLHRDLKPQNLLIDDKGTIKLADFGLARAFGIPIRVYTHEVVTLWYRSPEVLLGSARYSTPVDIWSIGTIFAELATKKPLFHGDSEIDQLFRIFRALGTPNNEVWPEVESLQDYKNTFPKWKPGSLASHVKNLDENGLDLLSKMLIYDPAKRISGKMALNHPYFNDLDNQIKKM,6.7447274948966935 +COc1cc(CN2CCc3ccccc3C2)ccc1O,MMPFCHNIINISCVKNNWSNDVRASLYSLMVLIILTTLVGNLIVIVSISHFKQLHTPTNWLIHSMATVDFLLGCLVMPYSMVRSAEHCWYFGEVFCKIHTSTDIMLSSASIFHLSFISIDRYYAVCDPLRYKAKMNILVICVMIFISWSVPAVFAFGMIFLELNFKGAEEIYYKHVHCRGGCSVFFSKISGVLTFMTSFYIPGSIMLCVYYRIYLIAKEQARLISDANQKLQIGLEMKNGISQSKERKAVKTLGIVMGVFLICWCPFFICTVMDPFLHYIIPPTLNDVLIWFGYLNSTFNPMVYAFFYPWFRKALKMMLFGKIFQKDSSRCKLFLELSS,4.922632094715843 +CCCCCCN(CCCCCC)C(=S)Cc1c([nH]c2ccccc12)-c1ccc(F)cc1,MAPWPHKNGSLAFWSDAPTLDPSAANTSGLPGVPWAAALAGALLALATVGGNLLVITAIARTPRLQTITNVFVTSLATADLVVGLLVMPPGATLALTGHWPLGATGCELWTSVDVLCVTASIETLCALAVDRYLAVTNPLRYGTLVTKRRARAAVVLVWIVSATVSFAPIMSQWWRVGADAEAQECHSNPRCCSFASNMPYALLSSSVSFYLPLLVMLFVYARVFVVAKRQRRLLRRELGRFPPEESPRSPSRSPSPATVGTPTASDGVPSCGRRPARLLPLGEHRALRTLGLIMGIFSLCWLPFFLANVLRALVGPSLVPSGVFIALNWLGYANSAFNPLIYCRSPDFRDAFRRLLCSYGGRGPEEPRVVTFPASPVASRQNSPLNRFDGYEGERPFPT,6.0 +Cl.CS(=O)(=O)N1CCC[C@@H]1C#CCN1CCCC1,MNFTPVNGSSANQSVRLVTAAHNHLETVEMVFIATVTGSLSLVTVVGNILVMLSIKVNRQLQTVNNYFLFSLGCADLIIGAFSMNLYTLYIIKGYWPLGAVVCDLWLALDYVVSNASVMNLLIISFDRYFCVTKPLTYPARRTTKMAGLMIAAAWVLSFVLWAPAILFWQFVVGKRTVPDNQCFIQFLSNPAVTFGTAIAAFYLPVVIMTVLYIHISLASRSRVHKHRPEGPKEKKAKTLAFLKSPLMKPSIKKPPPGGASREELRNGKLEEAPPPALPPPPRPVPDKDTSNESSSGSATQNTKERPPTELSTAEATTPALPAPTLQPRTLNPASKWSKIQIVTKQTGNECVTAIEIVPATPAGMRPAANVARKFASIARNQVRKKRQMAARERKVTRTIFAILLAFILTWTPYNVMVLVNTFCQSCIPERVWSIGYWLCYVNSTINPACYALCNATFKKTFRHLLLCQYRNIGTAR,4.872895201635192 +FC(F)Oc1ccc(nc1)-c1nnc([C@H]2C[C@@H](C2)NC(=O)c2ccc(F)cn2)n1-c1ccccc1F,MAASRRSQHHHHHHQQQLQPAPGASAPPPPPPPPLSPGLAPGTTPASPTASGLAPFASPRHGLALPEGDGSRDPPDRPRSPDPVDGTSCCSTTSTICTVAAAPVVPAVSTSSAAGVAPNPAGSGSNNSPSSSSSPTSSSSSSPSSPGSSLAESPEAAGVSSTAPLGPGAAGPGTGVPAVSGALRELLEACRNGDVSRVKRLVDAANVNAKDMAGRKSSPLHFAAGFGRKDVVEHLLQMGANVHARDDGGLIPLHNACSFGHAEVVSLLLCQGADPNARDNWNYTPLHEAAIKGKIDVCIVLLQHGADPNIRNTDGKSALDLADPSAKAVLTGEYKKDELLEAARSGNEEKLMALLTPLNVNCHASDGRKSTPLHLAAGYNRVRIVQLLLQHGADVHAKDKGGLVPLHNACSYGHYEVTELLLKHGACVNAMDLWQFTPLHEAASKNRVEVCSLLLSHGADPTLVNCHGKSAVDMAPTPELRERLTYEFKGHSLLQAAREADLAKVKKTLALEIINFKQPQSHETALHCAVASLHPKRKQVTELLLRKGANVNEKNKDFMTPLHVAAERAHNDVMEVLHKHGAKMNALDTLGQTALHRAALAGHLQTCRLLLSYGSDPSIISLQGFTAAQMGNEAVQQILSESTPIRTSDVDYRLLEASKAGDLETVKQLCSSQNVNCRDLEGRHSTPLHFAAGYNRVSVVEYLLHHGADVHAKDKGGLVPLHNACSYGHYEVAELLVRHGASVNVADLWKFTPLHEAAAKGKYEICKLLLKHGADPTKKNRDGNTPLDLVKEGDTDIQDLLRGDAALLDAAKKGCLARVQKLCTPENINCRDTQGRNSTPLHLAAGYNNLEVAEYLLEHGADVNAQDKGGLIPLHNAASYGHVDIAALLIKYNTCVNATDKWAFTPLHEAAQKGRTQLCALLLAHGADPTMKNQEGQTPLDLATADDIRALLIDAMPPEALPTCFKPQATVVSASLISPASTPSCLSAASSIDNLTGPLAELAVGGASNAGDGAAGTERKEGEVAGLDMNISQFLKSLGLEHLRDIFETEQITLDVLADMGHEELKEIGINAYGHRHKLIKGVERLLGGQQGTNPYLTFHCVNQGTILLDLAPEDKEYQSVEEEMQSTIREHRDGGNAGGIFNRYNVIRIQKVVNKKLRERFCHRQKEVSEENHNHHNERMLFHGSPFINAIIHKGFDERHAYIGGMFGAGIYFAENSSKSNQYVYGIGGGTGCPTHKDRSCYICHRQMLFCRVTLGKSFLQFSTMKMAHAPPGHHSVIGRPSVNGLAYAEYVIYRGEQAYPEYLITYQIMKPEAPSQTATAAEQKT,7.568636235841012 +Cc1nc2cccc(c2c(=O)n1-c1ccc(OCCCN2CCCC2)cc1)C(F)(F)F,MALIPDLAMETWLLLAVSLVLLYLYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIAEDEEWKRLRSLLSPTFTSGKLKEMVPIIAQYGDVLVRNLRREAETGKPVTLKDVFGAYSMDVITSTSFGVNIDSLNNPQDPFVENTKKLLRFDFLDPFFLSITVFPFLIPILEVLNICVFPREVTNFLRKSVKRMKESRLEDTQKHRVDFLQLMIDSQNSKETESHKALSDLELVAQSIIFIFAGYETTSSVLSFIMYELATHPDVQQKLQEEIDAVLPNKAPPTYDTVLQMEYLDMVVNETLRLFPIAMRLERVCKKDVEINGMFIPKGVVVMIPSYALHRDPKYWTEPEKFLPERFSKKNKDNIDPYIYTPFGSGPRNCIGMRFALMNMKLALIRVLQNFSFKPCKETQIPLKLSLGGLLQPEKPVVLKVESRDGTVSGA,4.568636235841012 +C[C@@H](Nc1nc2n(ncc2c(=O)n1Cc1ccccc1)C(C)(C)C)c1ccc(Cl)cc1,MESPTKEIEEFESNSLKYLQPEQIEKIWLRLRGLRKYKKTSQRLRSLVKQLERGEASVVDLKKNLEYAATVLESVYIDETRRLLDTEDELSDIQSDAVPSEVRDWLASTFTRQMGMMLRRSDEKPRFKSIVHAVQAGIFVERMYRRTSNMVGLSYPPAVIEALKDVDKWSFDVFSLNEASGDHALKFIFYELLTRYDLISRFKIPISALVSFVEALEVGYSKHKNPYHNLMHAADVTQTVHYLLYKTGVANWLTELEIFAIIFSAAIHDYEHTGTTNNFHIQTRSDPAILYNDRSVLENHHLSAAYRLLQDDEEMNILINLSKDDWREFRTLVIEMVMATDMSCHFQQIKAMKTALQQPEAIEKPKALSLMLHTADISHPAKAWDLHHRWTMSLLEEFFRQGDREAELGLPFSPLCDRKSTMVAQSQVGFIDFIVEPTFTVLTDMTEKIVSPLIDETSQTGGTGQRRSSLNSISSSDAKRSGVKTSGSEGSAPINNSVISVDYKSFKATWTEVVHINRERWRAKVPKEEKAKKEAEEKARLAAEEQQKEMEAKSQAEEGASGKAEKKTSGETKNQVNGTRANKSDNPRGKNSKAEKSSGEQQQNGDFKDGKNKTDKKDHSNIGNDSKKTDGTKQRSHGSPAPSTSSTCRLTLPVIKPPLRHFKRPAYASSSYAPSVSKKTDEHPARYKMLDQRIKMKKIQNISHNWNRK,8.823908740944319 +CCCN(C(=O)CC(O)=O)C1=C(C)CC(N([C@@H](C)c2ccc(OC)cc2)C1=O)c1ccc(cc1)C(N)=N,MAFPPRRRLRLGPRGLPLLLSGLLLPLCRAFNLDVDSPAEYSGPEGSYFGFAVDFFVPSASSRMFLLVGAPKANTTQPGIVEGGQVLKCDWSSTRRCQPIEFDATGNRDYAKDDPLEFKSHQWFGASVRSKQDKILACAPLYHWRTEMKQEREPVGTCFLQDGTKTVEYAPCRSQDIDADGQGFCQGGFSIDFTKADRVLLGGPGSFYWQGQLISDQVAEIVSKYDPNVYSIKYNNQLATRTAQAIFDDSYLGYSVAVGDFNGDGIDDFVSGVPRAARTLGMVYIYDGKNMSSLYNFTGEQMAAYFGFSVAATDINGDDYADVFIGAPLFMDRGSDGKLQEVGQVSVSLQRASGDFQTTKLNGFEVFARFGSAIAPLGDLDQDGFNDIAIAAPYGGEDKKGIVYIFNGRSTGLNAVPSQILEGQWAARSMPPSFGYSMKGATDIDKNGYPDLIVGAFGVDRAILYRARPVITVNAGLEVYPSILNQDNKTCSLPGTALKVSCFNVRFCLKADGKGVLPRKLNFQVELLLDKLKQKGAIRRALFLYSRSPSHSKNMTISRGGLMQCEELIAYLRDESEFRDKLTPITIFMEYRLDYRTAADTTGLQPILNQFTPANISRQAHILLDCGEDNVCKPKLEVSVDSDQKKIYIGDDNPLTLIVKAQNQGEGAYEAELIVSIPLQADFIGVVRNNEALARLSCAFKTENQTRQVVCDLGNPMKAGTQLLAGLRFSVHQQSEMDTSVKFDLQIQSSNLFDKVSPVVSHKVDLAVLAAVEIRGVSSPDHVFLPIPNWEHKENPETEEDVGPVVQHIYELRNNGPSSFSKAMLHLQWPYKYNNNTLLYILHYDIDGPMNCTSDMEINPLRIKISSLQTTEKNDTVAGQGERDHLITKRDLALSEGDIHTLGCGVAQCLKIVCQVGRLDRGKSAILYVKSLLWTETFMNKENQNHSYSLKSSASFNVIEFPYKNLPIEDITNSTLVTTNVTWGIQPAPMPVPVWVIILAVLAGLLLLAVLVFVMYRMGFFKRVRPPQEEQEREQLQPHENGEGNSET,3.0 +CC(N1CCC(CC1)n1c2cccc(Cl)c2[nH]c1=O)c1ccc(Br)cc1F,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,8.397940008672037 +Cn1ncc2cccc(-n3nc(COC(C)(C)C(O)=O)cc3-c3cccc(OC4CC4)c3)c12,MGGAVVDEGPTGVKAPDGGWGWAVLFGCFVITGFSYAFPKAVSVFFKELIQEFGIGYSDTAWISSILLAMLYGTGPLCSVCVNRFGCRPVMLVGGLFASLGMVAASFCRSIIQVYLTTGVITGLGLALNFQPSLIMLNRYFSKRRPMANGLAAAGSPVFLCALSPLGQLLQDRYGWRGGFLILGGLLLNCCVCAALMRPLVVTAQPGSGPPRPSRRLLDLSVFRDRGFVLYAVAASVMVLGLFVPPVFVVSYAKDLGVPDTKAAFLLTILGFIDIFARPAAGFVAGLGKVRPYSVYLFSFSMFFNGLADLAGSTAGDYGGLVVFCIFFGISYGMVGALQFEVLMAIVGTHKFSSAIGLVLLMEAVAVLVGPPSGGKLLDATHVYMYVFILAGAEVLTSSLILLLGNFFCIRKKPKEPQPEVAAAEEEKLHKPPADSGVDLREVEHFLKAEPEKNGEVVHTPETSV,7.769551078621726 +CCc1cc2c(cc1C(=C)c1ccc(cc1)C(O)=O)C(C)(C)CCC2(C)C,MYGNYSHFMKFPTGFGGSPGHTGSTSMSPSVALPTGKPMDSHPSYTDTPVSAPRTLSAVGTPLNALGSPYRVITSAMGPPSGALAAPPGINLVAPPSSQLNVVNSVSSSEDIKPLPGLPGIGNMNYPSTSPGSLVKHICAICGDRSSGKHYGVYSCEGCKGFFKRTIRKDLIYTCRDNKDCLIDKRQRNRCQYCRYQKCLVMGMKREAVQEERQRSRERAESEAECASSSHEDMPVERILEAELAVEPKTESYGDMNVENSTNDPVTNICHAADKQLFTLVEWAKRIPHFSDLTLEDQVILLRAGWNELLIASFSHRSVSVQDGILLATGLHVHRSSAHSAGVGSIFDRVLTELVSKMKDMQMDKSELGCLRAIVLFNPDAKGLSNPSEVETLREKVYATLEAYTKQKYPEQPGRFAKLLLRLPALRSIGLKCLEHLFFFKLIGDTPIDSFLMEMLETPLQIT,6.866461091629782 +CC(C)(CC(=O)N1CCN(CC1)c1ccc(Cl)cc1)CC1=Nc2ccccc2S(=O)(=O)N1,MGPTSVPLVKAHRSSVSDYVNYDIIVRHYNYTGKLNISADKENSIKLTSVVFILICCFIILENIFVLLTIWKTKKFHRPMYYFIGNLALSDLLAGVAYTANLLLSGATTYKLTPAQWFLREGSMFVALSASVFSLLAIAIERYITMLKMKLHNGSNNFRLFLLISACWVISLILGGLPIMGWNCISALSSCSTVLPLYHKHYILFCTTVFTLLLLSIVILYCRIYSLVRTRSRRLTFRKNISKASRSSEKSLALLKTVIIVLSVFIACWAPLFILLLLDVGCKVKTCDILFRAEYFLVLAVLNSGTNPIIYTLTNKEMRRAFIRIMSCCKCPSGDSAGKFKRPIIAGMEFSRSKSDNSSHPQKDEGDNPETIMSSGNVNSSS,5.003181978120485 +CC1(C)CN(CCO1)c1ncc(cn1)-c1nc2ccncc2n1-c1ccc(F)cc1,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,5.0 +COc1cc2c(Nc3cc(ccc3Br)C(F)(F)F)ncnc2cc1O[C@@H]1CO[C@H]2[C@H](F)CO[C@@H]12,MELRVLLCWASLAAALEETLLNTKLETADLKWVTFPQVDGQWEELSGLDEEQHSVRTYEVCDVQRAPGQAHWLRTGWVPRRGAVHVYATLRFTMLECLSLPRAGRSCKETFTVFYYESDADTATALTPAWMENPYIKVDTVAAEHLTRKRPGAEATGKVNVKTLRLGPLSKAGFYLAFQDQGACMALLSLHLFYKKCAQLTVNLTRFPETVPRELVVPVAGSCVVDAVPAPGPSPSLYCREDGQWAEQPVTGCSCAPGFEAAEGNTKCRACAQGTFKPLSGEGSCQPCPANSHSNTIGSAVCQCRVGYFRARTDPRGAPCTTPPSAPRSVVSRLNGSSLHLEWSAPLESGGREDLTYALRCRECRPGGSCAPCGGDLTFDPGPRDLVEPWVVVRGLRPDFTYTFEVTALNGVSSLATGPVPFEPVNVTTDREVPPAVSDIRVTRSSPSSLSLAWAVPRAPSGAVLDYEVKYHEKGAEGPSSVRFLKTSENRAELRGLKRGASYLVQVRARSEAGYGPFGQEHHSQTQLDESEGWREQLALIAGTAVVGVVLVLVVIVVAVLCLRKQSNGREAEYSDKHGQYLIGHGTKVYIDPFTYEDPNEAVREFAKEIDVSYVKIEEVIGAGEFGEVCRGRLKAPGKKESCVAIKTLKGGYTERQRREFLSEASIMGQFEHPNIIRLEGVVTNSMPVMILTEFMENGALDSFLRLNDGQFTVIQLVGMLRGIASGMRYLAEMSYVHRDLAARNILVNSNLVCKVSDFGLSRFLEENSSDPTYTSSLGGKIPIRWTAPEAIAFRKFTSASDAWSYGIVMWEVMSFGERPYWDMSNQDVINAIEQDYRLPPPPDCPTSLHQLMLDCWQKDRNARPRFPQVVSALDKMIRNPASLKIVARENGGASHPLLDQRQPHYSAFGSVGEWLRAIKMGRYEESFAAAGFGSFELVSQISAEDLLRIGVTLAGHQKKILASVQHMKSQAKPGTPGGTGGPAPQY,6.279840696594043 +COC[C@@H](F)CN(CCCCc1ccc2CCCNc2n1)CC[C@H](Nc1ncnc2ccccc12)C(O)=O,MGIELLCLFFLFLGRNDHVQGGCALGGAETCEDCLLIGPQCAWCAQENFTHPSGVGERCDTPANLLAKGCQLNFIENPVSQVEILKNKPLSVGRQKNSSDIVQIAPQSLILKLRPGGAQTLQVHVRQTEDYPVDLYYLMDLSASMDDDLNTIKELGSRLSKEMSKLTSNFRLGFGSFVEKPVSPFVKTTPEEIANPCSSIPYFCLPTFGFKHILPLTNDAERFNEIVKNQKISANIDTPEGGFDAIMQAAVCKEKIGWRNDSLHLLVFVSDADSHFGMDSKLAGIVIPNDGLCHLDSKNEYSMSTVLEYPTIGQLIDKLVQNNVLLIFAVTQEQVHLYENYAKLIPGATVGLLQKDSGNILQLIISAYEELRSEVELEVLGDTEGLNLSFTAICNNGTLFQHQKKCSHMKVGDTASFSVTVNIPHCERRSRHIIIKPVGLGDALELLVSPECNCDCQKEVEVNSSKCHHGNGSFQCGVCACHPGHMGPRCECGEDMLSTDSCKEAPDHPSCSGRGDCYCGQCICHLSPYGNIYGPYCQCDNFSCVRHKGLLCGGNGDCDCGECVCRSGWTGEYCNCTTSTDSCVSEDGVLCSGRGDCVCGKCVCTNPGASGPTCERCPTCGDPCNSKRSCIECHLSAAGQAREECVDKCKLAGATISEEEDFSKDGSVSCSLQGENECLITFLITTDNEGKTIIHSINEKDCPKPPNIPMIMLGVSLAILLIGVVLLCIWKLLVSFHDRKEVAKFEAERSKAKWQTGTNPLYRGSTSTFKNVTYKHREKQKVDLSTDC,7.301029995663981 +CC(C)n1nc(-c2cnc3ccccc3c2)c2c(N)ncnc12,MLEICLKLVGCKSKKGLSSSSSCYLEEALQRPVASDFEPQGLSEAARWNSKENLLAGPSENDPNLFVALYDFVASGDNTLSITKGEKLRVLGYNHNGEWCEAQTKNGQGWVPSNYITPVNSLEKHSWYHGPVSRNAAEYLLSSGINGSFLVRESESSPGQRSISLRYEGRVYHYRINTASDGKLYVSSESRFNTLAELVHHHSTVADGLITTLHYPAPKRNKPTVYGVSPNYDKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSAMEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQESSISDEVEKELGKQGVRGAVSTLLQAPELPTKTRTSRRAAEHRDTTDVPEMPHSKGQGESDPLDHEPAVSPLLPRKERGPPEGGLNEDERLLPKDKKTNLFSALIKKKKKTAPTPPKRSSSFREMDGQPERRGAGEEEGRDISNGALAFTPLDTADPAKSPKPSNGAGVPNGALRESGGSGFRSPHLWKKSSTLTSSRLATGEEEGGGSSSKRFLRSCSASCVPHGAKDTEWRSVTLPRDLQSTGRQFDSSTFGGHKSEKPALPRKRAGENRSDQVTRGTVTPPPRLVKKNEEAADEVFKDIMESSPGSSPPNLTPKPLRRQVTVAPASGLPHKEEAGKGSALGTPAAAEPVTPTSKAGSGAPGGTSKGPAEESRVRRHKHSSESPGRDKGKLSRLKPAPPPPPAASAGKAGGKPSQSPSQEAAGEAVLGAKTKATSLVDAVNSDAAKPSQPGEGLKKPVLPATPKPQSAKPSGTPISPAPVPSTLPSASSALAGDQPSSTAFIPLISTRVSLRKTRQPPERIASGAITKGVVLDSTEALCLAISRNSEQMASHSAVLEAGKNLYTFCVSYVDSIQQMRNKFAFREAINKLENNLRELQICPATAGSGPAATQDFSKLLSSVKEISDIVQR,5.769551078621726 +CC(C)(C)NC(=O)[C@@H]1CN(Cc2cccnc2)CCN1C[C@@H](O)C[C@@H](Cc1ccccc1)C(=O)N[C@@H]1[C@H](O)Cc2ccccc12,MEAPEEPAPVRGGPEATLEVRGSRCLRLSAFREELRALLVLAGPAFLVQLMVFLISFISSVFCGHLGKLELDAVTLAIAVINVTGVSVGFGLSSACDTLISQTYGSQNLKHVGVILQRSALVLLLCCFPCWALFLNTQHILLLFRQDPDVSRLTQTYVTIFIPALPATFLYMLQVKYLLNQGIVLPQIVTGVAANLVNALANYLFLHQLHLGVIGSALANLISQYTLALLLFLYILGKKLHQATWGGWSLECLQDWASFLRLAIPSMLMLCMEWWAYEVGSFLSGILGMVELGAQSIVYELAIIVYMVPAGFSVAASVRVGNALGAGDMEQARKSSTVSLLITVLFAVAFSVLLLSCKDHVGYIFTTDRDIINLVAQVVPIYAVSHLFEALACTSGGVLRGSGNQKVGAIVNTIGYYVVGLPIGIALMFATTLGVMGLWSGIIICTVFQAVCFLGFIIQLNWKKACQQAQVHANLKVNNVPRSGNSALPQDPLHPGCPENLEGILTNDVGKTGEPQSDQQMRQEEPLPEHPQDGAKLSRKQLVLRRGLLLLGVFLILLVGILVRFYVRIQ,5.769551078621726 +C\C(\C=C\C1=C(C)CCCC1(C)C)=C/C=C/C(/C)=C/C(O)=O,MDTKHFLPLDFSTQVNSSLTSPTGRGSMAAPSLHPSLGPGIGSPGQLHSPISTLSSPINGMGPPFSVISSPMGPHSMSVPTTPTLGFSTGSPQLSSPMNPVSSSEDIKPPLGLNGVLKVPAHPSGNMASFTKHICAICGDRSSGKHYGVYSCEGCKGFFKRTVRKDLTYTCRDNKDCLIDKRQRNRCQYCRYQKCLAMGMKREAVQEERQRGKDRNENEVESTSSANEDMPVERILEAELAVEPKTETYVEANMGLNPSSPNDPVTNICQAADKQLFTLVEWAKRIPHFSELPLDDQVILLRAGWNELLIASFSHRSIAVKDGILLATGLHVHRNSAHSAGVGAIFDRVLTELVSKMRDMQMDKTELGCLRAIVLFNPDSKGLSNPAEVEALREKVYASLEAYCKHKYPEQPGRFAKLLLRLPALRSIGLKCLEHLFFFKLIGDTPIDTFLMEMLEAPHQMT,9.397940008672037 +CC(C)n1nnc(n1)-c1o[nH]c(=O)c1CC(N)C(O)=O,MKIISPVLSNLVFSRSIKVLLCLLWIGYSQGTTHVLRFGGIFEYVESGPMGAEELAFRFAVNTINRNRTLLPNTTLTYDTQKINLYDSFEASKKACDQLSLGVAAIFGPSHSSSANAVQSICNALGVPHIQTRWKHQVSDNKDSFYVSLYPDFSSLSRAILDLVQFFKWKTVTVVYDDSTGLIRLQELIKAPSRYNLRLKIRQLPADTKDAKPLLKEMKRGKEFHVIFDCSHEMAAGILKQALAMGMMTEYYHYIFTTLDLFALDVEPYRYSGVNMTGFRILNTENTQVSSIIEKWSMERLQAPPKPDSGLLDGFMTTDAALMYDAVHVVSVAVQQFPQMTVSSLQCNRHKPWRFGTRFMSLIKEAHWEGLTGRITFNKTNGLRTDFDLDVISLKEEGLEKIGTWDPASGLNMTESQKGKPANITDSLSNRSLIVTTILEEPYVLFKKSDKPLYGNDRFEGYCIDLLRELSTILGFTYEIRLVEDGKYGAQDDVNGQWNGMVRELIDHKADLAVAPLAITYVREKVIDFSKPFMTLGISILYRKPNGTNPGVFSFLNPLSPDIWMYILLAYLGVSCVLFVIARFSPYEWYNPHPCNPDSDVVENNFTLLNSFWFGVGALMQQGSELMPKALSTRIVGGIWWFFTLIIISSYTANLAAFLTVERMESPIDSADDLAKQTKIEYGAVEDGATMTFFKKSKISTYDKMWAFMSSRRQSVLVKSNEEGIQRVLTSDYAFLMESTTIEFVTQRNCNLTQIGGLIDSKGYGVGTPMGSPYRDKITIAILQLQEEGKLHMMKEKWWRGNGCPEEESKEASALGVQNIGGIFIVLAAGLVLSVFVAVGEFLYKSKKNAQLEKRSFCSAMVEELRMSLKCQRRLKHKPQAPVIVKTEEVINMHTFNDRRLPGKETMA,7.0 +Cn1cc(cn1)-c1cc(-c2ccc(nc2)N2CCC3(CN(Cc4ccccc4)C3)C2)c2c(cnn2c1)C#N,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,7.920818753952375 +C[C@@H](O)[C@H]1COC(=O)N1c1ccnc(N[C@@H](C)c2ccccc2)n1,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGRHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,5.85078088734462 +OC(=O)c1ccc(cc1)-n1ncc(C(=O)NC2C3CC4CC(C3)CC2C4)c1SC1CCCC1,MAFMKKYLLPILGLFMAYYYYSANEEFRPEMLQGKKVIVTGASKGIGREMAYHLAKMGAHVVVTARSKETLQKVVSHCLELGAASAHYIAGTMEDMTFAEQFVAQAGKLMGGLDMLILNHITNTSLNLFHDDIHHVRKSMEVNFLSYVVLTVAALPMLKQSNGSIVVVSSLAGKVAYPMVAAYSASKFALDGFFSSIRKEYSVSRVNVSITLCVLGLIDTETAMKAVSGIVHMQAAPKEECALEIIKGGALRQEEVYYDSSLWTTLLIRNPCRKILEFLYSTSYNMDRFINK,8.301029995663981 +CCC(=O)c1cnc2c(OCCOC)cccc2c1Nc1ccc(F)cc1C,MAALQEKKSCSQRMEEFQRYCWNPDTGQMLGRTLSRWVWISLYYVAFYVVMSGIFALCIYVLMRTIDPYTPDYQDQLKSPGVTLRPDVYGEKGLDISYNVSDSTTWAGLAHTLHRFLAGYSPAAQEGSINCTSEKYFFQESFLAPNHTKFSCKFTADMLQNCSGRPDPTFGFAEGKPCFIIKMNRIVKFLPGNSTAPRVDCAFLDQPRDGPPLQVEYFPANGTYSLHYFPYYGKKAQPHYSNPLVAAKLLNVPRNRDVVIVCKILAEHVSFDNPHDPYEGKVEFKLKIQK,5.698970004336019 +CCC(C)Nc1nc2ccccc2c(=O)o1,MTLGRRLACLFLACVLPALLLGGTALASEIVGGRRARPHAWPFMVSLQLRGGHFCGATLIAPNFVMSAAHCVANVNVRAVRVVLGAHNLSRREPTRQVFAVQRIFENGYDPVNLLNDIVILQLNGSATINANVQVAQLPAQGRRLGNGVQCLAMGWGLLGRNRGIASVLQELNVTVVTSLCRRSNVCTLVRGRQAGVCFGDSGSPLVCNGLIHGIASFVRGGCASGLYPDAFAPVAQFVNWIDSIIQRSEDNPCPHPRDPDPASRTH,7.366531544420414 +On1cc(C2CCNCC2)c(n1)-c1ccc(cc1)-c1ccccc1,MRKSPGLSDCLWAWILLLSTLTGRSYGQPSLQDELKDNTTVFTRILDRLLDGYDNRLRPGLGERVTEVKTDIFVTSFGPVSDHDMEYTIDVFFRQSWKDERLKFKGPMTVLRLNNLMASKIWTPDTFFHNGKKSVAHNMTMPNKLLRITEDGTLLYTMRLTVRAECPMHLEDFPMDAHACPLKFGSYAYTRAEVVYEWTREPARSVVVAEDGSRLNQYDLLGQTVDSGIVQSSTGEYVVMTTHFHLKRKIGYFVIQTYLPCIMTVILSQVSFWLNRESVPARTVFGVTTVLTMTTLSISARNSLPKVAYATAMDWFIAVCYAFVFSALIEFATVNYFTKRGYAWDGKSVVPEKPKKVKDPLIKKNNTYAPTATSYTPNLARGDPGLATIAKSATIEPKEVKPETKPPEPKKTFNSVSKIDRLSRIAFPLLFGIFNLVYWATYLNREPQLKAPTPHQ,5.853871964321762 +Nc1ccccc1NC(=O)\C=C\c1sc(nc1-c1ccc(Cl)cc1)N1CCOCC1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,4.0 +Cc1cc(O)cc2ncn(-c3ccc(O)cc3)c(=S)c12,MTMTLHTKASGMALLHQIQGNELEPLNRPQLKIPLERPLGEVYLDSSKPAVYNYPEGAAYEFNAAAAANAQVYGQTGLPYGPGSEAAAFGSNGLGGFPPLNSVSPSPLMLLHPPPQLSPFLQPHGQQVPYYLENEPSGYTVREAGPPAFYRPNSDNRRQGGRERLASTNDKGSMAMESAKETRYCAVCNDYASGYHYGVWSCEGCKAFFKRSIQGHNDYMCPATNQCTIDKNRRKSCQACRLRKCYEVGMMKGGIRKDRRGGRMLKHKRQRDDGEGRGEVGSAGDMRAANLWPSPLMIKRSKKNSLALSLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNLADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLLLDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSLEEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMKCKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAEGFPATV,5.7667499904589 +Cc1cc(OCC(=O)Nc2nnc[nH]2)ccc1Cl,MQGDWVLLLLLGLRIHLSFGVIPVEEENPVFWNQKAKEALDVAKKLQPIQTSAKNLILFLGDGMGVPTVTATRILKGQLGGHLGPETPLAMDHFPFTALSKTYNVDRQVPDSAGTATAYLCGVKANYKTIGVSAAARFNQCNSTFGNEVFSVMHRAKKAGKSVGVVTTTRVQHASPAGTYAHTVNRDWYSDADMPSSALQEGCKDIATQLISNMDIDVILGGGRKFMFPKGTPDPEYPGDSDQSGVRLDSRNLVEEWLAKYQGTRYVWNREQLMQASQDPAVTRLMGLFEPTEMKYDVNRNASADPSLAEMTEVAVRLLSRNPQGFYLFVEGGRIDQGHHAGTAYLALTEAVMFDSAIEKASQLTNEKDTLTLITADHSHVFAFGGYTLRGTSIFGLAPLNAQDGKSYTSILYGNGPGYVLNSGNRPNVTDAESGDVNYKQQAAVPLSSETHGGEDVAIFARGPQAHLVHGVQEQNYIAHVMAFAGCLEPYTDCGLAPPADENRPTTPVQNSAITMNNVLLSLQLLVSMLLLVGTALVVS,4.0 +CN1C(CCC1=O)c1cc2[nH]c(cc2cc1Oc1ccc(nc1)S(C)(=O)=O)-c1ccccn1,MLDDRARMEAAKKEKVEQILAEFQLQEEDLKKVMRRMQKEMDRGLRLETHEEASVKMLPTYVRSTPEGSEVGDFLSLDLGGTNFRVMLVKVGEGEEGQWSVKTKHQMYSIPEDAMTGTAEMLFDYISECISDFLDKHQMKHKKLPLGFTFSFPVRHEDIDKGILLNWTKGFKASGAEGNNVVGLLRDAIKRRGDFEMDVVAMVNDTVATMISCYYEDHQCEVGMIVGTGCNACYMEEMQNVELVEGDEGRMCVNTEWGAFGDSGELDEFLLEYDRLVDESSANPGQQLYEKLIGGKYMGELVRLVLLRLVDENLLFHGEASEQLRTRGAFETRFVSQVESDTGDRKQIYNILSTLGLRPSTTDCDIVRRACESVSTRAAHMCSAGLAGVINRMRESRSEDVMRITVGVDGSVYKLHPSFKERFHASVRRLTPSCEITFIESEEGSGRGAALVSAVACKKACMLGQ,8.3767507096021 +FC1(F)CN(C(=O)CC#N)C11CCN(C1)c1ncnc2[nH]ccc12,MAPPSEETPLIPQRSCSLLSTEAGALHVLLPARGPGPPQRLSFSFGDHLAEDLCVQAAKASGILPVYHSLFALATEDLSCWFPPSHIFSVEDASTQVLLYRIRFYFPNWFGLEKCHRFGLRKDLASAILDLPVLEHLFAQHRSDLVSGRLPVGLSLKEQGECLSLAVLDLARMAREQAQRPGELLKTVSYKACLPPSLRDLIQGLSFVTRRRIRRTVRRALRRVAACQADRHSLMAKYIMDLERLDPAGAAETFHVGLPGALGGHDGLGLLRVAGDGGIAWTQGEQEVLQPFCDFPEIVDISIKQAPRVGPAGEHRLVTVTRTDNQILEAEFPGLPEALSFVALVDGYFRLTTDSQHFFCKEVAPPRLLEEVAEQCHGPITLDFAINKLKTGGSRPGSYVLRRSPQDFDSFLLTVCVQNPLGPDYKGCLIRRSPTGTFLLVGLSRPHSSLRELLATCWDGGLHVDGVAVTLTSCCIPRPKEKSNLIVVQRGHSPPTSSLVQPQSQYQLSQMTFHKIPADSLEWHENLGHGSFTKIYRGCRHEVVDGEARKTEVLLKVMDAKHKNCMESFLEAASLMSQVSYRHLVLLHGVCMAGDSTMVQEFVHLGAIDMYLRKRGHLVPASWKLQVVKQLAYALNYLEDKGLPHGNVSARKVLLAREGADGSPPFIKLSDPGVSPAVLSLEMLTDRIPWVAPECLREAQTLSLEADKWGFGATVWEVFSGVTMPISALDPAKKLQFYEDRQQLPAPKWTELALLIQQCMAYEPVQRPSFRAVIRDLNSLISSDYELLSDPTPGALAPRDGLWNGAQLYACQDPTIFEERHLKYISQLGKGNFGSVELCRYDPLGDNTGALVAVKQLQHSGPDQQRDFQREIQILKALHSDFIVKYRGVSYGPGRQSLRLVMEYLPSGCLRDFLQRHRARLDASRLLLYSSQICKGMEYLGSRRCVHRDLAARNILVESEAHVKIADFGLAKLLPLDKDYYVVREPGQSPIFWYAPESLSDNIFSRQSDVWSFGVVLYELFTYCDKSCSPSAEFLRMMGCERDVPALCRLLELLEEGQRLPAPPACPAEVHELMKLCWAPSPQDRPSFSALGPQLDMLWSGSRGCETHAFTAHPEGKHHSLSFS,7.958607314841775 +Cc1ccc(cc1-c1ccc2cn[nH]c2c1)C(=O)Nc1cccc(c1)C(C)(C)C#N,MILIPRMLLVLFLLLPILSSAKAQVNPAICRYPLGMSGGQIPDEDITASSQWSESTAAKYGRLDSEEGDGAWCPEIPVEPDDLKEFLQIDLHTLHFITLVGTQGRHAGGHGIEFAPMYKINYSRDGTRWISWRNRHGKQVLDGNSNPYDIFLKDLEPPIVARFVRFIPVTDHSMNVCMRVELYGCVWLDGLVSYNAPAGQQFVLPGGSIIYLNDSVYDGAVGYSMTEGLGQLTDGVSGLDDFTQTHEYHVWPGYDYVGWRNESATNGYIEIMFEFDRIRNFTTMKVHCNNMFAKGVKIFKEVQCYFRSEASEWEPNAISFPLVLDDVNPSARFVTVPLHHRMASAIKCQYHFADTWMMFSEITFQSDAAMYNNSEALPTSPMAPTTYDPMLKVDDSNTRILIGCLVAIIFILLAIIVIILWRQFWQKMLEKASRRMLDDEMTVSLSLPSDSSMFNNNRSSSPSEQGSNSTYDRIFPLRPDYQEPSRLIRKLPEFAPGEEESGCSGVVKPVQPSGPEGVPHYAEADIVNLQGVTGGNTYSVPAVTMDLLSGKDVAVEEFPRKLLTFKEKLGEGQFGEVHLCEVEGMEKFKDKDFALDVSANQPVLVAVKMLRADANKNARNDFLKEIKIMSRLKDPNIIHLLAVCITDDPLCMITEYMENGDLNQFLSRHEPPNSSSSDVRTVSYTNLKFMATQIASGMKYLSSLNFVHRDLATRNCLVGKNYTIKIADFGMSRNLYSGDYYRIQGRAVLPIRWMSWESILLGKFTTASDVWAFGVTLWETFTFCQEQPYSQLSDEQVIENTGEFFRDQGRQTYLPQPAICPDSVYKLMLSCWRRDTKNRPSFQEIHLLLLQQGDE,8.568636235841012 +Fc1cnc(Nc2ccccc2)nc1NC1CCN(CC1)C(=O)C=C,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,6.0 +NC1=N[C@](c2cccc(F)c12)(c1ccncc1)c1cccc(c1)-c1cncnc1,MAPALHWLLLWVGSGMLPAQGTHLGIRLPLRSGLAGPPLGLRLPRETDEESEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHIPNIFSLQLCGAGFPLNQTEALASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAVSQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTADMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRHQHDDFADDISLLK,7.167491087293763 +COc1ccccc1N1CCN(CCCOc2ccc(cc2OCc2ccccc2)C(=O)Nc2ccccc2OCCCC(O)=O)CC1,MVPLMELDELCLLDMLVYLEGFMAFVSIVGLRSVGSPYGRYSPQWPGIRVPARPAWFIQELPSMAWPLYEYIRPAAARLGNLPNRVLLAMFLIHYVQRTLVFPVLIRGGKPTLLVTFVLAFLFCTFNGYVQSRYLSQFAVYAEDWVTHPCFLTGFALWLVGMVINIHSDHILRNLRKPGETGYKIPRGGLFEYVSAANYFGELVEWCGFALASWSLQGVVFALFTLSTLLTRAKQHHQWYHEKFEDYPKSRKILIPFVL,5.455931955649724 +Cc1cccc(CN2C3N(CCC3(Cc3cccc(C)c3)c3ccccc23)C(=O)c2ccccc2C)c1,MKILDALLFPVIFIMFFIHLSIAQTDPELTIMTRLGQVQGTRLPVPDRSHVIAFLGIPFAEPPLGKMRFKPPEPKKPWNDVFDARDYPSACYQYVDTSYPGFSGTEMWNPNRMMSEDCLYLNVWVPATPRPHNLTVMVWIYGGGFYSGSSSLDVYDGRYLAHSEKVVVVSMNYRVSAFGFLALNGSAEAPGNVGLLDQRLALQWVQDNIHFFGGNPKQVTIFGESAGAASVGMHLLSPDSRPKFTRAILQSGVPNGPWRTVSFDEARRRAIKLGRLVGCPDGNDTDLIDCLRSKQPQDLIDQEWLVLPFSGLFRFSFVPVIDGVVFPDTPEAMLNSGNFKDTQILLGVNQNEGSYFLIYGAPGFSKDNESLITREDFLQGVKMSVPHANEIGLEAVILQYTDWMDEDNPIKNREAMDDIVGDHNVVCPLQHFAKMYAQYSILQGQTGTASQGNLGWGNSGSASNSGNSQVSVYLYMFDHRASNLVWPEWMGVIHGYEIEFVFGLPLEKRLNYTLEEEKLSRRMMKYWANFARTGNPNINVDGSIDSRRRWPVFTSTEQKHVGLNTDSLKVHKGLKSQFCALWNRFLPRLLNVTENIDDAERQWKAEFHRWSSYMMHWKNQFDHYSKQERCTNL,7.267606240177031 +CN(C)C(=O)Cc1c(nc2ccc(C)cn12)-c1ccc(C)cc1,MKTKLNIYNMQFLLFVFLVWDPARLVLANIQEDEAKNNITIFTRILDRLLDGYDNRLRPGLGDSITEVFTNIYVTSFGPVSDTDMEYTIDVFFRQKWKDERLKFKGPMNILRLNNLMASKIWTPDTFFHNGKKSVAHNMTMPNKLLRIQDDGTLLYTMRLTVQAECPMHLEDFPMDAHSCPLKFGSYAYTTSEVTYIWTYNASDSVQVAPDGSRLNQYDLLGQSIGKETIKSSTGEYTVMTAHFHLKRKIGYFVIQTYLPCIMTVILSQVSFWLNRESVPARTVFGVTTVLTMTTLSISARNSLPKVAYATAMDWFIAVCYAFVFSALIEFATVNYFTKRGWAWDGKSVVNDKKKEKASVMIQNNAYAVAVANYAPNLSKDPVLSTISKSATTPEPNKKPENKPAEAKKTFNSVSKIDRMSRIVFPVLFGTFNLVYWATYLNREPVLGVSP,-0.2552725051033062 +NC(=O)C1CCCc2c1[nH]c1ccc(Cl)cc21,MADEAALALQPGGSPSAAGADREAASSPAGEPLRKRPRRDGPGLERSPGEPGGAAPEREVPAAARGCPGAAAAALWREAEAEAAAAGGEQEAQATAAAGEGDNGPGLQGPSREPPLADNLYDEDDDDEGEEEEEAAAAAIGYRDNLLFGDEIITNGFHSCESDEEDRASHASSSDWTPRPRIGPYTFVQQHLMIGTDPRTILKDLLPETIPPPELDDMTLWQIVINILSEPPKRKKRKDINTIEDAVKLLQECKKIIVLTGAGVSVSCGIPDFRSRDGIYARLAVDFPDLPDPQAMFDIEYFRKDPRPFFKFAKEIYPGQFQPSLCHKFIALSDKEGKLLRNYTQNIDTLEQVAGIQRIIQCHGSFATASCLICKYKVDCEAVRGDIFNQVVPRCPRCPADEPLAIMKPEIVFFGENLPEQFHRAMKYDKDEVDLLIVIGSSLKVRPVALIPSSIPHEVPQILINREPLPHLHFDVELLGDCDVIINELCHRLGGEYAKLCCNPVKLSEITEKPPRTQKELAYLSELPPTPLHVSEDSSSPERTSPPDSSVIVTLLDQAAKSNDDLDVSESKGCMEEKPQEVQTSRNVESIAEQMENPDLKNVGSSTGEKNERTSVAGTVRKCWPNRVAKEQISRRLDGNQYLFLPPNRYIFHGAEVYSDSEDDVLSSSSCGSNSDSGTCQSPSLEEPMEDESEIEEFYNGLEDEPDVPERAGGAGFGTDGDDQEAINEAISVKQEVTDMNYPSNKS,4.008773924307505 +NCCCCCN1C(CC(=O)NCc2ccccc2)c2ccccc2N=C1Nc1ccc(cc1)-c1ccccc1,MDEEEDGAGAEESGQPRSFMRLNDLSGAGGRPGPGSAEKDPGSADSEAEGLPYPALAPVVFFYLSQDSRPRSWCLRTVCNPWFERISMLVILLNCVTLGMFRPCEDIACDSQRCRILQAFDDFIFAFFAVEMVVKMVALGIFGKKCYLGDTWNRLDFFIVIAGMLEYSLDLQNVSFSAVRTVRVLRPLRAINRVPSMRILVTLLLDTLPMLGNVLLLCFFVFFIFGIVGVQLWAGLLRNRCFLPENFSLPLSVDLERYYQTENEDESPFICSQPRENGMRSCRSVPTLRGDGGGGPPCGLDYEAYNSSSNTTCVNWNQYYTNCSAGEHNPFKGAINFDNIGYAWIAIFQVITLEGWVDIMYFVMDAHSFYNFIYFILLIIVGSFFMINLCLVVIATQFSETKQRESQLMREQRVRFLSNASTLASFSEPGSCYEELLKYLVYILRKAARRLAQVSRAAGVRVGLLSSPAPLGGQETQPSSSCSRSHRRLSVHHLVHHHHHHHHHYHLGNGTLRAPRASPEIQDRDANGSRRLMLPPPSTPALSGAPPGGAESVHSFYHADCHLEPVRCQAPPPRSPSEASGRTVGSGKVYPTVHTSPPPETLKEKALVEVAASSGPPTLTSLNIPPGPYSSMHKLLETQSTGACQSSCKISSPCLKADSGACGPDSCPYCARAGAGEVELADREMPDSDSEAVYEFTQDAQHSDLRDPHSRRQRSLGPDAEPSSVLAFWRLICDTFRKIVDSKYFGRGIMIAILVNTLSMGIEYHEQPEELTNALEISNIVFTSLFALEMLLKLLVYGPFGYIKNPYNIFDGVIVVISVWEIVGQQGGGLSVLRTFRLMRVLKLVRFLPALQRQLVVLMKTMDNVATFCMLLMLFIFIFSILGMHLFGCKFASERDGDTLPDRKNFDSLLWAIVTVFQILTQEDWNKVLYNGMASTSSWAALYFIALMTFGNYVLFNLLVAILVEGFQAEEISKREDASGQLSCIQLPVDSQGGDANKSESEPDFFSPSLDGDGDRKKCLALVSLGEHPELRKSLLPPLIIHTAATPMSLPKSTSTGLGEALGPASRRTSSSGSAEPGAAHEMKSPPSARSSPHSPWSAASSWTSRRSSRNSLGRAPSLKRRSPSGERRSLLSGEGQESQDEEESSEEERASPAGSDHRHRGSLEREAKSSFDLPDTLQVPGLHRTASGRGSASEHQDCNGKSASGRLARALRPDDPPLDGDDADDEGNLSKGERVRAWIRARLPACCLERDSWSAYIFPPQSRFRLLCHRIITHKMFDHVVLVIIFLNCITIAMERPKIDPHSAERIFLTLSNYIFTAVFLAEMTVKVVALGWCFGEQAYLRSSWNVLDGLLVLISVIDILVSMVSDSGTKILGMLRVLRLLRTLRPLRVISRAQGLKLVVETLMSSLKPIGNIVVICCAFFIIFGILGVQLFKGKFFVCQGEDTRNITNKSDCAEASYRWVRHKYNFDNLGQALMSLFVLASKDGWVDIMYDGLDAVGVDQQPIMNHNPWMLLYFISFLLIVAFFVLNMFVGVVVENFHKCRQHQEEEEARRREEKRLRRLEKKRRNLMLDDVIASGSSASAASEAQCKPYYSDYSRFRLLVHHLCTSHYLDLFITGVIGLNVVTMAMEHYQQPQILDEALKICNYIFTVIFVLESVFKLVAFGFRRFFQDRWNQLDLAIVLLSIMGITLEEIEVNASLPINPTIIRIMRVLRIARVLKLLKMAVGMRALLDTVMQALPQVGNLGLLFMLLFFIFAALGVELFGDLECDETHPCEGLGRHATFRNFGMAFLTLFRVSTGDNWNGIMKDTLRDCDQESTCYNTVISPIYFVSFVLTAQFVLVNVVIAVLMKHLEESNKEAKEEAELEAELELEMKTLSPQPHSPLGSPFLWPGVEGPDSPDSPKPGALHPAAHARSASHFSLEHPTDRQLFDTISLLIQGSLEWELKLMDELAGPGGQPSAFPSAPSLGGSDPQIPLAEMEALSLTSEIVSEPSCSLALTDDSLPDDMHTLLLSALESNMQPHPTELPGPDLLTVRKSGVSRTHSLPNDSYMCRHGSTAEGPLGHRGWGLPKAQSGSVLSVHSQPADTSYILQLPKDAPHLLQPHSAPTWGTIPKLPPPGRSPLAQRPLRRQAAIRTDSLDVQGLGSREDLLAEVSGPSPPLARAYSFWGQSSTQAQQHSRSHSKISKHMTPPAPCPGPEPNWGKGPPETRSSLELDTELSWISGDLLPPGGQEEPPSPRDLKKCYSVEAQSCQRRPTSWLDEQRRHSIAVSCLDSGSQPHLGTDPSNLGGQPLGGPGSRPKKKLSPPSITIDPPESQGPRTPPSPGICLRRRAPSSDSKDPLASGPPDSMAASPSPKKDVLSLSGLSSDPADLDP,6.853871964321762 +COc1cn(C(Cc2cnco2)C(=O)Nc2cnc(C(N)=O)c(F)c2)c(=O)cc1-c1cc(Cl)ccc1C#N,MIFLYQVVHFILFTSVSGECVTQLLKDTCFEGGDITTVFTPSAKYCQVVCTYHPRCLLFTFTAESPSEDPTRWFTCVLKDSVTETLPRVNRTAAISGYSFKQCSHQISACNKDIYVDLDMKGINYNSSVAKSAQECQERCTDDVHCHFFTYATRQFPSLEHRNICLLKHTQTGTPTRITKLDKVVSGFSLKSCALSNLACIRDIFPNTVFADSNIDSVMAPDAFVCGRICTHHPGCLFFTFFSQEWPKESQRNLCLLKTSESGLPSTRIKKSKALSGFSLQSCRHSIPVFCHSSFYHDTDFLGEELDIVAAKSHEACQKLCTNAVRCQFFTYTPAQASCNEGKGKCYLKLSSNGSPTKILHGRGGISGYTLRLCKMDNECTTKIKPRIVGGTASVRGEWPWQVTLHTTSPTQRHLCGGSIIGNQWILTAAHCFYGVESPKILRVYSGILNQSEIKEDTSFFGVQEIIIHDQYKMAESGYDIALLKLETTVNYTDSQRPICLPSKGDRNVIYTDCWVTGWGYRKLRDKIQNTLQKAKIPLVTNEECQKRYRGHKITHKMICAGYREGGKDACKGDSGGPLSCKHNEVWHLVGITSWGEGCAQRERPGVYTNVVEYVDWILEKTQAV,7.853871964321762 +Cn1cc(ccc1=O)-c1c(Cl)nc(N)n2nc(Cc3c(F)cccc3F)nc12,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,6.801342913045577 +Fc1ccccc1\C=N\Nc1ncc(Cl)c(Nc2cccc(NC(=O)C=C)c2)n1,MKPATGLWVWVSLLVAAGTVQPSDSQSVCAGTENKLSSLSDLEQQYRALRKYYENCEVVMGNLEITSIEHNRDLSFLRSVREVTGYVLVALNQFRYLPLENLRIIRGTKLYEDRYALAIFLNYRKDGNFGLQELGLKNLTEILNGGVYVDQNKFLCYADTIHWQDIVRNPWPSNLTLVSTNGSSGCGRCHKSCTGRCWGPTENHCQTLTRTVCAEQCDGRCYGPYVSDCCHRECAGGCSGPKDTDCFACMNFNDSGACVTQCPQTFVYNPTTFQLEHNFNAKYTYGAFCVKKCPHNFVVDSSSCVRACPSSKMEVEENGIKMCKPCTDICPKACDGIGTGSLMSAQTVDSSNIDKFINCTKINGNLIFLVTGIHGDPYNAIEAIDPEKLNVFRTVREITGFLNIQSWPPNMTDFSVFSNLVTIGGRVLYSGLSLLILKQQGITSLQFQSLKEISAGNIYITDNSNLCYYHTINWTTLFSTINQRIVIRDNRKAENCTAEGMVCNHLCSSDGCWGPGPDQCLSCRRFSRGRICIESCNLYDGEFREFENGSICVECDPQCEKMEDGLLTCHGPGPDNCTKCSHFKDGPNCVEKCPDGLQGANSFIFKYADPDRECHPCHPNCTQGCNGPTSHDCIYYPWTGHSTLPQHARTPLIAAGVIGGLFILVIVGLTFAVYVRRKSIKKKRALRRFLETELVEPLTPSGTAPNQAQLRILKETELKRVKVLGSGAFGTVYKGIWVPEGETVKIPVAIKILNETTGPKANVEFMDEALIMASMDHPHLVRLLGVCLSPTIQLVTQLMPHGCLLEYVHEHKDNIGSQLLLNWCVQIAKGMMYLEERRLVHRDLAARNVLVKSPNHVKITDFGLARLLEGDEKEYNADGGKMPIKWMALECIHYRKFTHQSDVWSYGVTIWELMTFGGKPYDGIPTREIPDLLEKGERLPQPPICTIDVYMVMVKCWMIDADSRPKFKELAAEFSRMARDPQRYLVIQGDDRMKLPSPNDSKFFQNLLDEEDLEDMMDAEEYLVPQAFNIPPPIYTSRARIDSNRSEIGHSPPPAYTPMSGNQFVYRDGGFAAEQGVSVPYRAPTSTIPEAPVAQGATAEIFDDSCCNGTLRKPVAPHVQEDSSTQRYSADPTVFAPERSPRGELDEEGYMTPMRDKPKQEYLNPVEENPFVSRRKNGDLQALDNPEYHNASNGPPKAEDEYVNEPLYLNTFANTLGKAEYLKNNILSMPEKAKKAFDNPDYWNHSLPPRSTLQHPDYLQEYSTKYFYKQNGRIRPIVAENPEYLSEFSLKPGTVLPPPPYRHRNTVV,5.718966632752272 +COc1cccc(OC)c1-c1ccc(C[C@H](NC(=O)C2(CCCNC2)S(=O)(=O)c2ccc(cc2)N2CCCC2)C(O)=O)cc1,MAWEARREPGPRRAAVRETVMLLLCLGVPTGRPYNVDTESALLYQGPHNTLFGYSVVLHSHGANRWLLVGAPTANWLANASVINPGAIYRCRIGKNPGQTCEQLQLGSPNGEPCGKTCLEERDNQWLGVTLSRQPGENGSIVTCGHRWKNIFYIKNENKLPTGGCYGVPPDLRTELSKRIAPCYQDYVKKFGENFASCQAGISSFYTKDLIVMGAPGSSYWTGSLFVYNITTNKYKAFLDKQNQVKFGSYLGYSVGAGHFRSQHTTEVVGGAPQHEQIGKAYIFSIDEKELNILHEMKGKKLGSYFGASVCAVDLNADGFSDLLVGAPMQSTIREEGRVFVYINSGSGAVMNAMETNLVGSDKYAARFGESIVNLGDIDNDGFEDVAIGAPQEDDLQGAIYIYNGRADGISSTFSQRIEGLQISKSLSMFGQSISGQIDADNNGYVDVAVGAFRSDSAVLLRTRPVVIVDASLSHPESVNRTKFDCVENGWPSVCIDLTLCFSYKGKEVPGYIVLFYNMSLDVNRKAESPPRFYFSSNGTSDVITGSIQVSSREANCRTHQAFMRKDVRDILTPIQIEAAYHLGPHVISKRSTEEFPPLQPILQQKKEKDIMKKTINFARFCAHENCSADLQVSAKIGFLKPHENKTYLAVGSMKTLMLNVSLFNAGDDAYETTLHVKLPVGLYFIKILELEEKQINCEVTDNSGVVQLDCSIGYIYVDHLSRIDISFLLDVSSLSRAEEDLSITVHATCENEEEMDNLKHSRVTVAIPLKYEVKLTVHGFVNPTSFVYGSNDENEPETCMVEKMNLTFHVINTGNSMAPNVSVEIMVPNSFSPQTDKLFNILDVQTTTGECHFENYQRVCALEQQKSAMQTLKGIVRFLSKTDKRLLYCIKADPHCLNFLCNFGKMESGKEASVHIQLEGRPSILEMDETSALKFEIRATGFPEPNPRVIELNKDENVAHVLLEGLHHQRPKRYFTIVIISSSLLLGLIVLLLISYVMWKAGFFKRQYKSILQEENRRDSWSYINSKSNDD,9.443697499232712 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+Oc1ccc2C[C@H]3N(CC=C)CC[C@@]45[C@@H](Oc1c24)C(=O)CC[C@@]35O,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,8.301029995663981 +OC(=O)c1ccc(Nc2nc3c(cccn3n2)-c2cnn(c2)C2CCCCC2)cc1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,9.301029995663981 +NS(=O)(=O)c1cc(C(=O)NCc2ccccc2)c(Cl)cc1Cl,MRALVLLLSLFLLGGQAQHVSDWTYSEGALDEAHWPQHYPACGGQRQSPINLQRTKVRYNPSLKGLNMTGYETQAGEFPMVNNGHTVQISLPSTMRMTVADGTVYIAQQMHFHWGGASSEISGSEHTVDGIRHVIEIHIVHYNSKYKSYDIAQDAPDGLAVLAAFVEVKNYPENTYYSNFISHLANIKYPGQRTTLTGLDVQDMLPRNLQHYYTYHGSLTTPPCTENVHWFVLADFVKLSRTQVWKLENSLLDHRNKTIHNDYRRTQPLNHRVVESNFPNQEYTLGSEFQFYLHKIEEILDYLRRALN,6.853871964321762 +N[C@@H](C1CCCCC1)C(=O)N1CCC[C@H]1C#N,MGSAPWAPVLLLALGLRGLQAGARRAPDPGFQERFFQQRLDHFNFERFGNKTFPQRFLVSDRFWVRGEGPIFFYTGNEGDVWAFANNSAFVAELAAERGALLVFAEHRYYGKSLPFGAQSTQRGHTELLTVEQALADFAELLRALRRDLGAQDAPAIAFGGSYGGMLSAYLRMKYPHLVAGALAASAPVLAVAGLGDSNQFFRDVTADFEGQSPKCTQGVREAFRQIKDLFLQGAYDTVRWEFGTCQPLSDEKDLTQLFMFARNAFTVLAMMDYPYPTDFLGPLPANPVKVGCDRLLSEAQRITGLRALAGLVYNASGSEHCYDIYRLYHSCADPTGCGTGPDARAWDYQACTEINLTFASNNVTDMFPDLPFTDELRQRYCLDTWGVWPRPDWLLTSFWGGDLRAASNIIFSNGNLDPWAGGGIRRNLSASVIAVTIQGGAHHLDLRASHPEDPASVVEARKLEATIIGEWVKAARREQQPALRGGPRLSL,4.399321087276388 +CC(C(N)=O)c1ccc(c(F)c1)-c1ccccc1,MSRQSISLRFPLLLLLLSPSPVFSADPGAPAPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPEIWTWLRTTLRPSPSFIHFLLTHGRWLWDFVNATFIRDTLMRLVLTVRSNLIPSPPTYNIAHDYISWESFSNVSYYTRILPSVPRDCPTPMDTKGKKQLPDAEFLSRRFLLRRKFIPDPQSTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQMLNGEVYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATIWLREHNRVCDLLKAEHPTWGDEQLFQTARLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGAQFQYRNRIAMEFNQLYHWHPLMPDSFRVGPQDYSYEQFLFNTSMLVDYGVEALVDAFSRQPAGRIGGGRNIDHHILHVAVDVIKESRVLRLQPFNEYRKRFGMKPYTSFQELTGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEMGAPFSLKGLLGNPICSPEYWKASTFGGEVGFNLVKTATLKKLVCLNTKTCPYVSFHVPDPRQEDRPGVERPPTEL,5.080921907623926 +COc1ccc(cc1OC1CCCC1)S(=O)(=O)C(CN(C)C(=O)c1ccccc1)CC(=O)NO,MHSFPPLLLLLFWGVVSHSFPATLETQEQDVDLVQKYLEKYYNLKNDGRQVEKRRNSGPVVEKLKQMQEFFGLKVTGKPDAETLKVMKQPRCGVPDVAQFVLTEGNPRWEQTHLTYRIENYTPDLPRADVDHAIEKAFQLWSNVTPLTFTKVSEGQADIMISFVRGDHRDNSPFDGPGGNLAHAFQPGPGIGGDAHFDEDERWTNNFREYNLHRVAAHELGHSLGLSHSTDIGALMYPSYTFSGDVQLAQDDIDGIQAIYGRSQNPVQPIGPQTPKACDSKLTFDAITTIRGEVMFFKDRFYMRTNPFYPEVELNFISVFWPQLPNGLEAAYEFADRDEVRFFKGNKYWAVQGQNVLHGYPKDIYSSFGFPRTVKHIDAALSEENTGKTYFFVANKYWRYDEYKRSMDPGYPKMIAHDFPGIGHKVDAVFMKDGFFYFFHGTRQYKFDPKTKRILTLQKANSWFNCRKN,5.0 +COC(=O)c1cc2NC(=O)\C(=C(/Nc3ccc(cc3)C(=O)NCCN3CCC(F)(F)CC3)c3ccccc3)c2cc1C,MGAPACALALCVAVAIVAGASSESLGTEQRVVGRAAEVPGPEPGQQEQLVFGSGDAVELSCPPPGGGPMGPTVWVKDGTGLVPSERVLVGPQRLQVLNASHEDSGAYSCRQRLTQRVLCHFSVRVTDAPSSGDDEDGEDEAEDTGVDTGAPYWTRPERMDKKLLAVPAANTVRFRCPAAGNPTPSISWLKNGREFRGEHRIGGIKLRHQQWSLVMESVVPSDRGNYTCVVENKFGSIRQTYTLDVLERSPHRPILQAGLPANQTAVLGSDVEFHCKVYSDAQPHIQWLKHVEVNGSKVGPDGTPYVTVLKTAGANTTDKELEVLSLHNVTFEDAGEYTCLAGNSIGFSHHSAWLVVLPAEEELVEADEAGSVYAGILSYGVGFFLFILVVAAVTLCRLRSPPKKGLGSPTVHKISRFPLKRQVSLESNASMSSNTPLVRIARLSSGEGPTLANVSELELPADPKWELSRARLTLGKPLGEGCFGQVVMAEAIGIDKDRAAKPVTVAVKMLKDDATDKDLSDLVSEMEMMKMIGKHKNIINLLGACTQGGPLYVLVEYAAKGNLREFLRARRPPGLDYSFDTCKPPEEQLTFKDLVSCAYQVARGMEYLASQKCIHRDLAARNVLVTEDNVMKIADFGLARDVHNLDYYKKTTNGRLPVKWMAPEALFDRVYTHQSDVWSFGVLLWEIFTLGGSPYPGIPVEELFKLLKEGHRMDKPANCTHDLYMIMRECWHAAPSQRPTFKQLVEDLDRVLTVTSTDEYLDLSAPFEQYSPGGQDTPSSSSSGDDSVFAHDLLPPAPPSSGGSRT,7.135488918941608 +CC(C)[C@H]1COC(=O)N1c1ccnc(NC(C)c2ccc(cc2)-n2ccnc2)n1,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGRHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,4.71669877129645 +Cc1ccc2nc(NC(=O)CSc3nc4CCSc4c(=O)n3-c3ccccc3)sc2c1,MELRVGNKYRLGRKIGSGSFGDIYLGANIASGEEVAIKLECVKTKHPQLHIESKFYKMMQGGVGIPSIKWCGAEGDYNVMVMELLGPSLEDLFNFCSRKFSLKTVLLLADQMISRIEYIHSKNFIHRDVKPDNFLMGLGKKGNLVYIIDFGLAKKYRDARTHQHIPYRENKNLTGTARYASINTHLGIEQSRRDDLESLGYVLMYFNLGSLPWQGLKAATKRQKYERISEKKMSTPIEVLCKGYPSEFSTYLNFCRSLRFDDKPDYSYLRQLFRNLFHRQGFSYDYVFDWNMLKFGAARNPEDVDRERREHEREERMGQLRGSATRALPPGPPTGATANRLRSAAEPVASTPASRIQPAGNTSPRAISRVDRERKVSMRLHRGAPANVSSSDLTGRQEVSRIPASQTSVPFDHLGK,5.39469495385889 +CCO[C@@H]([C@H](C)Cc1ccccc1)C(=C)CC[C@]12O[C@@]([C@H](O)[C@H]1O)(C(O)=O)[C@@](O)([C@H](O2)C(O)=O)C(O)=O,MEFVKCLGHPEEFYNLLRFRMGGRRNFIPKMDRNSLSNSLKTCYKYLDQTSRSFAAVIQALDGDIRHAVCVFYLILRAMDTVEDDMAISVEKKIPLLRNFHTFLYEPEWRFTESKEKHRVVLEDFPTISLEFRNLAEKYQTVIADICHRMGCGMAEFLNKDVTSKQDWDKYCHYVAGLVGIGLSRLFSASEFEDPIVGEDTECANSMGLFLQKTNIIRDYLEDQQEGRQFWPQEVWGKYVKKLEDFVKPENVDVAVKCLNELITNALQHIPDVITYLSRLRNQSVFNFCAIPQVMAIATLAACYNNHQVFKGVVKIRKGQAVTLMMDATNMPAVKAIIYQYIEEIYHRVPNSDPSASKAKQLISNIRTQSLPNCQLISRSHYSPIYLSFIMLLAALSWQYLSTLSQVTEDYVQREH,7.3979400086720375 +OCCN(CCO)C(=O)c1cc(n[nH]1)-c1ccc(Cl)cc1Cl,MISPFLVLAIGTCLTNSLVPEKEKDPKYWRDQAQETLKYALELQKLNTNVAKNVIMFLGDGMGVSTVTAARILKGQLHHNPGEETRLEMDKFPFVALSKTYNTNAQVPDSAGTATAYLCGVKANEGTVGVSAATERSRCNTTQGNEVTSILRWAKDAGKSVGIVTTTRVNHATPSAAYAHSADRDWYSDNEMPPEALSQGCKDIAYQLMHNIRDIDVIMGGGRKYMYPKNKTDVEYESDEKARGTRLDGLDLVDTWKSFKPRYKHSHFIWNRTELLTLDPHNVDYLLGLFEPGDMQYELNRNNVTDPSLSEMVVVAIQILRKNPKGFFLLVEGGRIDHGHHEGKAKQALHEAVEMDRAIGQAGSLTSSEDTLTVVTADHSHVFTFGGYTPRGNSIFGLAPMLSDTDKKPFTAILYGNGPGYKVVGGERENVSMVDYAHNNYQAQSAVPLRHETHGGEDVAVFSKGPMAHLLHGVHEQNYVPHVMAYAACIGANLGHCAPASSAGSLAAGPLLLALALYPLSVLF,7.327902142064282 +Clc1ccc2cc(ccc2c1)C(=O)NC[C@H]1CCN(Cc2cc(Cl)cc(Cl)c2)C(=O)[C@@H](CCN2CCOCC2)N1,MNSSFHLHFLDLNLNATEGNLSGPNVKNKSSPCEDMGIAVEVFLTLGVISLLENILVIGAIVKNKNLHSPMYFFVCSLAVADMLVSMSSAWETITIYLLNNKHLVIADAFVRHIDNVFDSMICISVVASMCSLLAIAVDRYVTIFYALRYHHIMTARRSGAIIAGIWAFCTGCGIVFILYSESTYVILCLISMFFAMLFLLVSLYIHMFLLARTHVKRIAALPGASSARQRTSMQGAVTVTMLLGVFTVCWAPFFLHLTLMLSCPQNLYCSRFMSHFNMYLILIMCNSVMDPLIYAFRSQEMRKTFKEIICCRGFRIACSFPRRD,7.0 +Cc1cc(C)c(c(C)c1)S(=O)(=O)N[C@@H](Cc1ccc(cc1)-c1cccc(NC(=O)NCc2ccccc2)c1)C(O)=O,MRARPRPRPLWATVLALGALAGVGVGGPNICTTRGVSSCQQCLAVSPMCAWCSDEALPLGSPRCDLKENLLKDNCAPESIEFPVSEARVLEDRPLSDKGSGDSSQVTQVSPQRIALRLRPDDSKNFSIQVRQVEDYPVDIYYLMDLSYSMKDDLWSIQNLGTKLATQMRKLTSNLRIGFGAFVDKPVSPYMYISPPEALENPCYDMKTTCLPMFGYKHVLTLTDQVTRFNEEVKKQSVSRNRDAPEGGFDAIMQATVCDEKIGWRNDASHLLVFTTDAKTHIALDGRLAGIVQPNDGQCHVGSDNHYSASTTMDYPSLGLMTEKLSQKNINLIFAVTENVVNLYQNYSELIPGTTVGVLSMDSSNVLQLIVDAYGKIRSKVELEVRDLPEELSLSFNATCLNNEVIPGLKSCMGLKIGDTVSFSIEAKVRGCPQEKEKSFTIKPVGFKDSLIVQVTFDCDCACQAQAEPNSHRCNNGNGTFECGVCRCGPGWLGSQCECSEEDYRPSQQDECSPREGQPVCSQRGECLCGQCVCHSSDFGKITGKYCECDDFSCVRYKGEMCSGHGQCSCGDCLCDSDWTGYYCNCTTRTDTCMSSNGLLCSGRGKCECGSCVCIQPGSYGDTCEKCPTCPDACTFKKECVECKKFDRGALHDENTCNRYCRDEIESVKELKDTGKDAVNCTYKNEDDCVVRFQYYEDSSGKSILYVVEEPECPKGPDILVVLLSVMGAILLIGLAALLIWKLLITIHDRKEFAKFEEERARAKWDTANNPLYKEATSTFTNITYRGT,7.221848749616356 +CS(=O)(=O)CCOCCNc1nnc(c(N)n1)-c1cccc(Cl)c1Cl,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,3.6989700043360187 +COC(=O)c1ccc2CCNCc2c1,MSGTDRSQAAGAVPDSDPGLAAVSSAYQRFEPRAYLRNNYAPPRGDLSCPDGVGPWKLRCLAQTFATGEVSGRTLIDIGSGPTIYQLLSACAHFEDITMTDFLEVNRQELRLWLREEPGAFDWSVYSQHVCLIEGKGESWQEKECQLRARVKRILPIDVHRPQPLGAGGLAPLPADALVSAFCLEAVSPDLASFQRALDHITTLLRPGGHLLLIGALEESWYLAGEARLAVVPVREEEVREALVRTATRCGICARTPMPAHLQTGVDDVKGIFFTRAQKKVGV,5.173925197299173 +CCCCCCCCNC(=O)[C@H](COP(O)(O)=S)NC(=O)CCCCCCC,MAAISTSIPVISQPQFTAMNEPQCFYNESIAFFYNRSGKHLATEWNTVSKLVMGLGITVCIFIMLANLLVMVAIYVNRRFHFPIYYLMANLAAADFFAGLAYFYLMFNTGPNTRRLTVSTWLLRQGLIDTSLTASVANLLAIAIERHITVFRMQLHTRMSNRRVVVVIVVIWTMAIVMGAIPSVGWNCICDIENCSNMAPLYSDSYLVFWAIFNLVTFVVMVVLYAHIFGYVRQRTMRMSRHSSGPRRNRDTMMSLLKTVVIVLGAFIICWTPGLVLLLLDVCCPQCDVLAYEKFFLLLAEFNSAMNPIIYSYRDKEMSATFRQILCCQRSENPTGPTEGSDRSASSLNHTILAGVHSNDHSVV,6.3223930472795065 +Cc1ccc(cc1-c1ccc2nc(N)ncc2c1)C(=O)Nc1cccc(c1)C(F)(F)F,MSQERPTFYRQELNKTIWEVPERYQNLSPVGSGAYGSVCAAFDTKTGLRVAVKKLSRPFQSIIHAKRTYRELRLLKHMKHENVIGLLDVFTPARSLEEFNDVYLVTHLMGADLNNIVKCQKLTDDHVQFLIYQILRGLKYIHSADIIHRDLKPSNLAVNEDCELKILDFGLARHTDDEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLTGRTLFPGTDHIDQLKLILRLVGTPGAELLKKISSESARNYIQSLTQMPKMNFANVFIGANPLAVDLLEKMLVLDSDKRITAAQALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES,8.221848749616356 +C[C@H](CN1CCC(CC1)n1nnc2ccccc12)NC(=O)c1ccc2ccccc2c1,MTATPESLFPTGDELDSSQLQMESDEVDTLKEGEDPADRMHPFLAIYELQSLKVHPLVFAPGVPVTAQVVGTERYTSGSKVGTCTLYSVRLTHGDFSWTTKKKYRHFQELHRDLLRHKVLMSLLPLARFAVAYSPARDAGNREMPSLPRAGPEGSTRHAASKQKYLENYLNRLLTMSFYRNYHAMTEFLEVSQLSFIPDLGRKGLEGMIRKRSGGHRVPGLTCCGRDQVCYRWSKRWLVVKDSFLLYMCLETGAISFVQLFDPGFEVQVGKRSTEARHGVRIDTSHRSLILKCSSYRQARWWAQEITELAQGPGRDFLQLHRHDSYAPPRPGTLARWFVNGAGYFAAVADAILRAQEEIFITDWWLSPEVYLKRPAHSDDWRLDIMLKRKAEEGVRVSILLFKEVELALGINSGYSKRALMLLHPNIKVMRHPDQVTLWAHHEKLLVVDQVVAFLGGLDLAYGRWDDLHYRLTDLGDSSESAASQPPTPRPDSPATPDLSHNQFFWLGKDYSNLITKDWVQLDRPFEDFIDRETTPRMPWRDVGVVVHGLPARDLARHFIQRWNFTKTTKAKYKTPTYPYLLPKSTSTANQLPFTLPGGQCTTVQVLRSVDRWSAGTLENSILNAYLHTIRESQHFLYIENQFFISCSDGRTVLNKVGDEIVDRILKAHKQGWCYRVYVLLPLLPGFEGDISTGGGNSIQAILHFTYRTLCRGEYSILHRLKAAMGTAWRDYISICGLRTHGELGGHPVSELIYIHSKVLIADDRTVIIGSANINDRSLLGKRDSELAVLIEDTETEPSLMNGAEYQAGRFALSLRKHCFGVILGANTRPDLDLRDPICDDFFQLWQDMAESNANIYEQIFRCLPSNATRSLRTLREYVAVEPLATVSPPLARSELTQVQGHLVHFPLKFLEDESLLPPLGSKEGMIPLEVWT,4.920818753952375 +O=c1oc(\C=C\c2ccccc2)nc2sc3CCCc3c12,MVSRYVPDMGDLIWVDFDPTKGSEQAGHRPAVVLSPFMYNNKTGMCLCVPCTTQSKGYPFEVVLSGQERDGVALADQVKSIAWRARGATKKGTVAPEELQLIKAKINVLIG,4.00436480540245 +CN\C(NCCSCc1ccc(CN(C)C)o1)=C/[N+]([O-])=O,MASPDWGYDDKNGPEQWSKLYPIANGNNQSPVDIKTSETKHDTSLKPISVSYNPATAKEIINVGHSFHVNFEDNDNRSVLKGGPFSDSYRLFQFHFHWGSTNEHGSEHTVDGVKYSAELHVAHWNSAKYSSLAEAASKADGLAVIGVLMKVGEANPKLQKVLDALQAIKTKGKRAPFTNFDPSTLLPSSLDFWTYPGSLTHPPLYESVTWIICKESISVSSEQLAQFRSLLSNVEGDNAVPMQHNNRPTQPLKGRTVRASF,4.258848401148215 +Cc1ccc(s1)-c1cc([nH]n1)C(=O)N[C@@H](C[C@@H](O)C(O)=O)Cc1ccc(cc1)-c1ccccc1,MGKSESQMDITDINTPKPKKKQRWTPLEISLSVLVLLLTIIAVTMIALYATYDDGICKSSDCIKSAARLIQNMDATTEPCTDFFKYACGGWLKRNVIPETSSRYGNFDILRDELEVVLKDVLQEPKTEDIVAVQKAKALYRSCINESAIDSRGGEPLLKLLPDIYGWPVATENWEQKYGASWTAEKAIAQLNSKYGKKVLINLFVGTDDKNSVNHVIHIDQPRLGLPSRDYYECTGIYKEACTAYVDFMISVARLIRQEERLPIDENQLALEMNKVMELEKEIANATAKPEDRNDPMLLYNKMTLAQIQNNFSLEINGKPFSWLNFTNEIMSTVNISITNEEDVVVYAPEYLTKLKPILTKYSARDLQNLMSWRFIMDLVSSLSRTYKESRNAFRKALYGTTSETATWRRCANYVNGNMENAVGRLYVEAAFAGESKHVVEDLIAQIREVFIQTLDDLTWMDAETKKRAEEKALAIKERIGYPDDIVSNDNKLNNEYLELNYKEDEYFENIIQNLKFSQSKQLKKLREKVDKDEWISGAAVVNAFYSSGRNQIVFPAGILQPPFFSAQQSNSLNYGGIGMVIGHEITHGFDDNGRNFNKDGDLVDWWTQQSASNFKEQSQCMVYQYGNFSWDLAGGQHLNGINTLGENIADNGGLGQAYRAYQNYIKKNGEEKLLPGLDLNHKQLFFLNFAQVWCGTYRPEYAVNSIKTDVHSPGNFRIIGTLQNSAEFSEAFHCRKNSYMNPEKKCRVW,9.0 +CC(C)NC(=O)Nc1nc2nc(NCCCN3CCN(C)CC3)ncc2cc1-c1c(Cl)cccc1Cl,MWSWKCLLFWAVLVTATLCTARPSPTLPEQAQPWGAPVEVESFLVHPGDLLQLRCRLRDDVQSINWLRDGVQLAESNRTRITGEEVEVQDSVPADSGLYACVTSSPSGSDTTYFSVNVSDALPSSEDDDDDDDSSSEEKETDNTKPNRMPVAPYWTSPEKMEKKLHAVPAAKTVKFKCPSSGTPNPTLRWLKNGKEFKPDHRIGGYKVRYATWSIIMDSVVPSDKGNYTCIVENEYGSINHTYQLDVVERSPHRPILQAGLPANKTVALGSNVEFMCKVYSDPQPHIQWLKHIEVNGSKIGPDNLPYVQILKTAGVNTTDKEMEVLHLRNVSFEDAGEYTCLAGNSIGLSHHSAWLTVLEALEERPAVMTSPLYLEIIIYCTGAFLISCMVGSVIVYKMKSGTKKSDFHSQMAVHKLAKSIPLRRQVTVSADSSASMNSGVLLVRPSRLSSSGTPMLAGVSEYELPEDPRWELPRDRLVLGKPLGEGCFGQVVLAEAIGLDKDKPNRVTKVAVKMLKSDATEKDLSDLISEMEMMKMIGKHKNIINLLGACTQDGPLYVIVEYASKGNLREYLQARRPPGLEYCYNPSHNPEEQLSSKDLVSCAYQVARGMEYLASKKCIHRDLAARNVLVTEDNVMKIADFGLARDIHHIDYYKKTTNGRLPVKWMAPEALFDRIYTHQSDVWSFGVLLWEIFTLGGSPYPGVPVEELFKLLKEGHRMDKPSNCTNELYMMMRDCWHAVPSQRPTFKQLVEDLDRIVALTSNQEYLDLSMPLDQYSPSFPDTRSSTCSSGEDSVFSHEPLPEEPCLPRHPAQLANGGLKRR,7.468521082957745 +Fc1cccc(Oc2nc(NC3CC3)n3ncc(\C=C4/NC(=O)NC4=O)c3n2)c1,MSGPVPSRARVYTDVNTHRPREYWDYESHVVEWGNQDDYQLVRKLGRGKYSEVFEAINITNNEKVVVKILKPVKKKKIKREIKILENLRGGPNIITLADIVKDPVSRTPALVFEHVNNTDFKQLYQTLTDYDIRFYMYEILKALDYCHSMGIMHRDVKPHNVMIDHEHRKLRLIDWGLAEFYHPGQEYNVRVASRYFKGPELLVDYQMYDYSLDMWSLGCMLASMIFRKEPFFHGHDNYDQLVRIAKVLGTEDLYDYIDKYNIELDPRFNDILGRHSRKRWERFVHSENQHLVSPEALDFLDKLLRYDHQSRLTAREAMEHPYFYTVVKDQARMGSSSMPGGSTPVSSANMMSGISSVPTPSPLGPLAGSPVIAAANPLGMPVPAAAGAQQ,8.0 +CCc1nnc(o1)C(C)(CO)NC(=O)c1c(C)nc2c(OCC3CCCCC3)cccn12,MFCTKLKDLKITGECPFSLLAPGQVPNESSEEAAGSSESCKATVPICQDIPEKNIQESLPQRKTSRSRVYLHTLAESICKLIFPEFERLNVALQRTLAKHKIKESRKSLEREDFEKTIAEQAVAAGVPVEVIKESLGEEVFKICYEEDENILGVVGGTLKDFLNSFSTLLKQSSHCQEAGKRGRLEDASILCLDKEDDFLHVYYFFPKRTTSLILPGIIKAAAHVLYETEVEVSLMPPCFHNDCSEFVNQPYLLYSVHMKSTKPSLSPSKPQSSLVIPTSLFCKTFPFHFMFDKDMTILQFGNGIRRLMNRRDFQGKPNFEEYFEILTPKINQTFSGIMTMLNMQFVVRVRRWDNSVKKSSRVMDLKGQMIYIVESSAILFLGSPCVDRLEDFTGRGLYLSDIPIHNALRDVVLIGEQARAQDGLKKRLGKLKATLEQAHQALEEEKKKTVDLLCSIFPCEVAQQLWQGQVVQAKKFSNVTMLFSDIVGFTAICSQCSPLQVITMLNALYTRFDQQCGELDVYKVETIGDAYCVAGGLHKESDTHAVQIALMALKMMELSDEVMSPHGEPIKMRIGLHSGSVFAGVVGVKMPRYCLFGNNVTLANKFESCSVPRKINVSPTTYRLLKDCPGFVFTPRSREELPPNFPSEIPGICHFLDAYQQGTNSKPCFQKKDVEDGNANFLGKASGID,5.251811972993799 +CCN1CCOc2ccc(cc12)C(=O)Nc1nnc(s1)-c1c(Cl)cccc1Cl,MAGVWAPEHSVEAHSNQSSAADGCGSVSVAFPITMMVTGFVGNALAMLLVVRSYRRRESKRKKSFLLCIGWLALTDLVGQLLTSPVVILVYLSQRRWEQLDPSGRLCTFFGLTMTVFGLSSLLVASAMAVERALAIRAPHWYASHMKTRATPVLLGVWLSVLAFALLPVLGVGRYSVQWPGTWCFISTGPAGNETDSAREPGSVAFASAFACLGLLALVVTFACNLATIKALVSRCRAKAAASQSSAQWGRITTETAIQLMGIMCVLSVCWSPLLIMMLKMIFNQMSVEQCKTQMGKEKECNSFLIAVRLASLNQILDPWVYLLLRKILLRKFCQIRDHTNYASSSTSLPCPGSSVLMWSDQLER,8.199970640755865 +Oc1ccc(\C=C\CN2CCN(CCOC(c3ccccc3)c3ccccc3)CC2)cc1,MSKSKCSVGPMSSVVAPAKESNAVGPREVELILVKEQNGVQLTNSTLINPPQTPVEAQERETWSKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPVLKGVGFTVILISFYVGFFYNVIIAWALHYFFSSFTMDLPWIHCNNTWNSPNCSDAHASNSSDGLGLNDTFGTTPAAEYFERGVLHLHQSRGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAMDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIITTSINSLTSFSSGFVVFSFLGYMAQKHNVPIRDVATDGPGLIFIIYPEAIATLPLSSAWAAVFFLMLLTLGIDSAMGGMESVITGLVDEFQLLHRHRELFTLGIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVQQFSDDIKQMTGQRPNLYWRLCWKLVSPCFLLYVVVVSIVTFRPPHYGAYIFPDWANALGWIIATSSMAMVPIYATYKFCSLPGSFREKLAYAITPEKDHQLVDRGEVRQFTLRHWLLL,7.366531544420414 +Nc1ccccc1NC(=O)\C=C\c1csc(C\C=C\c2ccccc2)n1,MAQTQGTRRKVCYYYDGDVGNYYYGQGHPMKPHRIRMTHNLLLNYGLYRKMEIYRPHKANAEEMTKYHSDDYIKFLRSIRPDNMSEYSKQMQRFNVGEDCPVFDGLFEFCQLSTGGSVASAVKLNKQQTDIAVNWAGGLHHAKKSEASGFCYVNDIVLAILELLKYHQRVLYIDIDIHHGDGVEEAFYTTDRVMTVSFHKYGEYFPGTGDLRDIGAGKGKYYAVNYPLRDGIDDESYEAIFKPVMSKVMEMFQPSAVVLQCGSDSLSGDRLGCFNLTIKGHAKCVEFVKSFNLPMLMLGGGGYTIRNVARCWTYETAVALDTEIPNELPYNDYFEYFGPDFKLHISPSNMTNQNTNEYLEKIKQRLFENLRMLPHAPGVQMQAIPEDAIPEESGDEDEDDPDKRISICSSDKRIACEEEFSDSEEEGEGGRKNSSNFKKAKRVKTEDEKEKDPEEKKEVTEEEKTKEEKPEAKGVKEEVKLA,6.0 +COc1cc(OC)c(F)c(c1F)-c1ccc(C(=O)Nc2ncc(CN(C)C)[nH]2)c2ncccc12,MGAPACALALCVAVAIVAGASSESLGTEQRVVGRAAEVPGPEPGQQEQLVFGSGDAVELSCPPPGGGPMGPTVWVKDGTGLVPSERVLVGPQRLQVLNASHEDSGAYSCRQRLTQRVLCHFSVRVTDAPSSGDDEDGEDEAEDTGVDTGAPYWTRPERMDKKLLAVPAANTVRFRCPAAGNPTPSISWLKNGREFRGEHRIGGIKLRHQQWSLVMESVVPSDRGNYTCVVENKFGSIRQTYTLDVLERSPHRPILQAGLPANQTAVLGSDVEFHCKVYSDAQPHIQWLKHVEVNGSKVGPDGTPYVTVLKTAGANTTDKELEVLSLHNVTFEDAGEYTCLAGNSIGFSHHSAWLVVLPAEEELVEADEAGSVYAGILSYGVGFFLFILVVAAVTLCRLRSPPKKGLGSPTVHKISRFPLKRQVSLESNASMSSNTPLVRIARLSSGEGPTLANVSELELPADPKWELSRARLTLGKPLGEGCFGQVVMAEAIGIDKDRAAKPVTVAVKMLKDDATDKDLSDLVSEMEMMKMIGKHKNIINLLGACTQGGPLYVLVEYAAKGNLREFLRARRPPGLDYSFDTCKPPEEQLTFKDLVSCAYQVARGMEYLASQKCIHRDLAARNVLVTEDNVMKIADFGLARDVHNLDYYKKTTNGRLPVKWMAPEALFDRVYTHQSDVWSFGVLLWEIFTLGGSPYPGIPVEELFKLLKEGHRMDKPANCTHDLYMIMRECWHAAPSQRPTFKQLVEDLDRVLTVTSTDEYLDLSAPFEQYSPGGQDTPSSSSSGDDSVFAHDLLPPAPPSSGGSRT,8.045757490560675 +CC[C@H](C)Oc1ccc(cc1Cl)\N=c1/[nH]c(=O)n(C[C@H](C)C(O)=O)c(=O)n1Cc1ccc(C)cc1,MNCISDFFTYETTKSVVVKSWTIGIINRVVQLLIISYFVGWVFLHEKAYQVRDTAIESSVVTKVKGSGLYANRVMDVSDYVTPPQGTSVFVIITKMIVTENQMQGFCPESEEKYRCVSDSQCGPERLPGGGILTGRCVNYSSVLRTCEIQGWCPTEVDTVETPIMMEAENFTIFIKNSIRFPLFNFEKGNLLPNLTARDMKTCRFHPDKDPFCPILRVGDVVKFAGQDFAKLARTGGVLGIKIGWVCDLDKAWDQCIPKYSFTRLDSVSEKSSVSPGYNFRFAKYYKMENGSEYRTLLKAFGIRFDVLVYGNAGKFNIIPTIISSVAAFTSVGVGTVLCDIILLNFLKGADQYKAKKFEEVNETTLKIAALTNPVYPSDQTTAEKQSTDSGAFSIGH,7.769551078621726 +C[C@H](O)CN1CCN(CC1)c1ccc(Nc2ncc3cc4C(=O)NCC5(CCCCC5)n4c3n2)nc1,MPRERRERDAKERDTMKEDGGAEFSARSRKRKANVTVFLQDPDEEMAKIDRTARDQCGSQPWDNNAVCADPCSLIPTPDKEDDDRVYPNSTCKPRIIAPSRGSPLPVLSWANREEVWKIMLNKEKTYLRDQHFLEQHPLLQPKMRAILLDWLMEVCEVYKLHRETFYLAQDFFDRYMATQENVVKTLLQLIGISSLFIAAKLEEIYPPKLHQFAYVTDGACSGDEILTMELMIMKALKWRLSPLTIVSWLNVYMQVAYLNDLHEVLLPQYPQQIFIQIAELLDLCVLDVDCLEFPYGILAASALYHFSSSELMQKVSGYQWCDIENCVKWMVPFAMVIRETGSSKLKHFRGVADEDAHNIQTHRDSLDLLDKARAKKAMLSEQNRASPLPSGLLTPPQSGKKQSSGPEMA,5.197226274708024 +CCCCCCCCCCCC(=O)O[C@@H]1[C@H]2C[C@H](OC(=O)c3ccco3)[C@]3(C)[C@@H](OC(C)=O)[C@H](C[C@@](C)(O)[C@@]13OC2(C)C)OC(=O)c1ccccc1,MDLEGDRNGGAKKKNFFKLNNKSEKDKKEKKPTVSVFSMFRYSNWLDKLYMVVGTLAAIIHGAGLPLMMLVFGEMTDIFANAGNLEDLMSNITNRSDINDTGFFMNLEEDMTRYAYYYSGIGAGVLVAAYIQVSFWCLAAGRQIHKIRKQFFHAIMRQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQSMATFFTGFIVGFTRGWKLTLVILAISPVLGLSAAVWAKILSSFTDKELLAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNKNLEEAKRIGIKKAITANISIGAAFLLIYASYALAFWYGTTLVLSGEYSIGQVLTVFFSVLIGAFSVGQASPSIEAFANARGAAYEIFKIIDNKPSIDSYSKSGHKPDNIKGNLEFRNVHFSYPSRKEVKILKGLNLKVQSGQTVALVGNSGCGKSTTVQLMQRLYDPTEGMVSVDGQDIRTINVRFLREIIGVVSQEPVLFATTIAENIRYGRENVTMDEIEKAVKEANAYDFIMKLPHKFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQVALDKARKGRTTIVIAHRLSTVRNADVIAGFDDGVIVEKGNHDELMKEKGIYFKLVTMQTAGNEVELENAADESKSEIDALEMSSNDSRSSLIRKRSTRRSVRGSQAQDRKLSTKEALDESIPPVSFWRIMKLNLTEWPYFVVGVFCAIINGGLQPAFAIIFSKIIGVFTRIDDPETKRQNSNLFSLLFLALGIISFITFFLQGFTFGKAGEILTKRLRYMVFRSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGAIGSRLAVITQNIANLGTGIIISFIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENFRTVVSLTQEQKFEHMYAQSLQVPYRNSLRKAHIFGITFSFTQAMMYFSYAGCFRFGAYLVAHKLMSFEDVLLVFSAVVFGAMAVGQVSSFAPDYAKAKISAAHIIMIIEKTPLIDSYSTEGLMPNTLEGNVTFGEVVFNYPTRPDIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPLAGKVLLDGKEIKRLNVQWLRAHLGIVSQEPILFDCSIAENIAYGDNSRVVSQEEIVRAAKEANIHAFIESLPNKYSTKVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVFQNGRVKEHGTHQQLLAQKGIYFSMVSVQAGTKRQ,5.287350298372789 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+OCCOCCN1CCN(CC1)C1=Nc2ccccc2Sc2ccccc12,MDVLSPGQGNNTTSPPAPFETGGNTTGISDVTVSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVKKVEKTGADTRHGASPAPQPKKSVNGESGSRNWRLGVESKAGGALCANGAVRQGDDGAALEVIEVHRVGNSKEHLPLPSEAGPTPCAPASFERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPTLLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRQ,6.522878745280337 +CCN(CC)C(=S)SSC(=S)N(CC)CC,MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHLKDGTCGLVEVEKGVLPQLEQPYVFIKRSDARTAPHGHVMVELVAELEGIQYGRSGETLGVLVPHVGEIPVAYRKVLLRKNGNKGAGGHSYGADLKSFDLGDELGTDPYEDFQENWNTKHSSGVTRELMRELNGGAYTRYVDNNFCGPDGYPLECIKDLLARAGKASCTLSEQLDFIDTKRGVYCCREHEHEIAWYTERSEKSYELQTPFEIKLAKKFDTFNGECPNFVFPLNSIIKTIQPRVEKKKLDGFMGRIRSVYPVASPNECNQMCLSTLMKCDHCGETSWQTGDFVKATCEFCGTENLTKEGATTCGYLPQNAVVKIYCPACHNSEVGPEHSLAEYHNESGLKTILRKGGRTIAFGGCVFSYVGCHNKCAYWVPRASANIGCNHTGVVGEGSEGLNDNLLEILQKEKVNINIVGDFKLNEEIAIILASFSASTSAFVETVKGLDYKAFKQIVESCGNFKVTKGKAKKGAWNIGEQKSILSPLYAFASEAARVVRSIFSRTLETAQNSVRVLQKAAITILDGISQYSLRLIDAMMFTSDLATNNLVVMAYITGGVVQLTSQWLTNIFGTVYEKLKPVLDWLEEKFKEGVEFLRDGWEIVKFISTCACEIVGGQIVTCAKEIKESVQTFFKLVNKFLALCADSIIIGGAKLKALNLGETFVTHSKGLYRKCVKSREETGLLMPLKAPKEIIFLEGETLPTEVLTEEVVLKTGDLQPLEQPTSEAVEAPLVGTPVCINGLMLLEIKDTEKYCALAPNMMVTNNTFTLKGGAPTKVTFGDDTVIEVQGYKSVNITFELDERIDKVLNEKCSAYTVELGTEVNEFACVVADAVIKTLQPVSELLTPLGIDLDEWSMATYYLFDESGEFKLASHMYCSFYPPDEDEEEGDCEEEEFEPSTQYEYGTEDDYQGKPLEFGATSAALQPEEEQEEDWLDDDSQQTVGQQDGSEDNQTTTIQTIVEVQPQLEMELTPVVQTIEVNSFSGYLKLTDNVYIKNADIVEEAKKVKPTVVVNAANVYLKHGGGVAGALNKATNNAMQVESDDYIATNGPLKVGGSCVLSGHNLAKHCLHVVGPNVNKGEDIQLLKSAYENFNQHEVLLAPLLSAGIFGADPIHSLRVCVDTVRTNVYLAVFDKNLYDKLVSSFLEMKSEKQVEQKIAEIPKEEVKPFITESKPSVEQRKQDDKKIKACVEEVTTTLEETKFLTENLLLYIDINGNLHPDSATLVSDIDITFLKKDAPYIVGDVVQEGVLTAVVIPTKKAGGTTEMLAKALRKVPTDNYITTYPGQGLNGYTVEEAKTVLKKCKSAFYILPSIISNEKQEILGTVSWNLREMLAHAEETRKLMPVCVETKAIVSTIQRKYKGIKIQEGVVDYGARFYFYTSKTTVASLINTLNDLNETLVTMPLGYVTHGLNLEEAARYMRSLKVPATVSVSSPDAVTAYNGYLTSSSKTPEEHFIETISLAGSYKDWSYSGQSTQLGIEFLKRGDKSVYYTSNPTTFHLDGEVITFDNLKTLLSLREVRTIKVFTTVDNINLHTQVVDMSMTYGQQFGPTYLDGADVTKIKPHNSHEGKTFYVLPNDDTLRVEAFEYYHTTDPSFLGRYMSALNHTKKWKYPQVNGLTSIKWADNNCYLATALLTLQQIELKFNPPALQDAYYRARAGEAANFCALILAYCNKTVGELGDVRETMSYLFQHANLDSCKRVLNVVCKTCGQQQTTLKGVEAVMYMGTLSYEQFKKGVQIPCTCGKQATKYLVQQESPFVMMSAPPAQYELKHGTFTCASEYTGNYQCGHYKHITSKETLYCIDGALLTKSSEYKGPITDVFYKENSYTTTIKPVTYKLDGVVCTEIDPKLDNYYKKDNSYFTEQPIDLVPNQPYPNASFDNFKFVCDNIKFADDLNQLTGYKKPASRELKVTFFPDLNGDVVAIDYKHYTPSFKKGAKLLHKPIVWHVNNATNKATYKPNTWCIRCLWSTKPVETSNSFDVLKSEDAQGMDNLACEDLKPVSEEVVENPTIQKDVLECNVKTTEVVGDIILKPANNSLKITEEVGHTDLMAAYVDNSSLTIKKPNELSRVLGLKTLATHGLAAVNSVPWDTIANYAKPFLNKVVSTTTNIVTRCLNRVCTNYMPYFFTLLLQLCTFTRSTNSRIKASMPTTIAKNTVKSVGKFCLEASFNYLKSPNFSKLINIIIWFLLLSVCLGSLIYSTAALGVLMSNLGMPSYCTGYREGYLNSTNVTIATYCTGSIPCSVCLSGLDSLDTYPSLETIQITISSFKWDLTAFGLVAEWFLAYILFTRFFYVLGLAAIMQLFFSYFAVHFISNSWLMWLIINLVQMAPISAMVRMYIFFASFYYVWKSYVHVVDGCNSSTCMMCYKRNRATRVECTTIVNGVRRSFYVYANGGKGFCKLHNWNCVNCDTFCAGSTFISDEVARDLSLQFKRPINPTDQSSYIVDSVTVKNGSIHLYFDKAGQKTYERHSLSHFVNLDNLRANNTKGSLPINVIVFDGKSKCEESSAKSASVYYSQLMCQPILLLDQALVSDVGDSAEVAVKMFDAYVNTFSSTFNVPMEKLKTLVATAEAELAKNVSLDNVLSTFISAARQGFVDSDVETKDVVECLKLSHQSDIEVTGDSCNNYMLTYNKVENMTPRDLGACIDCSARHINAQVAKSHNIALIWNVKDFMSLSEQLRKQIRSAAKKNNLPFKLTCATTRQVVNVVTTKIALKGGKIVNNWLKQLIKVTLVFLFVAAIFYLITPVHVMSKHTDFSSEIIGYKAIDGGVTRDIASTDTCFANKHADFDTWFSQRGGSYTNDKACPLIAAVITREVGFVVPGLPGTILRTTNGDFLHFLPRVFSAVGNICYTPSKLIEYTDFATSACVLAAECTIFKDASGKPVPYCYDTNVLEGSVAYESLRPDTRYVLMDGSIIQFPNTYLEGSVRVVTTFDSEYCRHGTCERSEAGVCVSTSGRWVLNNDYYRSLPGVFCGVDAVNLLTNMFTPLIQPIGALDISASIVAGGIVAIVVTCLAYYFMRFRRAFGEYSHVVAFNTLLFLMSFTVLCLTPVYSFLPGVYSVIYLYLTFYLTNDVSFLAHIQWMVMFTPLVPFWITIAYIICISTKHFYWFFSNYLKRRVVFNGVSFSTFEEAALCTFLLNKEMYLKLRSDVLLPLTQYNRYLALYNKYKYFSGAMDTTSYREAACCHLAKALNDFSNSGSDVLYQPPQTSITSAVLQSGFRKMAFPSGKVEGCMVQVTCGTTTLNGLWLDDVVYCPRHVICTSEDMLNPNYEDLLIRKSNHNFLVQAGNVQLRVIGHSMQNCVLKLKVDTANPKTPKYKFVRIQPGQTFSVLACYNGSPSGVYQCAMRPNFTIKGSFLNGSCGSVGFNIDYDCVSFCYMHHMELPTGVHAGTDLEGNFYGPFVDRQTAQAAGTDTTITVNVLAWLYAAVINGDRWFLNRFTTTLNDFNLVAMKYNYEPLTQDHVDILGPLSAQTGIAVLDMCASLKELLQNGMNGRTILGSALLEDEFTPFDVVRQCSGVTFQSAVKRTIKGTHHWLLLTILTSLLVLVQSTQWSLFFFLYENAFLPFAMGIIAMSAFAMMFVKHKHAFLCLFLLPSLATVAYFNMVYMPASWVMRIMTWLDMVDTSLSGFKLKDCVMYASAVVLLILMTARTVYDDGARRVWTLMNVLTLVYKVYYGNALDQAISMWALIISVTSNYSGVVTTVMFLARGIVFMCVEYCPIFFITGNTLQCIMLVYCFLGYFCTCYFGLFCLLNRYFRLTLGVYDYLVSTQEFRYMNSQGLLPPKNSIDAFKLNIKLLGVGGKPCIKVATVQSKMSDVKCTSVVLLSVLQQLRVESSSKLWAQCVQLHNDILLAKDTTEAFEKMVSLLSVLLSMQGAVDINKLCEEMLDNRATLQAIASEFSSLPSYAAFATAQEAYEQAVANGDSEVVLKKLKKSLNVAKSEFDRDAAMQRKLEKMADQAMTQMYKQARSEDKRAKVTSAMQTMLFTMLRKLDNDALNNIINNARDGCVPLNIIPLTTAAKLMVVIPDYNTYKNTCDGTTFTYASALWEIQQVVDADSKIVQLSEISMDNSPNLAWPLIVTALRANSAVKLQNNELSPVALRQMSCAAGTTQTACTDDNALAYYNTTKGGRFVLALLSDLQDLKWARFPKSDGTGTIYTELEPPCRFVTDTPKGPKVKYLYFIKGLNNLNRGMVLGSLAATVRLQAGNATEVPANSTVLSFCAFAVDAAKAYKDYLASGGQPITNCVKMLCTHTGTGQAITVTPEANMDQESFGGASCCLYCRCHIDHPNPKGFCDLKGKYVQIPTTCANDPVGFTLKNTVCTVCGMWKGYGCSCDQLREPMLQSADAQSFLNRVCGVSAARLTPCGTGTSTDVVYRAFDIYNDKVAGFAKFLKTNCCRFQEKDEDDNLIDSYFVVKRHTFSNYQHEETIYNLLKDCPAVAKHDFFKFRIDGDMVPHISRQRLTKYTMADLVYALRHFDEGNCDTLKEILVTYNCCDDDYFNKKDWYDFVENPDILRVYANLGERVRQALLKTVQFCDAMRNAGIVGVLTLDNQDLNGNWYDFGDFIQTTPGSGVPVVDSYYSLLMPILTLTRALTAESHVDTDLTKPYIKWDLLKYDFTEERLKLFDRYFKYWDQTYHPNCVNCLDDRCILHCANFNVLFSTVFPPTSFGPLVRKIFVDGVPFVVSTGYHFRELGVVHNQDVNLHSSRLSFKELLVYAADPAMHAASGNLLLDKRTTCFSVAALTNNVAFQTVKPGNFNKDFYDFAVSKGFFKEGSSVELKHFFFAQDGNAAISDYDYYRYNLPTMCDIRQLLFVVEVVDKYFDCYDGGCINANQVIVNNLDKSAGFPFNKWGKARLYYDSMSYEDQDALFAYTKRNVIPTITQMNLKYAISAKNRARTVAGVSICSTMTNRQFHQKLLKSIAATRGATVVIGTSKFYGGWHNMLKTVYSDVENPHLMGWDYPKCDRAMPNMLRIMASLVLARKHTTCCSLSHRFYRLANECAQVLSEMVMCGGSLYVKPGGTSSGDATTAYANSVFNICQAVTANVNALLSTDGNKIADKYVRNLQHRLYECLYRNRDVDTDFVNEFYAYLRKHFSMMILSDDAVVCFNSTYASQGLVASIKNFKSVLYYQNNVFMSEAKCWTETDLTKGPHEFCSQHTMLVKQGDDYVYLPYPDPSRILGAGCFVDDIVKTDGTLMIERFVSLAIDAYPLTKHPNQEYADVFHLYLQYIRKLHDELTGHMLDMYSVMLTNDNTSRYWEPEFYEAMYTPHTVLQAVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVNPYVCNAPGCDVTDVTQLYLGGMSYYCKSHKPPISFPLCANGQVFGLYKNTCVGSDNVTDFNAIATCDWTNAGDYILANTCTERLKLFAAETLKATEETFKLSYGIATVREVLSDRELHLSWEVGKPRPPLNRNYVFTGYRVTKNSKVQIGEYTFEKGDYGDAVVYRGTTTYKLNVGDYFVLTSHTVMPLSAPTLVPQEHYVRITGLYPTLNISDEFSSNVANYQKVGMQKYSTLQGPPGTGKSHFAIGLALYYPSARIVYTACSHAAVDALCEKALKYLPIDKCSRIIPARARVECFDKFKVNSTLEQYVFCTVNALPETTADIVVFDEISMATNYDLSVVNARLRAKHYVYIGDPAQLPAPRTLLTKGTLEPEYFNSVCRLMKTIGPDMFLGTCRRCPAEIVDTVSALVYDNKLKAHKDKSAQCFKMFYKGVITHDVSSAINRPQIGVVREFLTRNPAWRKAVFISPYNSQNAVASKILGLPTQTVDSSQGSEYDYVIFTQTTETAHSCNVNRFNVAITRAKVGILCIMSDRDLYDKLQFTSLEIPRRNVATLQAENVTGLFKDCSKVITGLHPTQAPTHLSVDTKFKTEGLCVDIPGIPKDMTYRRLISMMGFKMNYQVNGYPNMFITREEAIRHVRAWIGFDVEGCHATREAVGTNLPLQLGFSTGVNLVAVPTGYVDTPNNTDFSRVSAKPPPGDQFKHLIPLMYKGLPWNVVRIKIVQMLSDTLKNLSDRVVFVLWAHGFELTSMKYFVKIGPERTCCLCDRRATCFSTASDTYACWHHSIGFDYVYNPFMIDVQQWGFTGNLQSNHDLYCQVHGNAHVASCDAIMTRCLAVHECFVKRVDWTIEYPIIGDELKINAACRKVQHMVVKAALLADKFPVLHDIGNPKAIKCVPQADVEWKFYDAQPCSDKAYKIEELFYSYATHSDKFTDGVCLFWNCNVDRYPANSIVCRFDTRVLSNLNLPGCDGGSLYVNKHAFHTPAFDKSAFVNLKQLPFFYYSDSPCESHGKQVVSDIDYVPLKSATCITRCNLGGAVCRHHANEYRLYLDAYNMMISAGFSLWVYKQFDTYNLWNTFTRLQSLENVAFNVVNKGHFDGQQGEVPVSIINNTVYTKVDGVDVELFENKTTLPVNVAFELWAKRNIKPVPEVKILNNLGVDIAANTVIWDYKRDAPAHISTIGVCSMTDIAKKPTETICAPLTVFFDGRVDGQVDLFRNARNGVLITEGSVKGLQPSVGPKQASLNGVTLIGEAVKTQFNYYKKVDGVVQQLPETYFTQSRNLQEFKPRSQMEIDFLELAMDEFIERYKLEGYAFEHIVYGDFSHSQLGGLHLLIGLAKRFKESPFELEDFIPMDSTVKNYFITDAQTGSSKCVCSVIDLLLDDFVEIIKSQDLSVVSKVVKVTIDYTEISFMLWCKDGHVETFYPKLQSSQAWQPGVAMPNLYKMQRMLLEKCDLQNYGDSATLPKGIMMNVAKYTQLCQYLNTLTLAVPYNMRVIHFGAGSDKGVAPGTAVLRQWLPTGTLLVDSDLNDFVSDADSTLIGDCATVHTANKWDLIISDMYDPKTKNVTKENDSKEGFFTYICGFIQQKLALGGSVAIKITEHSWNADLYKLMGHFAWWTAFVTNVNASSSEAFLIGCNYLGKPREQIDGYVMHANYIFWRNTNPIQLSSYSLFDMSKFPLKLRGTAVMSLKEGQINDMILSLLSKGRLIIRENNRVVISSDVLVNN,5.029188389127482 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+CC1CC(=O)C(C(=O)c2cc3cccc(C)c3nc2C)C(=O)C1,MGHQNAAVSENQNHDDGAASSPGFKLVGFSKFVRKNPKSDKFKVKRFHHIEFWCGDATNVARRFSWGLGMRFSAKSDLSTGNMVHASYLLTSGDLRFLFTAPYSPSLSAGEIKPTTTASIPSFDHGSCRSFFSSHGLGVRAVAIEVEDAESAFSISVANGAIPSSPPIVLNEAVTIAEVKLYGDVVLRYVSYKAEDTEKSEFLPGFERVEDASSFPLDYGIRRLDHAVGNVPELGPALTYVAGFTGFHQFAEFTADDVGTAESGLNSAVLASNDEMVLLPINEPVHGTKRKSQIQTYLEHNEGAGLQHLALMSEDIFRTLREMRKRSSIGGFDFMPSPPPTYYQNLKKRVGDVLSDDQIKECEELGILVDRDDQGTLLQIFTKPLGDRPTIFIEIIQRVGCMMKDEEGKAYQSGGCGGFGKGNFSELFKSIEEYEKTLEAKQLVG,8.154901959985743 +OC(=O)c1cc(\C=C\C(=O)\C=C\c2ccc(O)c(c2)C(O)=O)ccc1O,MSEIENSTITSSADRMVGMDHAEVRYFTSYDHHGIHEEMLKDDVRTRSYRDSIYQNRHIFKDKVVLDVGCGTGILSMFAAKAGAKHVIGVDMSSIIEKAREIVAVNGLADKITLLQGKMEEVQLPFPSVDIIISEWMGYFLLYESMLDTVLYAQDRYLVPGGKIFPDKATMYLAGIEDGEYKDDKIGFWDNVYGFDYSPMKEIALTEPLVDTVELKALVTDPCPIITFDLYTVTKEDLAFEVPYSLPVKRSDFVHAVIAWFDIEFGACHKPINFSTGPHAKYTHWKQTVFYLRDVLTVEEEESISGVLSNRPNDKNKRDLDINLTYKLETQDQTRFAEGGCFYRM,4.259637310505756 +COc1ccc(cc1)S(=O)(=O)N1CCC[C@@H]1C(=O)Nc1nc2cc(O)c(O)cc2s1,AETDEDHAHWLEARMLLDNIYLQDGLIASLYRPEADKVAAIEGEFKLRTEQRKTFVELMKRGDLPV,6.0655015487564325 +C[Si]1(C)CN(CCN2CCC(Cc3c[nH]c4ccc(F)cc34)CC2)S(=O)(=O)c2ccccc12,MVLLSENASEGSNCTHPPAQVNISKAILLGVILGGLIIFGVLGNILVILSVACHRHLHSVTHYYIVNLAVADLLLTSTVLPFSAIFEILGYWAFGRVFCNIWAAVDVLCCTASIMGLCIISIDRYIGVSYPLRYPTIVTQRRGVRALLCVWALSLVISIGPLFGWRQQAPEDETICQINEEPGYVLFSALGSFYVPLTIILVMYCRVYVVAKRESRGLKSGLKTDKSDSEQVTLRIHRKNVPAEGSGVSSAKNKTHFSVRLLKFSREKKAAKTLGIVVGCFVLCWLPFFLVMPIGSFFPNFKPPETVFKIVFWLGYLNSCINPIIYPCSSQEFKKAFQNVLRIQCLRRRQSSKHALGYTLHPPSQAVEGQHRGMVRIPVGSGETFYKISKTDGVREWKFFSSMPQGSARITMPKDQSACTTARVRSKSFLQVCCCVGSSTPRPEENHQVPTIKIHTISLGENGEEV,7.0 +Br.Oc1ccc2C(CCCCc2c1O)C1=NCCN1,MASPALAAALAAAAAEGPNGSDAGEWGSGGGANASGTDWGPPPGQYSAGAVAGLAAVVGFLIVFTVVGNVLVVIAVLTSRALRAPQNLFLVSLASADILVATLVMPFSLANELMAYWYFGQVWCGVYLALDVLFCTSSIVHLCAISLDRYWSVTQAVEYNLKRTPRRVKATIVAVWLISAVISFPPLVSFYRRPDGAAYPQCGLNDETWYILSSCIGSFFAPCLIMGLVYARIYRVAKLRTRTLSEKRGPAGPDGASPTTENGLGKAAGENGHCAPPRTEVEPDESSAAERRRRRGALRRGGRRREGAEGDTGSADGPGPGLAAEQGARTASRSPGPGGRLSRASSRSVEFFLSRRRRARSSVCRRKVAQAREKRFTFVLAVVMGVFVLCWFPFFFSYSLYGICREACQLPEPLFKFFFWIGYCNSSLNPVIYTVFNQDFRRSFKHILFRRRRRGFRQ,5.3979400086720375 +CCN(CC)C(=O)c1ccc(cc1)[C@@H](N1C[C@@H](C)N(CC=C)C[C@@H]1C)c1cccc(O)c1,MELVPSARAELQSSPLVNLSDAFPSAFPSAGANASGSPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKLKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTQPRDGAVVCMLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDINRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRTPCGRQEPGSLRRPRQATTRERVTACTPSDGPGGGAAA,9.040958607678906 +Fc1cccc(c1)N([C@@H](C(=O)NC1CC(F)(F)C1)c1ccccc1Cl)C(=O)[C@@H]1CCC(=O)N1c1cc(ccn1)C#N,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,5.756961951313706 +COc1ncc(C)cc1-c1cccc2c(N)c(nnc12)C(=O)NC1CC1,MWGLAGGRLFGIFSAPVLVAVVCCAQSVNDPGNMSFVKETVDKLLKGYDIRLRPDFGGPPVCVGMNIDIASIDMVSEVNMDYTLTMYFQQYWRDKRLAYSGIPLNLTLDNRVADQLWVPDTYFLNDKKSFVHGVTVKNRMIRLHPDGTVLYGLRITTTAACMMDLRRYPLDEQNCTLEIESYGYTTDDIEFYWRGGDKAVTGVERIELPQFSIVEHRLVSRNVVFATGAYPRLSLSFRLKRNIGYFILQTYMPSILITILSWVSFWINYDASAARVALGITTVLTMTTINTHLRETLPKIPYVKAIDMYLMGCFVFVFLALLEYAFVNYIFFGRGPQRQKKLAEKTAKAKNDRSKSESNRVDAHGNILLTSLEVHNEMNEVSGGIGDTRNSAISFDNSGIQYRKQSMPREGHGRFLGDRSLPHKKTHLRRRSSQLKIKIPDLTDVNAIDRWSRIVFPFTFSLFNLVYWLYYVN,8.540607512240769 +COC(=O)Cn1nc(-c2cc(ccc2F)C(F)(F)F)c2cccc(C)c12,MTPMRKTNPLMKLINHSFIDLPTPSNISAWWNFGSLLGACLILQITTGLFLAMHYSPDASTAFSSIAHITRDVNYGWIIRYLHANGASMFFICLFLHIGRGLYYGSFLYSETWNIGIILLLATMATAFMGYVLPWGQMSFWGATVITNLLSAIPYIGTDLVQWIWGGYSVDSPTLTRFFTFHFILPFIIAALATLHLLFLHETGSNNPLGITSHSDKITFHPYYTIKDALGLLLFLLSLMTLTLFSPDLLGDPDNYTLANPLNTPPHIKPEWYFLFAYTILRSVPNKLGGVLALLLSILILAMIPILHMSKQQSMMFRPLSQSLYWLLAADLLILTWIGGQPVSYPFTIIGQVASVLYFTTILILMPTISLIENKMLKWA,5.981299501333757 +CCCCCCC(C)(C)\C=C/C\C=C/C\C=C/C\C=C/CCCC(=O)NCCO,MAGCRELELTNGSNGGLEFNPMKEYMILSDAQQIAVAVLCTLMGLLSALENVAVLYLILSSQRLRRKPSYLFIGSLAGADFLASVIFACNFVIFHVFHGVDSRNIFLLKIGSVTMTFTASVGSLLLTAVDRYLCLCYPPTYKALVTRGRALVALGVMWVLSALISYLPLMGWTCCPSPCSELFPLIPNDYLLGWLLFIAILFSGIIYTYGYVLWKAHQHVASLAEHQDRQVPGIARMRLDVRLAKTLGLVMAVLLICWFPALALMGHSLVTTLSDKVKEAFAFCSMLCLVNSMINPIIYALRSGEIRSAAQHCLTGWKKYLQGLGSEGKEEAPKSSVTETEAEVKTTTGPGSRTPGCSNC,6.815308569182402 +Nc1ncnc2n([C@@H]3O[C@H](COP(O)(O)=O)[C@@H](O)[C@H]3O)c(Br)nc12,MEDKLKKAKIIFVVGGPGSGKGTQCEKIVQKYGYTHLSTGDLLRAEVSSGSSRGKMLSSIMEKGELVPLETVLDMLRDAMLAKVDSSNGFLIDGYPREVKQGEEFERKIAQPTLLLYVDAGPETMTQRLLKRGETSGRVDDNEETIKKRLETYYKATEPVISFYDKRGIVRKVNAEGSVDTVFSQVCTYLDSLK,1.431798275933005 +Oc1ccc([C@H]2NC=N[C@H]2c2ccc(O)cc2I)c(I)c1,MTMTLHTKASGMALLHQIQGNELEPLNRPQLKIPLERPLGEVYLDSSKPAVYNYPEGAAYEFNAAAAANAQVYGQTGLPYGPGSEAAAFGSNGLGGFPPLNSVSPSPLMLLHPPPQLSPFLQPHGQQVPYYLENEPSGYTVREAGPPAFYRPNSDNRRQGGRERLASTNDKGSMAMESAKETRYCAVCNDYASGYHYGVWSCEGCKAFFKRSIQGHNDYMCPATNQCTIDKNRRKSCQACRLRKCYEVGMMKGGIRKDRRGGRMLKHKRQRDDGEGRGEVGSAGDMRAANLWPSPLMIKRSKKNSLALSLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNLADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLLLDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSLEEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMKCKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAEGFPATV,5.7447274948966935 +Nc1ccc(cc1)-c1cc(c([nH]1)-c1ccncc1)-c1ccc(F)cc1,MPPCQPQRPLLLLLLLLACQPQVPSAQVMDFLFEKWKLYGDQCHHNLSLLPPPTELVCNRTFDKYSCWPDTPANTTANISCPWYLPWHHKVQHRFVFKRCGPDGQWVRGPRGQPWRDASQCQMDGEEIEVQKEVAKMYSSFQVMYTVGYSLSLGALLLALAILGGLSKLHCTRNAIHANLFASFVLKASSVLVIDGLLRTRYSQKIGDDLSVSTWLSDGAVAGCRVAAVFMQYGIVANYCWLLVEGLYLHNLLGLATLPERSFFSLYLGIGWGAPMLFVVPWAVVKCLFENVQCWTSNDNMGFWWILRFPVFLAILINFFIFVRIVQLLVAKLRARQMHHTDYKFRLAKSTLTLIPLLGVHEVVFAFVTDEHAQGTLRSAKLFFDLFLSSFQGLLVAVLYCFLNKEVQSELRRRWHRWRLGKVLWEERNTSNHRASSSPGHGPPSKELQFGRGGGSQDSSAETPLAGGLPRLAESPF,5.853871964321762 +Nc1ncc(C2=CCNCC2)c2cc(oc12)-c1csc2cnccc12,MSTASAASSSSSSSAGEMIEAPSQVLNFEEIDYKEIEVEEVVGRGAFGVVCKAKWRAKDVAIKQIESESERKAFIVELRQLSRVNHPNIVKLYGACLNPVCLVMEYAEGGSLYNVLHGAEPLPYYTAAHAMSWCLQCSQGVAYLHSMQPKALIHRDLKPPNLLLVAGGTVLKICDFGTACDIQTHMTNNKGSAAWMAPEVFEGSNYSEKCDVFSWGIILWEVITRRKPFDEIGGPAFRIMWAVHNGTRPPLIKNLPKPIESLMTRCWSKDPSQRPSMEEIVKIMTHLMRYFPGADEPLQYPCQYSDEGQSNSATSTGSFMDIASTNTSNKSDTNMEQVPATNDTIKRLESKLLKNQAKQQSESGRLSLGASRGSSVESLPPTSEGKRMSADMSEIEARIAATTAYSKPKRGHRKTASFGNILDVPEIVISGNGQPRRRSIQDLTVTGTEPGQVSSRSSSPSVRMITTSGPTSEKPTRSHPWTPDDSTDTNGSDNSIPMAYLTLDHQLQPLAPCPNSKESMAVFEQHCKMAQEYMKVQTEIALLLQRKQELVAELDQDEKDQQNTSRLVQEHKKLLDENKSLSTYYQQCKKQLEVIRSQQQKRQGTS,4.627087997029894 +COC(=O)c1cccc(Oc2cccc(c2)-c2c(C)cnc3c(cccc23)C(F)(F)F)c1,SSPPQILPQLSPEQLGMIEKLVAAQQQCNRRSFSDRLRVTPWPMAPDPHSREARQQRFAHFTELAIVSVQEIVDFAKQLPGFLQLSREDQIALLKTSAIEVMLLETSRRYNPGSESITFLKDFSYNREDFAKAGLQVEFINPIFEFSRAMNELQLNDAEFALLIAISIFSADRPNVQDQLQVERLQHTYVEALHAYVSIHHPHDRLMFPRMLMKLVSLRTLSSVHSEQVFALRLQDKKLPPLLSEIWDVHE,6.0 +Cc1cc(O)cc(C)c1C[C@H](N)C(=O)N1Cc2ccccc2C[C@H]1CN[C@@H](Cc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)C(N)=O,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,9.0268721464003 +COCc1cnc(Nc2ccc(OC)nc2)c(c1)-c1nc(C)nc(N)n1,MELENYKQPVVLREDNCRRRRRMKPRSAAASLSSMELIPIEFVLPTSQRKCKSPETALLHVAGHGNVEQMKAQVWLRALETSVAADFYHRLGPHHFLLLYQKKGQWYEIYDKYQVVQTLDCLRYWKATHRSPGQIHLVQRHPPSEESQAFQRQLTALIGYDVTDVSNVHDDELEFTRRGLVTPRMAEVASRDPKLYAMHPWVTSKPLPEYLWKKIANNCIFIVIHRSTTSQTIKVSPDDTPGAILQSFFTKMAKKKSLMDIPESQSEQDFVLRVCGRDEYLVGETPIKNFQWVRHCLKNGEEIHVVLDTPPDPALDEVRKEEWPLVDDCTGVTGYHEQLTIHGKDHESVFTVSLWDCDRKFRVKIRGIDIPVLPRNTDLTVFVEANIQHGQQVLCQRRTSPKPFTEEVLWNVWLEFSIKIKDLPKGALLNLQIYCGKAPALSSKASAESPSSESKGKVQLLYYVNLLLIDHRFLLRRGEYVLHMWQISGKGEDQGSFNADKLTSATNPDKENSMSISILLDNYCHPIALPKHQPTPDPEGDRVRAEMPNQLRKQLEAIIATDPLNPLTAEDKELLWHFRYESLKHPKAYPKLFSSVKWGQQEIVAKTYQLLARREVWDQSALDVGLTMQLLDCNFSDENVRAIAVQKLESLEDDDVLHYLLQLVQAVKFEPYHDSALARFLLKRGLRNKRIGHFLFWFLRSEIAQSRHYQQRFAVILEAYLRGCGTAMLHDFTQQVQVIEMLQKVTLDIKSLSAEKYDVSSQVISQLKQKLENLQNSQLPESFRVPYDPGLKAGALAIEKCKVMASKKKPLWLEFKCADPTALSNETIGIIFKHGDDLRQDMLILQILRIMESIWETESLDLCLLPYGCISTGDKIGMIEIVKDATTIAKIQQSTVGNTGAFKDEVLNHWLKEKSPTEEKFQAAVERFVYSCAGYCVATFVLGIGDRHNDNIMITETGNLFHIDFGHILGNYKSFLGINKERVPFVLTPDFLFVMGTSGKKTSPHFQKFQDICVKAYLALRHHTNLLIILFSMMLMTGMPQLTSKEDIEYIRDALTVGKNEEDAKKYFLDQIEVCRDKGWTVQFNWFLHLVLGIKQGEKHSA,8.045757490560675 +OC1CNC(Nc2cc(O)cc(c2)C(=O)NCC(=O)N[C@@H](CC(O)=O)c2cc(Br)cc(c2)C(F)(F)F)=NC1,MCGSALAFFTAAFVCLQNDRRGPASFLWAAWVFSLVLGLGQGEDNRCASSNAASCARCLALGPECGWCVQEDFISGGSRSERCDIVSNLISKGCSVDSIEYPSVHVIIPTENEINTQVTPGEVSIQLRPGAEANFMLKVHPLKKYPVDLYYLVDVSASMHNNIEKLNSVGNDLSRKMAFFSRDFRLGFGSYVDKTVSPYISIHPERIHNQCSDYNLDCMPPHGYIHVLSLTENITEFEKAVHRQKISGNIDTPEGGFDAMLQAAVCESHIGWRKEAKRLLLVMTDQTSHLALDSKLAGIVVPNDGNCHLKNNVYVKSTTMEHPSLGQLSEKLIDNNINVIFAVQGKQFHWYKDLLPLLPGTIAGEIESKAANLNNLVVEAYQKLISEVKVQVENQVQGIYFNITAICPDGSRKPGMEGCRNVTSNDEVLFNVTVTMKKCDVTGGKNYAIIKPIGFNETAKIHIHRNCSCQCEDNRGPKGKCVDETFLDSKCFQCDENKCHFDEDQFSSESCKSHKDQPVCSGRGVCVCGKCSCHKIKLGKVYGKYCEKDDFSCPYHHGNLCAGHGECEAGRCQCFSGWEGDRCQCPSAAAQHCVNSKGQVCSGRGTCVCGRCECTDPRSIGRFCEHCPTCYTACKENWNCMQCLHPHNLSQAILDQCKTSCALMEQQHYVDQTSECFSSPSYLRIFFIIFIVTFLIGLLKVLIIRQVILQWNSNKIKSSSDYRVSASKKDKLILQSVCTRAVTYRREKPEEIKMDISKLNAHETFRCNF,9.301029995663981 +NC(=O)c1cnn2ccc(nc12)N1CCC[C@@H]1c1cc(F)ccc1F,MLRGGRRGQLGWHSWAAGPGSLLAWLILASAGAAPCPDACCPHGSSGLRCTRDGALDSLHHLPGAENLTELYIENQQHLQHLELRDLRGLGELRNLTIVKSGLRFVAPDAFHFTPRLSRLNLSFNALESLSWKTVQGLSLQELVLSGNPLHCSCALRWLQRWEEEGLGGVPEQKLQCHGQGPLAHMPNASCGVPTLKVQVPNASVDVGDDVLLRCQVEGRGLEQAGWILTELEQSATVMKSGGLPSLGLTLANVTSDLNRKNVTCWAENDVGRAEVSVQVNVSFPASVQLHTAVEMHHWCIPFSVDGQPAPSLRWLFNGSVLNETSFIFTEFLEPAANETVRHGCLRLNQPTHVNNGNYTLLAANPFGQASASIMAAFMDNPFEFNPEDPIPVSFSPVDTNSTSGDPVEKKDETPFGVSVAVGLAVFACLFLSTLLLVLNKCGRRNKFGINRPAVLAPEDGLAMSLHFMTLGGSSLSPTEGKGSGLQGHIIENPQYFSDACVHHIKRRDIVLKWELGEGAFGKVFLAECHNLLPEQDKMLVAVKALKEASESARQDFQREAELLTMLQHQHIVRFFGVCTEGRPLLMVFEYMRHGDLNRFLRSHGPDAKLLAGGEDVAPGPLGLGQLLAVASQVAAGMVYLAGLHFVHRDLATRNCLVGQGLVVKIGDFGMSRDIYSTDYYRVGGRTMLPIRWMPPESILYRKFTTESDVWSFGVVLWEIFTYGKQPWYQLSNTEAIDCITQGRELERPRACPPEVYAIMRGCWQREPQQRHSIKDVHARLQALAQAPPVYLDVLG,8.709965388637482 +Cc1nc2[C@H]3CCC[C@@H](Cc2c(n1)-c1ccc(F)cc1)N3C(=O)c1cccc(c1Cl)C(F)(F)F,MPACCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENVTEGGVTKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSRLSLSLHHSPPIPGQPEEMQLLQIEAVPRSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY,7.779891911959945 +COC1(C2CCCC1CN(Cc1c[nH]c3ccccc13)C2)c1ccnc(c1)C(N)=O,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,9.0 +C[C@@H](Oc1cc(sc1C(N)=O)-n1cnc2ccc(CN3CCN(C)CC3)cc12)c1ccccc1C(F)(F)F,MGRKEEDDCSSWKKQTTNIRKTFIFMEVLGSGAFSEVFLVKQRLTGKLFALKCIKKSPAFRDSSLENEIAVLKKIKHENIVTLEDIYESTTHYYLVMQLVSGGELFDRILERGVYTEKDASLVIQQVLSAVKYLHENGIVHRDLKPENLLYLTPEENSKIMITDFGLSKMEQNGIMSTACGTPGYVAPEVLAQKPYSKAVDCWSIGVITYILLCGYPPFYEETESKLFEKIKEGYYEFESPFWDDISESAKDFICHLLEKDPNERYTCEKALSHPWIDGNTALHRDIYPSVSLQIQKNFAKSKWRQAFNAAAVVHHMRKLHMNLHSPGVRPEVENRPPETQASETSRPSSPEITITEAPVLDHSVALPALTQLPCQHGRRPTAPGGRSLNCLVNGSLHISSSLVPMHQGSLAAGPCGCCSSCLNIGSKGKSSYCSEPTLLKKANKKQNFKSEVMVPVKASGSSHCRAGQTGVCLIM,5.0 +CCOc1ccc(CC(=O)CNN([C@@H](Cc2ccccc2)C(=O)NCc2ccc(CN)cc2)C(=O)CC)cc1,MILFKQATYFISLFATVSCGCLTQLYENAFFRGGDVASMYTPNAQYCQMRCTFHPRCLLFSFLPASSINDMEKRFGCFLKDSVTGTLPKVHRTGAVSGHSLKQCGHQISACHRDIYKGVDMRGVNFNVSKVSSVEECQKRCTNNIRCQFFSYATQTFHKAEYRNNCLLKYSPGGTPTAIKVLSNVESGFSLKPCALSEIGCHMNIFQHLAFSDVDVARVLTPDAFVCRTICTYHPNCLFFTFYTNVWKIESQRNVCLLKTSESGTPSSSTPQENTISGYSLLTCKRTLPEPCHSKIYPGVDFGGEELNVTFVKGVNVCQETCTKMIRCQFFTYSLLPEDCKEEKCKCFLRLSMDGSPTRIAYGTQGSSGYSLRLCNTGDNSVCTTKTSTRIVGGTNSSWGEWPWQVSLQVKLTAQRHLCGGSLIGHQWVLTAAHCFDGLPLQDVWRIYSGILNLSDITKDTPFSQIKEIIIHQNYKVSEGNHDIALIKLQAPLNYTEFQKPICLPSKGDTSTIYTNCWVTGWGFSKEKGEIQNILQKVNIPLVTNEECQKRYQDYKITQRMVCAGYKEGGKDACKGDSGGPLVCKHNGMWRLVGITSWGEGCARREQPGVYTKVAEYMDWILEKTQSSDGKAQMQSPA,7.050609993355087 +CCN(CC)CCOc1ccc(Nc2cc3n(CC)c(=O)c(cc3cn2)-c2c(F)cccc2F)nc1,MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGERLQIVNNTEGDWWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAENPRGTFLVRESETTKGAYCLSVSDFDNAKGLNVKHYKIRKLDSGGFYITSRTQFNSLQQLVAYYSKHADGLCHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWNGTTRVAIKTLKPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLLDFLKGETGKYLRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGLARLIEDNEYTARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMVNREVLDQVERGYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQYQPGENL,7.0 +ONC(=O)\C=C\c1cn(nn1)C(Cc1cccc(c1)-c1ccccc1)\C=C\c1ccccc1,MEEPEEPADSGQSLVPVYIYSPEYVSMCDSLAKIPKRASMVHSLIEAYALHKQMRIVKPKVASMEEMATFHTDAYLQHLQKVSQEGDDDHPDSIEYGLGYDCPATEGIFDYAAAIGGATITAAQCLIDGMCKVAINWSGGWHHAKKDEASGFCYLNDAVLGILRLRRKFERILYVDLDLHHGDGVEDAFSFTSKVMTVSLHKFSPGFFPGTGDVSDVGLGKGRYYSVNVPIQDGIQDEKYYQICESVLKEVYQAFNPKAVVLQLGADTIAGDPMCSFNMTPVGIGKCLKYILQWQLATLILGGGGYNLANTARCWTYLTGVILGKTLSSEIPDHEFFTAYGPDYVLEITPSCRPDRNEPHRIQQILNYIKGNLKHVV,6.394694953858891 +Cc1nc(sc1C(=O)NCc1ccc(cc1)-c1c(O)c(=O)c1=O)-c1ccc(cc1)C(F)(F)F,MGETLGDSPIDPESDSFTDTLSANISQEMTMVDTEMPFWPTNFGISSVDLSVMEDHSHSFDIKPFTTVDFSSISTPHYEDIPFTRTDPVVADYKYDLKLQEYQSAIKVEPASPPYYSEKTQLYNKPHEEPSNSLMAIECRVCGDKASGFHYGVHACEGCKGFFRRTIRLKLIYDRCDLNCRIHKKSRNKCQYCRFQKCLAVGMSHNAIRFGRMPQAEKEKLLAEISSDIDQLNPESADLRALAKHLYDSYIKSFPLTKAKARAILTGKTTDKSPFVIYDMNSLMMGEDKIKFKHITPLQEQSKEVAIRIFQGCQFRSVEAVQEITEYAKSIPGFVNLDLNDQVTLLKYGVHEIIYTMLASLMNKDGVLISEGQGFMTREFLKSLRKPFGDFMEPKFEFAVKFNALELDDSDLAIFIAVIILSGDRPGLLNVKPIEDIQDNLLQALELQLKLNHPESSQLFAKLLQKMTDLRQIVTEHVQLLQVIKKTETDMSLHPLLQEIYKDLY,5.0 +CN1CCN(CC1)C(=O)c1ccc2n3CC[C@H]4[C@H]([C@H](c5cccc(Cl)c5F)[C@@]5(N4CC4CC4)C(=O)Nc4cc(Cl)ccc54)c3nc2c1,EQETLVRPKPLLLKLLKSVGAQKDTYTMKEVLFYLGQYIMTKRLYDEKQQHIVYCSNDLLGDLFGVPSFSVKEHRKIYTMIYRNLVVVNQQESSD,8.0 +CC(C)(NCC(O)COc1cccc2[nH]ccc12)C1CCC(C)(CC1)NC(=O)CBr,MAPWPHKNGSLAFWSDAPTLDPSAANTSGLPGVPWAAALAGALLALATVGGNLLVITAIARTPRLQTITNVFVTSLATADLVVGLLVMPPGATLALTGHWPLGATGCELWTSVDVLCVTASIETLCALAVDRYLAVTNPLRYGTLVTKRRARAAVVLVWIVSATVSFAPIMSQWWRVGADAEAQECHSNPRCCSFASNMPYALLSSSVSFYLPLLVMLFVYARVFVVAKRQRRLLRRELGRFPPEESPRSPSRSPSPATVGTPTASDGVPSCGRRPARLLPLGEHRALRTLGLIMGIFSLCWLPFFLANVLRALVGPSLVPSGVFIALNWLGYANSAFNPLIYCRSPDFRDAFRRLLCSYGGRGPEEPRVVTFPASPVASRQNSPLNRFDGYEGERPFPT,8.698970004336019 +CC(NC(=O)C(=O)NCc1cccnc1)C(N1CCN(CC1)c1ccc(F)cc1)c1cccs1,MAVRELPGAWNFRDVADTATALRPGRLFRSSELSRLDDAGRATLRRLGITDVADLRSSREVARRGPGRVPDGIDVHLLPFPDLADDDADDSAPHETAFKRLLTNDGSNGESGESSQSINDAATRYMTDEYRQFPTRNGAQRALHRVVTLLAAGRPVLTHCFAGKDRTGFVVALVLEAVGLDRDVIVADYLRSNDSVPQLRARISEMIQQRFDTELAPEVVTFTKARLSDGVLGVRAEYLAAARQTIDETYGSLGGYLRDAGISQATVNRMRGVLLG,5.040958607678906 +[Br-],MTGHHGWGYGQDDGPSHWHKLYPIAQGDRQSPINIISSQAVYSPSLQPLELSYEACMSLSITNNGHSVQVDFNDSDDRTVVTGGPLEGPYRLKQFHFHWGKKHDVGSEHTVDGKSFPSELHLVHWNAKKYSTFGEAASAPDGLAVVGVFLETGDEHPSMNRLTDALYMVRFKGTKAQFSCFNPKCLLPASRHYWTYPGSLTTPPLSESVTWIVLREPICISERQMGKFRSLLFTSEDDERIHMVNNFRPPQPLKGRVVKASFRA,2.9746941347352296 +Cc1ccc2N(CCCc2c1)C(=O)CCc1nc2ccccc2c(=O)[nH]1,MAESSDKLYRVEYAKSGRASCKKCSESIPKDSLRMAIMVQSPMFDGKVPHWYHFSCFWKVGHSIRHPDVEVDGFSELRWDDQQKVKKTAEAGGVTGKGQDGIGSKAEKTLGDFAAEYAKSNRSTCKGCMEKIEKGQVRLSKKMVDPEKPQLGMIDRWYHPGCFVKNREELGFRPEYSASQLKGFSLLATEDKEALKKQLPGVKSEGKRKGDEVDGVDEVAKKKSKKEKDKDSKLEKALKAQNDLIWNIKDELKKVCSTNDLKELLIFNKQQVPSGESAILDRVADGMVFGALLPCEECSGQLVFKSDAYYCTGDVTAWTKCMVKTQTPNRKEWVTPKEFREISYLKKLKVKKQDRIFPPETSASVAATPPPSTASAPAAVNSSASADKPLSNMKILTLGKLSRNKDEVKAMIEKLGGKLTGTANKASLCISTKKEVEKMNKKMEEVKEANIRVVSEDFLQDVSASTKSLQELFLAHILSPWGAEVKAEPVEVVAPRGKSGAALSKKSKGQVKEEGINKSEKRMKLTLKGGAAVDPDSGLEHSAHVLEKGGKVFSATLGLVDIVKGTNSYYKLQLLEDDKENRYWIFRSWGRVGTVIGSNKLEQMPSKEDAIEHFMKLYEEKTGNAWHSKNFTKYPKKFYPLEIDYGQDEEAVKKLTVNPGTKSKLPKPVQDLIKMIFDVESMKKAMVEYEIDLQKMPLGKLSKRQIQAAYSILSEVQQAVSQGSSDSQILDLSNRFYTLIPHDFGMKKPPLLNNADSVQAKVEMLDNLLDIEVAYSLLRGGSDDSSKDPIDVNYEKLKTDIKVVDRDSEEAEIIRKYVKNTHATTHNAYDLEVIDIFKIEREGECQRYKPFKQLHNRRLLWHGSRTTNFAGILSQGLRIAPPEAPVTGYMFGKGIYFADMVSKSANYCHTSQGDPIGLILLGEVALGNMYELKHASHISKLPKGKHSVKGLGKTTPDPSANISLDGVDVPLGTGISSGVNDTSLLYNEYIVYDIAQVNLKYLLKLKFNFKTSLW,5.987162775294828 +C(N1CCC(CC1)\C=C/c1noc2ccccc12)c1ccccc1,MRPPQCLLHTPSLASPLLLLLLWLLGGGVGAEGREDAELLVTVRGGRLRGIRLKTPGGPVSAFLGIPFAEPPMGPRRFLPPEPKQPWSGVVDATTFQSVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLVWIYGGGFYSGASSLDVYDGRFLVQAERTVLVSMNYRVGAFGFLALPGSREAPGNVGLLDQRLALQWVQENVAAFGGDPTSVTLFGESAGAASVGMHLLSPPSRGLFHRAVLQSGAPNGPWATVGMGEARRRATQLAHLVGCPPGGTGGNDTELVACLRTRPAQVLVNHEWHVLPQESVFRFSFVPVVDGDFLSDTPEALINAGDFHGLQVLVGVVKDEGSYFLVYGAPGFSKDNESLISRAEFLAGVRVGVPQVSDLAAEAVVLHYTDWLHPEDPARLREALSDVVGDHNVVCPVAQLAGRLAAQGARVYAYVFEHRASTLSWPLWMGVPHGYEIEFIFGIPLDPSRNYTAEEKIFAQRLMRYWANFARTGDPNEPRDPKAPQWPPYTAGAQQYVSLDLRPLEVRRGLRAQACAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQDRCSDL,6.6777807052660805 +COc1cc2CN(C)CCc2cc1O,MRGTPLLLVSLFSLLQDGDCRLANAEEKLMDDLLNKTRYNNLIRPATSSSQLISIRLELSLSQLISVNEREQIMTTSIWLKQEWTDYRLAWNSSCYEGVNILRIPAKRVWLPDIVLYNNADGTYEVSVYTNVIVRSNGSIQWLPPAIYKSACKIEVKHFPFDQQNCTLKFRSWTYDHTEIDMVLKSPTAIMDDFTPSGEWDIVALPGRRTVNPQDPSYVDVTYDFIIKRKPLFYTINLIIPCVLITSLAILVFYLPSDCGEKMTLCISVLLALTFFLLLISKIVPPTSLDIPLIGKYLLFTMVLVTFSIVTTVCVLNVHHRSPSTHTMASWVKECFLHKLPTFLFMKRPGLEVSLVRVPHPSQLHLATADTAATSALGPTSPSNLYGSSMYFVNPVPAAPKSAVSSHTAGLPRDARLRSSGRFREDLQEALEGVSFIAQHLESDDRDQSVIEDWKFVAMVVDRLFLWVFVFVCILGTMGLFLPPLFQIHAPSKDS,3.0 +O[C@H](CCN1CCC(CCOC(c2ccc(F)cc2)c2ccc(F)cc2)CC1)c1ccccc1,MLLARMNPQVQPENNGADTGPEQPLRARKTAELLVVKERNGVQCLLAPRDGDAQPRETWGKKIDFLLSVVGFAVDLANVWRFPYLCYKNGGGAFLIPYTLFLIIAGMPLFYMELALGQYNREGAATVWKICPFFKGVGYAVILIALYVGFYYNVIIAWSLYYLFSSFTLNLPWTDCGHTWNSPNCTDPKLLNGSVLGNHTKYSKYKFTPAAEFYERGVLHLHESSGIHDIGLPQWQLLLCLMVVVIVLYFSLWKGVKTSGKVVWITATLPYFVLFVLLVHGVTLPGASNGINAYLHIDFYRLKEATVWIDAATQIFFSLGAGFGVLIAFASYNKFDNNCYRDALLTSSINCITSFVSGFAIFSILGYMAHEHKVNIEDVATEGAGLVFILYPEAISTLSGSTFWAVVFFVMLLALGLDSSMGGMEAVITGLADDFQVLKRHRKLFTFGVTFSTFLLALFCITKGGIYVLTLLDTFAAGTSILFAVLMEAIGVSWFYGVDRFSNDIQQMMGFRPGLYWRLCWKFVSPAFLLFVVVVSIINFKPLTYDDYIFPPWANWVGWGIALSSMVLVPIYVIYKFLSTQGSLWERLAYGITPENEHHLVAQRDIRQFQLQHWLAI,6.481486060122112 +FC(F)(F)c1ccccc1-c1cc2C(=O)c3ccccc3-c2nn1,MSNKCDVIVVGGGISGMAAAKLLHDCGLSVVVLEARDRVGGRTYTIRNKNVKYVDLGGSYVGPTQNRILRLAKELGLETYKVNEVERLIHFVKGKSYAFRGPFPPVWNPITYLDYNNLWRTMDEMGQEIPSDAPWKAPLAEEWDYMTMKELLDKICWTNSTKQIATLFVNLCVTAETHEVSALWFLWYVKQCGGTTRIISTTNGGQERKFIGGSGQVSERIKDILGDRVKLERPVIHIDQTGENVVVKTLNHEIYEAKYVISAIPPVLGMKIHHSPPLPILRNQLITRVPLGSVIKCMVYYKEPFWRKKDFCGTMVIEGEEAPIAYTLDDTKPDGSCAAIMGFILAHKARKLVRLTKEERLRKLCELYAKVLNSQEALQPVHYEEKNWCEEQYSGGCYTAYFPPGILTQYGRVLRQPVGKIFFAGTETASHWSGYMEGAVEAGERAAREILHAIGKIPEDEIWQPEPESVDVPARPITNTFLERHLPSVPGLLKLLGLTTILSATALGFLAHKKGLFVRF,5.0 +CNC(=O)[C@@H](NC(=O)[C@H](CC(C)C)[C@H](C)C(=O)NO)c1ccccc1,MSPAPRPPRCLLLPLLTLGTALASLGSAQSSSFSPEAWLQQYGYLPPGDLRTHTQRSPQSLSAAIAAMQKFYGLQVTGKADADTMKAMRRPRCGVPDKFGAEIKANVRRKRYAIQGLKWQHNEITFCIQNYTPKVGEYATYEAIRKAFRVWESATPLRFREVPYAYIREGHEKQADIMIFFAEGFHGDSTPFDGEGGFLAHAYFPGPNIGGDTHFDSAEPWTVRNEDLNGNDIFLVAVHELGHALGLEHSSDPSAIMAPFYQWMDTENFVLPDDDRRGIQQLYGGESGFPTKMPPQPRTTSRPSVPDKPKNPTYGPNICDGNFDTVAMLRGEMFVFKERWFWRVRNNQVMDGYPMPIGQFWRGLPASINTAYERKDGKFVFFKGDKHWVFDEASLEPGYPKHIKELGRGLPTDKIDAALFWMPNGKTYFFRGNKYYRFNEELRAVDSEYPKNIKVWEGIPESPRGSFMGSDEVFTYFYKGNKYWKFNNQKLKVEPGYPKSALRDWMGCPSGGRPDEGTEEETEVIIIEVDEEGGGAVSAAAVVLPVLLLLLVLAVGLAVFFFRRHGTPRRLLYCQRSLLDKV,7.251811972993799 +C[C@H](Nc1nccc(n1)S(C)=O)c1cc2cc(Cl)ccc2[nH]c1=O,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,7.0 +Oc1ccccc1-c1nc(NCCN2CCOCC2)c2ccccc2n1,MSLHFLYYCSEPTLDVKIAFCQGFDKQVDVSYIAKHYNMSKSKVDNQFYSVEVGDSTFTVLKRYQNLKPIGSGAQGIVCAAYDAVLDRNVAIKKLSRPFQNQTHAKRAYRELVLMKCVNHKNIISLLNVFTPQKTLEEFQDVYLVMELMDANLCQVIQMELDHERMSYLLYQMLCGIKHLHSAGIIHRDLKPSNIVVKSDCTLKILDFGLARTAGTSFMMTPYVVTRYYRAPEVILGMGYKENVDIWSVGCIMGEMVRHKILFPGRDYIDQWNKVIEQLGTPCPEFMKKLQPTVRNYVENRPKYAGLTFPKLFPDSLFPADSEHNKLKASQARDLLSKMLVIDPAKRISVDDALQHPYINVWYDPAEVEAPPPQIYDKQLDEREHTIEEWKELIYKEVMNSEEKTKNGVVKGQPSPSGAAVNSSESLPPSSSVNDISSMSTDQTLASDTDSSLEASAGPLGCCR,4.508078287413849 +Br.N#Cc1ccccc1-c1ccc(CN2C3=NCCCN3c3ccccc23)cc1,MRRLSSWRKMATAEKQKHDGRVKIGHYILGDTLGVGTFGKVKVGKHELTGHKVAVKILNRQKIRSLDVVGKIRREIQNLKLFRHPHIIKLYQVISTPSDIFMVMEYVSGGELFDYICKNGRLDEKESRRLFQQILSGVDYCHRHMVVHRDLKPENVLLDAHMNAKIADFGLSNMMSDGEFLRTSCGSPNYAAPEVISGRLYAGPEVDIWSSGVILYALLCGTLPFDDDHVPTLFKKICDGIFYTPQYLNPSVISLLKHMLQVDPMKRATIKDIREHEWFKQDLPKYLFPEDPSYSSTMIDDEALKEVCEKFECSEEEVLSCLYNRNHQDPLAVAYHLIIDNRRIMNEAKDFYLATSPPDSFLDDHHLTRPHPERVPFLVAETPRARHTLDELNPQKSKHQGVRKAKWHLGIRSQSRPNDIMAEVCRAIKQLDYEWKVVNPYYLRVRRKNPVTSTYSKMSLQLYQVDSRTYLLDFRSIDDEITEAKSGTATPQRSGSVSNYRSCQRSDSDAEAQGKSSEVSLTSSVTSLDSSPVDLTPRPGSHTIEFFEMCANLIKILAQ,6.468521082957745 +COc1cc2nc(Nc3c(C)cccc3C)c3cncn3c2cc1OC,MGCGCSSHPEDDWMENIDVCENCHYPIVPLDGKGTLLIRNGSEVRDPLVTYEGSNPPASPLQDNLVIALHSYEPSHDGDLGFEKGEQLRILEQSGEWWKAQSLTTGQEGFIPFNFVAKANSLEPEPWFFKNLSRKDAERQLLAPGNTHGSFLIRESESTAGSFSLSVRDFDQNQGEVVKHYKIRNLDNGGFYISPRITFPGLHELVRHYTNASDGLCTRLSRPCQTQKPQKPWWEDEWEVPRETLKLVERLGAGQFGEVWMGYYNGHTKVAVKSLKQGSMSPDAFLAEANLMKQLQHQRLVRLYAVVTQEPIYIITEYMENGSLVDFLKTPSGIKLTINKLLDMAAQIAEGMAFIEERNYIHRDLRAANILVSDTLSCKIADFGLARLIEDNEYTAREGAKFPIKWTAPEAINYGTFTIKSDVWSFGILLTEIVTHGRIPYPGMTNPEVIQNLERGYRMVRPDNCPEELYQLMRLCWKERPEDRPTFDYLRSVLEDFFTATEGQYQPQP,8.619788758288394 +CCCOc1ccc(NC(=O)O\N=C\c2ccccc2)cc1,MVQYELWAALPGASGVALACCFVAAAVALRWSGRRTARGAVVRARQRQRAGLENMDRAAQRFRLQNPDLDSEALLALPLPQLVQKLHSRELAPEAVLFTYVGKAWEVNKGTNCVTSYLADCETQLSQAPRQGLLYGVPVSLKECFTYKGQDSTLGLSLNEGVPAECDSVVVHVLKLQGAVPFVHTNVPQSMFSYDCSNPLFGQTVNPWKSSKSPGGSSGGEGALIGSGGSPLGLGTDIGGSIRFPSSFCGICGLKPTGNRLSKSGLKGCVYGQEAVRLSVGPMARDVESLALCLRALLCEDMFRLDPTVPPLPFREEVYTSSQPLRVGYYETDNYTMPSPAMRRAVLETKQSLEAAGHTLVPFLPSNIPHALETLSTGGLFSDGGHTFLQNFKGDFVDPCLGDLVSILKLPQWLKGLLAFLVKPLLPRLSAFLSNMKSRSAGKLWELQHEIEVYRKTVIAQWRALDLDVVLTPMLAPALDLNAPGRATGAVSYTMLYNCLDFPAGVVPVTTVTAEDEAQMEHYRGYFGDIWDKMLQKGMKKSVGLPVAVQCVALPWQEELCLRFMREVERLMTPEKQSS,8.031517051446064 +CCNC(=O)c1c(C)ccc2nc(Cn3nc(cc3C(F)(F)F)C3CC3)cc(=O)n12,MSTMRLLTLALLFSCSVARAACDPKIVNIGAVLSTRKHEQMFREAVNQANKRHGSWKIQLNATSVTHKPNAIQMALSVCEDLISSQVYAILVSHPPTPNDHFTPTPVSYTAGFYRIPVLGLTTRMSIYSDKSIHLSFLRTVPPYSHQSSVWFEMMRVYSWNHIILLVSDDHEGRAAQKRLETLLEERESKAEKVLQFDPGTKNVTALLMEAKELEARVIILSASEDDAATVYRAAAMLNMTGSGYVWLVGEREISGNALRYAPDGILGLQLINGKNESAHISDAVGVVAQAVHELLEKENITDPPRGCVGNTNIWKTGPLFKRVLMSSKYADGVTGRVEFNEDGDRKFANYSIMNLQNRKLVQVGIYNGTHVIPNDRKIIWPGGETEKPRGYQMSTRLKIVTIHQEPFVYVKPTLSDGTCKEEFTVNGDPVKKVICTGPNDTSPGSPRHTVPQCCYGFCIDLLIKLARTMNFTYEVHLVADGKFGTQERVNNSNKKEWNGMMGELLSGQADMIVAPLTINNERAQYIEFSKPFKYQGLTILVKKEIPRSTLDSFMQPFQSTLWLLVGLSVHVVAVMLYLLDRFSPFGRFKVNSEEEEEDALTLSSAMWFSWGVLLNSGIGEGAPRSFSARILGMVWAGFAMIIVASYTANLAAFLVLDRPEERITGINDPRLRNPSDKFIYATVKQSSVDIYFRRQVELSTMYRHMEKHNYESAAEAIQAVRDNKLHAFIWDSAVLEFEASQKCDLVTTGELFFRSGFGIGMRKDSPWKQNVSLSILKSHENGFMEDLDKTWVRYQECDSRSNAPATLTFENMAGVFMLVAGGIVAGIFLIFIEIAYKRHKDARRKQMQLAFAAVNVWRKNLQDRKSGRAEPDPKKKATFRAITSTLASSFKRRRSSKDTSTGGGRGALQNQKDTVLPRRAIEREEGQLQLCSRHRES,4.790484985457369 +C[C@@H](O)[C@@H]1NC(=O)[C@H](CCCCN)NC(=O)[C@@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](Cc2ccccc2)NC(=O)[C@H](Cc2ccc(Cl)cc2)NC(=O)CCCCCCNC(=O)[C@H](Cc2ccccc2)NC1=O,MEMSSEQLNGSQVWVSSPFDLNGSLGPSNGSNQTEPYYDMTSNAVLTFIYFVVCVVGLCGNTLVIYVILRYAKMKTITNIYILNLAIADELFMLGLPFLAMQVALVHWPFGKAICRVVMTVDGINQFTSIFCLTVMSIDRYLAVVHPIKSAKWRRPRTAKMINVAVWCVSLLVILPIMIYAGLRSNQWGRSSCTINWPGESGAWYTGFIIYAFILGFLVPLTIICLCYLFIIIKVKSSGIRVGSSKRKKSEKKVTRMVSIVVAVFIFCWLPFYIFNVSSVSVAISPTPALKGMFDFVVILTYANSCANPILYAFLSDNFKKSFQNVLCLVKVSGTEDGERSDSKQDKSRLNETTETQRTLLNGDLQTSI,8.08039897621589 +CN1CCN(CC1)c1nc2ccccc2c2CCCCc12,MPLCIPQVLLALFLSVLIAQGEGSRRRATQAHSTTQPALLRLSDHLLANYKKGVRPVRDWRKPTLVSIDVIMYAILNVDEKNQVLTTYIWYRQFWTDEFLQWTPEDFDNVTKLSIPTDSIWVPDILINEFVDVGKSPSIPYVYVHHQGEVQNYKPLQLVTACSLDIYNFPFDVQNCSLTFTSWLHTIQDINISLWRTPEEVRSDKSIFINQGEWELLGVFTKFQEFSIETSNSYAEMKFYVVIRRRPLFYAVSLLLPSIFLMVVDIVGFCLPPDSGERVSFKITLLLGYSVFLIIVSDTLPATAIGTPLIGVYFVVCMALLVISLAETIFIVQLVHKQDLQRPVPDWLRHLVLDRIAWLLCLGEQPMAHRPPATFQANKTDDCSAMGNHCSHVGSPQDLEKTSRSRDSPLPPPREASLAVRGLLQELSSIRHSLEKRDEMREVARDWLRVGYVLDRLLFRIYLLAVLAYSITLVTLWSIWHYS,10.009998764965339 +Cc1ccc(CCNC(=O)C2CCC(=O)N2Cc2cccnc2)cc1,MWCIVLFSLLAWVYAEPTMYGEILSPNYPQAYPSEVEKSWDIEVPEGYGIHLYFTHLDIELSENCAYDSVQIISGDTEEGRLCGQRSSNNPHSPIVEEFQVPYNKLQVIFKSDFSNEERFTGFAAYYVATDINECTDFVDVPCSHFCNNFIGGYFCSCPPEYFLHDDMKNCGVNCSGDVFTALIGEIASPNYPKPYPENSRCEYQIRLEKGFQVVVTLRREDFDVEAADSAGNCLDSLVFVAGDRQFGPYCGHGFPGPLNIETKSNALDIIFQTDLTGQKKGWKLRYHGDPMPCPKEDTPNSVWEPAKAKYVFRDVVQITCLDGFEVVEGRVGATSFYSTCQSNGKWSNSKLKCQPVDCGIPESIENGKVEDPESTLFGSVIRYTCEEPYYYMENGGGGEYHCAGNGSWVNEVLGPELPKCVPVCGVPREPFEEKQRIIGGSDADIKNFPWQVFFDNPWAGGALINEYWVLTAAHVVEGNREPTMYVGSTSVQTSRLAKSKMLTPEHVFIHPGWKLLEVPEGRTNFDNDIALVRLKDPVKMGPTVSPICLPGTSSDYNLMDGDLGLISGWGRTEKRDRAVRLKAARLPVAPLRKCKEVKVEKPTADAEAYVFTPNMICAGGEKGMDSCKGDSGGAFAVQDPNDKTKFYAAGLVSWGPQCGTYGLYTRVKNYVDWIMKTMQENSTPRED,4.301029995663981 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+CCc1cnc(nc1NC(C)C)-c1ccccn1,MSFRAARLSMRNRRNDTLDSTRTLYSSASRSTDLSYSESDLVNFIQANFKKRECVFFTKDSKATENVCKCGYAQSQHMEGTQINQSEKWNYKKHTKEFPTDAFGDIQFETLGKKGKYIRLSCDTDAEILYELLTQHWHLKTPNLVISVTGGAKNFALKPRMRKIFSRLIYIAQSKGAWILTGGTHYGLMKYIGEVVRDNTISRSSEENIVAIGIAAWGMVSNRDTLIRNCDAEGYFLAQYLMDDFTRDPLYILDNNHTHLLLVDNGCHGHPTVEAKLRNQLEKYISERTIQDSNYGGKIPIVCFAQGGGKETLKAINTSIKNKIPCVVVEGSGQIADVIASLVEVEDALTSSAVKEKLVRFLPRTVSRLPEEETESWIKWLKEILECSHLLTVIKMEEAGDEIVSNAISYALYKAFSTSEQDKDNWNGQLKLLLEWNQLDLANDEIFTNDRRWESADLQEVMFTALIKDRPKFVRLFLENGLNLRKFLTHDVLTELFSNHFSTLVYRNLQIAKNSYNDALLTFVWKLVANFRRGFRKEDRNGRDEMDIELHDVSPITRHPLQALFIWAILQNKKELSKVIWEQTRGCTLAALGASKLLKTLAKVKNDINAAGESEELANEYETRAVELFTECYSSDEDLAEQLLVYSCEAWGGSNCLELAVEATDQHFIAQPGVQNFLSKQWYGEISRDTKNWKIILCLFIIPLVGCGFVSFRKKPVDKHKKLLWYYVAFFTSPFVVFSWNVVFYIAFLLLFAYVLLMDFHSVPHPPELVLYSLVFVLFCDEVRQWYVNGVNYFTDLWNVMDTLGLFYFIAGIVFRLHSSNKSSLYSGRVIFCLDYIIFTLRLIHIFTVSRNLGPKIIMLQRMLIDVFFFLFLFAVWMVAFGVARQGILRQNEQRWRWIFRSVIYEPYLAMFGQVPSDVDGTTYDFAHCTFTGNESKPLCVELDEHNLPRFPEWITIPLVCIYMLSTNILLVNLLVAMFGYTVGTVQENNDQVWKFQRYFLVQEYCSRLNIPFPFIVFAYFYMVVKKCFKCCCKEKNMESSVCCFKNEDNETLAWEGVMKENYLVKINTKANDTSEEMRHRFRQLDTKLNDLKGLLKEIANKIK,6.3979400086720375 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+CN1C[C@H](N(C2CCN(CC2)C2(C)CCN(CC2)C(=O)c2c(C)cc(nc2C)C#N)C1=O)c1ccccc1,MDYQVSSPIYDINYYTSEPCQKINVKQIAARLLPPLYSLVFIFGFVGNMLVILILINCKRLKSMTDIYLLNLAISDLFFLLTVPFWAHYAAAQWDFGNTMCQLLTGLYFIGFFSGIFFIILLTIDRYLAVVHAVFALKARTVTFGVVTSVITWVVAVFASLPGIIFTRSQKEGLHYTCSSHFPYSQYQFWKNFQTLKIVILGLVLPLLVMVICYSGILKTLLRCRNEKKRHRAVRLIFTIMIVYFLFWAPYNIVLLLNTFQEFFGLNNCSSSNRLDQAMQVTETLGMTHCCINPIIYAFVGEKFRNYLLVFFQKHIAKRFCKCCSIFQQEAPERASSVYTRSTGEQEISVGL,7.619788758288394 +CCOC(=O)C1C(c2ccccc2C(F)(F)F)c2c(N)c3CCCCc3nc2N=C1C,MHSKVTIICIRFLFWFLLLCMLIGKSHTEDDIIIATKNGKVRGMNLTVFGGTVTAFLGIPYAQPPLGRLRFKKPQSLTKWSDIWNATKYANSCCQNIDQSFPGFHGSEMWNPNTDLSEDCLYLNVWIPAPKPKNATVLIWIYGGGFQTGTSSLHVYDGKFLARVERVIVVSMNYRVGALGFLALPGNPEAPGNMGLFDQQLALQWVQKNIAAFGGNPKSVTLFGESAGAASVSLHLLSPGSHSLFTRAILQSGSFNAPWAVTSLYEARNRTLNLAKLTGCSRENETEIIKCLRNKDPQEILLNEAFVVPYGTPLSVNFGPTVDGDFLTDMPDILLELGQFKKTQILVGVNKDEGTAFLVYGAPGFSKDNNSIITRKEFQEGLKIFFPGVSEFGKESILFHYTDWVDDQRPENYREALGDVVGDYNFICPALEFTKKFSEWGNNAFFYYFEHRSSKLPWPEWMGVMHGYEIEFVFGLPLERRDNYTKAEEILSRSIVKRWANFAKYGNPNETQNNSTSWPVFKSTEQKYLTLNTESTRIMTKLRAQQCRFWTSFFPKVLEMTGNIDEAEWEWKAGFHRWNNYMMDWKNQFNDYTSKKESCVGL,4.0 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+CCC(CC)[C@H](NC(C)=O)[C@H]1[C@@H](C[C@@H]([C@H]1OC(=O)NCCCOC(=O)\C=C\c1ccc(O)c(O)c1)C(O)=O)NC(N)=N,MNPNQKIITIGSICMVIGIVSLMLQIGNMISIWVSHSIQTGNQRQAEPISNTKFLTEKAVASVTLAGNSSLCPISGWAVYSKDNSIRIGSRGDVFVIREPFISCSHLECRTFFLTQGALLNDKHSNGTVKDRSPHRTLMSCPVGEAPSPYNSRFESVAWSASACHDGTSWLTIGISGPDNGAVAVLKYNGIITDTIKSWRNNILRTQESECACVNGSCFTVMTDGPSSGQASYKIFKMEKGKVVKSVELDAPNYHYEECSCYPDAGEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGVFGDNPRPNDGTGSCGPVSPNGAYGVKGFSFKYGNGVWIGRTKSTNSRSGFEMIWDPNGWTGTDSSFSVKQDIVAITDWSGYSGSFVQHPELTGLDCIRPCFWVELIRGRPKESTIWTSGSSISFCGVNSDTVSWSWPDGAELPFTIDK,7.136677139879544 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+Clc1ccc(CC(=O)Nc2ccc(cc2)S(=O)(=O)Nc2ccccc2)cc1Cl,MAVESRSRVTSKLVKAHRAMLNSVTQEDLKVDRLPGADYPNPSKKYSSRTEFRDKTDYIMYNPRPRDEPSSENPVSVSPLLCELAAARSRIHFNPTETTIGIVTCGGICPGLNDVIRSITLTGINVYNVKRVIGFRFGYWGLSKKGSQTAIELHRGRVTNIHHYGGTILGSSRGPQDPKEMVDTLERLGVNILFTVGGDGTQRGALVISQEAKRRGVDISVFGVPKTIDNDLSFSHRTFGFQTAVEKAVQAIRAAYAEAVSANYGVGVVKLMGRDSGFIAAQAAVASAQANICLVPENPISEQEVMSLLERRFCHSRSCVIIVAEGFGQDWGRGSGGYDASGNKKLIDIGVILTEKVKAFLKANKSRYPDSTVKYIDPSYMIRACPPSANDALFCATLATLAVHEAMAGATGCIIAMRHNNYILVPIKVATSVRRVLDLRGQLWRQVREITVDLGSDVRLARKLEIRRELEAINRNRDRLHEELAKL,4.787812395596042 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+CC(C(O)=O)n1cnc2ccccc2c1=O,MAELSEEALLSVLPTIRVPKAGDRVHKDECAFSFDTPESEGGLYICMNTFLGFGKQYVERHFNKTGQRVYLHLRRTRRPKEEDPATGTGDPPRKKPTRLAIGVEGGFDLSEEKFELDEDVKIVILPDYLEIARDGLGGLPDIVRDRVTSAVEALLSADSASRKQEVQAWDGEVRQVSKHAFSLKQLDNPARIPPCGWKCSKCDMRENLWLNLTDGSILCGRRYFDGSGGNNHAVEHYRETGYPLAVKLGTITPDGADVYSYDEDDMVLDPSLAEHLSHFGIDMLKMQKTDKTMTELEIDMNQRIGEWELIQESGVPLKPLFGPGYTGIRNLGNSCYLNSVVQVLFSIPDFQRKYVDKLEKIFQNAPTDPTQDFSTQVAKLGHGLLSGEYSKPVPESGDGERVPEQKEVQDGIAPRMFKALIGKGHPEFSTNRQQDAQEFFLHLINMVERNCRSSENPNEVFRFLVEEKIKCLATEKVKYTQRVDYIMQLPVPMDAALNKEELLEYEEKKRQAEEEKMALPELVRAQVPFSSCLEAYGAPEQVDDFWSTALQAKSVAVKTTRFASFPDYLVIQIKKFTFGLDWVPKKLDVSIEMPEELDISQLRGTGLQPGEEELPDIAPPLVTPDEPKGSLGFYGNEDEDSFCSPHFSSPTSPMLDESVIIQLVEMGFPMDACRKAVYYTGNSGAEAAMNWVMSHMDDPDFANPLILPGSSGPGSTSAAADPPPEDCVTTIVSMGFSRDQALKALRATNNSLERAVDWIFSHIDDLDAEAAMDISEGRSAADSISESVPVGPKVRDGPGKYQLFAFISHMGTSTMCGHYVCHIKKEGRWVIYNDQKVCASEKPPKDLGYIYFYQRVAS,4.075720713938118 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+Brc1c(Br)c(Br)c2n(CC#N)cnc2c1Br,MSGPVPSRARVYTDVNTHRPREYWDYESHVVEWGNQDDYQLVRKLGRGKYSEVFEAINITNNEKVVVKILKPVKKKKIKREIKILENLRGGPNIITLADIVKDPVSRTPALVFEHVNNTDFKQLYQTLTDYDIRFYMYEILKALDYCHSMGIMHRDVKPHNVMIDHEHRKLRLIDWGLAEFYHPGQEYNVRVASRYFKGPELLVDYQMYDYSLDMWSLGCMLASMIFRKEPFFHGHDNYDQLVRIAKVLGTEDLYDYIDKYNIELDPRFNDILGRHSRKRWERFVHSENQHLVSPEALDFLDKLLRYDHQSRLTAREAMEHPYFYTVVKDQARMGSSSMPGGSTPVSSANMMSGISSVPTPSPLGPLAGSPVIAAANPLGMPVPAAAGAQQ,5.896196279044043 +CCOCCN([C@H](CC)c1nc2ccccc2c(=O)n1-c1ccc(OCC)cc1)C(=O)Cc1ccc(cc1)-c1ccccc1,MVLEVSDHQVLNDAEVAALLENFSSSYDYGENESDSCCTSPPCPQDFSLNFDRAFLPALYSLLFLLGLLGNGAVAAVLLSRRTALSSTDTFLLHLAVADTLLVLTLPLWAVDAAVQWVFGSGLCKVAGALFNINFYAGALLLACISFDRYLNIVHATQLYRRGPPARVTLTCLAVWGLCLLFALPDFIFLSAHHDERLNATHCQYNFPQVGRTALRVLQLVAGFLLPLLVMAYCYAHILAVLLVSRGQRRLRAMRLVVVVVVAFALCWTPYHLVVLVDILMDLGALARNCGRESRVDVAKSVTSGLGYMHCCLNPLLYAFVGVKFRERMWMLLLRLGCPNQRGLQRQPSSSRRDSSWSETSEASYSGL,8.045757490560675 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+CC1(CC1)Oc1ccc2[nH]nc(-c3cc(ncn3)N3CC[C@@H](N)C3)c2c1,HSDSISSLASEREYITSLDLSANELRDIDALSQKCCISVHLEHLEKLELHQNALTSFPQQLCETLKSLTHLDLHSNKFTSFPSYLLKMSCIANLDVSRNDIGPSVVLDPTVKCPTLKQFNLSYNQLSFVPENLTDVVEKLEQLILEGNKISGICSPLRLKELKILNLSKNHISSLSENFLEACPKVESFSARMNFLAAMPFLPPSMTILKLSQNKFSCIPEAILNLPHLRSLDMSSNDIQYLPGPAHWKSLNLRELLFSHNQISILDLSEKAYLWSRVEKLHLSHNKLKEIPPEIGCLENLTSLDVSYNLELRSFPNEMGKLSKIWDLPLDELHLNFDFKHIGCKAKDIIRFLQQRLKKAVPYNRMKLMIVGNTGSGKTTLLQQLMKTKKSDLGMQSATVGIDVKDWPIQIRDKRKRDLVLNVWDFAGREEFYSTHPHFMTQRALYLAVYDLSKGQAEVDAMKPWLFNIKARASSSPVILVGTHLDVSDEKQRKACMSKITKELLNKRGFPAIRDYHFVNATEESDALAKLRKTIINESLNFKIRDQLVVGQLIPDCYVELEKIILSERKNVPIEFPVIDRKRLLQLVRENQLQLDENELPHAVHFLNESGVLLHFQDPALQLSDLYFVEPKWLCKIMAQILTVKVEGCPKHPKGIISRRDVEKFLSKKRKFPKNYMSQYFKLLEKFQIALPIGEEYLLVPSSLSDHRPVIELPHCENSEIIIRLYEMPYFPMGFWSRLINRLLEISPYMLSGRERALRPNRMYWRQGIYLNWSPEAYCLVGSEVLDNHPESFLKITVPSCRKGCILLGQVVDHIDSLMEEWFPGLLEIDICGEGETLLKKWALYSFNDGEEHQKILLDDLMKKAEEGDLLVNPDQPR,8.701146923590294 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+COc1ccc(cc1OC)[C@H](Cc1c(Cl)c[n+]([O-])cc1Cl)OC(=O)c1ccc(CNC[C@@H](C(=O)O[C@H]2CN3CCC2CC3)c2ccccc2)s1,MKKSRSVMTVMADDNVKDYFECSLSKSYSSSSNTLGIDLWRGRRCCSGNLQLPPLSQRQSERARTPEGDGISRPTTLPLTTLPSIAITTVSQECFDVENGPSPGRSPLDPQASSSAGLVLHATFPGHSQRRESFLYRSDSDYDLSPKAMSRNSSLPSEQHGDDLIVTPFAQVLASLRSVRNNFTILTNLHGTSNKRSPAASQPPVSRVNPQEESYQKLAMETLEELDWCLDQLETIQTYRSVSEMASNKFKRMLNRELTHLSEMSRSGNQVSEYISNTFLDKQNDVEIPSPTQKDREKKKKQQLMTQISGVKKLMHSSSLNNTSISRFGVNTENEDHLAKELEDLNKWGLNIFNVAGYSHNRPLTCIMYAIFQERDLLKTFRISSDTFITYMMTLEDHYHSDVAYHNSLHAADVAQSTHVLLSTPALDAVFTDLEILAAIFAAAIHDVDHPGVSNQFLINTNSELALMYNDESVLENHHLAVGFKLLQEEHCDIFMNLTKKQRQTLRKMVIDMVLATDMSKHMSLLADLKTMVETKKVTSSGVLLLDNYTDRIQVLRNMVHCADLSNPTKSLELYRQWTDRIMEEFFQQGDKERERGMEISPMCDKHTASVEKSQVGFIDYIVHPLWETWADLVQPDAQDILDTLEDNRNWYQSMIPQSPSPPLDEQNRDCQGLMEKFQFELTLDEEDSEGPEKEGEGHSYFSSTKTLCVIDPENRDSLGETDIDIATEDKSPVDT,8.259637310505756 +CC1CC2N=C(N)N=C(N)C2CC1C,MKISLISAVSESGVIGSGPDIPWSVKGEQLLFKALTYNQWLLVGRKTFDSMGVLPNRKYAVVSKNGISSSNENVLVFPSIENALKELSKVTDHVYVSGGGQIYNSLIEKADIIHLSTVHVEVEGDIKFPIMPENFNLVFEQFFMSNINYTYQIWKKG,6.102372908709558 +Cc1nnc2[C@H](CC(=O)OC(C)(C)C)N=C(c3c(C)c(C)sc3-n12)c1ccc(Cl)cc1,NPPPPETSNPNKPKRQTNQLQYLLRVVLKTLWKHQFAWPFQQPVDAVKLNLPDYYKIIKTPMDMGTIKKRLENNYYWNAQECIQDFNTMFTNCYIYAKPGDDIVLMAEALEKLFLQKINELPT,6.348915910756989 +FC(F)(F)c1ccc2CCC(CC3CN=CN3)=Cc2c1,MVTRTRETWGKKIDFLLSVVGFAVDLANVWRFPYLCYKNGGGAFLIPYTLFLIIAGMPLFYMELALGQFNREGAATVWKICPFFKGVGYAVILIALYVGFYYNVIIAWSLYYLFASFTLNLPWTNCGHAWNSPNCTDPKLLNASVLGDHTKYSKYKFTPAAEFYERGVLHLHESSGIHDIGLPQWQLLLCLMVVIVVLYVSLWKGVKTSGKVVWITATLPYFVLFVLLVHGVTLPGASNGINAYLHIDFYRLKEATVWIDAATQIFFSLGAGFGVLIAFASYNKFDNNCYRDALLTSTINCVTSFISGFAIFSILGYMAHEHKVKIEDVATEGAGLVFVLYPEAISTLSGSTFWAVLFFLMLLALGLDSSMGGMEAVITGLADDFQVLKRHRKLFTCAVTLGTFLLAMFCITKGGIYVLTLLDTFAAGTSILFAVLMEAIGVSWFYGVDRFSNDIQQMMGFKPGLYWRLCWKFVSPAFLLFVVVVSIINFKPLTYDDYVYPPWANWVGWGIALSSMILVPAYVIYKFFSIRGSLWERVAYGITPENEHHLLALEIELSSLQSFVITSCPIDPLLSSFLFISCQKTLVFKKSGPAPLI,5.0 +CCc1nnc(-c2ccc(cc2)-c2ccccc2)n1-c1cccc(COC)c1C,MAVAHGPVATSSPEQNGAVPSEATKKDQNLTRGNWGNQIEFVLTSVGYAVGLGNVWRFPYLCYRNGGGAFMFPYFIMLVFCGIPLFFMELSFGQFASQGCLGVWRISPMFKGVGYGMMVVSTYIGIYYNVVICIAFYYFFSSMTHVLPWAYCNNPWNTPDCAGVLDASNLTNGSRPTALSGNLSHLFNYTLQRTSPSEEYWRLYVLKLSDDIGDFGEVRLPLLGCLGVSWVVVFLCLIRGVKSSGKVVYFTATFPYVVLTILFVRGVTLEGAFTGIMYYLTPKWDKILEAKVWGDAASQIFYSLGCAWGGLITMASYNKFHNNCYRDSVIISITNCATSVYAGFVIFSILGFMANHLGVDVSRVADHGPGLAFVAYPEALTLLPISPLWSLLFFFMLILLGLGTQFCLLETLVTAIVDEVGNEWILQKKTYVTLGVAVAGFLLGIPLTSQAGIYWLLLMDNYAASFSLVVISCIMCVSIMYIYGHRNYFQDIQMMLGFPPPLFFQICWRFVSPTIIFFILIFTVIQYRPITYNHYQYPGWAVAIGFLMALSSVICIPLYALFQLCRTDGDTLLQRLKNATKPSRDWGPALLEHRTGRYAPTTTPSPEDGFEVQPLHPDKAQIPIVGSNGSSRLQDSRI,5.619788758288394 +CC(C)(O)C(=O)Nc1ccc(c(c1O)C(F)(F)F)[N+]([O-])=O,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAPPGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLVLDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGPTFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGTSTISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAECKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYKSGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYGDLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGGGGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMDSYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASSTTSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,5.0 +C[C@H](Oc1cc(nc(n1)-c1ccc(Oc2cc(Cl)ccc2F)cc1)C(N)=O)C(N)=O,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,6.568636235841012 +Cc1cccc(CCN2CCC(CC2)C(=O)c2ccc(NS(C)(=O)=O)cc2)n1,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,7.700057099977233 +Cc1cc(Nc2cc3ncccc3c(N[C@H]3C[C@@H]4CCC[C@H](C3)N4Cc3ccc(O)cc3)n2)n[nH]1,MPLRHWGMARGSKPVGDGAQPMAAMGGLKVLLHWAGPGGGEPWVTFSESSLTAEEVCIHIAHKVGITPPCFNLFALFDAQAQVWLPPNHILEIPRDASLMLYFRIRFYFRNWHGMNPREPAVYRCGPPGTEASSDQTAQGMQLLDPASFEYLFEQGKHEFVNDVASLWELSTEEEIHHFKNESLGMAFLHLCHLALRHGIPLEEVAKKTSFKDCIPRSFRRHIRQHSALTRLRLRNVFRRFLRDFQPGRLSQQMVMVKYLATLERLAPRFGTERVPVCHLRLLAQAEGEPCYIRDSGVAPTDPGPESAAGPPTHEVLVTGTGGIQWWPVEEEVNKEEGSSGSSGRNPQASLFGKKAKAHKAVGQPADRPREPLWAYFCDFRDITHVVLKEHCVSIHRQDNKCLELSLPSRAAALSFVSLVDGYFRLTADSSHYLCHEVAPPRLVMSIRDGIHGPLLEPFVQAKLRPEDGLYLIHWSTSHPYRLILTVAQRSQAPDGMQSLRLRKFPIEQQDGAFVLEGWGRSFPSVRELGAALQGCLLRAGDDCFSLRRCCLPQPGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASDPTVFHKRYLKKIRDLGEGHFGKVSLYCYDPTNDGTGEMVAVKALKADCGPQHRSGWKQEIDILRTLYHEHIIKYKGCCEDQGEKSLQLVMEYVPLGSLRDYLPRHSIGLAQLLLFAQQICEGMAYLHAQHYIHRDLAARNVLLDNDRLVKIGDFGLAKAVPEGHEYYRVREDGDSPVFWYAPECLKEYKFYYASDVWSFGVTLYELLTHCDSSQSPPTKFLELIGIAQGQMTVLRLTELLERGERLPRPDKCPCEVYHLMKNCWETEASFRPTFENLIPILKTVHEKYQGQAPSVFSVC,7.301029995663981 +COc1ccc(cc1-c1cn(C\C=C\C)c(=O)c2[nH]ccc12)C(=O)N1CCCC1,AENESTPIQQLLEHFLRQLQRKDPHGFFAFPVTDAIAPGYSMIIKHPMDFGTMKDKIVANEYKSVTEFKADFKLMCDNAMTYNRPDTVYYKLAKKILHAGFKMMSKQAALLGNEDTAVEEPVPEVVPVQVETAKKSKKPSREVISCMFEPEGNACSLTDSTAEEHVLALVEHAADEARDRINRFLPGGKMGYLKRNGDGSLLYSVVNTAEPDADEEETHPVDLSSLSSKLLPGFTTLGFKDERRNKVTFLSSATTALSMQNNSVFGDLKSDEMELLYSAYGDETGVQCALSLQEFVKDAGSYSKKVVDDLLDQITGGDHSRTLFQLKQRRNVPMKPPDEAKVGDTL,7.4089353929735005 +COCCOCCOCCOCCOCCOCCOCCOCCOCCOCCOc1cc(F)c(CSc2ncc(N(C)c3ccc(OC)c(OC)c3)n2-c2ccc(F)cc2)c(F)c1,MTPNSTGEVPSPIPKGALGLSLALASLIITANLLLALGIAWDRRLRSPPAGCFFLSLLLAGLLTGLALPTLPGLWNQSRRGYWSCLLVYLAPNFSFLSLLANLLLVHGERYMAVLRPLQPPGSIRLALLLTWAGPLLFASLPALGWNHWTPGANCSSQAIFPAPYLYLEVYGLLLPAVGAAAFLSVRVLATAHRQLQDICRLERAVCRDEPSALARALTWRQARAQAGAMLLFGLCWGPYVATLLLSVLAYEQRPPLGPGTLLSLLSLGSASAAAVPVAMGLGDQRYTAPWRAAAQRCLQGLWGRASRDSPGPSIAYHPSSQSSVDLDLN,6.236572006437062 +Brc1ccc(OCCN2CCC(CC2=O)N[C@@H]2C[C@H]2c2ccccc2)cc1,MLSGKKAAAAAAAAAAAATGTEAGPGTAGGSENGSEVAAQPAGLSGPAEVGPGAVGERTPRKKEPPRASPPGGLAEPPGSAGPQAGPTVVPGSATPMETGIAETPEGRRTSRRKRAKVEYREMDESLANLSEDEYYSEEERNAKAEKEKKLPPPPPQAPPEEENESEPEEPSGVEGAAFQSRLPHDRMTSQEAACFPDIISGPQQTQKVFLFIRNRTLQLWLDNPKIQLTFEATLQQLEAPYNSDTVLVHRVHSYLERHGLINFGIYKRIKPLPTKKTGKVIIIGSGVSGLAAARQLQSFGMDVTLLEARDRVGGRVATFRKGNYVADLGAMVVTGLGGNPMAVVSKQVNMELAKIKQKCPLYEANGQAVPKEKDEMVEQEFNRLLEATSYLSHQLDFNVLNNKPVSLGQALEVVIQLQEKHVKDEQIEHWKKIVKTQEELKELLNKMVNLKEKIKELHQQYKEASEVKPPRDITAEFLVKSKHRDLTALCKEYDELAETQGKLEEKLQELEANPPSDVYLSSRDRQILDWHFANLEFANATPLSTLSLKHWDQDDDFEFTGSHLTVRNGYSCVPVALAEGLDIKLNTAVRQVRYTASGCEVIAVNTRSTSQTFIYKCDAVLCTLPLGVLKQQPPAVQFVPPLPEWKTSAVQRMGFGNLNKVVLCFDRVFWDPSVNLFGHVGSTTASRGELFLFWNLYKAPILLALVAGEAAGIMENISDDVIVGRCLAILKGIFGSSAVPQPKETVVSRWRADPWARGSYSYVAAGSSGNDYDLMAQPITPGPSIPGAPQPIPRLFFAGEHTIRNYPATVHGALLSGLREAGRIADQFLGAMYTLPRQATPGVPAQQSPSM,8.0 +Cc1ccn(Cc2cc(C(O)=O)c3ccccc3n2)n1,MDSKHQCVKLNDGHFMPVLGFGTYAPPEVPRSKALEVTKLAIEAGFRHIDSAHLYNNEEQVGLAIRSKIADGSVKREDIFYTSKLWSTFHRPELVRPALENSLKKAQLDYVDLYLIHSPMSLKPGEELSPTDENGKVIFDIVDLCTTWEAMEKCKDAGLAKSIGVSNFNRRQLEMILNKPGLKYKPVCNQVECHPYFNRSKLLDFCKSKDIVLVAYSALGSQRDKRWVDPNSPVLLEDPVLCALAKKHKRTPALIALRYQLQRGVVVLAKSYNEQRIRQNVQVFEFQLTAEDMKAIDGLDRNLHYFNSDSFASHPNYPYSDEY,3.9318141382538383 +NC(=O)c1cn(nc1Nc1ccc(cc1)[C@@H](O)C(F)(F)F)[C@H]1CC[C@@H](C[C@@H]1C#N)N1CCC1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,7.886056647693163 +CC1(C)Oc2ccc(cc2NC1=O)S(=O)(=O)NCCCn1ccnc1,MVLEMLNPIHYNITSIVPEAMPAATMPVLLLTGLFLLVWNYEGTSSIPGPGYCMGIGPLISHGRFLWMGIGSACNYYNRVYGEFMRVWISGEETLIISKSSSMFHIMKHNHYSSRFGSKLGLQCIGMHEKGIIFNNNPELWKTTRPFFMKALSGPGLVRMVTVCAESLKTHLDRLEEVTNESGYVDVLTLLRRVMLDTSNTLFLRIPLDESAIVVKIQGYFDAWQALLIKPDIFFKISWLYKKYEKSVKDLKDAIEVLIAEKRRRISTEEKLEECMDFATELILAEKRGDLTRENVNQCILEMLIAAPDTMSVSLFFMLFLIAKHPNVEEAIIKEIQTVIGERDIKIDDIQKLKVMENFIYESMRYQPVVDLVMRKALEDDVIDGYPVKKGTNIILNIGRMHRLEFFPKPNEFTLENFAKNVPYRYFQPFGFGPRGCAGKYIAMVMMKAILVTLLRRFHVKTLQGQCVESIQKIHDLSLHPDETKNMLEMIFTPRNSDRCLEH,6.30189945437661 +FC(F)(F)CCC(=O)N1CCC(=CC1)c1cccn2nc(Nc3ccc(cc3)C(=O)N3CCC4(CCCNC4)CC3)nc12,MQYLNIKEDCNAMAFCAKMRSSKKTEVNLEAPEPGVEVIFYLSDREPLRLGSGEYTAEELCIRAAQACRISPLCHNLFALYDENTKLWYAPNRTITVDDKMSLRLHYRMRFYFTNWHGTNDNEQSVWRHSPKKQKNGYEKKKIPDATPLLDASSLEYLFAQGQYDLVKCLAPIRDPKTEQDGHDIENECLGMAVLAISHYAMMKKMQLPELPKDISYKRYIPETLNKSIRQRNLLTRMRINNVFKDFLKEFNNKTICDSSVSTHDLKVKYLATLETLTKHYGAEIFETSMLLISSENEMNWFHSNDGGNVLYYEVMVTGNLGIQWRHKPNVVSVEKEKNKLKRKKLENKHKKDEEKNKIREEWNNFSYFPEITHIVIKESVVSINKQDNKKMELKLSSHEEALSFVSLVDGYFRLTADAHHYLCTDVAPPLIVHNIQNGCHGPICTEYAINKLRQEGSEEGMYVLRWSCTDFDNILMTVTCFEKSEQVQGAQKQFKNFQIEVQKGRYSLHGSDRSFPSLGDLMSHLKKQILRTDNISFMLKRCCQPKPREISNLLVATKKAQEWQPVYPMSQLSFDRILKKDLVQGEHLGRGTRTHIYSGTLMDYKDDEGTSEEKKIKVILKVLDPSHRDISLAFFEAASMMRQVSHKHIVYLYGVCVRDVENIMVEEFVEGGPLDLFMHRKSDVLTTPWKFKVAKQLASALSYLEDKDLVHGNVCTKNLLLAREGIDSECGPFIKLSDPGIPITVLSRQECIERIPWIAPECVEDSKNLSVAADKWSFGTTLWEICYNGEIPLKDKTLIEKERFYESRCRPVTPSCKELADLMTRCMNYDPNQRPFFRAIMRDINKLEEQNPDIVSEKKPATEVDPTHFEKRFLKRIRDLGEGHFGKVELCRYDPEGDNTGEQVAVKSLKPESGGNHIADLKKEIEILRNLYHENIVKYKGICTEDGGNGIKLIMEFLPSGSLKEYLPKNKNKINLKQQLKYAVQICKGMDYLGSRQYVHRDLAARNVLVESEHQVKIGDFGLTKAIETDKEYYTVKDDRDSPVFWYAPECLMQSKFYIASDVWSFGVTLHELLTYCDSDSSPMALFLKMIGPTHGQMTVTRLVNTLKEGKRLPCPPNCPDEVYQLMRKCWEFQPSNRTSFQNLIEGFEALLK,8.876148359032914 +CC(C)CC(=O)N1CCN(CC1)c1nc(C)c2cc(NC(=O)COc3ccc(Cl)cc3)ccc2n1,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,6.795880017344075 +Oc1ccc(cc1)C1=Cc2cc(O)ccc2C11Cc2ccc(OCCN3CCCCC3)cc2C1,MTMTLHTKASGMALLHQIQGNELEPLNRPQLKIPLERPLGEVYLDSSKPAVYNYPEGAAYEFNAAAAANAQVYGQTGLPYGPGSEAAAFGSNGLGGFPPLNSVSPSPLMLLHPPPQLSPFLQPHGQQVPYYLENEPSGYTVREAGPPAFYRPNSDNRRQGGRERLASTNDKGSMAMESAKETRYCAVCNDYASGYHYGVWSCEGCKAFFKRSIQGHNDYMCPATNQCTIDKNRRKSCQACRLRKCYEVGMMKGGIRKDRRGGRMLKHKRQRDDGEGRGEVGSAGDMRAANLWPSPLMIKRSKKNSLALSLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNLADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLLLDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSLEEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMKCKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAEGFPATV,9.0 +CSCC[C@H](NC(=O)[C@H](CC(C)C)NC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CCCCN)NC(=O)[C@@H]1CCCN1C(=O)[C@@H](N)CCCN=C(N)N)C(N)=O,MDNVLPVDSDLSPNISTNTSEPNQFVQPAWQIVLWAAAYTVIVVTSVVGNVVVMWIILAHKRMRTVTNYFLVNLAFAEASMAAFNTVVNFTYAVHNEWYYGLFYCKFHNFFPIAAVFASIYSMTAVAFDRYMAIIHPLQPRLSATATKVVICVIWVLALLLAFPQGYYSTTETMPSRVVCMIEWPEHPNKIYEKVYHICVTVLIYFLPLLVIGYAYTVVGITLWASEIPGDSSDRYHEQVSAKRKVVKMMIVVVCTFAICWLPFHIFFLLPYINPDLYLKKFIQQVYLAIMWLAMSSTMYNPIIYCCLNDRFRLGFKHAFRCCPFISAGDYEGLEMKSTRYLQTQGSVYKVSRLETTISTVVGAHEEEPEDGPKATPSSLDLTSNCSSRSDSKTMTESFSFSSNVLS,9.585026652029182 +CC[C@H](Nc1ncnc(N)c1-c1nnc(C)o1)c1nc2cccc(C)c2c(=O)n1C1CC1,MCFSFIMPPAMADILDIWAVDSQIASDGSIPVDFLLPTGIYIQLEVPREATISYIKQMLWKQVHNYPMFNLLMDIDSYMFACVNQTAVYEELEDETRRLCDVRPFLPVLKLVTRSCDPGEKLDSKIGVLIGKGLHEFDSLKDPEVNEFRRKMRKFSEEKILSLVGLSWMDWLKQTYPPEHEPSIPENLEDKLYGGKLIVAVHFENCQDVFSFQVSPNMNPIKVNELAIQKRLTIHGKEDEVSPYDYVLQVSGRVEYVFGDHPLIQFQYIRNCVMNRALPHFILVECCKIKKMYEQEMIAIEAAINRNSSNLPLPLPPKKTRIISHVWENNNPFQIVLVKGNKLNTEETVKVHVRAGLFHGTELLCKTIVSSEVSGKNDHIWNEPLEFDINICDLPRMARLCFAVYAVLDKVKTKKSTKTINPSKYQTIRKAGKVHYPVAWVNTMVFDFKGQLRTGDIILHSWSSFPDELEEMLNPMGTVQTNPYTENATALHVKFPENKKQPYYYPPFDKIIEKAAEIASSDSANVSSRGGKKFLPVLKEILDRDPLSQLCENEMDLIWTLRQDCREIFPQSLPKLLLSIKWNKLEDVAQLQALLQIWPKLPPREALELLDFNYPDQYVREYAVGCLRQMSDEELSQYLLQLVQVLKYEPFLDCALSRFLLERALGNRRIGQFLFWHLRSEVHIPAVSVQFGVILEAYCRGSVGHMKVLSKQVEALNKLKTLNSLIKLNAVKLNRAKGKEAMHTCLKQSAYREALSDLQSPLNPCVILSELYVEKCKYMDSKMKPLWLVYNNKVFGEDSVGVIFKNGDDLRQDMLTLQMLRLMDLLWKEAGLDLRMLPYGCLATGDRSGLIEVVSTSETIADIQLNSSNVAAAAAFNKDALLNWLKEYNSGDDLDRAIEEFTLSCAGYCVASYVLGIGDRHSDNIMVKKTGQLFHIDFGHILGNFKSKFGIKRERVPFILTYDFIHVIQQGKTGNTEKFGRFRQCCEDAYLILRRHGNLFITLFALMLTAGLPELTSVKDIQYLKDSLALGKSEEEALKQFKQKFDEALRESWTTKVNWMAHTVRKDYRS,7.309803919971486 +COC(=O)[C@@H](CC(C)C)NC(=O)N(C[C@@H](O)[C@@H](Cc1ccccc1)NC(=O)OC(C)(C)C)Cc1ccccc1,MLTFMASDSEEEVCDERTSLMSAESPTPRSCQEGRQGPEDGENTAQWRSQENEEDGEEDPDRYVCSGVPGRPPGLEEELTLKYGAKHVIMLFVPVTLCMIVVVATIKSVRFYTEKNGQLIYTPFTEDTPSVGQRLLNSVLNTLIMISVIVVMTIFLVVLYKYRCYKFIHGWLIMSSLMLLFLFTYIYLGEVLKTYNVAMDYPTLLLTVWNFGAVGMVCIHWKGPLVLQQAYLIMISALMALVFIKYLPEWSAWVILGAISVYDLVAVLCPKGPLRMLVETAQERNEPIFPALIYSSAMVWTVGMAKLDPSSQGALQLPYDPEMEEDSYDSFGEPSYPEVFEPPLTGYPGEELEEEEERGVKLGLGDFIFYSVLVGKAAATGSGDWNTTLACFVAILIGLCLTLLLLAVFKKALPALPISITFGLIFYFSTDNLVRPFMDTLASHQLYI,5.221848749616356 +CCCS(=O)(=O)Nc1ccc(F)c(-c2cc3ccncc3[nH]2)c1F,MAALSGGGGGGAEPGQALFNGDMEPEAGAGAGAAASSAADPAIPEEVWNIKQMIKLTQEHIEALLDKFGGEHNPPSIYLEAYEEYTSKLDALQQREQQLLESLGNGTDFSVSSSASMDTVTSSSSSSLSVLPSSLSVFQNPTDVARSNPKSPQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQDGEKKPIGWDTDISWLTGEELHVEVLENVPLTTHNFVRKTFFTLAFCDFCRKLLFQGFRCQTCGYKFHQRCSTEVPLMCVNYDQLDLLFVSKFFEHHPIPQEEASLAETALTSGSSPSAPASDSIGPQILTSPSPSKSIPIPQPFRPADEDHRNQFGQRDRSSSAPNVHINTIEPVNIDDLIRDQGFRGDGGSTTGLSATPPASLPGSLTNVKALQKSPGPQRERKSSSSSEDRNRMKTLGRRDSSDDWEIPDGQITVGQRIGSGSFGTVYKGKWHGDVAVKMLNVTAPTPQQLQAFKNEVGVLRKTRHVNILLFMGYSTKPQLAIVTQWCEGSSLYHHLHIIETKFEMIKLIDIARQTAQGMDYLHAKSIIHRDLKSNNIFLHEDLTVKIGDFGLATVKSRWSGSHQFEQLSGSILWMAPEVIRMQDKNPYSFQSDVYAFGIVLYELMTGQLPYSNINNRDQIIFMVGRGYLSPDLSKVRSNCPKAMKRLMAECLKKKRDERPLFPQILASIELLARSLPKIHRSASEPSLNRAGFQTEDFSLYACASPKTPIQAGGYGAFPVH,5.0 +CN1[C@@H]2CC[C@H]1[C@H]([C@@H](C2)c1ccccc1)c1ccccc1,METTPLNSQKVLSECKDREDCQENGVLQKGVPTTADRAEPSQISNGYSAVPSTSAGDEASHSIPAATTTLVAEIRQGERETWGKKMDFLLSVIGYAVDLGNIWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIIAWALYYLISSLTDRLPWTSCTNSWNTGNCTNYFAQDNITWTLHSTSPAEEFYLRHVLQIHQSKGLQDLGTISWQLTLCIVLIFTVIYFSIWKGVKTSGKVVWVTATFPYIVLSVLLVRGATLPGAWRGVVFYLKPNWQKLLETGVWVDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHIWAKRREWFVLIVVITCVLGSLLTLTSGGAYVVTLLEEYATGPAVLTVALIEAVAVSWFYGITQFCSDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPHWSIVLGYCIGMSSVICIPTYIIYRLISTPGTLKERIIKSITPETPTEIPCGDIRMNAV,4.384049948343599 +CC(C)(C)OC(=O)NCCc1c[nH]c2c1C(=O)C(=CC2=O)c1ccccc1F,MAHAMENSWTISKEYHIDEEVGFALPNPQENLPDFYNDWMFIAKHLPDLIESGQLRERVEKLNMLSIDHLTDHKSQRLARLVLGCITMAYVWGKGHGDVRKVLPRNIAVPYCQLSKKLELPPILVYADCVLANWKKKDPNKPLTYENMDVLFSFRDGDCSKGFFLVSLLVEIAAASAIKVIPTVFKAMQMQERDTLLKALLEIASCLEKALQVFHQIHDHVNPKAFFSVLRIYLSGWKGNPQLSDGLVYEGFWEDPKEFAGGSAGQSSVFQCFDVLLGIQQTAGGGHAAQFLQDMRRYMPPAHRNFLCSLESNPSVREFVLSKGDAGLREAYDACVKALVSLRSYHLQIVTKYILIPASQQPKENKTSEDPSKLEAKGTGGTDLMNFLKTVRSTTEKSLLKEG,5.679853713888946 +FC(F)(F)COC(=O)c1ncn-2c1[C@@H]1CCCN1C(=O)c1cc(ccc-21)-c1ccco1,MSSPNIWSTGSSVYSTPVFSQKMTVWILLLLSLYPGFTSQKSDDDYEDYASNKTWVLTPKVPEGDVTVILNNLLEGYDNKLRPDIGVKPTLIHTDMYVNSIGPVNAINMEYTIDIFFAQTWYDRRLKFNSTIKVLRLNSNMVGKIWIPDTFFRNSKKADAHWITTPNRMLRIWNDGRVLYTLRLTIDAECQLQLHNFPMDEHSCPLEFSSYGYPREEIVYQWKRSSVEVGDTRSWRLYQFSFVGLRNTTEVVKTTSGDYVVMSVYFDLSRRMGYFTIQTYIPCTLIVVLSWVSFWINKDAVPARTSLGITTVLTMTTLSTIARKSLPKVSYVTAMDLFVSVCFIFVFSALVEYGTLHYFVSNRKPSKDKDKKKKNPAPTIDIRPRSATIQMNNATHLQERDEEYGYECLDGKDCASFFCCFEDCRTGAWRHGRIHIRIAKMDSYARIFFPTAFCLFNLVYWVSYLYL,8.148741651280925 +Clc1ccc(Cn2cc(NC(=O)c3cc(on3)-c3ccco3)cn2)cc1,MPAHLLQDDISSSYTTTTTITAPPSRVLQNGGDKLETMPLYLEDDIRPDIKDDIYDPTYKDKEGPSPKVEYVWRNIILMSLLHLGALYGITLIPTCKFYTWLWGVFYYFVSALGITAGAHRLWSHRSYKARLPLRLFLIIANTMAFQNDVYEWARDHRAHHKFSETHADPHNSRRGFFFSHVGWLLVRKHPAVKEKGSTLDLSDLEAEKLVMFQRRYYKPGLLMMCFILPTLVPWYFWGETFQNSVFVATFLRYAVVLNATWLVNSAAHLFGYRPYDKNISPRENILVSLGAVGEGFHNYHHSFPYDYSASEYRWHINFTTFFIDCMAALGLAYDRKKVSKAAILARIKRTGDGNYKSG,4.346787486224656 +COc1ccc(cc1)-c1ccc(CC(=O)NC2CCN(Cc3ccc4OCOc4c3)CC2)cc1,MSVGAGKEGVGRAVGLRGSRGCQAVEEDPFLDCGAQAPGQGGGGRWRLPQPAWVDGRALHSREQATCTGCMDLQASLLSTGPNASNISDGQDNFTLAGPPPRTRSVSYINIIMPSVFGTICLLGIVGNSTVIFAVVKKSKLHWCSNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSMATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVKILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRTVSNAQTADEERTESKGT,7.301029995663981 +CC(C)CN1C[C@@H](c2ccc(cc2)C#N)[C@@]2(C1)N(C)C(=O)N(C2=O)c1cc(Cl)cc(Cl)c1,MAPSSPRPALPALLVLLGALFPGPGNAQTSVSPSKVILPRGGSVLVTCSTSCDQPKLLGIETPLPKKELLLPGNNRKVYELSNVQEDSQPMCYSNCPDGQSTAKTFLTVYWTPERVELAPLPSWQPVGKNLTLRCQVEGGAPRANLTVVLLRGEKELKREPAVGEPAEVTTTVLVRRDHHGANFSCRTELDLRPQGLELFENTSAPYQLQTFVLPATPPQLVSPRVLEVDTQGTVVCSLDGLFPVSEAQVHLALGDQRLNPTVTYGNDSFSAKASVSVTAEDEGTQRLTCAVILGNQSQETLQTVTIYSFPAPNVILTKPEVSEGTEVTVKCEAHPRAKVTLNGVPAQPLGPRAQLLLKATPEDNGRSFSCSATLEVAGQLIHKNQTRELRVLYGPRLDERDCPGNWTWPENSQQTPMCQAWGNPLPELKCLKDGTFPLPIGESVTVTRDLEGTYLCRARSTQGEVTRKVTVNVLSPRYEIVIITVVAAAVIMGTAGLSTYLYNRQRKIKKYRLQQAQKGTPMKPNTQATPP,7.853871964321762 +CC(=O)Nc1ccc2CC3CCC(Cc2c1)C3NS(=O)(=O)c1ccccc1,MTELPAPLSYFQNAQMSEDNHLSNTVRSQNDNRERQEHNDRRSLGHPEPLSNGRPQGNSRQVVEQDEEEDEELTLKYGAKHVIMLFVPVTLCMVVVVATIKSVSFYTRKDGQLIYTPFTEDTETVGQRALHSILNAAIMISVIVVMTILLVVLYKYRCYKVIHAWLIISSLLLLFFFSFIYLGEVFKTYNVAVDYITVALLIWNFGVVGMISIHWKGPLRLQQAYLIMISALMALVFIKYLPEWTAWLILAVISVYDLVAVLCPKGPLRMLVETAQERNETLFPALIYSSTMVWLVNMAEGDPEAQRRVSKNSKYNAESTERESQDTVAENDDGGFSEEWEAQRDSHLGPHRSTPESRAAVQELSSSILAGEDPEERGVKLGLGDFIFYSVLVGKASATASGDWNTTIACFVAILIGLCLTLLLLAIFKKALPALPISITFGLVFYFATDYLVQPFMDQLAFHQFYI,6.0 +COc1ccc(cc1OC)-c1cc(CNCC2CCNCC2)sc1-c1ccc(OC)c(OC)c1,MAENVVEPGPPSAKRPKLSSPALSASASDGTDFGSLFDLEHDLPDELINSTELGLTNGGDINQLQTSLGMVQDAASKHKQLSELLRSGSSPNLNMGVGGPGQVMASQAQQSSPGLGLINSMVKSPMTQAGLTSPNMGMGTSGPNQGPTQSTGMMNSPVNQPAMGMNTGMNAGMNPGMLAAGNGQGIMPNQVMNGSIGAGRGRQNMQYPNPGMGSAGNLLTEPLQQGSPQMGGQTGLRGPQPLKMGMMNNPNPYGSPYTQNPGQQIGASGLGLQIQTKTVLSNNLSPFAMDKKAVPGGGMPNMGQQPAPQVQQPGLVTPVAQGMGSGAHTADPEKRKLIQQQLVLLLHAHKCQRREQANGEVRQCNLPHCRTMKNVLNHMTHCQSGKSCQVAHCASSRQIISHWKNCTRHDCPVCLPLKNAGDKRNQQPILTGAPVGLGNPSSLGVGQQSAPNLSTVSQIDPSSIERAYAALGLPYQVNQMPTQPQVQAKNQQNQQPGQSPQGMRPMSNMSASPMGVNGGVGVQTPSLLSDSMLHSAINSQNPMMSENASVPSLGPMPTAAQPSTTGIRKQWHEDITQDLRNHLVHKLVQAIFPTPDPAALKDRRMENLVAYARKVEGDMYESANNRAEYYHLLAEKIYKIQKELEEKRRTRLQKQNMLPNAAGMVPVSMNPGPNMGQPQPGMTSNGPLPDPSMIRGSVPNQMMPRITPQSGLNQFGQMSMAQPPIVPRQTPPLQHHGQLAQPGALNPPMGYGPRMQQPSNQGQFLPQTQFPSQGMNVTNIPLAPSSGQAPVSQAQMSSSSCPVNSPIMPPGSQGSHIHCPQLPQPALHQNSPSPVPSRTPTPHHTPPSIGAQQPPATTIPAPVPTPPAMPPGPQSQALHPPPRQTPTPPTTQLPQQVQPSLPAAPSADQPQQQPRSQQSTAASVPTPTAPLLPPQPATPLSQPAVSIEGQVSNPPSTSSTEVNSQAIAEKQPSQEVKMEAKMEVDQPEPADTQPEDISESKVEDCKMESTETEERSTELKTEIKEEEDQPSTSATQSSPAPGQSKKKIFKPEELRQALMPTLEALYRQDPESLPFRQPVDPQLLGIPDYFDIVKSPMDLSTIKRKLDTGQYQEPWQYVDDIWLMFNNAWLYNRKTSRVYKYCSKLSEVFEQEIDPVMQSLGYCCGRKLEFSPQTLCCYGKQLCTIPRDATYYSYQNRYHFCEKCFNEIQGESVSLGDDPSQPQTTINKEQFSKRKNDTLDPELFVECTECGRKMHQICVLHHEIIWPAGFVCDGCLKKSARTRKENKFSAKRLPSTRLGTFLENRVNDFLRRQNHPESGEVTVRVVHASDKTVEVKPGMKARFVDSGEMAESFPYRTKALFAFEEIDGVDLCFFGMHVQEYGSDCPPPNQRRVYISYLDSVHFFRPKCLRTAVYHEILIGYLEYVKKLGYTTGHIWACPPSEGDDYIFHCHPPDQKIPKPKRLQEWYKKMLDKAVSERIVHDYKDIFKQATEDRLTSAKELPYFEGDFWPNVLEESIKELEQEEEERKREENTSNESTDVTKGDSKNAKKKNNKKTSKNKSSLSRGNKKKPGMPNVSNDLSQKLYATMEKHKEVFFVIRLIAGPAANSLPPIVDPDPLIPCDLMDGRDAFLTLARDKHLEFSSLRRAQWSTMCMLVELHTQSQDRFVYTCNECKHHVETRWHCTVCEDYDLCITCYNTKNHDHKMEKLGLGLDDESNNQQAAATQSPGDSRRLSIQRCIQSLVHACQCRNANCSLPSCQKMKRVVQHTKGCKRKTNGGCPICKQLIALCCYHAKHCQENKCPVPFCLNIKQKLRQQQLQHRLQQAQMLRRRMASMQRTGVVGQQQGLPSPTPATPTTPTGQQPTTPQTPQPTSQPQPTPPNSMPPYLPRTQAAGPVSQGKAAGQVTPPTPPQTAQPPLPGPPPAAVEMAMQIQRAAETQRQMAHVQIFQRPIQHQMPPMTPMAPMGMNPPPMTRGPSGHLEPGMGPTGMQQQPPWSQGGLPQPQQLQSGMPRPAMMSVAQHGQPLNMAPQPGLGQVGISPLKPGTVSQQALQNLLRTLRSPSSPLQQQQVLSILHANPQLLAAFIKQRAAKYANSNPQPIPGQPGMPQGQPGLQPPTMPGQQGVHSNPAMQNMNPMQAGVQRAGLPQQQPQQQLQPPMGGMSPQAQQMNMNHNTMPSQFRDILRRQQMMQQQQQQGAGPGIGPGMANHNQFQQPQGVGYPPQQQQRMQHHMQQMQQGNMGQIGQLPQALGAEAGASLQAYQQRLLQQQMGSPVQPNPMSPQQHMLPNQAQSPHLQGQQIPNSLSNQVRSPQPVPSPRPQSQPPHSSPSPRMQPQPSPHHVSPQTSSPHPGLVAAQANPMEQGHFASPDQNSMLSQLASNPGMANLHGASATDLGLSTDNSDLNSNLSQSTLDIH,5.0 +CCOc1ccc2cc(ccc2c1)-c1nn(C2CCN(CC)CC2)c2ncnc(N)c12,MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGERLQIVNNTEGDWWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAENPRGTFLVRESETTKGAYCLSVSDFDNAKGLNVKHYKIRKLDSGGFYITSRTQFNSLQQLVAYYSKHADGLCHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWNGTTRVAIKTLKPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLLDFLKGETGKYLRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGLARLIEDNEYTARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMVNREVLDQVERGYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQYQPGENL,5.061480274823508 +C[C@@H](N)Cn1ncc2ccc(O)cc12,MVNLGNAVRSLLMHLIGLLVWQFDISISPVAAIVTDTFNSSDGGRLFQFPDGVQNWPALSIVVIIIMTIGGNILVIMAVSMEKKLHNATNYFLMSLAIADMLVGLLVMPLSLLAILYDYVWPLPRYLCPVWISLDVLFSTASIMHLCAISLDRYVAIRNPIEHSRFNSRTKAIMKIAIVWAISIGVSVPIPVIGLRDESKVFVNNTTCVLNDPNFVLIGSFVAFFIPLTIMVITYFLTIYVLRRQTLMLLRGHTEEELANMSLNFLNCCCKKNGGEEENAPNPNPDQKPRRKKKEKRPRGTMQAINNEKKASKVLGIVFFVFLIMWCPFFITNILSVLCGKACNQKLMEKLLNVFVWIGYVCSGINPLVYTLFNKIYRRAFSKYLRCDYKPDKKPPVRQIPRVAATALSGRELNVNIYRHTNERVARKANDPEPGIEMQVENLELPVNPSNVVSERISSV,7.060480747381382 +CC(C)CN(Cc1cc(Cl)c2OCCCOc2c1)C(=O)C(C)CNCc1ccc(F)cc1F,MPPAGINMASQNKNTSFAPDLNPSQDHISSLPFNFSYSDYDLPLDGDEDMTKTQTFFAAKIVIGVALAGIMLVCGIGNFVFIAALARYKKLRNLTNLLIANLAISDFLVAIVCCPFEMDYYVVRQLSWEHGHVLCASVNYLRTVSLYVSTNALLAIAIDRYLAIVHPLKPRMNYQTASFLIALVWMVSILIAIPSAYFTTETILDIVKNQEKIFCGQIWPVDQQLYYKSYFLFVFGLEFVGPVVAMTLCYARISQELWFKAVPGFQTEQIRKRLRCRRKTVLLLMGILTAYVLCWAPFYGFTIVRDFFPTVFVKEKHYLTAFYVVECIAMSNSMINTICFVTVKNNTMKYFKKMLLLHWQPSRYGSKSSADLDLKTSGVPATEEVDCIRLK,8.070581074285707 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+Oc1ccc2ccccc2c1Cc1c([nH]c(=S)[nH]c1=O)-c1ccccc1,MVLYTTPFPNSCLSALHCVSWALIFPCYWLVDRLAASFIPTTYEKRQRADDPCCLQLLCTALFTPIYLALLVASLPFAFLGFLFWSPLQSARRPYIYSRLEDKGLAGGAALLSEWKGTGPGKSFCFATANVCLLPDSLARVNNLFNTQARAKEIGQRIRNGAARPQIKIYIDSPTNTSISAASFSSLVSPQGGDGVARAVPGSIKRTASVEYKGDGGRHPGDEAANGPASGDPVDSSSPEDACIVRIGGEEGGRPPEADDPVPGGQARNGAGGGPRGQTPNHNQQDGDSGSLGSPSASRESLVKGRAGPDTSASGEPGANSKLLYKASVVKKAAARRRRHPDEAFDHEVSAFFPANLDFLCLQEVFDKRAATKLKEQLHGYFEYILYDVGVYGCQGCCSFKCLNSGLLFASRYPIMDVAYHCYPNKCNDDALASKGALFLKVQVGSTPQDQRIVGYIACTHLHAPQEDSAIRCGQLDLLQDWLADFRKSTSSSSAANPEELVAFDVVCGDFNFDNCSSDDKLEQQHSLFTHYRDPCRLGPGEEKPWAIGTLLDTNGLYDEDVCTPDNLQKVLESEEGRREYLAFPTSKSSGQKGRKELLKGNGRRIDYMLHAEEGLCPDWKAEVEEFSFITQLSGLTDHLPVAMRLMVSSGEEEA,5.301029995663981 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+CCN1C2=N[C@H](Cc3ccccc3)CN2c2c(nc(Br)n2Cc2ccc(OC)cc2)C1=O,MERAGPSFGQQRQQQQPQQQKQQQRDQDSVEAWLDDHWDFTFSYFVRKATREMVNAWFAERVHTIPVCKEGIRGHTESCSCPLQQSPRADNSAPGTPTRKISASEFDRPLRPIVVKDSEGTVSFLSDSEKKEQMPLTPPRFDHDEGDQCSRLLELVKDISSHLDVTALCHKIFLHIHGLISADRYSLFLVCEDSSNDKFLISRLFDVAEGSTLEEVSNNCIRLEWNKGIVGHVAALGEPLNIKDAYEDPRFNAEVDQITGYKTQSILCMPIKNHREEVVGVAQAINKKSGNGGTFTEKDEKDFAAYLAFCGIVLHNAQLYETSLLENKRNQVLLDLASLIFEEQQSLEVILKKIAATIISFMQVQKCTIFIVDEDCSDSFSSVFHMECEELEKSSDTLTREHDANKINYMYAQYVKNTMEPLNIPDVSKDKRFPWTTENTGNVNQQCIRSLLCTPIKNGKKNKVIGVCQLVNKMEENTGKVKPFNRNDEQFLEAFVIFCGLGIQNTQMYEAVERAMAKQMVTLEVLSYHASAAEEETRELQSLAAAVVPSAQTLKITDFSFSDFELSDLETALCTIRMFTDLNLVQNFQMKHEVLCRWILSVKKNYRKNVAYHNWRHAFNTAQCMFAALKAGKIQNKLTDLEILALLIAALSHDLDHRGVNNSYIQRSEHPLAQLYCHSIMEHHHFDQCLMILNSPGNQILSGLSIEEYKTTLKIIKQAILATDLALYIKRRGEFFELIRKNQFNLEDPHQKELFLAMLMTACDLSAITKPWPIQQRIAELVATEFFDQGDRERKELNIEPTDLMNREKKNKIPSMQVGFIDAICLQLYEALTHVSEDCFPLLDGCRKNRQKWQALAEQQEKMLINGESGQAKRN,7.318758762624412 +COc1ccc(COc2ccc(Cc3cnc(N)nc3N)cc2OC)cc1,MRLLLALLGVLLSVPGPPVLSLEASEEVELEPCLAPSLEQQEQELTVALGQPVRLCCGRAERGGHWYKEGSRLAPAGRVRGWRGRLEIASFLPEDAGRYLCLARGSMIVLQNLTLITGDSLTSSNDDEDPKSHRDPSNRHSYPQQAPYWTHPQRMEKKLHAVPAGNTVKFRCPAAGNPTPTIRWLKDGQAFHGENRIGGIRLRHQHWSLVMESVVPSDRGTYTCLVENAVGSIRYNYLLDVLERSPHRPILQAGLPANTTAVVGSDVELLCKVYSDAQPHIQWLKHIVINGSSFGADGFPYVQVLKTADINSSEVEVLYLRNVSAEDAGEYTCLAGNSIGLSYQSAWLTVLPEEDPTWTAAAPEARYTDIILYASGSLALAVLLLLAGLYRGQALHGRHPRPPATVQKLSRFPLARQFSLESGSSGKSSSSLVRGVRLSSSGPALLAGLVSLDLPLDPLWEFPRDRLVLGKPLGEGCFGQVVRAEAFGMDPARPDQASTVAVKMLKDNASDKDLADLVSEMEVMKLIGRHKNIINLLGVCTQEGPLYVIVECAAKGNLREFLRARRPPGPDLSPDGPRSSEGPLSFPVLVSCAYQVARGMQYLESRKCIHRDLAARNVLVTEDNVMKIADFGLARGVHHIDYYKKTSNGRLPVKWMAPEALFDRVYTHQSDVWSFGILLWEIFTLGGSPYPGIPVEELFSLLREGHRMDRPPHCPPELYGLMRECWHAAPSQRPTFKQLVEALDKVLLAVSEEYLDLRLTFGPYSPSGGDASSTCSSSDSVFSHDPLPLGSSSFPFGSGVQT,5.0 +COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1,MSFFNFRKIFKLGSEKKKKQYEHVKRDLNPEDFWEIIGELGDGAFGKVYKAQNKETSVLAAAKVIDTKSEEELEDYMVEIDILASCDHPNIVKLLDAFYYENNLWILIEFCAGGAVDAVMLELERPLTESQIQVVCKQTLDALNYLHDNKIIHRDLKAGNILFTLDGDIKLADFGVSAKNTRTIQRRDSFIGTPYWMAPEVVMCETSKDRPYDYKADVWSLGITLIEMAEIEPPHHELNPMRVLLKIAKSEPPTLAQPSRWSSNFKDFLKKCLEKNVDARWTTSQLLQHPFVTVDSNKPIRELIAEAKAEVTEEVEDGKEEDEEEETENSLPIPASKRASSDLSIASSEEDKLSQNACILESVSEKTERSNSEDKLNSKILNEKPTTDEPEKAVEDINEHITDAQLEAMTELHDRTAVIKENEREKRPKLENLPDTEDQETVDINSVSEGKENNIMITLETNIEHNLKSEEEKDQEKQQMFENKLIKSEEIKDTILQTVDLVSQETGEKEANIQAVDSEVGLTKEDTQEKLGEDDKTQKDVISNTSDVIGTCEAADVAQKVDEDSAEDTQSNDGKEVVEVGQKLINKPMVGPEAGGTKEVPIKEIVEMNEIEEGKNKEQAINSSENIMDINEEPGTTEGEEITESSSTEEMEVRSVVADTDQKALGSEVQDASKVTTQIDKEKKEIPVSIKKEPEVTVVSQPTEPQPVLIPSININSDSGENKEEIGSLSKTETILPPESENPKENDNDSGTGSTADTSSIDLNLSISSFLSKTKDSGSISLQETRRQKKTLKKTRKFIVDGVEVSVTTSKIVTDSDSKTEELRFLRRQELRELRFLQKEEQRAQQQLNSKLQQQREQIFRRFEQEMMSKKRQYDQEIENLEKQQKQTIERLEQEHTNRLRDEAKRIKGEQEKELSKFQNMLKNRKKEVINEVEKAPKELRKELMKRRKEELAQSQHAQEQEFVQKQQQELDGSLKKIIQQQKAELANIERECLNNKQQLMRAREAAIWELEERHLQEKHQLLKQQLKDQYFMQRHQLLKRHEKETEQMQRYNQRLIEELKNRQTQERARLPKIQRSEAKTRMAMFKKSLRINSTATPDQDRDKIKQFAAQEEKRQKNERMAQHQKHENQMRDLQLQCEANVRELHQLQNEKCHLLVEHETQKLKELDEEHSQELKEWREKLRPRKKTLEEEFARKLQEQEVFFKMTGESECLNPSTQSRISKFYPIPSLHSTGS,6.036212172654444 +Clc1ccc(nc1)-n1c(nc2ccncc12)-c1cnc(nc1)N1CCOCC1,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,5.0 +CNC(=N)c1ccc2C(=O)c3ccccc3S(=O)(=O)c2c1,MTDLEKPNLAGHMFDVGLIGGGISGLAAAKLLSEYKINVLVLEARDRVGGRTYTVRNEHVKWVDVGGAYVGPTQNRILRLSKELGIETYKVNVNERLVQYVKGKTYPFRGAFPPVWNPLAYLDYNNLWRTMDEMGKEIPVDAPWQARHAQEWDKMTMKDLIDKICWTKTAREFAYLFVNINVTSEPHEVSALWFLWYVRQCGGTARIFSVTNGGQERKFVGGSGQVSEQIMGLLGDKVKLSSPVTYIDQTDDNIIVETLNHEHYECKYVISAIPPILTAKIHFKPELPPERNQLIQRLPMGAVIKCMVYYKEAFWKKKDYCGCMIIEDEEAPIAITLDDTKPDGSLPAIMGFILARKADRQAKLHKDIRKRKICELYAKVLGSQEALYPVHYEEKNWCEEQYSGGCYTAYFPPGIMTQYGRVIRQPVGRIYFAGTETATQWSGYMEGAVEAGERAAREVLNALGKVAKKDIWVEEPESKDVPAIEITHTFLERNLPSVPGLLKITGVSTSVALLCFVLYKIKKLPC,7.221848749616356 +Cc1ccc(cc1Nc1nccc(n1)-c1cccnc1)[N+]([O-])=O,MRLPGAMPALALKGELLLLSLLLLLEPQISQGLVVTPPGPELVLNVSSTFVLTCSGSAPVVWERMSQEPPQEMAKAQDGTFSSVLTLTNLTGLDTGEYFCTHNDSRGLETDERKRLYIFVPDPTVGFLPNDAEELFIFLTEITEITIPCRVTDPQLVVTLHEKKGDVALPVPYDHQRGFSGIFEDRSYICKTTIGDREVDSDAYYVYRLQVSSINVSVNAVQTVVRQGENITLMCIVIGNEVVNFEWTYPRKESGRLVEPVTDFLLDMPYHIRSILHIPSAELEDSGTYTCNVTESVNDHQDEKAINITVVESGYVRLLGEVGTLQFAELHRSRTLQVVFEAYPPPTVLWFKDNRTLGDSSAGEIALSTRNVSETRYVSELTLVRVKVAEAGHYTMRAFHEDAEVQLSFQLQINVPVRVLELSESHPDSGEQTVRCRGRGMPQPNIIWSACRDLKRCPRELPPTLLGNSSEEESQLETNVTYWEEEQEFEVVSTLRLQHVDRPLSVRCTLRNAVGQDTQEVIVVPHSLPFKVVVISAILALVVLTIISLIILIMLWQKKPRYEIRWKVIESVSSDGHEYIYVDPMQLPYDSTWELPRDQLVLGRTLGSGAFGQVVEATAHGLSHSQATMKVAVKMLKSTARSSEKQALMSELKIMSHLGPHLNVVNLLGACTKGGPIYIITEYCRYGDLVDYLHRNKHTFLQHHSDKRRPPSAELYSNALPVGLPLPSHVSLTGESDGGYMDMSKDESVDYVPMLDMKGDVKYADIESSNYMAPYDNYVPSAPERTCRATLINESPVLSYMDLVGFSYQVANGMEFLASKNCVHRDLAARNVLICEGKLVKICDFGLARDIMRDSNYISKGSTFLPLKWMAPESIFNSLYTTLSDVWSFGILLWEIFTLGGTPYPELPMNEQFYNAIKRGYRMAQPAHASDEIYEIMQKCWEEKFEIRPPFSQLVLLLERLLGEGYKKKYQQVDEEFLRSDHPAILRSQARLPGFHGLRSPLDTSSVLYTAVQPNEGDNDYIIPLPDPKPEVADEGPLEGSPSLASSTLNEVNTSSTISCDSPLEPQDEPEPEPQLELQVEPEPELEQLPDSGCPAPRAEAEDSFL,4.0 +CO[C@H]1CC[C@@H](CC1)C(=O)N1Cc2cccnc2Nc2ccc(cc12)N1CCc2nn(C)cc2C1,MSKKISGGSVVEMQGDEMTRIIWELIKEKLIFPYVELDLHSYDLGIENRDATNDQVTKDAAEAIKKHNVGVKCATITPDEKRVEEFKLKQMWKSPNGTIRNILGGTVFREAIICKNIPRLVSGWVKPIIIGHHAYGDQYRATDFVVPGPGKVEITYTPSDGTQKVTYLVHNFEEGGGVAMGMYNQDKSIEDFAHSSFQMALSKGWPLYLSTKNTILKKYDGRFKDIFQEIYDKQYKSQFEAQKIWYEHRLIDDMVAQAMKSEGGFIWACKNYDGDVQSDSVAQGYGSLGMMTSVLVCPDGKTVEAEAAHGTVTRHYRMYQKGQETSTNPIASIFAWTRGLAHRAKLDNNKELAFFANALEEVSIETIEAGFMTKDLAACIKGLPNVQRSDYLNTFEFMDKLGENLKIKLAQAKL,6.542118103266008 +COCCn1c2cc3c(Nc4ccc(OC)c(OC)c4)ncnc3cc2oc1=O,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,7.259637310505756 +CC(C)c1nc2CCN(CCc2c(Nc2ccc(cc2)C(F)(F)F)n1)c1ncc(OC=O)cc1Cl,MEQRASLDSEESESPPQENSCLDPPDRDPNCKPPPVKPHIFTTRSRTRLFGKGDSEEASPLDCPYEEGGLASCPIITVSSVLTIQRPGDGPASVRPSSQDSVSAGEKPPRLYDRRSIFDAVAQSNCQELESLLPFLQRSKKRLTDSEFKDPETGKTCLLKAMLNLHNGQNDTIALLLDVARKTDSLKQFVNASYTDSYYKGQTALHIAIERRNMTLVTLLVENGADVQAAANGDFFKKTKGRPGFYFGELPLSLAACTNQLAIVKFLLQNSWQPADISARDSVGNTVLHALVEVADNTVDNTKFVTSMYNEILILGAKLHPTLKLEEITNRKGLTPLALAASSGKIGVLAYILQREIHEPECRHLSRKFTEWAYGPVHSSLYDLSCIDTCEKNSVLEVIAYSSSETPNRHDMLLVEPLNRLLQDKWDRFVKRIFYFNFFVYCLYMIIFTAAAYYRPVEGLPPYKLKNTVGDYFRVTGEILSVSGGVYFFFRGIQYFLQRRPSLKSLFVDSYSEILFFVQSLFMLVSVVLYFSQRKEYVASMVFSLAMGWTNMLYYTRGFQQMGIYAVMIEKMILRDLCRFMFVYLVFLFGFSTAVVTLIEDGKNNSLPMESTPHKCRGSACKPGNSYNSLYSTCLELFKFTIGMGDLEFTENYDFKAVFIILLLAYVILTYILLLNMLIALMGETVNKIAQESKNIWKLQRAITILDTEKSFLKCMRKAFRSGKLLQVGFTPDGKDDYRWCFRVDEVNWTTWNTNVGIINEDPGNCEGVKRTLSFSLRSGRVSGRNWKNFALVPLLRDASTRDRHATQQEEVQLKHYTGSLKPEDAEVFKDSMVPGEK,5.694648630553376 +FC(F)Oc1ccc(NCc2cc3C(=O)N(CCn3n2)c2ccc(F)cc2F)c(F)c1,MVLLLILSVLLLKEDVRGSAQSSERRVVAHMPGDIIIGALFSVHHQPTVDKVHERKCGAVREQYGIQRVEAMLHTLERINSDPTLLPNITLGCEIRDSCWHSAVALEQSIEFIRDSLISSEEEEGLVRCVDGSSSFRSKKPIVGVIGPGSSSVAIQVQNLLQLFNIPQIAYSATSMDLSDKTLFKYFMRVVPSDAQQARAMVDIVKRYNWTYVSAVHTEGNYGESGMEAFKDMSAKEGICIAHSYKIYSNAGEQSFDKLLKKLRSHLPKARVVACFCEGMTVRGLLMAMRRLGLAGEFLLLGSDGWADRYDVTDGYQREAVGGITIKLQSPDVKWFDDYYLKLRPETNLRNPWFQEFWQHRFQCRLEGFAQENSKYNKTCNSSLTLRTHHVQDSKMGFVINAIYSMAYGLHNMQMSLCPGYAGLCDAMKPIDGRKLLDSLMKTNFTGVSGDMILFDENGDSPGRYEIMNFKEMGKDYFDYINVGSWDNGELKMDDDEVWSKKNNIIRSVCSEPCEKGQIKVIRKGEVSCCWTCTPCKENEYVFDEYTCKACQLGSWPTDDLTGCDLIPVQYLRWGDPEPIAAVVFACLGLLATLFVTVIFIIYRDTPVVKSSSRELCYIILAGICLGYLCTFCLIAKPKQIYCYLQRIGIGLSPAMSYSALVTKTNRIARILAGSKKKICTKKPRFMSACAQLVIAFILICIQLGIIVALFIMEPPDIMHDYPSIREVYLICNTTNLGVVTPLGYNGLLILSCTFYAFKTRNVPANFNEAKYIAFTMYTTCIIWLAFVPIYFGSNYKIITMCFSVSLSATVALGCMFVPKVYIILAKPERNVRSAFTTSTVVRMHVGDGKSSSAASRSSSLVNLWKRRGSSGETLRYKDRRLAQHKSEIECFTPKGSMGNGGRATMSSSNGKSVTWAQNEKSTRGQHLWQRLSVHINKKENPNQTAVIKPFPKSTENRGPGAAAGGGSGPGVAGAGNAGCTATGGPEPPDAGPKALYDVAEAEESFPAAARPRSPSPISTLSHLAGSAGRTDDDAPSLHSETAARSSSSQGSLMEQISSVVTRFTANISELNSMMLSTAATPGPPGTPICSSYLIPKEIQLPTTMTTFAEIQPLPAIEVTGGAQGATGVSPAQETPTGAESAPGKPDLEELVALTPPSPFRDSVDSGSTTPNSPVSESALCIPSSPKYDTLIIRDYTQSSSSL,4.522878745280337 +COc1ccc(cc1)C(=O)N1c2ccccc2Sc2ccc(OC)cc12,MREIVHIQAGQCGNQIGAKFWEVISDEHGIDPTGSYHGDSDLQLERINVYYNEAAGNKYVPRAILVDLEPGTMDSVRSGPFGQIFRPDNFVFGQSGAGNNWAKGHYTEGAELVDSVLDVVRKESESCDCLQGFQLTHSLGGGTGSGMGTLLISKIREEYPDRIMNTFSVVPSPKVSDTVVEPYNATLSVHQLVENTDETYCIDNEALYDICFRTLKLTTPTYGDLNHLVSATMSGVTTCLRFPGQLNADLRKLAVNMVPFPRLHFFMPGFAPLTSRGSQQYRALTVPELTQQMFDAKNMMAACDPRHGRYLTVAAVFRGRMSMKEVDEQMLNVQNKNSSYFVEWIPNNVKTAVCDIPPRGLKMSATFIGNSTAIQELFKRISEQFTAMFRRKAFLHWYTGEGMDEMEFTEAESNMNDLVSEYQQYQDATADEQGEFEEEGEEDEA,5.490797477668897 +CC[N+]([O-])(CC)CCOc1ccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cc1,MRLPGAMPALALKGELLLLSLLLLLEPQISQGLVVTPPGPELVLNVSSTFVLTCSGSAPVVWERMSQEPPQEMAKAQDGTFSSVLTLTNLTGLDTGEYFCTHNDSRGLETDERKRLYIFVPDPTVGFLPNDAEELFIFLTEITEITIPCRVTDPQLVVTLHEKKGDVALPVPYDHQRGFSGIFEDRSYICKTTIGDREVDSDAYYVYRLQVSSINVSVNAVQTVVRQGENITLMCIVIGNEVVNFEWTYPRKESGRLVEPVTDFLLDMPYHIRSILHIPSAELEDSGTYTCNVTESVNDHQDEKAINITVVESGYVRLLGEVGTLQFAELHRSRTLQVVFEAYPPPTVLWFKDNRTLGDSSAGEIALSTRNVSETRYVSELTLVRVKVAEAGHYTMRAFHEDAEVQLSFQLQINVPVRVLELSESHPDSGEQTVRCRGRGMPQPNIIWSACRDLKRCPRELPPTLLGNSSEEESQLETNVTYWEEEQEFEVVSTLRLQHVDRPLSVRCTLRNAVGQDTQEVIVVPHSLPFKVVVISAILALVVLTIISLIILIMLWQKKPRYEIRWKVIESVSSDGHEYIYVDPMQLPYDSTWELPRDQLVLGRTLGSGAFGQVVEATAHGLSHSQATMKVAVKMLKSTARSSEKQALMSELKIMSHLGPHLNVVNLLGACTKGGPIYIITEYCRYGDLVDYLHRNKHTFLQHHSDKRRPPSAELYSNALPVGLPLPSHVSLTGESDGGYMDMSKDESVDYVPMLDMKGDVKYADIESSNYMAPYDNYVPSAPERTCRATLINESPVLSYMDLVGFSYQVANGMEFLASKNCVHRDLAARNVLICEGKLVKICDFGLARDIMRDSNYISKGSTFLPLKWMAPESIFNSLYTTLSDVWSFGILLWEIFTLGGTPYPELPMNEQFYNAIKRGYRMAQPAHASDEIYEIMQKCWEEKFEIRPPFSQLVLLLERLLGEGYKKKYQQVDEEFLRSDHPAILRSQARLPGFHGLRSPLDTSSVLYTAVQPNEGDNDYIIPLPDPKPEVADEGPLEGSPSLASSTLNEVNTSSTISCDSPLEPQDEPEPEPQLELQVEPEPELEQLPDSGCPAPRAEAEDSFL,6.920818753952375 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+OC(=O)[C@H]1CC[C@@H](CC1)C(=O)N1CC[C@](C1)(c1ccc(cc1)C(F)(C(F)(F)F)C(F)(F)F)S(=O)(=O)c1ccc(Cl)cc1,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,6.97469413473523 +COc1cc2c(CNCC22CCCC2)cc1Nc1ncc(Cl)c(Nc2ccccc2S(=O)(=O)C(C)C)n1,MGAIGLLWLLPLLLSTAAVGSGMGTGQRAGSPAAGPPLQPREPLSYSRLQRKSLAVDFVVPSLFRVYARDLLLPPSSSELKAGRPEARGSLALDCAPLLRLLGPAPGVSWTAGSPAPAEARTLSRVLKGGSVRKLRRAKQLVLELGEEAILEGCVGPPGEAAVGLLQFNLSELFSWWIRQGEGRLRIRLMPEKKASEVGREGRLSAAIRASQPRLLFQIFGTGHSSLESPTNMPSPSPDYFTWNLTWIMKDSFPFLSHRSRYGLECSFDFPCELEYSPPLHDLRNQSWSWRRIPSEEASQMDLLDGPGAERSKEMPRGSFLLLNTSADSKHTILSPWMRSSSEHCTLAVSVHRHLQPSGRYIAQLLPHNEAAREILLMPTPGKHGWTVLQGRIGRPDNPFRVALEYISSGNRSLSAVDFFALKNCSEGTSPGSKMALQSSFTCWNGTVLQLGQACDFHQDCAQGEDESQMCRKLPVGFYCNFEDGFCGWTQGTLSPHTPQWQVRTLKDARFQDHQDHALLLSTTDVPASESATVTSATFPAPIKSSPCELRMSWLIRGVLRGNVSLVLVENKTGKEQGRMVWHVAAYEGLSLWQWMVLPLLDVSDRFWLQMVAWWGQGSRAIVAFDNISISLDCYLTISGEDKILQNTAPKSRNLFERNPNKELKPGENSPRQTPIFDPTVHWLFTTCGASGPHGPTQAQCNNAYQNSNLSVEVGSEGPLKGIQIWKVPATDTYSISGYGAAGGKGGKNTMMRSHGVSVLGIFNLEKDDMLYILVGQQGEDACPSTNQLIQKVCIGENNVIEEEIRVNRSVHEWAGGGGGGGGATYVFKMKDGVPVPLIIAAGGGGRAYGAKTDTFHPERLENNSSVLGLNGNSGAAGGGGGWNDNTSLLWAGKSLQEGATGGHSCPQAMKKWGWETRGGFGGGGGGCSSGGGGGGYIGGNAASNNDPEMDGEDGVSFISPLGILYTPALKVMEGHGEVNIKHYLNCSHCEVDECHMDPESHKVICFCDHGTVLAEDGVSCIVSPTPEPHLPLSLILSVVTSALVAALVLAFSGIMIVYRRKHQELQAMQMELQSPEYKLSKLRTSTIMTDYNPNYCFAGKTSSISDLKEVPRKNITLIRGLGHGAFGEVYEGQVSGMPNDPSPLQVAVKTLPEVCSEQDELDFLMEALIISKFNHQNIVRCIGVSLQSLPRFILMELMAGGDLKSFLRETRPRPSQPSSLAMLDLLHVARDIACGCQYLEENHFIHRDIAARNCLLTCPGPGRVAKIGDFGMARDIYRASYYRKGGCAMLPVKWMPPEAFMEGIFTSKTDTWSFGVLLWEIFSLGYMPYPSKSNQEVLEFVTSGGRMDPPKNCPGPVYRIMTQCWQHQPEDRPNFAIILERIEYCTQDPDVINTALPIEYGPLVEEEEKVPVRPKDPEGVPPLLVSQQAKREEERSPAAPPPLPTTSSGKAAKKPTAAEISVRVPRGPAVEGGHVNMAFSQSNPPSELHKVHGSRNKPTSLWNPTYGSWFTEKPTKKNNPIAKKEPHDRGNLGLEGSCTVPPNVATGRLPGASLLLEPSSLTANMKEVPLFRLRHFPCGNVNYGYQQQGLPLEAATAPGAGHYEDTILKSKNSMNQPGP,8.0 +C[C@]1(N)CC[C@@H](Nc2c(cnn3cc(cc23)-c2ccccc2Cl)C(N)=O)C1(C)C,MPLRHWGMARGSKPVGDGAQPMAAMGGLKVLLHWAGPGGGEPWVTFSESSLTAEEVCIHIAHKVGITPPCFNLFALFDAQAQVWLPPNHILEIPRDASLMLYFRIRFYFRNWHGMNPREPAVYRCGPPGTEASSDQTAQGMQLLDPASFEYLFEQGKHEFVNDVASLWELSTEEEIHHFKNESLGMAFLHLCHLALRHGIPLEEVAKKTSFKDCIPRSFRRHIRQHSALTRLRLRNVFRRFLRDFQPGRLSQQMVMVKYLATLERLAPRFGTERVPVCHLRLLAQAEGEPCYIRDSGVAPTDPGPESAAGPPTHEVLVTGTGGIQWWPVEEEVNKEEGSSGSSGRNPQASLFGKKAKAHKAVGQPADRPREPLWAYFCDFRDITHVVLKEHCVSIHRQDNKCLELSLPSRAAALSFVSLVDGYFRLTADSSHYLCHEVAPPRLVMSIRDGIHGPLLEPFVQAKLRPEDGLYLIHWSTSHPYRLILTVAQRSQAPDGMQSLRLRKFPIEQQDGAFVLEGWGRSFPSVRELGAALQGCLLRAGDDCFSLRRCCLPQPGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASDPTVFHKRYLKKIRDLGEGHFGKVSLYCYDPTNDGTGEMVAVKALKADCGPQHRSGWKQEIDILRTLYHEHIIKYKGCCEDQGEKSLQLVMEYVPLGSLRDYLPRHSIGLAQLLLFAQQICEGMAYLHAQHYIHRDLAARNVLLDNDRLVKIGDFGLAKAVPEGHEYYRVREDGDSPVFWYAPECLKEYKFYYASDVWSFGVTLYELLTHCDSSQSPPTKFLELIGIAQGQMTVLRLTELLERGERLPRPDKCPCEVYHLMKNCWETEASFRPTFENLIPILKTVHEKYQGQAPSVFSVC,7.327902142064282 +O=C(NCCCN1CCC(Cc2ccccc2)CC1)c1ccc2ccccc2c1,MLLARMNPQVQPENNGADTGPEQPLRARKTAELLVVKERNGVQCLLAPRDGDAQPRETWGKKIDFLLSVVGFAVDLANVWRFPYLCYKNGGGAFLIPYTLFLIIAGMPLFYMELALGQYNREGAATVWKICPFFKGVGYAVILIALYVGFYYNVIIAWSLYYLFSSFTLNLPWTDCGHTWNSPNCTDPKLLNGSVLGNHTKYSKYKFTPAAEFYERGVLHLHESSGIHDIGLPQWQLLLCLMVVVIVLYFSLWKGVKTSGKVVWITATLPYFVLFVLLVHGVTLPGASNGINAYLHIDFYRLKEATVWIDAATQIFFSLGAGFGVLIAFASYNKFDNNCYRDALLTSSINCITSFVSGFAIFSILGYMAHEHKVNIEDVATEGAGLVFILYPEAISTLSGSTFWAVVFFVMLLALGLDSSMGGMEAVITGLADDFQVLKRHRKLFTFGVTFSTFLLALFCITKGGIYVLTLLDTFAAGTSILFAVLMEAIGVSWFYGVDRFSNDIQQMMGFRPGLYWRLCWKFVSPAFLLFVVVVSIINFKPLTYDDYIFPPWANWVGWGIALSSMVLVPIYVIYKFLSTQGSLWERLAYGITPENEHHLVAQRDIRQFQLQHWLAI,6.465973893943865 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+NS(=O)(=O)c1ccc(OCc2ccc(F)cc2)cc1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,7.619788758288394 +COC(=O)c1c2CCCc2nc(N)c1C#N,MKARELDVPGAWEITPTIHVDSRGLFFEWLTDHGFRAFAGHSLDVRQVNCSVSSAGVLRGLHFAQLPPSQAKYVTCVSGSVFDVVVDIREGSPTFGRWDSVLLDDQDRRTIYVSEGLAHGFLALQDNSTVMYLCSAEYNPQREHTICATDPTLAVDWPLVDGAAPSLSDRDAAAPSFEDVRASGLLPRWEQTQRFIGEMRGT,5.352128234693767 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+CCOC(=O)C1Oc2c(ccc3[nH]c(=O)n(C1c1ccccn1)c23)-c1c(C)noc1C,MLQNVTPHNKLPGEGNAGLLGLGPEAAAPGKRIRKPSLLYEGFESPTMASVPALQLTPANPPPPEVSNPKKPGRVTNQLQYLHKVVMKALWKHQFAWPFRQPVDAVKLGLPDYHKIIKQPMDMGTIKRRLENNYYWAASECMQDFNTMFTNCYIYNKPTDDIVLMAQTLEKIFLQKVASMPQEEQELVVTIPKNSHKKGAKLAALQGSVTSAHQVPAVSSVSHTALYTPPPEIPTTVLNIPHPSVISSPLLKSLHSAGPPLLAVTAAPPAQPLAKKKGVKRKADTTTPTPTAILAPGSPASPPGSLEPKAARLPPMRRESGRPIKPPRKDLPDSQQQHQSSKKGKLSEQLKHCNGILKELLSKKHAAYAWPFYKPVDASALGLHDYHDIIKHPMDLSTVKRKMENRDYRDAQEFAADVRLMFSNCYKYNPPDHDVVAMARKLQDVFEFRYAKMPDEPLEPGPLPVSTAMPPGLAKSSSESSSEESSSESSSEEEEEEDEEDEEEEESESSDSEEERAHRLAELQEQLRAVHEQLAALSQGPISKPKRKREKKEKKKKRKAEKHRGRAGADEDDKGPRAPRPPQPKKSKKASGSGGGSAALGPSGFGPSGGSGTKLPKKATKTAPPALPTGYDSEEEEESRPMSYDEKRQLSLDINKLPGEKLGRVVHIIQAREPSLRDSNPEEIEIDFETLKPSTLRELERYVLSCLRKKPRKPYTIKKPVGKTKEELALEKKRELEKRLQDVSGQLNSTKKPPKKANEKTESSSAQQVAVSRLSASSSSSDSSSSSSSSSSSDTSDSDSG,7.0 +CCCCCCCCCCNC(=O)CCCSC[C@H](NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](C)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](N)CCCCN)[C@@H](C)O)C(=O)N[C@@H](CO)C(=O)N[C@@H]([C@@H](C)O)C(=O)NCC(=O)NCC(=O)N[C@@H](CCCCN)C(O)=O,MSVNYAAGLSPYADKGKCGLPEIFDPPEELERKVWELARLVWQSSSVVFHTGAGISTASGIPDFRGPHGVWTMEERGLAPKFDTTFESARPTQTHMALVQLERVGLLRFLVSQNVDGLHVRSGFPRDKLAELHGNMFVEECAKCKTQYVRDTVVGTMGLKATGRLCTVAKARGLRACRGELRDTILDWEDSLPDRDLALADEASRNADLSITLGTSLQIRPSGNLPLATKRRGGRLVIVNLQPTKHDRHADLRIHGYVDEVMTRLMKHLGLEIPAWDGPRVLERALPPLPRPPTPKLEPKEESPTRINGSIPAGPKQEPCAQHNGSEPASPKRERPTSPAPHRPPKRVKAKAVPS,3.602059991327962 +CC(C)(C)c1ccc(cc1)C(=O)Nc1cn2cc(CO)ccc2n1,MSTEADEGITFSVPPFAPSGFCTIPEGGICRRGGAAAVGEGEEHQLPPPPPGSFWNVESAAAPGIGCPAATSSSSATRGRGSSVGGGSRRTTVAYVINEASQGQLVVAESEALQSLREACETVGATLETLHFGKLDFGETTVLDRFYNADIAVVEMSDAFRQPSLFYHLGVRESFSMANNIILYCDTNSDSLQSLKEIICQKNTMCTGNYTFVPYMITPHNKVYCCDSSFMKGLTELMQPNFELLLGPICLPLVDRFIQLLKVAQASSSQYFRESILNDIRKARNLYTGKELAAELARIRQRVDNIEVLTADIVINLLLSYRDIQDYDSIVKLVETLEKLPTFDLASHHHVKFHYAFALNRRNLPGDRAKALDIMIPMVQSEGQVASDMYCLVGRIYKDMFLDSNFTDTESRDHGASWFKKAFESEPTLQSGINYAVLLLAAGHQFESSFELRKVGVKLSSLLGKKGNLEKLQSYWEVGFFLGASVLANDHMRVIQASEKLFKLKTPAWYLKSIVETILIYKHFVKLTTEQPVAKQELVDFWMDFLVEATKTDVTVVRFPVLILEPTKIYQPSYLSINNEVEEKTISIWHVLPDDKKGIHEWNFSASSVRGVSISKFEERCCFLYVLHNSDDFQIYFCTELHCKKFFEMVNTITEEKGRSTEEGDCESDLLEYDYEYDENGDRVVLGKGTYGIVYAGRDLSNQVRIAIKEIPERDSRYSQPLHEEIALHKHLKHKNIVQYLGSFSENGFIKIFMEQVPGGSLSALLRSKWGPLKDNEQTIGFYTKQILEGLKYLHDNQIVHRDIKGDNVLINTYSGVLKISDFGTSKRLAGINPCTETFTGTLQYMAPEIIDKGPRGYGKAADIWSLGCTIIEMATGKPPFYELGEPQAAMFKVGMFKVHPEIPESMSAEAKAFILKCFEPDPDKRACANDLLVDEFLKVSSKKKKTQPKLSALSAGSNEYLRSISLPVPVLVEDTSSSSEYGSVSPDTELKVDPFSFKTRAKSCGERDVKGIRTLFLGIPDENFEDHSAPPSPEEKDSGFFMLRKDSERRATLHRILTEDQDKIVRNLMESLAQGAEEPKLKWEHITTLIASLREFVRSTDRKIIATTLSKLKLELDFDSHGISQVQVVLFGFQDAVNKVLRNHNIKPHWMFALDSIIRKAVQTAITILVPELRPHFSLASESDTADQEDLDVEDDHEEQPSNQTVRRPQAVIEDAVATSGVSTLSSTVSHDSQSAHRSLNVQLGRMKIETNRLLEELVRKEKELQALLHRAIEEKDQEIKHLKLKSQPIEIPELPVFHLNSSGTNTEDSELTDWLRVNGADEDTISRFLAEDYTLLDVLYYVTRDDLKCLRLRGGMLCTLWKAIIDFRNKQT,6.889410289700751 +Cc1ccc(CN2C3CC2CN(C3)c2ccc(cn2)-c2cc(OCC(C)(C)O)cn3ncc(C#N)c23)nn1,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,6.991399828238082 +CC(C)(CO)NS(=O)(=O)c1cccc(CNC(=O)c2cnc(nc2)-c2cccc(F)c2)c1,MPNYKLTYFNMRGRAEIIRYIFAYLDIQYEDHRIEQADWPEIKSTLPFGKIPILEVDGLTLHQSLAIARYLTKNTDLAGNTEMEQCHVDAIVDTLDDFMSCFPWAEKKQDVKEQMFNELLTYNAPHLMQDLDTYLGGREWLIGNSVTWADFYWEICSTTLLVFKPDLLDNHPRLVTLRKKVQAIPAVANWIKRRPQTKL,7.638272163982407 +NC(=O)c1cc(c(Cl)cc1SCc1ccccc1)S(N)(=O)=O,MRALVLLLSLFLLGGQAQHVSDWTYSEGALDEAHWPQHYPACGGQRQSPINLQRTKVRYNPSLKGLNMTGYETQAGEFPMVNNGHTVQISLPSTMRMTVADGTVYIAQQMHFHWGGASSEISGSEHTVDGIRHVIEIHIVHYNSKYKSYDIAQDAPDGLAVLAAFVEVKNYPENTYYSNFISHLANIKYPGQRTTLTGLDVQDMLPRNLQHYYTYHGSLTTPPCTENVHWFVLADFVKLSRTQVWKLENSLLDHRNKTIHNDYRRTQPLNHRVVESNFPNQEYTLGSEFQFYLHKIEEILDYLRRALN,5.823908740944319 +CCN(CC)[C@@H]1[C@@H](CO)[C@H]2CN(Cc3ccccc3)[C@@H]([C@@H]12)c1ccccc1,MASLSQLSSHLNYTCGAENSTGASQARPHAYYALSYCALILAIVFGNGLVCMAVLKERALQTTTNYLVVSLAVADLLVATLVMPWVVYLEVTGGVWNFSRICCDVFVTLDVMMCTASILNLCAISIDRYTAVVMPVHYQHGTGQSSCRRVALMITAVWVLAFAVSCPLLFGFNTTGDPTVCSISNPDFVIYSSVVSFYLPFGVTVLVYARIYVVLKQRRRKRILTRQNSQCNSVRPGFPQQTLSPDPAHLELKRYYSICQDTALGGPGFQERGGELKREEKTRNSLSPTIAPKLSLEVRKLSNGRLSTSLKLGPLQPRGVPLREKKATQMVAIVLGAFIVCWLPFFLTHVLNTHCQTCHVSPELYSATTWLGYVNSALNPVIYTTFNIEFRKAFLKILSC,4.87942606879415 +Cc1c(CCO)sc[n+]1Cc1cnc(C)nc1N,MKILDALLFPVIFIMFFIHLSIAQTDPELTIMTRLGQVQGTRLPVPDRSHVIAFLGIPFAEPPLGKMRFKPPEPKKPWNDVFDARDYPSACYQYVDTSYPGFSGTEMWNPNRMMSEDCLYLNVWVPATPRPHNLTVMVWIYGGGFYSGSSSLDVYDGRYLAHSEKVVVVSMNYRVSAFGFLALNGSAEAPGNVGLLDQRLALQWVQDNIHFFGGNPKQVTIFGESAGAASVGMHLLSPDSRPKFTRAILQSGVPNGPWRTVSFDEARRRAIKLGRLVGCPDGNDTDLIDCLRSKQPQDLIDQEWLVLPFSGLFRFSFVPVIDGVVFPDTPEAMLNSGNFKDTQILLGVNQNEGSYFLIYGAPGFSKDNESLITREDFLQGVKMSVPHANEIGLEAVILQYTDWMDEDNPIKNREAMDDIVGDHNVVCPLQHFAKMYAQYSILQGQTGTASQGNLGWGNSGSASNSGNSQVSVYLYMFDHRASNLVWPEWMGVIHGYEIEFVFGLPLEKRLNYTLEEEKLSRRMMKYWANFARTGNPNINVDGSIDSRRRWPVFTSTEQKHVGLNTDSLKVHKGLKSQFCALWNRFLPRLLNVTENIDDAERQWKAEFHRWSSYMMHWKNQFDHYSKQERCTNL,3.2441251443275085 +Nc1cccn2c1n[nH]c2=O,MSGGGPSGGGPGGSGRARTSSFAEPGGGGGGGGGGPGGSASGPGGTGGGKASVGAMGGGVGASSSGGGPGGSGGGGSGGPGAGTSFPPPGVKLGRDSGKVTTVVATLGQGPERSQEVAYTDIKVIGNGSFGVVYQARLAETRELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDELYLNLVLEYVPETVYRVARHFTKAKLTIPILYVKVYMYQLFRSLAYIHSQGVCHRDIKPQNLLVDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFKSRTPPEAIALCSSLLEYTPSSRLSPLEACAHSFFDELRCLGTQLPNNRPLPPLFNFSAGELSIQPSLNAILIPPHLRSPAGTTTLTPSSQALTETPTSSDWQSTDATPTLTNSS,4.301029995663981 +CC(C)n1cnc2c(NCc3ccc(cc3)-c3ccccc3)nc(N[C@H]3CC[C@@H](CC3)NS(=O)(=O)C(F)(F)F)nc12,MLGNSAPGPATREAGSALLALQQTALQEDQENINPEKAAPVQQPRTRAALAVLKSGNPRGLAQQQRPKTRRVAPLKDLPVNDEHVTVPPWKANSKQPAFTIHVDEAEKEAQKKPAESQKIEREDALAFNSAISLPGPRKPLVPLDYPMDGSFESPHTMDMSIILEDEKPVSVNEVPDYHEDIHTYLREMEVKCKPKVGYMKKQPDITNSMRAILVDWLVEVGEEYKLQNETLHLAVNYIDRFLSSMSVLRGKLQLVGTAAMLLASKFEEIYPPEVAEFVYITDDTYTKKQVLRMEHLVLKVLTFDLAAPTVNQFLTQYFLHQQPANCKVESLAMFLGELSLIDADPYLKYLPSVIAGAAFHLALYTVTGQSWPESLIRKTGYTLESLKPCLMDLHQTYLKAPQHAQQSIREKYKNSKYHGVSLLNPPETLNL,5.301029995663981 +COc1cn(Cc2ccccc2)c(NCc2cccc(Cl)c2C)nc1=O,MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY,6.552841968657781 +CC1(C)CCC(CN2CCN(CC2)c2ccc(C(=O)NS(=O)(=O)c3ccc(NCCCN4CCOCC4)c(c3)[N+]([O-])=O)c(c2)-n2ncc3nc4[nH]ccc4cc23)=C(C1)c1ccc(Cl)cc1,MAHAGRTGYDNREIVMKYIHYKLSQRGYEWDAGDVGAAPPGAAPAPGIFSSQPGHTPHPAASRDPVARTSPLQTPAAPGAAAGPALSPVPPVVHLTLRQAGDDFSRRYRRDFAEMSSQLHLTPFTARGRFATVVEELFRDGVNWGRIVAFFEFGGVMCVESVNREMSPLVDNIALWMTEYLNRHLHTWIQDNGGWDAFVELYGPSMRPLFDFSWLSLKTLLSLALVGACITLGAYLGHK,8.0 +CC[C@@H](O)COc1cc(-c2ccc(nc2)N2CCN(Cc3ccccn3)CC2)c2c(cnn2c1)C#N,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,6.623423042943488 +Cc1cc(C)nc(Nc2cc(N[C@@H]3CCCC[C@@H]3N)cnc2C(N)=O)c1,MASSGMADSANHLPFFFGNITREEAEDYLVQGGMSDGLYLLRQSRNYLGGFALSVAHGRKAHHYTIERELNGTYAIAGGRTHASPADLCHYHSQESDGLVCLLKKPFNRPQGVQPKTGPFEDLKENLIREYVKQTWNLQGQALEQAIISQKPQLEKLIATTAHEKMPWFHGKISREESEQIVLIGSKTNGKFLIRARDNNGSYALCLLHEGKVLHYRIDKDKTGKLSIPEGKKFDTLWQLVEHYSYKADGLLRVLTVPCQKIGTQGNVNFGGRPQLPGSHPATWSAGGIISRIKSYSFPKPGHRKSSPAQGNRQESTVSFNPYEPELAPWAADKGPQREALPMDTEVYESPYADPEEIRPKEVYLDRKLLTLEDKELGSGNFGTVKKGYYQMKKVVKTVAVKILKNEANDPALKDELLAEANVMQQLDNPYIVRMIGICEAESWMLVMEMAELGPLNKYLQQNRHVKDKNIIELVHQVSMGMKYLEESNFVHRDLAARNVLLVTQHYAKISDFGLSKALRADENYYKAQTHGKWPVKWYAPECINYYKFSSKSDVWSFGVLMWEAFSYGQKPYRGMKGSEVTAMLEKGERMGCPAGCPREMYDLMNLCWTYDVENRPGFAAVELRLRNYYYDVVN,7.236572006437062 +O=C(Cc1ccco1)Nc1nnc(CCCCc2nnc(NC(=O)Cc3ccco3)s2)s1,MMRLRGSGMLRDLLLRSPAGVSATLRRAQPLVTLCRRPRGGGRPAAGPAAAARLHPWWGGGGWPAEPLARGLSSSPSEILQELGKGSTHPQPGVSPPAAPAAPGPKDGPGETDAFGNSEGKELVASGENKIKQGLLPSLEDLLFYTIAEGQEKIPVHKFITALKSTGLRTSDPRLKECMDMLRLTLQTTSDGVMLDKDLFKKCVQSNIVLLTQAFRRKFVIPDFMSFTSHIDELYESAKKQSGGKVADYIPQLAKFSPDLWGVSVCTVDGQRHSTGDTKVPFCLQSCVKPLKYAIAVNDLGTEYVHRYVGKEPSGLRFNKLFLNEDDKPHNPMVNAGAIVVTSLIKQGVNNAEKFDYVMQFLNKMAGNEYVGFSNATFQSERESGDRNFAIGYYLKEKKCFPEGTDMVGILDFYFQLCSIEVTCESASVMAATLANGGFCPITGERVLSPEAVRNTLSLMHSCGMYDFSGQFAFHVGLPAKSGVAGGILLVVPNVMGMMCWSPPLDKMGNSVKGIHFCHDLVSLCNFHNYDNLRHFAKKLDPRREGGDQRVKSVINLLFAAYTGDVSALRRFALSAMDMEQRDYDSRTALHVAAAEGHVEVVKFLLEACKVNPFPKDRWNNTPMDEALHFGHHDVFKILQEYQVQYTPQGDSDNGKENQTVHKNLDGLL,6.494850021680094 +CCC(CN(C)S(=O)(=O)C1CC1)N1[C@@H]([C@H](C[C@](C)(CC(=O)NS(C)(=O)=O)C1=O)c1cccc(Cl)c1)c1ccc(Cl)cc1,MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGPDEAPRMPEAAPPVAPAPAAPTPA,8.221848749616356 +COC(=O)c1ccc(cc1)S(=O)(=O)NC(=O)c1ccc(Cl)cc1Cl,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,5.920818753952375 +Clc1ccc(cc1)-c1cc2ncn(-c3ccc4ncccc4c3)c(=O)c2s1,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,7.200659450546418 +CCN(CC)c1ccc(C=NNC(=O)c2ccccc2)c(O)c1,MVSFSKNKVLSAAVFASVLLLDNNNSAFNNNLCSKNAKGLNLNKRLLHETQAHVDDAHHAHHVADAHHAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAADAHHAHHAAYAHHAHHASDAHHAADAHHAAYAHHAHHAADAHHAADAHHAAYAHHAHHAADAHHAADAHHATDAHHAHHAADAHHATDAHHAADAHHAADAHHATDAHHAADAHHATDAHHAADAHHAADAHHATDSHHAHHAADAHHAAAHHATDAHHAAAHHATDAHHAAAHHEAATHCLRH,4.301029995663981 +CCC(Nc1nc(NC(CC)C2CC2)nc(n1)-c1cccc(Cl)n1)C1CC1,MAGYLRVVRSLCRASGSRPAWAPAALTAPTSQEQPRRHYADKRIKVAKPVVEMDGDEMTRIIWQFIKEKLILPHVDIQLKYFDLGLPNRDQTDDQVTIDSALATQKYSVAVKCATITPDEARVEEFKLKKMWKSPNGTIRNILGGTVFREPIICKNIPRLVPGWTKPITIGRHAHGDQYKATDFVADRAGTFKMVFTPKDGSGVKEWEVYNFPAGGVGMGMYNTDESISGFAHSCFQYAIQKKWPLYMSTKNTILKAYDGRFKDIFQEIFDKHYKTDFDKNKIWYEHRLIDDMVAQVLKSSGGFVWACKNYDGDVQSDILAQGFGSLGLMTSVLVCPDGKTIEAEAAHGTVTRHYREHQKGRPTSTNPIASIFAWTRGLEHRGKLDGNQDLIRFAQMLEKVCVETVESGAMTKDLAGCIHGLSNVKLNEHFLNTTDFLDTIKSNLDRALGRQ,7.853871964321762 +C[C@@H]1CCN(C[C@@H]1N(C)c1ncnc2[nH]ccc12)C(=O)CC#N,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASTPTNATAASDANTGDRGQTNNAASASASNST,5.0 +Fc1ccc(cc1)-c1nn2ccccc2c1-c1ccncc1,MGPGVLLLLLVATAWHGQGIPVIEPSVPELVVKPGATVTLRCVGNGSVEWDGPPSPHWTLYSDGSSSILSTNNATFQNTGTYRCTEPGDPLGGSAAIHLYVKDPARPWNVLAQEVVVFEDQDALLPCLLTDPVLEAGVSLVRVRGRPLMRHTNYSFSPWHGFTIHRAKFIQSQDYQCSALMGGRKVMSISIRLKVQKVIPGPPALTLVPAELVRIRGEAAQIVCSASSVDVNFDVFLQHNNTKLAIPQQSDFHNNRYQKVLTLNLDQVDFQHAGNYSCVASNVQGKHSTSMFFRVVESAYLNLSSEQNLIQEVTVGEGLNLKVMVEAYPGLQGFNWTYLGPFSDHQPEPKLANATTKDTYRHTFTLSLPRLKPSEAGRYSFLARNPGGWRALTFELTLRYPPEVSVIWTFINGSGTLLCAASGYPQPNVTWLQCSGHTDRCDEAQVLQVWDDPYPEVLSQEPFHKVTVQSLLTVETLEHNQTYECRAHNSVGSGSWAFIPISAGAHTHPPDEFLFTPVVVACMSIMALLLLLLLLLLYKYKQKPKYQVRWKIIESYEGNSYTFIDPTQLPYNEKWEFPRNNLQFGKTLGAGAFGKVVEATAFGLGKEDAVLKVAVKMLKSTAHADEKEALMSELKIMSHLGQHENIVNLLGACTHGGPVLVITEYCCYGDLLNFLRRKAEAMLGPSLSPGQDPEGGVDYKNIHLEKKYVRRDSGFSSQGVDTYVEMRPVSTSSNDSFSEQDLDKEDGRPLELRDLLHFSSQVAQGMAFLASKNCIHRDVAARNVLLTNGHVAKIGDFGLARDIMNDSNYIVKGNARLPVKWMAPESIFDCVYTVQSDVWSYGILLWEIFSLGLNPYPGILVNSKFYKLVKDGYQMAQPAFAPKNIYSIMQACWALEPTHRPTFQQICSFLQEQAQEDRRERDYTNLPSSSRSGGSGSSSSELEEESSSEHLTCCEQGDIAQPLLQPNNYQFC,5.0 +CC(C)c1cnn2c(NCc3ccccc3N(C)C)nc(OC3CCN(C)CC3)nc12,MAKQYDSVECPFCDEVSKYEKLAKIGQGTFGEVFKARHRKTGQKVALKKVLMENEKEGFPITALREIKILQLLKHENVVNLIEICRTKASPYNRCKGSIYLVFDFCEHDLAGLLSNVLVKFTLSEIKRVMQMLLNGLYYIHRNKILHRDMKAANVLITRDGVLKLADFGLARAFSLAKNSQPNRYTNRVVTLWYRPPELLLGERDYGPPIDLWGAGCIMAEMWTRSPIMQGNTEQHQLALISQLCGSITPEVWPNVDNYELYEKLELVKGQKRKVKDRLKAYVRDPYALDLIDKLLVLDPAQRIDSDDALNHDFFWSDPMPSDLKGMLSTHLTSMFEYLAPPRRKGSQITQQSTNQSRNPATTNQTEFERVF,5.127843727251707 +COc1cc(ncc1C#N)N1CC2(CC1=O)CCN(C[C@H](O)c1ccc3C(=O)OCc3c1C)CC2,MNASSRNVFDTLIRVLTESMFKHLRKWVVTRFFGHSRQRARLVSKDGRCNIEFGNVEAQSRFIFFVDIWTTVLDLKWRYKMTIFITAFLGSWFFFGLLWYAVAYIHKDLPEFHPSANHTPCVENINGLTSAFLFSLETQVTIGYGFRCVTEQCATAIFLLIFQSILGVIINSFMCGAILAKISRPKKRAKTITFSKNAVISKRGGKLCLLIRVANLRKSLLIGSHIYGKLLKTTVTPEGETIILDQININFVVDAGNENLFFISPLTIYHVIDHNSPFFHMAAETLLQQDFELVVFLDGTVESTSATCQVRTSYVPEEVLWGYRFAPIVSKTKEGKYRVDFHNFSKTVEVETPHCAMCLYNEKDVRARMKRGYDNPNFILSEVNETDDTKM,7.482804102050026 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+CN1CCN(CC1)c1ccc(cn1)-c1cnc(NCc2c3CCOc3ccc2F)n2cncc12,MGQTGKKSEKGPVCWRKRVKSEYMRLRQLKRFRRADEVKSMFSSNRQKILERTEILNQEWKQRRIQPVHILTSVSSLRGTRECSVTSDLDFPTQVIPLKTLNAVASVPIMYSWSPLQQNFMVEDETVLHNIPYMGDEVLDQDGTFIEELIKNYDGKVHGDRECGFINDEIFVELVNALGQYNDDDDDDDGDDPEEREEKQKDLEDHRDDKESRPPRKFPSDKIFEAISSMFPDKGTAEELKEKYKELTEQQLPGALPPECTPNIDGPNAKSVQREQSLHSFHTLFCRRCFKYDCFLHPFHATPNTYKRKNTETALDNKPCGPQCYQHLEGAKEFAAALTAERIKTPPKRPGGRRRGRLPNNSSRPSTPTINVLESKDTDSDREAGTETGGENNDKEEEEKKDETSSSSEANSRCQTPIKMKPNIEPPENVEWSGAEASMFRVLIGTYYDNFCAIARLIGTKTCRQVYEFRVKESSIIAPAPAEDVDTPPRKKKRKHRLWAAHCRKIQLKKDGSSNHVYNYQPCDHPRQPCDSSCPCVIAQNFCEKFCQCSSECQNRFPGCRCKAQCNTKQCPCYLAVRECDPDLCLTCGAADHWDSKNVSCKNCSIQRGSKKHLLLAPSDVAGWGIFIKDPVQKNEFISEYCGEIISQDEADRRGKVYDKYMCSFLFNLNNDFVVDATRKGNKIRFANHSVNPNCYAKVMMVNGDHRIGIFAKRAIQTGEELFFDYRYSQADALKYVGIEREMEIP,7.549750891680639 +Cc1cccc(c1)C1CC(=NN1c1ccc(cc1)S(N)(=O)=O)c1ccccc1,MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIE,4.522878745280337 +OC(=O)C(=O)Nc1sc2CN(CCc3ccccc3)CCc2c1C(O)=O,MTMYLWLKLLAFGFAFLDTEVFVTGQSPTPSPTGLTTAKMPSVPLSSDPLPTHTTAFSPASTFERENDFSETTTSLSPDNTSTQVSPDSLDNASAFNTTGVSSVQTPHLPTHADSQTPSAGTDTQTFSGSAANAKLNPTPGSNAISDVPGERSTASTFPTDPVSPLTTTLSLAHHSSAALPARTSNTTITANTSDAYLNASETTTLSPSGSAVISTTTIATTPSKPTCDEKYANITVDYLYNKETKLFTAKLNVNENVECGNNTCTNNEVHNLTECKNASVSISHNSCTAPDKTLILDVPPGVEKFQLHDCTQVEKADTTICLKWKNIETFTCDTQNITYRFQCGNMIFDNKEIKLENLEPEHEYKCDSEILYNNHKFTNASKIIKTDFGSPGEPQIIFCRSEAAHQGVITWNPPQRSFHNFTLCYIKETEKDCLNLDKNLIKYDLQNLKPYTKYVLSLHAYIIAKVQRNGSAAMCHFTTKSAPPSQVWNMTVSMTSDNSMHVKCRPPRDRNGPHERYHLEVEAGNTLVRNESHKNCDFRVKDLQYSTDYTFKAYFHNGDYPGEPFILHHSTSYNSKALIAFLAFLIIVTSIALLVVLYKIYDLHKKRSCNLDEQQELVERDDEKQLMNVEPIHADILLETYKRKIADEGRLFLAEFQSIPRVFSKFPIKEARKPFNQNKNRYVDILPYDYNRVELSEINGDAGSNYINASYIDGFKEPRKYIAAQGPRDETVDDFWRMIWEQKATVIVMVTRCEEGNRNKCAEYWPSMEEGTRAFGDVVVKINQHKRCPDYIIQKLNIVNKKEKATGREVTHIQFTSWPDHGVPEDPHLLLKLRRRVNAFSNFFSGPIVVHCSAGVGRTGTYIGIDAMLEGLEAENKVDVYGYVVKLRRQRCLMVQVEAQYILIHQALVEYNQFGETEVNLSELHPYLHNMKKRDPPSEPSPLEAEFQRLPSYRSWRTQHIGNQEENKSKNRNSNVIPYDYNRVPLKHELEMSKESEHDSDESSDDDSDSEEPSKYINASFIMSYWKPEVMIAAQGPLKETIGDFWQMIFQRKVKVIVMLTELKHGDQEICAQYWGEGKQTYGDIEVDLKDTDKSSTYTLRVFELRHSKRKDSRTVYQYQYTNWSVEQLPAEPKELISMIQVVKQKLPQKNSSEGNKHHKSTPLLIHCRDGSQQTGIFCALLNLLESAETEEVVDIFQVVKALRKARPGMVSTFEQYQFLYDVIASTYPAQNGQVKKNNHQEDKIEFDNEVDKVKQDANCVNPLGAPEKLPEAKEQAEGSEPTSGTEGPEHSVNGPASPALNQGS,2.853871964321762 +COc1ccc2c(c1)[nH]c1c2[nH]cc2nc3ccccc3c12,MDNGMFSGFIMIKNLLLFCISMNLSSHFGFSQMPTSSVKDETNDNITIFTRILDGLLDGYDNRLRPGLGERITQVRTDIYVTSFGPVSDTEMEYTIDVFFRQSWKDERLRFKGPMQRLPLNNLLASKIWTPDTFFHNGKKSIAHNMTTPNKLLRLEDDGTLLYTMRLTISAECPMQLEDFPMDAHACPLKFGSYAYPNSEVVYVWTNGSTKSVVVAEDGSRLNQYHLMGQTVGTENISTSTGEYTIMTAHFHLKRKIGYFVIQTYLPCIMTVILSQVSFWLNRESVPARTVFGVTTVLTMTTLSISARNSLPKVAYATAMDWFIAVCYAFVFSALIEFATVNYFTKRGWAWDGKKALEAAKIKKKREVILNKSTNAFTTGKMSHPPNIPKEQTPAGTSNTTSVSVKPSEEKTSESKKTYNSISKIDKMSRIVFPVLFGTFNLVYWATYLNREPVIKGAASPK,6.647817481888637 +COc1ccc(\C=C\c2ccnc3nc([nH]c(=O)c23)N2CCCCC2)cc1,MPPSISAFQAAYIGIEVLIALVSVPGNVLVIWAVKVNQALRDATFCFIVSLAVADVAVGALVIPLAILINIGPQTYFHTCLMVACPVLILTQSSILALLAIAVDRYLRVKIPLRYKMVVTPRRAAVAIAGCWILSFVVGLTPMFGWNNLSAVERAWAANGSMGEPVIKCEFEKVISMEYMVYFNFFVWVLPPLLLMVLIYLEVFYLIRKQLNKKVSASSGDPQKYYGKELKIAKSLALILFLFALSWLPLHILNCITLFCPSCHKPSILTYIAIFLTHGNSAMNPIVYAFRIQKFRVTFLKIWNDHFRCQPAPPIDEDLPEERPDD,5.519993057042849 +CC(CC1(NC(=O)NC1=O)c1ccccn1)C(=O)N1CCN([C@@H](C)C1)c1ccc(F)c(F)c1,MRQSLLFLTSVVPFVLAPRPPDDPGFGPHQRLEKLDSLLSDYDILSLSNIQQHSVRKRDLQTSTHVETLLTFSALKRHFKLYLTSSTERFSQNFKVVVVDGKNESEYTVKWQDFFTGHVVGEPDSRVLAHIRDDDVIIRINTDGAEYNIEPLWRFVNDTKDKRMLVYKSEDIKNVSRLQSPKVCGYLKVDNEELLPKGLVDREPPEELVHRVKRRADPDPMKNTCKLLVVADHRFYRYMGRGEESTTTNYLIELIDRVDDIYRNTSWDNAGFKGYGIQIEQIRILKSPQEVKPGEKHYNMAKSYPNEEKDAWDVKMLLEQFSFDIAEEASKVCLAHLFTYQDFDMGTLGLAYVGSPRANSHGGVCPKAYYSPVGKKNIYLNSGLTSTKNYGKTILTKEADLVTTHELGHNFGAEHDPDGLAECAPNEDQGGKYVMYPIAVSGDHENNKMFSNCSKQSIYKTIESKAQECFQERSNKVCGNSRVDEGEECDPGIMYLNNDTCCNSDCTLKEGVQCSDRNSPCCKNCQFETAQKKCQEAINATCKGVSYCTGNSSECPPPGNAEDDTVCLDLGKCKDGKCIPFCEREQQLESCACNETDNSCKVCCRDLSGRCVPYVDAEQKNLFLRKGKPCTVGFCDMNGKCEKRVQDVIERFWDFIDQLSINTFGKFLADNIVGSVLVFSLIFWIPFSILVHCVDKKLDKQYESLSLFHPSNVEMLSSMDSASVRIIKPFPAPQTPGRLQPAPVIPSAPAAPKLDHQRMDTIQEDPSTDSHMDEDGFEKDPFPNSSTAAKSFEDLTDHPVTRSEKAASFKLQRQNRVDSKETEC,5.3979400086720375 +Cc1c(O)c(ccc1OCCCCOc1ccc(C(O)=O)c(Cl)c1)C(=O)CC1CCCC1,MGSLLALLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEDCGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHGDAPTAITGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAASQRLNASFTWVASDGWGALESVVAGSEGAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEQRFRCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTRLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTHNEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSLIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFIFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVVAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAARASSSLGQGSGSQFVPTVCNGREVVDSTTSSL,6.292429823902063 +C(c1ccccc1)n1c(nc2ccccc12)-c1ccccc1,MTADELVFFVNGKKVVEKNADPETTLLAYLRRKLGLRGTKLGCGEGGCGACTVMLSKYDRLQDKIIHFSANACLAPICTLHHVAVTTVEGIGSTKTRLHPVQERIAKSHGSQCGFCTPGIVMSMYTLLRNQPEPTVEEIEDAFQGNLCRCTGYRPILQGFRTFAKNGGCCGGNGNNPNCCMNQKKDHTVTLSPSLFNPEEFMPLDPTQEPIFPPELLRLKDVPPKQLRFEGERVTWIQASTLKELLDLKAQHPEAKLVVGNTEIGIEMKFKNQLFPMIICPAWIPELNAVEHGPEGISFGAACALSSVEKTLLEAVAKLPTQKTEVFRGVLEQLRWFAGKQVKSVASLGGNIITASPISDLNPVFMASGTKLTIVSRGTRRTVPMDHTFFPSYRKTLLGPEEILLSIEIPYSREDEFFSAFKQASRREDDIAKVTCGMRVLFQPGSMQVKELALCYGGMADRTISALKTTQKQLSKFWNEKLLQDVCAGLAEELSLSPDAPGGMIEFRRTLTLSFFFKFYLTVLKKLGKDSKDKCGKLDPTYTSATLLFQKDPPANIQLFQEVPNGQSKEDTVGRPLPHLAAAMQASGEAVYCDDIPRYENELFLRLVTSTRAHAKIKSIDVSEAQKVPGFVCFLSADDIPGSNETGLFNDETVFAKDTVTCVGHIIGAVVADTPEHAERAAHVVKVTYEDLPAIITIEDAIKNNSFYGSELKIEKGDLKKGFSEADNVVSGELYIGGQDHFYLETHCTIAIPKGEEGEMELFVSTQNAMKTQSFVAKMLGVPVNRILVRVKRMGGGFGGKETRSTLVSVAVALAAYKTGHPVRCMLDRNEDMLITGGRHPFLARYKVGFMKTGTIVALEVDHYSNAGNSRDLSHSIMERALFHMDNCYKIPNIRGTGRLCKTNLSSNTAFRGFGGPQALFIAENWMSEVAVTCGLPAEEVRWKNMYKEGDLTHFNQRLEGFSVPRCWDECLKSSQYYARKSEVDKFNKENCWKKRGLCIIPTKFGISFTVPFLNQAGALIHVYTDGSVLVSHGGTEMGQGLHTKMVQVASKALKIPISKIYISETSTNTVPNSSPTAASVSTDIYGQAVYEACQTILKRLEPFKKKNPDGSWEDWVMAAYQDRVSLSTTGFYRTPNLGYSFETNSGNAFHYFTYGVACSEVEIDCLTGDHKNLRTDIVMDVGSSLNPAIDIGQVEGAFVQGLGLFTLEELHYSPEGSLHTRGPSTYKIPAFGSIPTEFRVSLLRDCPNKKAIYASKAVGEPPLFLGASVFFAIKDAIRAARAQHTNNNTKELFRLDSPATPEKIRNACVDKFTTLCVTGAPGNCKPWSLRV,5.013228265733755 +CCC[C@H](N)c1cccc(n1)-c1cc(OCCCOC)c2cnn(-c3cccc(CO)n3)c2c1,MNKPITPSTYVRCLNVGLIRKLSDFIDPQEGWKKLAVAIKKPSGDDRYNQFHIRRFEALLQTGKSPTSELLFDWGTTNCTVGDLVDLLIQNEFFAPASLLLPDAVPKTANTLPSKEAITVQQKQMPFCDKDRTLMTPVQNLEQSYMPPDSSSPENKSLEVSDTRFHSFSFYELKNVTNNFDERPISVGGNKMGEGGFGVVYKGYVNNTTVAVKKLAAMVDITTEELKQQFDQEIKVMAKCQHENLVELLGFSSDGDDLCLVYVYMPNGSLLDRLSCLDGTPPLSWHMRCKIAQGAANGINFLHENHHIHRDIKSANILLDEAFTAKISDFGLARASEKFAQTVMTSRIVGTTAYMAPEALRGEITPKSDIYSFGVVLLEIITGLPAVDEHREPQLLLDIKEEIEDEEKTIEDYIDKKMNDADSTSVEAMYSVASQCLHEKKNKRPDIKKVQQLLQEMTAS,7.0 +CCOc1ccccc1N1CCNCC1,MDPLNLSWYDDDLERQNWSRPFNGSEGKADRPHYNYYAMLLTLLIFIIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMIAIVWVLSFTISCPLLFGLNNTDQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRKRRKRVNTKRSSRAFRANLKTPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRMDAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSNPDSPAKPEKNGHAKIVNPRIAKFFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFMKILHC,6.84163750790475 +CCCc1c(C)c2cc3c(C)coc3cc2oc1=O,MATANGAVENGQPDRKPPALPRPIRNLEVKFTKIFINNEWHESKSGKKFATCNPSTREQICEVEEGDKPDVDKAVEAAQVAFQRGSPWRRLDALSRGRLLHQLADLVERDRATLAALETMDTGKPFLHAFFIDLEGCIRTLRYFAGWADKIQGKTIPTDDNVVCFTRHEPIGVCGAITPWNFPLLMLVWKLAPALCCGNTMVLKPAEQTPLTALYLGSLIKEAGFPPGVVNIVPGFGPTVGAAISSHPQINKIAFTGSTEVGKLVKEAASRSNLKRVTLELGGKNPCIVCADADLDLAVECAHQGVFFNQGQCCTAASRVFVEEQVYSEFVRRSVEYAKKRPVGDPFDVKTEQGPQIDQKQFDKILELIESGKKEGAKLECGGSAMEDKGLFIKPTVFSEVTDNMRIAKEEIFGPVQPILKFKSIEEVIKRANSTDYGLTAAVFTKNLDKALKLASALESGTVWINCYNALYAQAPFGGFKMSGNGRELGEYALAEYTEVKTVTIKLGDKNP,5.958607314841775 +CC(C)c1cc(NC(=O)Nc2ccc(Oc3ccnc(Nc4cc(cc(c4)C(=O)NCCN4CCOCC4)C#C)n3)c(Cl)c2Cl)n(n1)-c1ccc(C)cc1,MASSGMADSANHLPFFFGNITREEAEDYLVQGGMSDGLYLLRQSRNYLGGFALSVAHGRKAHHYTIERELNGTYAIAGGRTHASPADLCHYHSQESDGLVCLLKKPFNRPQGVQPKTGPFEDLKENLIREYVKQTWNLQGQALEQAIISQKPQLEKLIATTAHEKMPWFHGKISREESEQIVLIGSKTNGKFLIRARDNNGSYALCLLHEGKVLHYRIDKDKTGKLSIPEGKKFDTLWQLVEHYSYKADGLLRVLTVPCQKIGTQGNVNFGGRPQLPGSHPATWSAGGIISRIKSYSFPKPGHRKSSPAQGNRQESTVSFNPYEPELAPWAADKGPQREALPMDTEVYESPYADPEEIRPKEVYLDRKLLTLEDKELGSGNFGTVKKGYYQMKKVVKTVAVKILKNEANDPALKDELLAEANVMQQLDNPYIVRMIGICEAESWMLVMEMAELGPLNKYLQQNRHVKDKNIIELVHQVSMGMKYLEESNFVHRDLAARNVLLVTQHYAKISDFGLSKALRADENYYKAQTHGKWPVKWYAPECINYYKFSSKSDVWSFGVLMWEAFSYGQKPYRGMKGSEVTAMLEKGERMGCPAGCPREMYDLMNLCWTYDVENRPGFAAVELRLRNYYYDVVN,7.568636235841012 +COc1cc(ccc1Nc1nc2NCC(C)c2c(Nc2ccccc2S(=O)(=O)NC2CCCC2)n1)N1CCOCC1,MSGVSEPLSRVKLGTLRRPEGPAEPMVVVPVDVEKEDVRILKVCFYSNSFNPGKNFKLVKCTVQTEIREIITSILLSGRIGPNIRLAECYGLRLKHMKSDEIHWLHPQMTVGEVQDKYECLHVEAEWRYDLQIRYLPEDFMESLKEDRTTLLYFYQQLRNDYMQRYASKVSEGMALQLGCLELRRFFKDMPHNALDKKSNFELLEKEVGLDLFFPKQMQENLKPKQFRKMIQQTFQQYASLREEECVMKFFNTLAGFANIDQETYRCELIQGWNITVDLVIGPKGIRQLTSQDAKPTCLAEFKQIRSIRCLPLEEGQAVLQLGIEGAPQALSIKTSSLAEAENMADLIDGYCRLQGEHQGSLIIHPRKDGEKRNSLPQIPMLNLEARRSHLSESCSIESDIYAEIPDETLRRPGGPQYGIAREDVVLNRILGEGFFGEVYEGVYTNHKGEKINVAVKTCKKDCTLDNKEKFMSEAVIMKNLDHPHIVKLIGIIEEEPTWIIMELYPYGELGHYLERNKNSLKVLTLVLYSLQICKAMAYLESINCVHRDIAVRNILVASPECVKLGDFGLSRYIEDEDYYKASVTRLPIKWMSPESINFRRFTTASDVWMFAVCMWEILSFGKQPFFWLENKDVIGVLEKGDRLPKPDLCPPVLYTLMTRCWDYDPSDRPRFTELVCSLSDVYQMEKDIAMEQERNARYRTPKILEPTAFQEPPPKPSRPKYRPPPQTNLLAPKLQFQVPEGLCASSPTLTSPMEYPSPVNSLHTPPLHRHNVFKRHSMREEDFIQPSSREEAQQLWEAEKVKMRQILDKQQKQMVEDYQWLRQEEKSLDPMVYMNDKSPLTPEKEVGYLEFTGPPQKPPRLGAQSIQPTANLDRTDDLVYLNVMELVRAVLELKNELCQLPPEGYVVVVKNVGLTLRKLIGSVDDLLPSLPSSSRTEIEGTQKLLNKDLAELINKMRLAQQNAVTSLSEECKRQMLTASHTLAVDAKNLLDAVDQAKVLANLAHPPAE,7.301029995663981 +CCn1nnc(n1)[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1cnc2c(NCc3ccc(Cl)cc3F)ncnc12,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,6.598599459218455 +Cc1nn(Cc2ccc(NC(=O)C3[C@H]4C[C@@H]5C[C@@H](C[C@H]3C5)C4)cc2)c(C)c1CC(O)=O,MSANATLKPLCPILEQMSRLQSHSNTSIRYIDHAAVLLHGLASLLGLVENGVILFVVGCRMRQTVVTTWVLHLALSDLLASASLPFFTYFLAVGHSWELGTTFCKLHSSIFFLNMFASGFLLSAISLDRCLQVVRPVWAQNHRTVAAAHKVCLVLWALAVLNTVPYFVFRDTISRLDGRIMCYYNVLLLNPGPDRDATCNSRQVALAVSKFLLAFLVPLAIIASSHAAVSLRLQHRGRRRPGRFVRLVAAVVAAFALCWGPYHVFSLLEARAHANPGLRPLVWRGLPFVTSLAFFNSVANPVLYVLTCPDMLRKLRRSLRTVLESVLVDDSELGGAGSSRRRRTSSTARSASPLALCSRPEEPRGPARLLGWLLGSCAASPQTGPLNRALSSTSS,8.397940008672037 +CCN(CC)CCSc1nnc(COc2ccc3c(C)cc(=O)oc3c2)o1,MSSKCDVVVVGGGISGMAAAKLLHDSGLNVIVLEARDRVGGRTYTLRNQKVKYVDLGGSYVGPTQNHILRLSKELGLETYKVNEVERLIHHTKGKSYPFRGSFPSVWNPITYLDHNNLWRTMDDMGREIPSDAPWKAPLAEQWDLMTMKELLDKICWTESSKQLAILFVNLCVTAEIHEVSALWFLWYVKQCGGTTRIFSTSNGGQERKFVGGSGQVSERIMDLLGDRVKLERPVIHIDQTGENVLVETLNHELYEAKYVISAVPPVLGMKIHFNPPLPMMRNQLITRVPLGSVIKSIVYYKEPFWRNMDYCGSMIIEGEEAPVAYALDDTKPDGSYPAIIGFILAHKARKLARLTKEERLKKLCDLYAKVLGSQEALHPVHYEEKNWCEEQYSGGCYTSYFPPGIMTQYGRVLRQPVGRIYFAGTETATHWSGYMEGAVEAGERAAREILHAMGKIPEDEIWLPEPESVDVPAKPITTTFLQRHLPSVPGLLKLIGLTTIFSATALGFLAHKRGLLVRI,6.2549252084179425 +Fc1cc(ccc1Cl)-c1c(nc2cccnn12)C(=O)N1CCC1,MMHVNNFPFRRHSWICFDVDNGTSAGRSPLDPMTSPGSGLILQANFVHSQRRESFLYRSDSDYDLSPKSMSRNSSIASDIHGDDLIVTPFAQVLASLRTVRNNFAALTNLQDRAPSKRSPMCNQPSINKATITEEAYQKLASETLEELDWCLDQLETLQTRHSVSEMASNKFKRMLNRELTHLSEMSRSGNQVSEFISNTFLDKQHEVEIPSPTQKEKEKKKRPMSQISGVKKLMHSSSLTNSSIPRFGVKTEQEDVLAKELEDVNKWGLHVFRIAELSGNRPLTVIMHTIFQERDLLKTFKIPVDTLITYLMTLEDHYHADVAYHNNIHAADVVQSTHVLLSTPALEAVFTDLEILAAIFASAIHDVDHPGVSNQFLINTNSELALMYNDSSVLENHHLAVGFKLLQEENCDIFQNLTKKQRQSLRKMVIDIVLATDMSKHMNLLADLKTMVETKKVTSSGVLLLDNYSDRIQVLQNMVHCADLSNPTKPLQLYRQWTDRIMEEFFRQGDRERERGMEISPMCDKHNASVEKSQVGFIDYIVHPLWETWADLVHPDAQDILDTLEDNREWYQSTIPQSPSPAPDDPEEGRQGQTEKFQFELTLEEDGESDTEKDSGSQVEEDTSCSDSKTLCTQDSESTEIPLDEQVEEEAVGEEEESQPEACVIDDRSPDT,7.761953896871204 +CC(C)c1ccc(OC2CN(Cc3nn4c(ncc4c(=O)[nH]3)C3CCOCC3)C2)cc1,MGSGSSSYRPKAIYLDIDGRIQKVIFSKYCNSSDIMDLFCIATGLPRNTTISLLTTDDAMVSIDPTMPANSERTPYKVRPVAIKQLSAGVEDKRTTSRGQSAERPLRDRRVVGLEQPRREGAFESGQVEPRPREPQGCYQEGQRIPPEREELIQSVLAQVAEQFSRAFKINELKAEVANHLAVLEKRVELEGLKVVEIEKCKSDIKKMREELAARSSRTNCPCKYSFLDNHKKLTPRRDVPTYPKYLLSPETIEALRKPTFDVWLWEPNEMLSCLEHMYHDLGLVRDFSINPVTLRRWLFCVHDNYRNNPFHNFRHCFCVAQMMYSMVWLCSLQEKFSQTDILILMTAAICHDLDHPGYNNTYQINARTELAVRYNDISPLENHHCAVAFQILAEPECNIFSNIPPDGFKQIRQGMITLILATDMARHAEIMDSFKEKMENFDYSNEEHMTLLKMILIKCCDISNEVRPMEVAEPWVDCLLEEYFMQSDREKSEGLPVAPFMDRDKVTKATAQIGFIKFVLIPMFETVTKLFPMVEEIMLQPLWESRDRYEELKRIDDAMKELQKKTDSLTSGATEKSRERSRDVKNSEGDCA,6.872895201635192 +COc1cn(C(C)C(=O)Nc2ccc(cc2)C(O)=O)c(=O)cc1-c1cc(Cl)ccc1C#N,MIFLYQVVHFILFTSVSGECVTQLLKDTCFEGGDITTVFTPSAKYCQVVCTYHPRCLLFTFTAESPSEDPTRWFTCVLKDSVTETLPRVNRTAAISGYSFKQCSHQISACNKDIYVDLDMKGINYNSSVAKSAQECQERCTDDVHCHFFTYATRQFPSLEHRNICLLKHTQTGTPTRITKLDKVVSGFSLKSCALSNLACIRDIFPNTVFADSNIDSVMAPDAFVCGRICTHHPGCLFFTFFSQEWPKESQRNLCLLKTSESGLPSTRIKKSKALSGFSLQSCRHSIPVFCHSSFYHDTDFLGEELDIVAAKSHEACQKLCTNAVRCQFFTYTPAQASCNEGKGKCYLKLSSNGSPTKILHGRGGISGYTLRLCKMDNECTTKIKPRIVGGTASVRGEWPWQVTLHTTSPTQRHLCGGSIIGNQWILTAAHCFYGVESPKILRVYSGILNQSEIKEDTSFFGVQEIIIHDQYKMAESGYDIALLKLETTVNYTDSQRPICLPSKGDRNVIYTDCWVTGWGYRKLRDKIQNTLQKAKIPLVTNEECQKRYRGHKITHKMICAGYREGGKDACKGDSGGPLSCKHNEVWHLVGITSWGEGCAQRERPGVYTNVVEYVDWILEKTQAV,5.468521082957745 +O[C@H]1CCN(C1)C(=O)CN1CN(c2ccccc2)C2(CCN(CC2)C(=O)c2cnc3[nH]ncc3c2)C1=O,MRTLNTSAMDGTGLVVERDFSVRILTACFLSLLILSTLLGNTLVCAAVIRFRHLRSKVTNFFVISLAVSDLLVAVLVMPWKAVAEIAGFWPFGSFCNIWVAFDIMCSTASILNLCVISVDRYWAISSPFRYERKMTPKAAFILISVAWTLSVLISFIPVQLSWHKAKPTSPSDGNATSLAETIDNCDSSLSRTYAISSSVISFYIPVAIMIVTYTRIYRIAQKQIRRIAALERAAVHAKNCQTTTGNGKPVECSQPESSFKMSFKRETKVLKTLSVIMGVFVCCWLPFFILNCILPFCGSGETQPFCIDSNTFDVFVWFGWANSSLNPIIYAFNADFRKAFSTLLGCYRLCPATNNAIETVSINNNGAAMFSSHHEPRGSISKECNLVYLIPHAVGSSEDLKKEEAAGIARPLEKLSPALSVILDYDTDVSLEKIQPITQNGQHPT,5.817585347565446 +CC(NC(C)(C)C)C(=O)c1ccc(Cl)cc1,MSKSKCSVGLMSSVVAPAKEPNAVGPKEVELILVKEQNGVQLTSSTLTNPRQSPVEAQDRETWGKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPILKGVGFTVILISLYVGFFYNVIIAWALHYLFSSFTTELPWIHCNNSWNSPNCSDAHPGDSSGDSSGLNDTFGTTPAAEYFERGVLHLHQSHGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAIDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIVTTSINSLTSFSSGFVVFSFLGYMAQKHSVPIGDVAKDGPGLIFIIYPEAIATLPLSSAWAVVFFIMLLTLGIDSAMGGMESVITGLIDEFQLLHRHRELFTLFIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVGQFSDDIQQMTGQRPSLYWRLCWKLVSPCFLLFVVVVSIVTFRPPHYGAYIFPDWANALGWVIATSSMAMVPIYAAYKFCSLPGSFREKLAYAIAPEKDRELVDRGEVRQFTLRHWLKV,5.634699251362012 +N#Cc1cc(ccc1OCC1CC1)-c1ccnc2[nH]c(nc12)-c1ccc(cc1)N1CCOCC1,MQSTANYLWHTDDLLGQGATASVYKARNKKSGELVAVKVFNTTSYLRPREVQVREFEVLRKLNHQNIVKLFAVEETGGSRQKVLVMEYCSSGSLLSVLESPENAFGLPEDEFLVVLRCVVAGMNHLRENGIVHRDIKPGNIMRLVGEEGQSIYKLTDFGAARELDDDEKFVSVYGTEEYLHPDMYERAVLRKPQQKAFGVTVDLWSIGVTLYHAATGSLPFIPFGGPRRNKEIMYRITTEKPAGAIAGAQRRENGPLEWSYTLPITCQLSLGLQSQLVPILANILEVEQAKCWGFDQFFAETSDILQRVVVHVFSLSQAVLHHIYIHAHNTIAIFQEAVHKQTSVAPRHQEYLFEGHLCVLEPSVSAQHIAHTTASSPLTLFSTAIPKGLAFRDPALDVPKFVPKVDLQADYNTAKGVLGAGYQALRLARALLDGQELMFRGLHWVMEVLQATCRRTLEVARTSLLYLSSSLGTERFSSVAGTPEIQELKAAAELRSRLRTLAEVLSRCSQNITETQESLSSLNRELVKSRDQVHEDRSIQQIQCCLDKMNFIYKQFKKSRMRPGLGYNEEQIHKLDKVNFSHLAKRLLQVFQEECVQKYQASLVTHGKRMRVVHETRNHLRLVGCSVAACNTEAQGVQESLSKLLEELSHQLLQDRAKGAQASPPPIAPYPSPTRKDLLLHMQELCEGMKLLASDLLDNNRIIERLNRVPAPPDV,6.0 +O=C(CC1CC1)N1CCC(CC1)Oc1ccc(NC(=O)N2Cc3ccncc3C2)cc1,MNPAAEAEFNILLATDSYKVTHYKQYPPNTSKVYSYFECREKKTENSKLRKVKYEETVFYGLQYILNKYLKGKVVTKEKIQEAKDVYKEHFQDDVFNEKGWNYILEKYDGHLPIEIKAVPEGFVIPRGNVLFTVENTDPECYWLTNWIETILVQSWYPITVATNSREQKKILAKYLLETSGNLDGLEYKLHDFGYRGVSSQETAGIGASAHLVNFKGTDTVAGLALIKKYYGTKDPVPGYSVPAAEHSTITAWGKDHEKDAFEHIVTQFSSVPVSVVSDSYDIYNACEKIWGEDLRHLIVSRSTQAPLIIRPDSGNPLDTVLKVLEILGKKFPVTENSKGYKLLPPYLRVIQGDGVDINTLQEIVEGMKQKMWSIENIAFGSGGGLLQKLTRDLLNCSFKCSYVVTNGLGINVFKDPVADPNKRSKKGRLSLHRTPAGNFVTLEEGKGDLEEYGQDLLHTVFKNGKVTKSYSFDEIRKNAQLNIELEAAHH,7.71669877129645 +O=C(Nc1nc(nc2cn(nc12)-c1ccccc1)-c1ccccc1)c1cccs1,MPNNSTALSLANVTYITMEIFIGLCAIVGNVLVICVVKLNPSLQTTTFYFIVSLALADIAVGVLVMPLAIVVSLGITIHFYSCLFMTCLLLIFTHASIMSLLAIAVDRYLRVKLTVRYKRVTTHRRIWLALGLCWLVSFLVGLTPMFGWNMKLTSEYHRNVTFLSCQFVSVMRMDYMVYFSFLTWIFIPLVVMCAIYLDIFYIIRNKLSLNLSNSKETGAFYGREFKTAKSLFLVLFLFALSWLPLSIINCIIYFNGEVPQLVLYMGILLSHANSMMNPIVYAYKIKKFKETYLLILKACVVCHPSDSLDTSIEKNSE,8.229147988357855 +CC(C)(C)CC(=O)Nc1sc2CCCCc2c1C(=O)N1CCC(F)(F)CC1,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,8.327902142064282 +COc1c(Nc2cc(NC(=O)C3CC3)nc3[nH]c(CO)nc23)cccc1-c1ncn(C)n1,PGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASD,8.259637310505756 +Brc1cccc(NC(=O)CCN2CCCC2)c1,MRALLLLGFLLVSLESTLSIPPWEAPKEHKYKAEEHTVVLTVTGEPCHFPFQYHRQLYHKCTHKGRPGPQPWCATTPNFDQDQRWGYCLEPKKVKDHCSKHSPCQKGGTCVNMPSGPHCLCPQHLTGNHCQKEKCFEPQLLRFFHKNEIWYRTEQAAVARCQCKGPDAHCQRLASQACRTNPCLHGGRCLEVEGHRLCHCPVGYTGAFCDVDTKASCYDGRGLSYRGLARTTLSGAPCQPWASEATYRNVTAEQARNWGLGGHAFCRNPDNDIRPWCFVLNRDRLSWEYCDLAQCQTPTQAAPPTPVSPRLHVPLMPAQPAPPKPQPTTRTPPQSQTPGALPAKREQPPSLTRNGPLSCGQRLRKSLSSMTRVVGGLVALRGAHPYIAALYWGHSFCAGSLIAPCWVLTAAHCLQDRPAPEDLTVVLGQERRNHSCEPCQTLAVRSYRLHEAFSPVSYQHDLALLRLQEDADGSCALLSPYVQPVCLPSGAARPSETTLCQVAGWGHQFEGAEEYASFLQEAQVPFLSLERCSAPDVHGSSILPGMLCAGFLEGGTDACQGDSGGPLVCEDQAAERRLTLQGIISWGSGCGDRNKPGVYTDVAYYLAWIREHTVS,4.301029995663981 +CNC(=O)c1ccc(cc1F)-c1ccc2nnc(n2n1)C(F)(F)c1cc2cn(C)nc2cc1F,GDSDISSPLLQNTVHIDLSALNPELVQAVQHVVIGPSSLIVHFNEVIGRGHFGCVYHGTLLDNDGKKIHCAVKSLNRITDIGEVSQFLTEGIIMKDFSHPNVLSLLGICLRSEGSPLVVLPYMKHGDLRNFIRNETHNPTVKDLIGFGLQVAKGMKYLASKKFVHRDLAARNCMLDEKFTVKVADFGLARDMYDKEYYSVHNKTGAKLPVKWMALESLQTQKFTTKSDVWSFGVLLWELMTRGAPPYPDVNTFDITVYLLQGRRLLQPEYCPDPLYEVMLKCWHPKAEMRPSFSELVSRISAIFSTFIG,7.585026652029182 +CC1CN(CC(=O)NC2C3CC4CC2CC(C4)(C3)C(N)=O)S(=O)(=O)N(C1)c1ccc(cn1)C(F)(F)F,MAVMKNYLLPILVLFLAYYYYSTNEEFRPEMLQGKKVIVTGASKGIGREMAYHLSKMGAHVVLTARSEEGLQKVVSRCLELGAASAHYIAGTMEDMTFAEQFIVKAGKLMGGLDMLILNHITQTSLSLFHDDIHSVRRVMEVNFLSYVVMSTAALPMLKQSNGSIAVISSLAGKMTQPMIAPYSASKFALDGFFSTIRTELYITKVNVSITLCVLGLIDTETAMKEISGIINAQASPKEECALEIIKGTALRKSEVYYDKSPLTPILLGNPGRKIMEFFSLRYYNKDMFVSN,6.026872146400302 +Cc1ccncc1-c1cccc2n(CC(F)(F)F)cnc12,MWELVALLLLTLAYLFWPKRRCPGAKYPKSLLSLPLVGSLPFLPRHGHMHNNFFKLQKKYGPIYSVRMGTKTTVIVGHHQLAKEVLIKKGKDFSGRPQMATLDIASNNRKGIAFADSGAHWQLHRRLAMATFALFKDGDQKLEKIICQEISTLCDMLATHNGQSIDISFPVFVAVTNVISLICFNTSYKNGDPELNVIQNYNEGIIDNLSKDSLVDLVPWLKIFPNKTLEKLKSHVKIRNDLLNKILENYKEKFRSDSITNMLDTLMQAKMNSDNGNAGPDQDSELLSDNHILTTIGDIFGAGVETTTSVVKWTLAFLLHNPQVKKKLYEEIDQNVGFSRTPTISDRNRLLLLEATIREVLRLRPVAPMLIPHKANVDSSIGEFAVDKGTEVIINLWALHHNEKEWHQPDQFMPERFLNPAGTQLISPSVSYLPFGAGPRSCIGEILARQELFLIMAWLLQRFDLEVPDDGQLPSLEGIPKVVFLIDSFKVKIKVRQAWREAQAEGST,7.698970004336019 +CC(C)c1cccc(OCc2cccc(c2)N2C(N)=NC(N)=NC2(C)C)c1,MSRAAARFKIPMPETKADFAFPSLRAFSIVVALDMQHGIGDGESIPWRVPEDMTFFKNQTTLLRNKKPPTEKKRNAVVMGRKTWESVPVKFRPLKGRLNIVLSSKATVEELLAPLPEGQRAAAAQDVVVVNGGLAEALRLLARPLYCSSIETAYCVGGAQVYADAMLSPCIEKLQEVYLTRIYATAPACTRFFPFPPENAATAWDLASSQGRRKSEAEGLEFEICKYVPRNHEERQYLELIDRIMKTGIVKEDRTGVGTISLFGAQMRFSLRDNRLPLLTTKRVFWRGVCEELLWFLRGETSAQLLADKDIHIWDGNGSREFLDSRGLTENKEMDLGPVYGFQWRHFGADYKGFEANYDGEGVDQIKLIVETIKTNPNDRRLLVTAWNPCALQKMALPPCHLLAQFYVNTDTSELSCMLYQRSCDMGLGVPFNIASYALLTILIAKATGLRPGELVHTLGDAHVYRNHVDALKAQLERVPHAFPTLIFKEERQYLEDYELTDMEVIDYVPHPAIKMEMAV,6.7599502278873524 +COc1ccc(NC(=O)Cn2nnc(n2)-c2ccccc2NC(=O)c2cc(OC)cc(OC)c2)cc1,MEYHMEYSPNEVIKQEREVFVGKEKSGSKFKRKRSIFIVLTVSICFMFALMLFYFTRNENNKTLFTNSLSNNINDDYIINSLLKSESGKKFIVSKLEELISSYDKEKKMRTTGAEENNMNMNGIDDKDNKSVSFVNKKNGNLKVNNNNQVSYSNLFDTKFLMDNLETVNLFYIFLKENNKKYETSEEMQKRFIIFSENYRKIELHNKKTNSLYKRGMNKFGDLSPEEFRSKYLNLKTHGPFKTLSPPVSYEANYEDVIKKYKPADAKLDRIAYDWRLHGGVTPVKDQALCGSCWAFSSVGSVESQYAIRKKALFLFSEQELVDCSVKNNGCYGGYITNAFDDMIDLGGLCSQDDYPYVSNLPETCNLKRCNERYTIKSYVSIPDDKFKEALRYLGPISISIAASDDFAFYRGGFYDGECGAAPNHAVILVGYGMKDIYNEDTGRMEKFYYYIIKNSWGSDWGEGGYINLETDENGYKKTCSIGTEAYVPLLE,5.175874166083451 +C[C@@H](O)[C@@H]1NC(=O)[C@H](CCCCN)NC(=O)[C@@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](Cc2ccncc2)NC(=O)[C@H](Cc2ccccc2)NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@@H](CCCCNC(=O)[C@H](Cc2ccccc2)NC1=O)NC[C@H](Cc1ccc(O)cc1)NC(=O)CSC[C@@H]1C[C@H]2[C@@H](Cc3c[nH]c4cccc2c34)N(C)C1,MDMLHPSSVSTTSEPENASSAWPPDATLGNVSAGPSPAGLAVSGVLIPLVYLVVCVVGLLGNSLVIYVVLRHTASPSVTNVYILNLALADELFMLGLPFLAAQNALSYWPFGSLMCRLVMAVDGINQFTSIFCLTVMSVDRYLAVVHPTRSARWRTAPVARTVSAAVWVASAVVVLPVVVFSGVPRGMSTCHMQWPEPAAAWRAGFIIYTAALGFFGPLLVICLCYLLIVVKVRSAGRRVWAPSCQRRRRSERRVTRMVVAVVALFVLCWMPFYVLNIVNVVCPLPEEPAFFGLYFLVVALPYANSCANPILYGFLSYRFKQGFRRVLLRPSRRVRSQEPTVGPPEKTEEEDEEEEDGEESREGGKGKEMNGRVSQITQPGTSGQERPPSRVASKEQQLLPQEASTGEKSSTMRISYL,7.97469413473523 +Cc1c(OCC(=O)NCCN2CCOCC2)ccc2c3CCCc3c(=O)oc12,MSPNFKLQCHFILIFLTALRGESRYLELREAADYDPFLLFSANLKRELAGEQPYRRALRCLDMLSLQGQFTFTADRPQLHCAAFFISEPEEFITIHYDQVSIDCQGGDFLKVFDGWILKGEKFPSSQDHPLPSAERYIDFCESGLSRRSIRSSQNVAMIFFRVHEPGNGFTLTIKTDPNLFPCNVISQTPNGKFTLVVPHQHRNCSFSIIYPVVIKISDLTLGHVNGLQLKKSSAGCEGIGDFVELLGGTGLDPSKMTPLADLCYPFHGPAQMKVGCDNTVVRMVSSGKHVNRVTFEYRQLEPYELENPNGNSIGEFCLSGL,4.275724130399211 +Clc1ccccc1-n1[nH]c2c(c3ccccc3[nH]c2=O)c1=O,MSTMHLLTFALLFSCSFARAACDPKIVNIGAVLSTRKHEQMFREAVNQANKRHGSWKIQLNATSVTHKPNAIQMALSVCEDLISSQVYAILVSHPPTPNDHFTPTPVSYTAGFYRIPVLGLTTRMSIYSDKSIHLSFLRTVPPYSHQSSVWFEMMRVYNWNHIILLVSDDHEGRAAQKRLETLLEERESKAEKVLQFDPGTKNVTALLMEARELEARVIILSASEDDAATVYRAAAMLNMTGSGYVWLVGEREISGNALRYAPDGIIGLQLINGKNESAHISDAVGVVAQAVHELLEKENITDPPRGCVGNTNIWKTGPLFKRVLMSSKYADGVTGRVEFNEDGDRKFANYSIMNLQNRKLVQVGIYNGTHVIPNDRKIIWPGGETEKPRGYQMSTRLKIVTIHQEPFVYVKPTMSDGTCKEEFTVNGDPVKKVICTGPNDTSPGSPRHTVPQCCYGFCIDLLIKLARTMNFTYEVHLVADGKFGTQERVNNSNKKEWNGMMGELLSGQADMIVAPLTINNERAQYIEFSKPFKYQGLTILVKKEIPRSTLDSFMQPFQSTLWLLVGLSVHVVAVMLYLLDRFSPFGRFKVNSEEEEEDALTLSSAMWFSWGVLLNSGIGEGAPRSFSARILGMVWAGFAMIIVASYTANLAAFLVLDRPEERITGINDPRLRNPSDKFIYATVKQSSVDIYFRRQVELSTMYRHMEKHNYESAAEAIQAVRDNKLHAFIWDSAVLEFEASQKCDLVTTGELFFRSGFGIGMRKDSPWKQNVSLSILKSHENGFMEDLDKTWVRYQECDSRSNAPATLTFENMAGVFMLVAGGIVAGIFLIFIEIAYKRHKDARRKQMQLAFAAVNVWRKNLQDRKSGRAEPDPKKKATFRAITSTLASSFKRRRSSKDTSTGGGRGALQNQKDTVLPRRAIEREEGQLQLCSRHRES,6.212539525481585 +O=C(Nc1ccccc1C(=O)Nc1cccnc1)c1ccc(cc1)-n1ccccc1=O,MGRPLHLVLLSASLAGLLLLGESLFIRREQANNILARVTRANSFLEEMKKGHLERECMEETCSYEEAREVFEDSDKTNEFWNKYKDGDQCETSPCQNQGKCKDGLGEYTCTCLEGFEGKNCELFTRKLCSLDNGDCDQFCHEEQNSVVCSCARGYTLADNGKACIPTGPYPCGKQTLERRKRSVAQATSSSGEAPDSITWKPYDAADLDPTENPFDLLDFNQTQPERGDNNLTRIVGGQECKDGECPWQALLINEENEGFCGGTILSEFYILTAAHCLYQAKRFKVRVGDRNTEQEEGGEAVHEVEVVIKHNRFTKETYDFDIAVLRLKTPITFRMNVAPACLPERDWAESTLMTQKTGIVSGFGRTHEKGRQSTRLKMLEVPYVDRNSCKLSSSFIITQNMFCAGYDTKQEDACQGDSGGPHVTRFKDTYFVTGIVSWGEGCARKGKYGIYTKVTAFLKWIDRSMKTRGLPKAKSHAPEVITSSPLK,7.366531544420414 +CC(C)CCNCCN1CN(c2ccccc2)C2(CCN(CC2)C2CCC(C)(C)c3ccccc23)C1=O,MEPLFPAPFWEVIYGSHLQGNLSLLSPNHSLLPPHLLLNASHGAFLPLGLKVTIVGLYLAVCVGGLLGNCLVMYVILRHTKMKTATNIYIFNLALADTLVLLTLPFQGTDILLGFWPFGNALCKTVIAIDYYNMFTSTFTLTAMSVDRYVAICHPIRALDVRTSSKAQAVNVAIWALASVVGVPVAIMGSAQVEDEEIECLVEIPTPQDYWGPVFAICIFLFSFIVPVLVISVCYSLMIRRLRGVRLLSGSREKDRNLRRITRLVLVVVAVFVGCWTPVQVFVLAQGLGVQPSSETAVAILRFCTALGYVNSCLNPILYAFLDENFKACFRKFCCASALRRDVQVSDRVRSIAKDVALACKTSETVPRPA,9.397940008672037 +CC(C)[C@@H]1NC(=O)[C@@H](Cc2ccccc2)NC(=O)[C@H](CC(O)=O)NC(=O)CNC(=O)[C@H](CCCN=C(N)N)NC1=O,MPRAPAPLYACLLGLCALLPRLAGLNICTSGSATSCEECLLIHPKCAWCSKEDFGSPRSITSRCDLRANLVKNGCGGEIESPASSFHVLRSLPLSSKGSGSAGWDVIQMTPQEIAVNLRPGDKTTFQLQVRQVEDYPVDLYYLMDLSLSMKDDLDNIRSLGTKLAEEMRKLTSNFRLGFGSFVDKDISPFSYTAPRYQTNPCIGYKLFPNCVPSFGFRHLLPLTDRVDSFNEEVRKQRVSRNRDAPEGGFDAVLQAAVCKEKIGWRKDALHLLVFTTDDVPHIALDGKLGGLVQPHDGQCHLNEANEYTASNQMDYPSLALLGEKLAENNINLIFAVTKNHYMLYKNFTALIPGTTVEILDGDSKNIIQLIINAYNSIRSKVELSVWDQPEDLNLFFTATCQDGVSYPGQRKCEGLKIGDTASFEVSLEARSCPSRHTEHVFALRPVGFRDSLEVGVTYNCTCGCSVGLEPNSARCNGSGTYVCGLCECSPGYLGTRCECQDGENQSVYQNLCREAEGKPLCSGRGDCSCNQCSCFESEFGKIYGPFCECDNFSCARNKGVLCSGHGECHCGECKCHAGYIGDNCNCSTDISTCRGRDGQICSERGHCLCGQCQCTEPGAFGEMCEKCPTCPDACSTKRDCVECLLLHSGKPDNQTCHSLCRDEVITWVDTIVKDDQEAVLCFYKTAKDCVMMFTYVELPSGKSNLTVLREPECGNTPNAMTILLAVVGSILLVGLALLAIWKLLVTIHDRREFAKFQSERSRARYEMASNPLYRKPISTHTVDFTFNKFNKSYNGTVD,9.958607314841775 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+[I-].CC[N+](CC)(CC)CCCCOc1ccc(\C=C\c2ccccc2)cc1,MELGGPGAPRLLPPLLLLLGTGLLRASSHVETRAHAEERLLKKLFSGYNKWSRPVANISDVVLVRFGLSIAQLIDVDEKNQMMTTNVWVKQEWHDYKLRWDPADYENVTSIRIPSELIWRPDIVLYNNADGDFAVTHLTKAHLFHDGRVQWTPPAIYKSSCSIDVTFFPFDQQNCTMKFGSWTYDKAKIDLVNMHSRVDQLDFWESGEWVIVDAVGTYNTRKYECCAEIYPDITYAFVIRRLPLFYTINLIIPCLLISCLTVLVFYLPSECGEKITLCISVLLSLTVFLLLITEIIPSTSLVIPLIGEYLLFTMIFVTLSIVITVFVLNVHHRSPRTHTMPTWVRRVFLDIVPRLLLMKRPSVVKDNCRRLIESMHKMASAPRFWPEPEGEPPATSGTQSLHPPSPSFCVPLDVPAEPGPSCKSPSDQLPPQQPLEAEKASPHPSPGPCRPPHGTQAPGLAKARSLSVQHMSSPGEAVEGGVRCRSRSIQYCVPRDDAAPEADGQAAGALASRNTHSAELPPPDQPSPCKCTCKKEPSSVSPSATVKTRSTKAPPPHLPLSPALTRAVEGVQYIADHLKAEDTDFSVKEDWKYVAMVIDRIFLWMFIIVCLLGTVGLFLPPWLAGMI,5.522878745280337 +Brc1cccc(c1)-c1cnnc(NCc2ccccc2)c1,MWGLAGGRLFGIFSAPVLVAVVCCAQSVNDPGNMSFVKETVDKLLKGYDIRLRPDFGGPPVCVGMNIDIASIDMVSEVNMDYTLTMYFQQYWRDKRLAYSGIPLNLTLDNRVADQLWVPDTYFLNDKKSFVHGVTVKNRMIRLHPDGTVLYGLRITTTAACMMDLRRYPLDEQNCTLEIESYGYTTDDIEFYWRGGDKAVTGVERIELPQFSIVEHRLVSRNVVFATGAYPRLSLSFRLKRNIGYFILQTYMPSILITILSWVSFWINYDASAARVALGITTVLTMTTINTHLRETLPKIPYVKAIDMYLMGCFVFVFLALLEYAFVNYIFFGRGPQRQKKLAEKTAKAKNDRSKSESNRVDAHGNILLTSLEVHNEMNEVSGGIGDTRNSAISFDNSGIQYRKQSMPREGHGRFLGDRSLPHKKTHLRRRSSQLKIKIPDLTDVNAIDRWSRIVFPFTFSLFNLVYWLYYVN,7.721246399047171 +CNC(=O)[C@@H](NC(=O)c1cccc(n1)-c1cccc(F)c1)C(C)(C)C,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,7.892790030352131 +Fc1ccc2OCCc2c1CNc1ncc(Br)c2c(ncn12)C#N,MGQTGKKSEKGPVCWRKRVKSEYMRLRQLKRFRRADEVKSMFSSNRQKILERTEILNQEWKQRRIQPVHILTSVSSLRGTRECSVTSDLDFPTQVIPLKTLNAVASVPIMYSWSPLQQNFMVEDETVLHNIPYMGDEVLDQDGTFIEELIKNYDGKVHGDRECGFINDEIFVELVNALGQYNDDDDDDDGDDPEEREEKQKDLEDHRDDKESRPPRKFPSDKIFEAISSMFPDKGTAEELKEKYKELTEQQLPGALPPECTPNIDGPNAKSVQREQSLHSFHTLFCRRCFKYDCFLHPFHATPNTYKRKNTETALDNKPCGPQCYQHLEGAKEFAAALTAERIKTPPKRPGGRRRGRLPNNSSRPSTPTINVLESKDTDSDREAGTETGGENNDKEEEEKKDETSSSSEANSRCQTPIKMKPNIEPPENVEWSGAEASMFRVLIGTYYDNFCAIARLIGTKTCRQVYEFRVKESSIIAPAPAEDVDTPPRKKKRKHRLWAAHCRKIQLKKDGSSNHVYNYQPCDHPRQPCDSSCPCVIAQNFCEKFCQCSSECQNRFPGCRCKAQCNTKQCPCYLAVRECDPDLCLTCGAADHWDSKNVSCKNCSIQRGSKKHLLLAPSDVAGWGIFIKDPVQKNEFISEYCGEIISQDEADRRGKVYDKYMCSFLFNLNNDFVVDATRKGNKIRFANHSVNPNCYAKVMMVNGDHRIGIFAKRAIQTGEELFFDYRYSQADALKYVGIEREMEIP,7.061480274823508 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+Oc1cc(on1)[C@H]1C2CCC(CC2)[C@@H]1Nc1nc(ncc1F)-c1c[nH]c2ncc(F)cc12,MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGERLQIVNNTEGDWWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAENPRGTFLVRESETTKGAYCLSVSDFDNAKGLNVKHYKIRKLDSGGFYITSRTQFNSLQQLVAYYSKHADGLCHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWNGTTRVAIKTLKPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLLDFLKGETGKYLRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGLARLIEDNEYTARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMVNREVLDQVERGYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQYQPGENL,5.3979400086720375 +COc1ccc(Cl)c(c1)-c1ccc(cn1)[C@H]1C[C@@H]1N,MSNKCDVVVVGGGISGMAAAKLLHDSGLNVVVLEARDRVGGRTYTLRNQKVKYVDLGGSYVGPTQNRILRLAKELGLETYKVNEVERLIHHVKGKSYPFRGPFPPVWNPITYLDHNNFWRTMDDMGREIPSDAPWKAPLAEEWDNMTMKELLDKLCWTESAKQLATLFVNLCVTAETHEVSALWFLWYVKQCGGTTRIISTTNGGQERKFVGGSGQVSERIMDLLGDRVKLERPVIYIDQTRENVLVETLNHEMYEAKYVISAIPPTLGMKIHFNPPLPMMRNQMITRVPLGSVIKCIVYYKEPFWRKKDYCGTMIIDGEEAPVAYTLDDTKPEGNYAAIMGFILAHKARKLARLTKEERLKKLCELYAKVLGSLEALEPVHYEEKNWCEEQYSGGCYTTYFPPGILTQYGRVLRQPVDRIYFAGTETATHWSGYMEGAVEAGERAAREILHAMGKIPEDEIWQSEPESVDVPAQPITTTFLERHLPSVPGLLRLIGLTTIFSATALGFLAHKRGLLVRV,6.0 +CNc1ccc(CNC(=O)c2ccnc(Cc3ccc4ncc(Cl)cc4c3)c2)c(C)n1,MILFKQATYFISLFATVSCGCLTQLYENAFFRGGDVASMYTPNAQYCQMRCTFHPRCLLFSFLPASSINDMEKRFGCFLKDSVTGTLPKVHRTGAVSGHSLKQCGHQISACHRDIYKGVDMRGVNFNVSKVSSVEECQKRCTNNIRCQFFSYATQTFHKAEYRNNCLLKYSPGGTPTAIKVLSNVESGFSLKPCALSEIGCHMNIFQHLAFSDVDVARVLTPDAFVCRTICTYHPNCLFFTFYTNVWKIESQRNVCLLKTSESGTPSSSTPQENTISGYSLLTCKRTLPEPCHSKIYPGVDFGGEELNVTFVKGVNVCQETCTKMIRCQFFTYSLLPEDCKEEKCKCFLRLSMDGSPTRIAYGTQGSSGYSLRLCNTGDNSVCTTKTSTRIVGGTNSSWGEWPWQVSLQVKLTAQRHLCGGSLIGHQWVLTAAHCFDGLPLQDVWRIYSGILNLSDITKDTPFSQIKEIIIHQNYKVSEGNHDIALIKLQAPLNYTEFQKPICLPSKGDTSTIYTNCWVTGWGFSKEKGEIQNILQKVNIPLVTNEECQKRYQDYKITQRMVCAGYKEGGKDACKGDSGGPLVCKHNGMWRLVGITSWGEGCARREQPGVYTKVAEYMDWILEKTQSSDGKAQMQSPA,6.259637310505756 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+CCCNC(=O)N(CCCN1[C@H]2CC[C@@H]1C[C@@H](C2)n1c(C)nnc1C(C)C)c1ccccc1,MDYQVSSPIYDINYYTSEPCQKINVKQIAARLLPPLYSLVFIFGFVGNMLVILILINCKRLKSMTDIYLLNLAISDLFFLLTVPFWAHYAAAQWDFGNTMCQLLTGLYFIGFFSGIFFIILLTIDRYLAVVHAVFALKARTVTFGVVTSVITWVVAVFASLPGIIFTRSQKEGLHYTCSSHFPYSQYQFWKNFQTLKIVILGLVLPLLVMVICYSGILKTLLRCRNEKKRHRAVRLIFTIMIVYFLFWAPYNIVLLLNTFQEFFGLNNCSSSNRLDQAMQVTETLGMTHCCINPIIYAFVGEKFRNYLLVFFQKHIAKRFCKCCSIFQQEAPERASSVYTRSTGEQEISVGL,6.567030709125594 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+FC(F)(F)c1cccc(c1)N1C2=C(C(N(C(=O)NC3CCS(=N)(=O)CC3)C1=O)c1ccc(cc1)C#N)C(=O)CC2,MTLGRRLACLFLACVLPALLLGGTALASEIVGGRRARPHAWPFMVSLQLRGGHFCGATLIAPNFVMSAAHCVANVNVRAVRVVLGAHNLSRREPTRQVFAVQRIFENGYDPVNLLNDIVILQLNGSATINANVQVAQLPAQGRRLGNGVQCLAMGWGLLGRNRGIASVLQELNVTVVTSLCRRSNVCTLVRGRQAGVCFGDSGSPLVCNGLIHGIASFVRGGCASGLYPDAFAPVAQFVNWIDSIIQRSEDNPCPHPRDPDPASRTH,9.0 +Cn1cc(cn1)-c1ccc2cnc(NC(=O)c3ccc(OC4CCNCC4)cc3)cc2c1,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASTPTNATAASDANTGDRGQTNNAASASASNST,6.481486060122112 +O=C(COC(=O)c1cc(nc2ccccc12)-c1ccccc1)N1CCN(CC1)C(=O)c1ccco1,MANLRTQKRLAASVVGVGKRKVWLDPNETSEIAQANSRNAIRKLVKNGTIVKKAVTVHSKSRTRAHAQSKREGRHSGYGKRKGTREARLPSQVVWIRRLRVLRRLLAKYRDAGKIDKHLYHVLYKESKGNAFKHKRALVEHIIQAKADAQREKALNEEAEARRLKNRAARDRRAQRVAEKRDALLKEDA,5.410497203736236 +OC(=O)[C@H]1CNC[C@@H](CN\N=C\c2ccc(o2)-c2ccc(Cl)cc2[N+]([O-])=O)C1,MATDNSKVADGQISTEVSEAPVASDKPKTLVVKVQKKAGDLPDRDTWKGRFDFLMSCVGYAIGLGNVWRFPYLCGKNGGGAFLIPYFLTLIFAGVPLFLLECSLGQYTSIGGLGVWKLAPMFKGVGLAAAVLSFWLNIYYIVIISWAIYYLYNSFTTTLPWKQCDNPWNTDRCFSNYSLVNTTNMTSAVVEFWERNMHQMTDGLDKPGQIRWPLAITLAIAWVLVYFCIWKGVGWTGKVVYFSATYPYIMLIILFFRGVTLPGAKEGILFYITPNFRKLSDSEVWLDAATQIFFSYGLGLGSLIALGSYNSFHNNVYRDSIIVCCINSCTSMFAGFVIFSIVGFMAHVTKRSIADVAASGPGLAFLAYPEAVTQLPISPLWAILFFSMLLMLGIDSQFCTVEGFITALVDEYPRLLRNRRELFIAAVCIVSYLIGLSNITQGGIYVFKLFDYYSASGMSLLFLVFFECVSISWFYGVNRFYDNIQEMVGSRPCIWWKLCWSFFTPIIVAGVFLFSAVQMTPLTMGSYVFPKWGQGVGWLMALSSMVLIPGYMAYMFLTLKGSLKQRLQVMIQPSEDIVRPENGPEQPQAGSSASKEAYI,5.830031826003108 +COc1ccc(CNS(=O)(=O)c2ccc(cc2)N2C(=O)N[C@@H](CC(C)C)C2=O)cc1OC,MAERKGTAKVDFLKKIEKEIQQKWDTERVFEVNASNLEKQTSKGKYFVTFPYPYMNGRLHLGHTFSLSKCEFAVGYQRLKGKCCLFPFGLHCTGMPIKACADKLKREIELYGCPPDFPDEEEEEEETSVKTEDIIIKDKAKGKKSKAAAKAGSSKYQWGIMKSLGLSDEEIVKFSEAEHWLDYFPPLAIQDLKRMGLKVDWRRSFITTDVNPYYDSFVRWQFLTLRERNKIKFGKRYTIYSPKDGQPCMDHDRQTGEGVGPQEYTLLKLKVLEPYPSKLSGLKGKNIFLVAATLRPETMFGQTNCWVRPDMKYIGFETVNGDIFICTQKAARNMSYQGFTKDNGVVPVVKELMGEEILGASLSAPLTSYKVIYVLPMLTIKEDKGTGVVTSVPSDSPDDIAALRDLKKKQALRAKYGIRDDMVLPFEPVPVIEIPGFGNLSAVTICDELKIQSQNDREKLAEAKEKIYLKGFYEGIMLVDGFKGQKVQDVKKTIQKKMIDAGDALIYMEPEKQVMSRSSDECVVALCDQWYLDYGEENWKKQTSQCLKNLETFCEETRRNFEATLGWLQEHACSRTYGLGTHLPWDEQWLIESLSDSTIYMAFYTVAHLLQGGNLHGQAESPLGIRPQQMTKEVWDYVFFKEAPFPKTQIAKEKLDQLKQEFEFWYPVDLRVSGKDLVPNHLSYYLYNHVAMWPEQSDKWPTAVRANGHLLLNSEKMSKSTGNFLTLTQAIDKFSADGMRLALADAGDTVEDANFVEAMADAGILRLYTWVEWVKEMVANWDSLRSGPASTFNDRVFASELNAGIIKTDQNYEKMMFKEALKTGFFEFQAAKDKYRELAVEGMHRELVFRFIEVQTLLLAPFCPHLCEHIWTLLGKPDSIMNASWPVAGPVNEVLIHSSQYLMEVTHDLRLRLKNYMMPAKGKKTDKQPLQKPSHCTIYVAKNYPPWQHTTLSVLRKHFEANNGKLPDNKVIASELGSMPELKKYMKKVMPFVAMIKENLEKMGPRILDLQLEFDEKAVLMENIVYLTNSLELEHIEVKFASEAEDKIREDCCPGKPLNVFRIEPGVSVSLVNPQPSNGHFSTKIEIRQGDNCDSIIRRLMKMNRGIKDLSKVKLMRFDDPLLGPRRVPVLGKEYTEKTPISEHAVFNVDLMSKKIHLTENGIRVDIGDTIIYLVH,4.577902836868289 +CCOC(=O)C(CC)Cc1ccc(cc1)C(=O)NCc1ccccc1C(F)(F)F,MTLRAAVFDLDGVLALPAVFGVLGRTEEALALPRGLLNDAFQKGGPEGATTRLMKGEITLSQWIPLMEENCRKCSETAKVCLPKNFSIKEIFDKAISARKINRPMLQAALMLRKKGFTTAILTNTWLDDRAERDGLAQLMCELKMHFDFLIESCQVGMVKPEPQIYKFLLDTLKASPSEVVFLDDIGANLKPARDLGMVTILVQDTDTALKELEKVTGIQLLNTPAPLPTSCNPSDMSHGYVTVKPRVRLHFVELGSGPAVCLCHGFPESWYSWRYQIPALAQAGYRVLAMDMKGYGESSAPPEIEEYCMEVLCKEMVTFLDKLGLSQAVFIGHDWGGMLVWYMALFYPERVRAVASLNTPFIPANPNMSPLESIKANPVFDYQLYFQEPGVAEAELEQNLSRTFKSLFRASDESVLSMHKVCEAGGLFVNSPEEPSLSRMVTEEEIQFYVQQFKKSGFRGPLNWYRNMERNWKWACKSLGRKILIPALMVTAEKDFVLVPQMSQHMEDWIPHLKRGHIEDCGHWTQMDKPTEVNQILIKWLDSDARNPPVVSKM,7.356547323513812 +Nc1nc(N)c(c(CCCc2ccccc2)n1)-c1cccc(Cl)c1,MMEQVCDVFDIYAICACCKVESKNEGKKNEVFNNYTFRGLGNKGVLPWKCNSLDMKYFRAVTTYVNESKYEKLKYKRCKYLNKETVDNVNDMPNSKKLQNVVVMGRTNWESIPKKFKPLSNRINVILSRTLKKEDFDEDVYIINKVEDLIVLLGKLNYYKCFIIGGSVVYQEFLEKKLIKKIYFTRINSTYECDVFFPEINENEYQIISVSDVYTSNNTTLDFIIYKKTNNKMLNEQNCIKGEEKNNDMPLKNDDKDTCHMKKLTEFYKNVDKYKINYENDDDDEEEDDFVYFNFNKEKEEKNKNSIHPNDFQIYNSLKYKYHPEYQYLNIIYDIMMNGNKQSDRTGVGVLSKFGYIMKFDLSQYFPLLTTKKLFLRGIIEELLWFIRGETNGNTLLNKNVRIWEANGTREFLDNRKLFHREVNDLGPIYGFQWRHFGAEYTNMYDNYENKGVDQLKNIINLIKNDPTSRRILLCAWNVKDLDQMALPPCHILCQFYVFDGKLSCIMYQRSCDLGLGVPFNIASYSIFTHMIAQVCNLQPAQFIHVLGNAHVYNNHIDSLKIQLNRIPYPFPTLKLNPDIKNIEDFTISDFTIQNYVHHEKISMDMAA,8.3767507096021 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+CCN(CC)CCOc1ccc2c3ccc(OCCN(CC)CC)cc3s(=O)c2c1,MCGGRGGIWLALAAALLHVSLQGEFQRRLYKELVKNYNPLERPVANDSQPLTVYFSLSLLQIMDVDEKNQVLTTNIWLQMSWTDHYLQWNMSEYPGVKNVRFPDGQIWKPDILLYNSADERFDATFHTNVLVNASGHCQYLPPGIFKSSCYIDVRWFPFDVQQCKLKFGSWSYGGWSLDLQMQEADISSYIPNGEWDLMGIPGKRNEKFYECCKEPYPDVTYTVTMRRRTLYYGLNLLIPCVLISALALLVFLLPADSGEKISLGITVLLSLTVFMLLVAEIMPATSDSVPLIAQYFASTMIIVGLSVVVTVIVLRYHHHDPDGGKMPKWTRIILLNWCAWFLRMKRPGEDKVRPACQHKPRRCSLASVELSAGAGPPTSNGNLLYIGFRGLEGMHCAPTPDSGVVCGRLACSPTHDEHLMHGAHPSDGDPDLAKILEEVRYIANRFRCQDESEVICSEWKFAACVVDRLCLMAFSVFTIICTIGILMSAPNFVEAVSKDFA,6.161150909262744 +CN1CCC(CNc2ccc3ncc(-c4cccc(OC(F)(F)F)c4)n3n2)CC1,MLLSKINSLAHLRAAPCNDLHATKLAPGKEKEPLESQYQVGPLLGSGGFGSVYSGIRVSDNLPVAIKHVEKDRISDWGELPNGTRVPMEVVLLKKVSSGFSGVIRLLDWFERPDSFVLILERPEPVQDLFDFITERGALQEELARSFFWQVLEAVRHCHNCGVLHRDIKDENILIDLNRGELKLIDFGSGALLKDTVYTDFDGTRVYSPPEWIRYHRYHGRSAAVWSLGILLYDMVCGDIPFEHDEEIIRGQVFFRQRVSSECQHLIRWCLALRPSDRPTFEEIQNHPWMQDVLLPQETAEIHLHSLSPGPSK,8.154901959985743 +Cc1cccc(c1)-c1cnc(NC2=NC[C@@]3(CN4CCC3CC4)O2)nc1,MGSGPLSLPLALSPPRLLLLLLLSLLPVARASEAEHRLFERLFEDYNEIIRPVANVSDPVIIHFEVSMSQLVKVDEVNQIMETNLWLKQIWNDYKLKWNPSDYGGAEFMRVPAQKIWKPDIVLYNNAVGDFQVDDKTKALLKYTGEVTWIPPAIFKSSCKIDVTYFPFDYQNCTMKFGSWSYDKAKIDLVLIGSSMNLKDYWESGEWAIIKAPGYKHDIKYNCCEEIYPDITYSLYIRRLPLFYTINLIIPCLLISFLTVLVFYLPSDCGEKVTLCISVLLSLTVFLLVITETIPSTSLVIPLIGEYLLFTMIFVTLSIVITVFVLNVHYRTPTTHTMPSWVKTVFLNLLPRVMFMTRPTSNEGNAQKPRPLYGAELSNLNCFSRAESKGCKEGYPCQDGMCGYCHHRRIKISNFSANLTRSSSSESVDAVLSLSALSPEIKEAIQSVKYIAENMKAQNEAKEIQDDWKYVAMVIDRIFLWVFTLVCILGTAGLFLQPLMAREDA,4.0 +Nc1ccc(cn1)C#CCCN1CCC(=CC1)c1ccccc1,MASLSQLSSHLNYTCGAENSTGASQARPHAYYALSYCALILAIVFGNGLVCMAVLKERALQTTTNYLVVSLAVADLLVATLVMPWVVYLEVTGGVWNFSRICCDVFVTLDVMMCTASILNLCAISIDRYTAVVMPVHYQHGTGQSSCRRVALMITAVWVLAFAVSCPLLFGFNTTGDPTVCSISNPDFVIYSSVVSFYLPFGVTVLVYARIYVVLKQRRRKRILTRQNSQCNSVRPGFPQQTLSPDPAHLELKRYYSICQDTALGGPGFQERGGELKREEKTRNSLSPTIAPKLSLEVRKLSNGRLSTSLKLGPLQPRGVPLREKKATQMVAIVLGAFIVCWLPFFLTHVLNTHCQTCHVSPELYSATTWLGYVNSALNPVIYTTFNIEFRKAFLKILSC,8.154901959985743 +COc1cc2c(Nc3ccc(Cl)c(Cl)c3)ncnc2cc1OCc1noc(n1)C1CCCN1,MELRVLLCWASLAAALEETLLNTKLETADLKWVTFPQVDGQWEELSGLDEEQHSVRTYEVCDVQRAPGQAHWLRTGWVPRRGAVHVYATLRFTMLECLSLPRAGRSCKETFTVFYYESDADTATALTPAWMENPYIKVDTVAAEHLTRKRPGAEATGKVNVKTLRLGPLSKAGFYLAFQDQGACMALLSLHLFYKKCAQLTVNLTRFPETVPRELVVPVAGSCVVDAVPAPGPSPSLYCREDGQWAEQPVTGCSCAPGFEAAEGNTKCRACAQGTFKPLSGEGSCQPCPANSHSNTIGSAVCQCRVGYFRARTDPRGAPCTTPPSAPRSVVSRLNGSSLHLEWSAPLESGGREDLTYALRCRECRPGGSCAPCGGDLTFDPGPRDLVEPWVVVRGLRPDFTYTFEVTALNGVSSLATGPVPFEPVNVTTDREVPPAVSDIRVTRSSPSSLSLAWAVPRAPSGAVLDYEVKYHEKGAEGPSSVRFLKTSENRAELRGLKRGASYLVQVRARSEAGYGPFGQEHHSQTQLDESEGWREQLALIAGTAVVGVVLVLVVIVVAVLCLRKQSNGREAEYSDKHGQYLIGHGTKVYIDPFTYEDPNEAVREFAKEIDVSYVKIEEVIGAGEFGEVCRGRLKAPGKKESCVAIKTLKGGYTERQRREFLSEASIMGQFEHPNIIRLEGVVTNSMPVMILTEFMENGALDSFLRLNDGQFTVIQLVGMLRGIASGMRYLAEMSYVHRDLAARNILVNSNLVCKVSDFGLSRFLEENSSDPTYTSSLGGKIPIRWTAPEAIAFRKFTSASDAWSYGIVMWEVMSFGERPYWDMSNQDVINAIEQDYRLPPPPDCPTSLHQLMLDCWQKDRNARPRFPQVVSALDKMIRNPASLKIVARENGGASHPLLDQRQPHYSAFGSVGEWLRAIKMGRYEESFAAAGFGSFELVSQISAEDLLRIGVTLAGHQKKILASVQHMKSQAKPGTPGGTGGPAPQY,6.279840696594043 +Clc1ccc(CN2CCCC(C2)Nc2ccc3[nH]ncc3c2)cc1,MSRPPPTGKMPGAPETAPGDGAGASRQRKLEALIRDPRSPINVESLLDGLNSLVLDLDFPALRKNKNIDNFLNRYEKIVKKIRGLQMKAEDYDVVKVIGRGAFGEVQLVRHKASQKVYAMKLLSKFEMIKRSDSAFFWEERDIMAFANSPWVVQLFYAFQDDRYLYMVMEYMPGGDLVNLMSNYDVPEKWAKFYTAEVVLALDAIHSMGLIHRDVKPDNMLLDKHGHLKLADFGTCMKMDETGMVHCDTAVGTPDYISPEVLKSQGGDGFYGRECDWWSVGVFLYEMLVGDTPFYADSLVGTYSKIMDHKNSLCFPEDAEISKHAKNLICAFLTDREVRLGRNGVEEIRQHPFFKNDQWHWDNIRETAAPVVPELSSDIDSSNFDDIEDDKGDVETFPIPKAFVGNQLPFIGFTYYRENLLLSDSPSCRETDSIQSRKNEESQEIQKKLYTLEEHLSNEMQAKEELEQKCKSVNTRLEKTAKELEEEITLRKSVESALRQLEREKALLQHKNAEYQRKADHEADKKRNLENDVNSLKDQLEDLKKRNQNSQISTEKVNQLQRQLDETNALLRTESDTAARLRKTQAESSKQIQQLESNNRDLQDKNCLLETAKLKLEKEFINLQSALESERRDRTHGSEIINDLQGRICGLEEDLKNGKILLAKVELEKRQLQERFTDLEKEKSNMEIDMTYQLKVIQQSLEQEEAEHKATKARLADKNKIYESIEEAKSEAMKEMEKKLLEERTLKQKVENLLLEAEKRCSLLDCDLKQSQQKINELLKQKDVLNEDVRNLTLKIEQETQKRCLTQNDLKMQTQQVNTLKMSEKQLKQENNHLMEMKMNLEKQNAELRKERQDADGQMKELQDQLEAEQYFSTLYKTQVRELKEECEEKTKLGKELQQKKQELQDERDSLAAQLEITLTKADSEQLARSIAEEQYSDLEKEKIMKELEIKEMMARHKQELTEKDATIASLEETNRTLTSDVANLANEKEELNNKLKDVQEQLSRLKDEEISAAAIKAQFEKQLLTERTLKTQAVNKLAEIMNRKEPVKRGNDTDVRRKEKENRKLHMELKSEREKLTQQMIKYQKELNEMQAQIAEESQIRIELQMTLDSKDSDIEQLRSQLQALHIGLDSSSIGSGPGDAEADDGFPESRLEGWLSLPVRNNTKKFGWVKKYVIVSSKKILFYDSEQDKEQSNPYMVLDIDKLFHVRPVTQTDVYRADAKEIPRIFQILYANEGESKKEQEFPVEPVGEKSNYICHKGHEFIPTLYHFPTNCEACMKPLWHMFKPPPALECRRCHIKCHKDHMDKKEEIIAPCKVYYDISTAKNLLLLANSTEEQQKWVSRLVKKIPKKPPAPDPFARSSPRTSMKIQQNQSIRRPSRQLAPNKPS,7.958607314841775 +O=C(N[C@]12CC[C@](C1)(CCC2)C#Cc1ccccn1)c1cnccn1,MVLLLILSVLLLKEDVRGSAQSSERRVVAHMPGDIIIGALFSVHHQPTVDKVHERKCGAVREQYGIQRVEAMLHTLERINSDPTLLPNITLGCEIRDSCWHSAVALEQSIEFIRDSLISSEEEEGLVRCVDGSSSSFRSKKPIVGVIGPGSSSVAIQVQNLLQLFNIPQIAYSATSMDLSDKTLFKYFMRVVPSDAQQARAMVDIVKRYNWTYVSAVHTEGNYGESGMEAFKDMSAKEGICIAHSYKIYSNAGEQSFDKLLKKLTSHLPKARVVACFCEGMTVRGLLMAMRRLGLAGEFLLLGSDGWADRYDVTDGYQREAVGGITIKLQSPDVKWFDDYYLKLRPETNHRNPWFQEFWQHRFQCRLEGFPQENSKYNKTCNSSLTLKTHHVQDSKMGFVINAIYSMAYGLHNMQMSLCPGYAGLCDAMKPIDGRKLLESLMKTNFTGVSGDTILFDENGDSPGRYEIMNFKEMGKDYFDYINVGSWDNGELKMDDDEVWSKKSNIIRSVCSEPCEKGQIKVIRKGEVSCCWTCTPCKENEYVFDEYTCKACQLGSWPTDDLTGCDLIPVQYLRWGDPEPIAAVVFACLGLLATLFVTVVFIIYRDTPVVKSSSRELCYIILAGICLGYLCTFCLIAKPKQIYCYLQRIGIGLSPAMSYSALVTKTNRIARILAGSKKKICTKKPRFMSACAQLVIAFILICIQLGIIVALFIMEPPDIMHDYPSIREVYLICNTTNLGVVTPLGYNGLLILSCTFYAFKTRNVPANFNEAKYIAFTMYTTCIIWLAFVPIYFGSNYKIITMCFSVSLSATVALGCMFVPKVYIILAKPERNVRSAFTTSTVVRMHVGDGKSSSAASRSSSLVNLWKRRGSSGETLRYKDRRLAQHKSEIECFTPKGSMGNGGRATMSSSNGKSVTWAQNEKSSRGQHLWQRLSIHINKKENPNQTAVIKPFPKSTESRGLGAGAGAGGSAGGVGATGGAGCAGAGPGGPESPDAGPKALYDVAEAEEHFPAPARPRSPSPISTLSHRAGSASRTDDDVPSLHSEPVARSSSSQGSLMEQISSVVTRFTANISELNSMMLSTAAPSPGVGAPLCSSYLIPKEIQLPTTMTTFAEIQPLPAIEVTGGAQPAAGAQAAGDAARESPAAGPEAAAAKPDLEELVALTPPSPFRDSVDSGSTTPNSPVSESALCIPSSPKYDTLIIRDYTQSSSSL,8.18045606445813 +CC[C@H]1N(C2CCCC2)c2nc(Nc3ccc(cc3OC)C(=O)NC3CCN(C)CC3)ncc2N(C)C1=O,MSFFNFRKIFKLGSEKKKKQYEHVKRDLNPEDFWEIIGELGDGAFGKVYKAQNKETSVLAAAKVIDTKSEEELEDYMVEIDILASCDHPNIVKLLDAFYYENNLWILIEFCAGGAVDAVMLELERPLTESQIQVVCKQTLDALNYLHDNKIIHRDLKAGNILFTLDGDIKLADFGVSAKNTRTIQRRDSFIGTPYWMAPEVVMCETSKDRPYDYKADVWSLGITLIEMAEIEPPHHELNPMRVLLKIAKSEPPTLAQPSRWSSNFKDFLKKCLEKNVDARWTTSQLLQHPFVTVDSNKPIRELIAEAKAEVTEEVEDGKEEDEEEETENSLPIPASKRASSDLSIASSEEDKLSQNACILESVSEKTERSNSEDKLNSKILNEKPTTDEPEKAVEDINEHITDAQLEAMTELHDRTAVIKENEREKRPKLENLPDTEDQETVDINSVSEGKENNIMITLETNIEHNLKSEEEKDQEKQQMFENKLIKSEEIKDTILQTVDLVSQETGEKEANIQAVDSEVGLTKEDTQEKLGEDDKTQKDVISNTSDVIGTCEAADVAQKVDEDSAEDTQSNDGKEVVEVGQKLINKPMVGPEAGGTKEVPIKEIVEMNEIEEGKNKEQAINSSENIMDINEEPGTTEGEEITESSSTEEMEVRSVVADTDQKALGSEVQDASKVTTQIDKEKKEIPVSIKKEPEVTVVSQPTEPQPVLIPSININSDSGENKEEIGSLSKTETILPPESENPKENDNDSGTGSTADTSSIDLNLSISSFLSKTKDSGSISLQETRRQKKTLKKTRKFIVDGVEVSVTTSKIVTDSDSKTEELRFLRRQELRELRFLQKEEQRAQQQLNSKLQQQREQIFRRFEQEMMSKKRQYDQEIENLEKQQKQTIERLEQEHTNRLRDEAKRIKGEQEKELSKFQNMLKNRKKEVINEVEKAPKELRKELMKRRKEELAQSQHAQEQEFVQKQQQELDGSLKKIIQQQKAELANIERECLNNKQQLMRAREAAIWELEERHLQEKHQLLKQQLKDQYFMQRHQLLKRHEKETEQMQRYNQRLIEELKNRQTQERARLPKIQRSEAKTRMAMFKKSLRINSTATPDQDRDKIKQFAAQEEKRQKNERMAQHQKHENQMRDLQLQCEANVRELHQLQNEKCHLLVEHETQKLKELDEEHSQELKEWREKLRPRKKTLEEEFARKLQEQEVFFKMTGESECLNPSTQSRISKFYPIPSLHSTGS,5.3872161432802645 +CNC(=O)CN1CCN([C@@H](C)C1)c1ccc2[nH]c(c(C(C)C)c2n1)-c1cn2ncnc2c(C)c1C,MGFCRSALHPLSLLVQAIMLAMTLALGTLPAFLPCELQPHGLVNCNWLFLKSVPHFSMAAPRGNVTSLSLSSNRIHHLHDSDFAHLPSLRHLNLKWNCPPVGLSPMHFPCHMTIEPSTFLAVPTLEELNLSYNNIMTVPALPKSLISLSLSHTNILMLDSASLAGLHALRFLFMDGNCYYKNPCRQALEVAPGALLGLGNLTHLSLKYNNLTVVPRNLPSSLEYLLLSYNRIVKLAPEDLANLTALRVLDVGGNCRRCDHAPNPCMECPRHFPQLHPDTFSHLSRLEGLVLKDSSLSWLNASWFRGLGNLRVLDLSENFLYKCITKTKAFQGLTQLRKLNLSFNYQKRVSFAHLSLAPSFGSLVALKELDMHGIFFRSLDETTLRPLARLPMLQTLRLQMNFINQAQLGIFRAFPGLRYVDLSDNRISGASELTATMGEADGGEKVWLQPGDLAPAPVDTPSSEDFRPNCSTLNFTLDLSRNNLVTVQPEMFAQLSHLQCLRLSHNCISQAVNGSQFLPLTGLQVLDLSHNKLDLYHEHSFTELPRLEALDLSYNSQPFGMQGVGHNFSFVAHLRTLRHLSLAHNNIHSQVSQQLCSTSLRALDFSGNALGHMWAEGDLYLHFFQGLSGLIWLDLSQNRLHTLLPQTLRNLPKSLQVLRLRDNYLAFFKWWSLHFLPKLEVLDLAGNQLKALTNGSLPAGTRLRRLDVSCNSISFVAPGFFSKAKELRELNLSANALKTVDHSWFGPLASALQILDVSANPLHCACGAAFMDFLLEVQAAVPGLPSRVKCGSPGQLQGLSIFAQDLRLCLDEALSWDCFALSLLAVALGLGVPMLHHLCGWDLWYCFHLCLAWLPWRGRQSGRDEDALPYDAFVVFDKTQSAVADWVYNELRGQLEECRGRWALRLCLEERDWLPGKTLFENLWASVYGSRKTLFVLAHTDRVSGLLRASFLLAQQRLLEDRKDVVVLVILSPDGRRSRYVRLRQRLCRQSVLLWPHQPSGQRSFWAQLGMALTRDNHHFYNRNFCQGPTAE,4.301029995663981 +COC(=O)c1cccc(OCC(=O)Nc2ccc(cc2)-c2nc3cc(C)cc(C)c3o2)c1,MLAATVLTLALLGNAHACSKGTSHEAGIVCRITKPALLVLNHETAKVIQTAFQRASYPDITGEKAMMLLGQVKYGLHNIQISHLSIASSQVELVEAKSIDVSIQNVSVVFKGTLKYGYTTAWWLGIDQSIDFEIDSAIDLQINTQLTCDSGRVRTDAPDCYLSFHKLLLHLQGEREPGWIKQLFTNFISFTLKLVLKGQICKEINVISNIMADFVQTRAASILSDGDIGVDISLTGDPVITASYLESHHKGHFIYKNVSEDLPLPTFSPTLLGDSRMLYFWFSERVFHSLAKVAFQDGRLMLSLMGDEFKAVLETWGFNTNQEIFQEVVGGFPSQAQVTVHCLKMPKISCQNKGVVVNSSVMVKFLFPRPDQQHSVAYTFEEDIVTTVQASYSKKKLFLSLLDFQITPKTVSNLTESSSESVQSFLQSMITAVGIPEVMSRLEVVFTALMNSKGVSLFDIINPEIITRDGFLLLQMDFGFPEHLLVDFLQSLS,5.0 +Cc1cc(Cl)ccc1-n1ccc(n1)C(=O)N[C@H]1CCN(C1)c1nccn2cccc12,MDLHLFDYSEPGNFSDISWPCNSSDCIVVDTVMCPNMPNKSVLLYTLSFIYIFIFVIGMIANSVVVWVNIQAKTTGYDTHCYILNLAIADLWVVLTIPVWVVSLVQHNQWPMGELTCKVTHLIFSINLFGSIFFLTCMSVDRYLSITYFTNTPSSRKKMVRRVVCILVWLLAFCVSLPDTYYLKTVTSASNNETYCRSFYPEHSIKEWLIGMELVSVVLGFAVPFSIIAVFYFLLARAISASSDQEKHSSRKIIFSYVVVFLVCWLPYHVAVLLDIFSILHYIPFTCRLEHALFTALHVTQCLSLVHCCVNPVLYSFINRNYRYELMKAFIFKYSAKTGLTKLIDASRVSETEYSALEQSTK,6.301029995663981 +Nc1nc2cc(ccc2o1)-c1ccc2ncc(nc2c1)N1CCNC(=O)C1,MLGTGPAAATTAATTSSNVSVLQQFASGLKSRNEETRAKAAKELQHYVTMELREMSQEESTRFYDQLNHHIFELVSSSDANERKGGILAIASLIGVEGGNATRIGRFANYLRNLLPSNDPVVMEMASKAIGRLAMAGDTFTAEYVEFEVKRALEWLGADRNEGRRHAAVLVLRELAISVPTFFFQQVQPFFDNIFVAVWDPKQAIREGAVAALRACLILTTQREPKEMQKPQWYRHTFEEAEKGFDETLAKEKGMNRDDRIHGALLILNELVRISSMEGERLREEMEEITQQQLVHDKYCKDLMGFGTKPRHITPFTSFQAVQPQQSNALVGLLGYSSHQGLMGFGTSPSPAKSTLVESRCCRDLMEEKFDQVCQWVLKCRNSKNSLIQMTILNLLPRLAAFRPSAFTDTQYLQDTMNHVLSCVKKEKERTAAFQALGLLSVAVRSEFKVYLPRVLDIIRAALPPKDFAHKRQKAMQVDATVFTCISMLARAMGPGIQQDIKELLEPMLAVGLSPALTAVLYDLSRQIPQLKKDIQDGLLKMLSLVLMHKPLRHPGMPKGLAHQLASPGLTTLPEASDVGSITLALRTLGSFEFEGHSLTQFVRHCADHFLNSEHKEIRMEAARTCSRLLTPSIHLISGHAHVVSQTAVQVVADVLSKLLVVGITDPDPDIRYCVLASLDERFDAHLAQAENLQALFVALNDQVFEIRELAICTVGRLSSMNPAFVMPFLRKMLIQILTELEHSGIGRIKEQSARMLGHLVSNAPRLIRPYMEPILKALILKLKDPDPDPNPGVINNVLATIGELAQVSGLEMRKWVDELFIIIMDMLQDSSLLAKRQVALWTLGQLVASTGYVVEPYRKYPTLLEVLLNFLKTEQNQGTRREAIRVLGLLGALDPYKHKVNIGMIDQSRDASAVSLSESKSSQDSSDYSTSEMLVNMGNLPLDEFYPAVSMVALMRIFRDQSLSHHHTMVVQAITFIFKSLGLKCVQFLPQVMPTFLNVIRVCDGAIREFLFQQLGMLVSFVKSHIRPYMDEIVTLMREFWVMNTSIQSTIILLIEQIVVALGGEFKLYLPQLIPHMLRVFMHDNSPGRIVSIKLLAAIQLFGANLDDYLHLLLPPIVKLFDAPEAPLPSRKAALETVDRLTESLDFTDYASRIIHPIVRTLDQSPELRSTAMDTLSSLVFQLGKKYQIFIPMVNKVLVRHRINHQRYDVLICRIVKGYTLADEEEDPLIYQHRMLRSGQGDALASGPVETGPMKKLHVSTINLQKAWGAARRVSKDDWLEWLRRLSLELLKDSSSPSLRSCWALAQAYNPMARDLFNAAFVSCWSELNEDQQDELIRSIELALTSQDIAEVTQTLLNLAEFMEHSDKGPLPLRDDNGIVLLGERAAKCRAYAKALHYKELEFQKGPTPAILESLISINNKLQQPEAAAGVLEYAMKHFGELEIQATWYEKLHEWEDALVAYDKKMDTNKDDPELMLGRMRCLEALGEWGQLHQQCCEKWTLVNDETQAKMARMAAAAAWGLGQWDSMEEYTCMIPRDTHDGAFYRAVLALHQDLFSLAQQCIDKARDLLDAELTAMAGESYSRAYGAMVSCHMLSELEEVIQYKLVPERREIIRQIWWERLQGCQRIVEDWQKILMVRSLVVSPHEDMRTWLKYASLCGKSGRLALAHKTLVLLLGVDPSRQLDHPLPTVHPQVTYAYMKNMWKSARKIDAFQHMQHFVQTMQQQAQHAIATEDQQHKQELHKLMARCFLKLGEWQLNLQGINESTIPKVLQYYSAATEHDRSWYKAWHAWAVMNFEAVLHYKHQNQARDEKKKLRHASGANITNATTAATTAATATTTASTEGSNSESEAESTENSPTPSPLQKKVTEDLSKTLLMYTVPAVQGFFRSISLSRGNNLQDTLRVLTLWFDYGHWPDVNEALVEGVKAIQIDTWLQVIPQLIARIDTPRPLVGRLIHQLLTDIGRYHPQALIYPLTVASKSTTTARHNAANKILKNMCEHSNTLVQQAMMVSEELIRVAILWHEMWHEGLEEASRLYFGERNVKGMFEVLEPLHAMMERGPQTLKETSFNQAYGRDLMEAQEWCRKYMKSGNVKDLTQAWDLYYHVFRRISKQLPQLTSLELQYVSPKLLMCRDLELAVPGTYDPNQPIIRIQSIAPSLQVITSKQRPRKLTLMGSNGHEFVFLLKGHEDLRQDERVMQLFGLVNTLLANDPTSLRKNLSIQRYAVIPLSTNSGLIGWVPHCDTLHALIRDYREKKKILLNIEHRIMLRMAPDYDHLTLMQKVEVFEHAVNNTAGDDLAKLLWLKSPSSEVWFDRRTNYTRSLAVMSMVGYILGLGDRHPSNLMLDRLSGKILHIDFGDCFEVAMTREKFPEKIPFRLTRMLTNAMEVTGLDGNYRITCHTVMEVLREHKDSVMAVLEAFVYDPLLNWRLMDTNTKGNKRSRTRTDSYSAGQSVEILDGVELGEPAHKKTGTTVPESIHSFIGDGLVKPEALNKKAIQIINRVRDKLTGRDFSHDDTLDVPTQVELLIKQATSHENLCQCYIGWCPFW,5.0 +C[C@@H](CNc1cc(C)cc2n(ncc12)-c1cccc(NC2CC2)c1)NS(=O)(=O)c1c(C)cc(C)cc1C,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,9.500312917381596 +OCCn1cc(c(n1)-c1ccncc1)-c1ccc2C(CCc2c1)N=O,MARENGESSSSWKKQAEDIKKIFEFKETLGTGAFSEVVLAEEKATGKLFAVKCIPKKALKGKESSIENEIAVLRKIKHENIVALEDIYESPNHLYLVMQLVSGGELFDRIVEKGFYTEKDASTLIRQVLDAVYYLHRMGIVHRDLKPENLLYYSQDEESKIMISDFGLSKMEGKGDVMSTACGTPGYVAPEVLAQKPYSKAVDCWSIGVIAYILLCGYPPFYDENDSKLFEQILKAEYEFDSPYWDDISDSAKDFIRNLMEKDPNKRYTCEQAARHPWIAGDTALNKNIHESVSAQIRKNFAKSKWRQAFNATAVVRHMRKLHLGSSLDSSNASVSSSLSLASQKDCLAPSTLCSFISSSSGVSGVGAERRPRPTTVTAVHSGSK,5.0 +CCCCCCCC(=O)OC(CNC(=O)ON=C1CCCCC1)COC,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,6.0 +FC(F)Oc1ccccc1CC(N1CCNCC1)c1cccc(F)c1,METTPLNSQKQLSACEDGEDCQENGVLQKVVPTPGDKVESGQISNGYSAVPSPGAGDDTRHSIPATTTTLVAELHQGERETWGKKVDFLLSVIGYAVDLGNVWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIMAWALYYLISSFTDQLPWTSCKNSWNTGNCTNYFSEDNITWTLHSTSPAEEFYTRHVLQIHRSKGLQDLGGISWQLALCIMLIFTVIYFSIWKGVKTSGKVVWVTATFPYIILSVLLVRGATLPGAWRGVLFYLKPNWQKLLETGVWIDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHVWAKRRERFVLAVVITCFFGSLVTLTFGGAYVVKLLEEYATGPAVLTVALIEAVAVSWFYGITQFCRDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPYWSIILGYCIGTSSFICIPTYIAYRLIITPGTFKERIIKSITPETPTEIPCGDIRLNAV,7.920818753952375 +CCNS(=O)(=O)c1ccccc1Nc1nc(Nc2ccc(N3CCC(CC3)N3CCN(C)CC3)c(OC)c2)ncc1NC(=O)c1cc(OC)ccc1OC,MGAPACALALCVAVAIVAGASSESLGTEQRVVGRAAEVPGPEPGQQEQLVFGSGDAVELSCPPPGGGPMGPTVWVKDGTGLVPSERVLVGPQRLQVLNASHEDSGAYSCRQRLTQRVLCHFSVRVTDAPSSGDDEDGEDEAEDTGVDTGAPYWTRPERMDKKLLAVPAANTVRFRCPAAGNPTPSISWLKNGREFRGEHRIGGIKLRHQQWSLVMESVVPSDRGNYTCVVENKFGSIRQTYTLDVLERSPHRPILQAGLPANQTAVLGSDVEFHCKVYSDAQPHIQWLKHVEVNGSKVGPDGTPYVTVLKTAGANTTDKELEVLSLHNVTFEDAGEYTCLAGNSIGFSHHSAWLVVLPAEEELVEADEAGSVYAGILSYGVGFFLFILVVAAVTLCRLRSPPKKGLGSPTVHKISRFPLKRQVSLESNASMSSNTPLVRIARLSSGEGPTLANVSELELPADPKWELSRARLTLGKPLGEGCFGQVVMAEAIGIDKDRAAKPVTVAVKMLKDDATDKDLSDLVSEMEMMKMIGKHKNIINLLGACTQGGPLYVLVEYAAKGNLREFLRARRPPGLDYSFDTCKPPEEQLTFKDLVSCAYQVARGMEYLASQKCIHRDLAARNVLVTEDNVMKIADFGLARDVHNLDYYKKTTNGRLPVKWMAPEALFDRVYTHQSDVWSFGVLLWEIFTLGGSPYPGIPVEELFKLLKEGHRMDKPANCTHDLYMIMRECWHAAPSQRPTFKQLVEDLDRVLTVTSTDEYLDLSAPFEQYSPGGQDTPSSSSSGDDSVFAHDLLPPAPPSSGGSRT,7.267606240177031 +OCC1CCC(O1)n1cnc2c(NC3CCCCCCC3)cc(Cl)nc12,MAQTPAFNKPKVELHVHLDGAIKPETILYYGRKRGIALPADTPEELQNIIGMDKPLSLPEFLAKFDYYMPAIAGCREAVKRIAYEFVEMKAKDGVVYVEVRYSPHLLANSKVEPIPWNQAEGDLTPDEVVSLVNQGLQEGERDFGVKVRSILCCMRHQPSWSSEVVELCKKYREQTVVAIDLAGDETIEGSSLFPGHVKAYAEAVKSGVHRTVHAGEVGSANVVKEAVDTLKTERLGHGYHTLEDATLYNRLRQENMHFEVCPWSSYLTGAWKPDTEHPVVRFKNDQVNYSLNTDDPLIFKSTLDTDYQMTKNEMGFTEEEFKRLNINAAKSSFLPEDEKKELLDLLYKAYGMPSPASAEQCL,4.0 +C(Oc1cc(nc2c(nccc12)-c1ccn[nH]1)N1CCOCC1)C1CCCO1,MGEHGLELASMIPALRELGSATPEEYNTVVQKPRQILCQFIDRILTDVNVVAVELVKKTDSQPTSVMLLDFIQHIMKSSPLMFVNVSGSHEAKGSCIEFSNWIITRLLRIAATPSCHLLHKKICEVICSLLFLFKSKSPAIFGVLTKELLQLFEDLVYLHRRNVMGHAVEWPVVMSRFLSQLDEHMGYLQSAPLQLMSMQNLEFIEVTLLMVLTRIIAIVFFRRQELLLWQIGCVLLEYGSPKIKSLAISFLTELFQLGGLPAQPASTFFSSFLELLKHLVEMDTDQLKLYEEPLSKLIKTLFPFEAEAYRNIEPVYLNMLLEKLCVMFEDGVLMRLKSDLLKAALCHLLQYFLKFVPAGYESALQVRKVYVRNICKALLDVLGIEVDAEYLLGPLYAALKMESMEIIEEIQCQTQQENLSSNSDGISPKRRRLSSSLNPSKRAPKQTEEIKHVDMNQKSILWSALKQKAESLQISLEYSGLKNPVIEMLEGIAVVLQLTALCTVHCSHQNMNCRTFKDCQHKSKKKPSVVITWMSLDFYTKVLKSCRSLLESVQKLDLEATIDKVVKIYDALIYMQVNSSFEDHILEDLCGMLSLPWIYSHSDDGCLKLTTFAANLLTLSCRISDSYSPQAQSRCVFLLTLFPRRIFLEWRTAVYNWALQSSHEVIRASCVSGFFILLQQQNSCNRVPKILIDKVKDDSDIVKKEFASILGQLVCTLHGMFYLTSSLTEPFSEHGHVDLFCRNLKATSQHECSSSQLKASVCKPFLFLLKKKIPSPVKLAFIDNLHHLCKHLDFREDETDVKAVLGTLLNLMEDPDKDVRVAFSGNIKHILESLDSEDGFIKELFVLRMKEAYTHAQISRNNELKDTLILTTGDIGRAAKGDLVPFALLHLLHCLLSKSASVSGAAYTEIRALVAAKSVKLQSFFSQYKKPICQFLVESLHSSQMTALPNTPCQNADVRKQDVAHQREMALNTLSEIANVFDFPDLNRFLTRTLQVLLPDLAAKASPAASALIRTLGKQLNVNRREILINNFKYIFSHLVCSCSKDELERALHYLKNETEIELGSLLRQDFQGLHNELLLRIGEHYQQVFNGLSILASFASSDDPYQGPRDIISPELMADYLQPKLLGILAFFNMQLLSSSVGIEDKKMALNSLMSLMKLMGPKHVSSVRVKMMTTLRTGLRFKDDFPELCCRAWDCFVRCLDHACLGSLLSHVIVALLPLIHIQPKETAAIFHYLIIENRDAVQDFLHEIYFLPDHPELKKIKAVLQEYRKETSESTDLQTTLQLSMKAIQHENVDVRIHALTSLKETLYKNQEKLIKYATDSETVEPIISQLVTVLLKGCQDANSQARLLCGECLGELGAIDPGRLDFSTTETQGKDFTFVTGVEDSSFAYGLLMELTRAYLAYADNSRAQDSAAYAIQELLSIYDCREMETNGPGHQLWRRFPEHVREILEPHLNTRYKSSQKSTDWSGVKKPIYLSKLGSNFAEWSASWAGYLITKVRHDLASKIFTCCSIMMKHDFKVTIYLLPHILVYVLLGCNQEDQQEVYAEIMAVLKHDDQHTINTQDIASDLCQLSTQTVFSMLDHLTQWARHKFQALKAEKCPHSKSNRNKVDSMVSTVDYEDYQSVTRFLDLIPQDTLAVASFRSKAYTRAVMHFESFITEKKQNIQEHLGFLQKLYAAMHEPDGVAGVSAIRKAEPSLKEQILEHESLGLLRDATACYDRAIQLEPDQIIHYHGVVKSMLGLGQLSTVITQVNGVHANRSEWTDELNTYRVEAAWKLSQWDLVENYLAADGKSTTWSVRLGQLLLSAKKRDITAFYDSLKLVRAEQIVPLSAASFERGSYQRGYEYIVRLHMLCELEHSIKPLFQHSPGDSSQEDSLNWVARLEMTQNSYRAKEPILALRRALLSLNKRPDYNEMVGECWLQSARVARKAGHHQTAYNALLNAGESRLAELYVERAKWLWSKGDVHQALIVLQKGVELCFPENETPPEGKNMLIHGRAMLLVGRFMEETANFESNAIMKKYKDVTACLPEWEDGHFYLAKYYDKLMPMVTDNKMEKQGDLIRYIVLHFGRSLQYGNQFIYQSMPRMLTLWLDYGTKAYEWEKAGRSDRVQMRNDLGKINKVITEHTNYLAPYQFLTAFSQLISRICHSHDEVFVVLMEIIAKVFLAYPQQAMWMMTAVSKSSYPMRVNRCKEILNKAIHMKKSLEKFVGDATRLTDKLLELCNKPVDGSSSTLSMSTHFKMLKKLVEEATFSEILIPLQSVMIPTLPSILGTHANHASHEPFPGHWAYIAGFDDMVEILASLQKPKKISLKGSDGKFYIMMCKPKDDLRKDCRLMEFNSLINKCLRKDAESRRRELHIRTYAVIPLNDECGIIEWVNNTAGLRPILTKLYKEKGVYMTGKELRQCMLPKSAALSEKLKVFREFLLPRHPPIFHEWFLRTFPDPTSWYSSRSAYCRSTAVMSMVGYILGLGDRHGENILFDSLTGECVHVDFNCLFNKGETFEVPEIVPFRLTHNMVNGMGPMGTEGLFRRACEVTMRLMRDQREPLMSVLKTFLHDPLVEWSKPVKGHSKAPLNETGEVVNEKAKTHVLDIEQRLQGVIKTRNRVTGLPLSIEGHVHYLIQEATDENLLCQMYLGWTPYM,6.581698708680254 +CCOc1ccc2noc3-c4ccccc4C(=O)c1c23,MIDTLRPVPFASEMAISKTVAWLNEQLELGNEQLLLMDCRPQELYESSHIESAINVAIPGIMLRRLQKGNLPVRALFTRCEDRDRFTRRCGTDTVVLYDENSSDWNENTGGESVLGLLLKKLKDEGCRAFYLEGGFSKFQAEFALHCETNLDGSCSSSSPPLPVLGLGGLRISSDSSSDIESDLDRDPNSATDSDGSPLSNSQPSFPVEILPFLYLGCAKDSTNLDVLEEFGIKYILNVTPNLPNLFENAGEFKYKQIPISDHWSQNLSQFFPEAISFIDEARGKNCGVLVHCLAGISRSVTVTVAYLMQKLNLSMNDAYDIVKMKKSNISPNFNFMGQLLDFERTLGLSSPCDNRVPAQQLYFTAPSNQNVYQVDSLQST,4.945272067917802 +Cc1ccc(cc1)-c1c(C)c2CN(Cc3ccc(F)cc3)Cc2c(C)c1[C@H](OC(C)(C)C)C(O)=O,FLDGIDKAQDEHEKYHSNWRAMASDFNLPPVVAKEIVASCDKCQLKGEAMHGQVDCSPGIWQLDCTHLEGKVILVAVHVASGYIEAEVIPAETGQETAYFLLKLAGRWPVKTIHTDNGSNFTSTTVKAACWWAGIKQEFGIPYNPQSQGVVESMNKELKKIIGQVRDQAEHLKTAVQMAVFIHNFKRKGGIGGYSAGERIVDIIATDIQTKELQKQITKIQNFRVYYRDSRDPLWKGPAKLLWKGEGAVVIQDNSDIKVVPRRKVKIIRDYGKQMAGDDCVASRQDED,7.443697499232712 +COc1cc(ccc1O[C@H]1CCOC1)-c1cc2ncccc2c(OC[C@H]2CNC(=O)C2)n1,MASSGMADSANHLPFFFGNITREEAEDYLVQGGMSDGLYLLRQSRNYLGGFALSVAHGRKAHHYTIERELNGTYAIAGGRTHASPADLCHYHSQESDGLVCLLKKPFNRPQGVQPKTGPFEDLKENLIREYVKQTWNLQGQALEQAIISQKPQLEKLIATTAHEKMPWFHGKISREESEQIVLIGSKTNGKFLIRARDNNGSYALCLLHEGKVLHYRIDKDKTGKLSIPEGKKFDTLWQLVEHYSYKADGLLRVLTVPCQKIGTQGNVNFGGRPQLPGSHPATWSAGGIISRIKSYSFPKPGHRKSSPAQGNRQESTVSFNPYEPELAPWAADKGPQREALPMDTEVYESPYADPEEIRPKEVYLDRKLLTLEDKELGSGNFGTVKKGYYQMKKVVKTVAVKILKNEANDPALKDELLAEANVMQQLDNPYIVRMIGICEAESWMLVMEMAELGPLNKYLQQNRHVKDKNIIELVHQVSMGMKYLEESNFVHRDLAARNVLLVTQHYAKISDFGLSKALRADENYYKAQTHGKWPVKWYAPECINYYKFSSKSDVWSFGVLMWEAFSYGQKPYRGMKGSEVTAMLEKGERMGCPAGCPREMYDLMNLCWTYDVENRPGFAAVELRLRNYYYDVVN,8.853871964321762 +CC1CNc2c(C1)cccc2S(=O)(=O)NC(CCCNC(N)=N)C(=O)N1CCC(CCOC(=O)CCC(O)=O)CC1,MARVRGPRLPGCLALAALFSLVHSQHVFLAHQQASSLLQRARRANKGFLEEVRKGNLERECLEEPCSREEAFEALESLSATDAFWAKYTACESARNPREKLNECLEGNCAEGVGMNYRGNVSVTRSGIECQLWRSRYPHKPEINSTTHPGADLRENFCRNPDGSITGPWCYTTSPTLRREECSVPVCGQDRVTVEVIPRSGGSTTSQSPLLETCVPDRGREYRGRLAVTTSGSRCLAWSSEQAKALSKDQDFNPAVPLAENFCRNPDGDEEGAWCYVADQPGDFEYCDLNYCEEPVDGDLGDRLGEDPDPDAAIEGRTSEDHFQPFFNEKTFGAGEADCGLRPLFEKKQVQDQTEKELFESYIEGRIVEGQDAEVGLSPWQVMLFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTVDDLLVRIGKHSRTRYERKVEKISMLDKIYIHPRYNWKENLDRDIALLKLKRPIELSDYIHPVCLPDKQTAAKLLHAGFKGRVTGWGNRRETWTTSVAEVQPSVLQVVNLPLVERPVCKASTRIRITDNMFCAGYKPGEGKRGDACEGDSGGPFVMKSPYNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWIQKVIDRLGS,7.468521082957745 +CC(C)[C@H](CO)Nc1nc(Nc2cc(n(C)n2)C(C)(C)C)c2c[nH]nc2n1,MNTQQLAKLRSIVPEMRRVRHIHFVGIGGAGMGGIAEVLANEGYQISGSDLAPNPVTQQLMNLGATIYFNHRPENVRDASVVVVSSAISADNPEIVAAHEARIPVIRRAEMLAELMRFRHGIAIAGTHGKTTTTAMVSSIYAEAGLDPTFVNGGLVKAAGVHARLGHGRYLIAEADESDASFLHLQPMVAIVTNIEADHMDTYQGDFENLKQTFINFLHNLPFYGRAVMCVDDPVIRELLPRVGRQTTTYGFSEDADVRVEDYQQIGPQGHFTLLRQDKEPMRVTLNAPGRHNALNAAAAVAVATEEGIDDEAILRALESFQGTGRRFDFLGEFPLEPVNGKSGTAMLVDDYGHHPTEVDATIKAARAGWPDKNLVMLFQPHRFTRTRDLYDDFANVLTQVDTLLMLEVYPAGEAPIPGADSRSLCRTIRGRGKIDPILVPDPARVAEMLAPVLTGNDLILVQGAGNIGKIARSLAEIKLKPQTPEEEQHD,6.72584215073632 +COc1ccc(cc1)-c1nsc(C)c1C(=O)NC(N)=NCc1cccc2ccccc12,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,6.301029995663981 +CCCCCc1ccc(cc1)S(=O)(=O)NCCc1c(n[nH]c1-c1cccs1)-c1cnccn1,MGVYRVCVSTGASIYAGSKNKVELWLVGQHGEVELGSCLRPTRNKEEEFKVNVSKYLGSLLFVRLRKKHFLKEDAWFCNWISVQALGAAEDKYWFPCYRWVVGDGVQSLPVGTGCTTVGDPQGLFQKHREQELEERRKLYQWGSWKEGLILNVAGSKLTDLPVDERFLEDKKIDFEASLAWGLAELALKNSLNILAPWKTLDDFNRIFWCGRSKLARRVRDSWQEDSLFGYQFLNGANPMLLRRSVQLPARLVFPPGMEELQAQLEKELKAGTLFEADFALLDNIKANVILYCQQYLAAPLVMLKLQPDGKLMPMVIQLHLPKIGSSPPPLFLPTDPPMVWLLAKCWVRSSDFQVHELNSHLLRGHLMAEVFTVATMRCLPSIHPVFKLIVPHLRYTLEINVRARNGLVSDFGIFDQIMSTGGGGHVQLLQQAGAFLTYRSFCPPDDLADRGLLGVESSFYAQDALRLWEIISRYVQGIMGLYYKTDEAVRDDLELQSWCREITEIGLQGAQKQGFPTSLQSVAQACHFVTMCIFTCTGQHSSIHLGQLDWFTWVPNAPCTMRLPPPTTKDATLETVMATLPNLHQSSLQMSIVWQLGRDQPIMVPLGQHQEEYFSGPEPRAVLEKFREELAIMDKEIEVRNEKLDIPYEYLRPSIVENSVAI,7.920818753952375 +Nc1nc2-c3ccccc3C(=O)c2c(n1)-c1ccncc1,MPPSISAFQAAYIGIEVLIALVSVPGNVLVIWAVKVNQALRDATFCFIVSLAVADVAVGALVIPLAILINIGPQTYFHTCLMVACPVLILTQSSILALLAIAVDRYLRVKIPLRYKMVVTPRRAAVAIAGCWILSFVVGLTPMFGWNNLSAVERAWAANGSMGEPVIKCEFEKVISMEYMVYFNFFVWVLPPLLLMVLIYLEVFYLIRKQLNKKVSASSGDPQKYYGKELKIAKSLALILFLFALSWLPLHILNCITLFCPSCHKPSILTYIAIFLTHGNSAMNPIVYAFRIQKFRVTFLKIWNDHFRCQPAPPIDEDLPEERPDD,7.785156151952302 +COc1ccc(Cl)cc1NC(=O)CN1CCC(CC1)n1nnc2cc(C)ccc12,MAGLPRRIIKETQRLLAEPVPGIKAEPDESNARYFHVVIAGPQDSPFEGGTFKLELFLPEEYPMAAPKVRFMTKIYHPNVDKLGRICLDILKDKWSPALQIRTVLLSIQALLSAPNPDDPLANDVAEQWKTNEAQAIETARAWTRLYAMNNI,4.698970004336019 +CN1CCCC1c1cccnc1,MANSGTGAPPPLLLLPLLLLLGTGLLPASSHIETRAHAEERLLKRLFSGYNKWSRPVANISDVVLVRFGLSIAQLIDVDEKNQMMTTNVWVKQEWHDYKLRWDPGDYENVTSIRIPSELIWRPDIVLYNNADGDFAVTHLTKAHLFYDGRVQWTPPAIYKSSCSIDVTFFPFDQQNCTMKFGSWTYDKAKIDLVSMHSRVDQLDFWESGEWVIVDAVGTYNTRKYECCAEIYPDITYAFIIRRLPLFYTINLIIPCLLISCLTVLVFYLPSECGEKVTLCISVLLSLTVFLLLITEIIPSPTSLVIPLIGEYLLFTMIFVTLSIVITVFVLNVHHRSPRTHTMPAWVRRVFLDIVPRLLFMKRPSVVKDNCRRLIESMHKMANAPRFWPEPVGEPGILSDICNQGLSPAPTFCNPTDTAVETQPTCRSPPLEVPDLKTSEVEKASPCPSPGSCPPPKSSSGAPMLIKARSLSVQHVPSSQEAAEDGIRCRSRSIQYCVSQDGAASLADSKPTSSPTSLKARPSQLPVSDQASPCKCTCKEPSPVSPVTVLKAGGTKAPPQHLPLSPALTRAVEGVQYIADHLKAEDTDFSVKEDWKYVAMVIDRIFLWMFIIVCLLGTVGLFLPPWLAAC,5.0 +NC(=O)CC1(COC1)NC(=O)c1cc(OCC2CC2)c(cn1)N1CC(F)(F)C1,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,7.330683119433888 +COc1cc(F)cc(n1)[C@@H](CO)NC(=O)[C@@H](C)N1Cc2ncc(cc2C1=O)-c1nc(Nc2cn(C)nn2)ncc1Cl,MAAAAAAGAGPEMVRGQVFDVGPRYTNLSYIGEGAYGMVCSAYDNVNKVRVAIKKISPFEHQTYCQRTLREIKILLRFRHENIIGINDIIRAPTIEQMKDVYIVQDLMETDLYKLLKTQHLSNDHICYFLYQILRGLKYIHSANVLHRDLKPSNLLLNTTCDLKICDFGLARVADPDHDHTGFLTEYVATRWYRAPEIMLNSKGYTKSIDIWSVGCILAEMLSNRPIFPGKHYLDQLNHILGILGSPSQEDLNCIINLKARNYLLSLPHKNKVPWNRLFPNADSKALDLLDKMLTFNPHKRIEVEQALAHPYLEQYYDPSDEPIAEAPFKFDMELDDLPKEKLKELIFEETARFQPGYRS,8.769551078621726 +CCOP(=O)(OCC)Oc1nc(Cl)c(Cl)cc1Cl,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNSPLVPAGDTTNITEFYNKSLSSFKENEDNIQCGENFMDMECFMILNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFVDFHVFHRKDSPNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCKKLQSVCSDIFPLIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNTASMHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,4.6020599913279625 +Cl.Cl.Cc1cc(N)nc2cc(ccc12)-c1ccc(CN)cc1,MEDHMFGVQQIQPNVISVRLFKRKVGGLGFLVKERVSKPPVIISDLIRGGAAEQSGLIQAGDIILAVNGRPLVDLSYDSALEVLRGIASETHVVLILRGPEGFTTHLETTFTGDGTPKTIRVTQPLGPPTKAVDLSHQPPAGKEQPLAVDGASGPGNGPQHAYDDGQEAGSLPHANGLAPRPPGQDPAKKATRVSLQGRGENNELLKEIEPVLSLLTSGSRGVKGGAPAKAEMKDMGIQVDRDLDGKSHKPLPLGVENDRVFNDLWGKGNVPVVLNNPYSEKEQPPTSGKQSPTKNGSPSKCPRFLKVKNWETEVVLTDTLHLKSTLETGCTEYICMGSIMHPSQHARRPEDVRTKGQLFPLAKEFIDQYYSSIKRFGSKAHMERLEEVNKEIDTTSTYQLKDTELIYGAKHAWRNASRCVGRIQWSKLQVFDARDCTTAHGMFNYICNHVKYATNKGNLRSAITIFPQRTDGKHDFRVWNSQLIRYAGYKQPDGSTLGDPANVQFTEICIQQGWKPPRGRFDVLPLLLQANGNDPELFQIPPELVLEVPIRHPKFEWFKDLGLKWYGLPAVSNMLLEIGGLEFSACPFSGWYMGTEIGVRDYCDNSRYNILEEVAKKMNLDMRKTSSLWKDQALVEINIAVLYSFQSDKVTIVDHHSATESFIKHMENEYRCRGGCPADWVWIVPPMSGSITPVFHQEMLNYRLTPSFEYQPDPWNTHVWKGTNGTPTKRRAIGFKKLAEAVKFSAKLMGQAMAKRVKATILYATETGKSQAYAKTLCEIFKHAFDAKVMSMEEYDIVHLEHETLVLVVTSTFGNGDPPENGEKFGCALMEMRHPNSVQEERKSYKVRFNSVSSYSDSQKSSGDGPDLRDNFESAGPLANVRFSVFGLGSRAYPHFCAFGHAVDTLLEELGGERILKMREGDELCGQEEAFRTWAKKVFKAACDVFCVGDDVNIEKANNSLISNDRSWKRNKFRLTFVAEAPELTQGLSNVHKKRVSAARLLSRQNLQSPKSSRSTIFVRLHTNGSQELQYQPGDHLGVFPGNHEDLVNALIERLEDAPPVNQMVKVELLEERNTALGVISNWTDELRLPPCTIFQAFKYYLDITTPPTPLQLQQFASLATSEKEKQRLLVLSKGLQEYEEWKWGKNPTIVEVLEEFPSIQMPATLLLTQLSLLQPRYYSISSSPDMYPDEVHLTVAIVSYRTRDGEGPIHHGVCSSWLNRIQADELVPCFVRGAPSFHLPRNPQVPCILVGPGTGIAPFRSFWQQRQFDIQHKGMNPCPMVLVFGCRQSKIDHIYREETLQAKNKGVFRELYTAYSREPDKPKKYVQDILQEQLAESVYRALKEQGGHIYVCGDVTMAADVLKAIQRIMTQQGKLSAEDAGVFISRMRDDNRYHEDIFGVTLRTYEVTNRLRSESIAFIEESKKDTDEVFSS,7.055517327849831 +C[C@H]1CN(C[C@@H](C)O1)c1ncc(C(=O)NC2C3CC4CC2CC(O)(C4)C3)c(n1)C1CCCC1,MAFMKKYLLPILGLFMAYYYYSANEEFRPEMLQGKKVIVTGASKGIGREMAYHLAKMGAHVVVTARSKETLQKVVSHCLELGAASAHYIAGTMEDMTFAEQFVAQAGKLMGGLDMLILNHITNTSLNLFHDDIHHVRKSMEVNFLSYVVLTVAALPMLKQSNGSIVVVSSLAGKVAYPMVAAYSASKFALDGFFSSIRKEYSVSRVNVSITLCVLGLIDTETAMKAVSGIVHMQAAPKEECALEIIKGGALRQEEVYYDSSLWTTLLIRNPCRKILEFLYSTSYNMDRFINK,7.568636235841012 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+CC(CS)C(=O)N1C(Cc2ccccc12)C(O)=O,MGAAPGRRGPRLLRPPPPLLLLLLLLRPPPAALTLDPGLLPGDFAADEAGARLFASSYNSSAEQVLFRSTAASWAHDTNITAENARRQEEEALLSQEFAEAWGKKAKELYDPVWQNFTDPELRRIIGAVRTLGPANLPLAKRQQYNSLLSNMSQIYSTGKVCFPNKTASCWSLDPDLNNILASSRSYAMLLFAWEGWHNAVGIPLKPLYQEFTALSNEAYRQDGFSDTGAYWRSWYDSPTFEEDLERIYHQLEPLYLNLHAYVRRVLHRRYGDRYINLRGPIPAHLLGNMWAQSWESIYDMVVPFPDKPNLDVTSTMVQKGWNATHMFRVAEEFFTSLGLLPMPPEFWAESMLEKPEDGREVVCHASAWDFYNRKDFRIKQCTQVTMDQLSTVHHEMGHVQYYLQYKDQPVSLRRANPGFHEAIGDVLALSVSTPAHLHKIGLLDHVTNDTESDINYLLKMALEKIAFLPFGYLVDQWRWGVFSGRTPSSRYNFDWWYLRTKYQGICPPVVRNETHFDAGAKFHIPSVTPYIRYFVSFVLQFQFHQALCMEAGHQGPLHQCDIYQSTRAGAKLRAVLQAGCSRPWQEVLKDMVASDALDAQPLLDYFQPVTQWLQEQNERNGEVLGWPEYQWRPPLPNNYPEGIDLVTDEAEASRFVEEYDRSFQAVWNEYAEANWNYNTNITTEASKILLQKNMQIANHTLTYGNWARRFDVSNFQNATSKRIIKKVQDLQRAVLPVKELEEYNQILLDMETIYSVANVCRVDGSCLQLEPDLTNLMATSRKYDELLWVWTSWRDKVGRAILPYFPKYVEFTNKAARLNGYVDAGDSWRSMYETPTLEQDLERLFQELQPLYLNLHAYVGRALHRHYGAQHINLEGPIPAHLLGNMWAQTWSNIYDLVAPFPSASTMDATEAMIKQGWTPRRMFEEADKFFISLGLLPVPPEFWNKSMLEKPTDGREVVCHASAWDFYNGKDFRIKQCTTVNMEDLVVVHHEMGHIQYFMQYKDLPVALREGANPGFHEAIGDVLALSVSTPKHLHSINLLSSEGGGYEHDINFLMKMALDKIAFIPFSYLVDEWRWRVFDGSITKENYNQEWWSLRLKYQGLCPPAPRSQGDFDPGAKFHIPSSVPYIRYFVSFIIQFQFHEALCKAAGHTGPLHTCDIYQSKEAGKRLADAMKLGYSKPWPEAMKVITGQPNMSASAMMNYFKPLMDWLLTENGRHGEKLGWPQYTWTPNSARSEGSLPDSGRVNFLGMNLDAQQARVGQWVLLFLGVALLLASLGLTQRLFSIRYQSLRQPHHGPQFGSEVELRHS,7.638272163982407 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+NCCCCCCCCCCCCNC(=O)[C@H](Cc1cccc(O)c1)NC(=O)Cc1ccccc1,MEPWPLLLLFSLCSAGLVLGSEHETRLVAKLFKDYSSVVRPVEDHRQVVEVTVGLQLIQLINVDEVNQIVTTNVRLKQGDMVDLPRPSCVTLGVPLFSHLQNEQWVDYNLKWNPDDYGGVKKIHIPSEKIWRPDLVLYNNADGDFAIVKFTKVLLQYTGHITWTPPAIFKSYCEIIVTHFPFDEQNCSMKLGTWTYDGSVVAINPESDQPDLSNFMESGEWVIKESRGWKHSVTYSCCPDTPYLDITYHFVMQRLPLYFIVNVIIPCLLFSFLTGLVFYLPTDSGEKMTLSISVLLSLTVFLLVIVELIPSTSSAVPLIGKYMLFTMVFVIASIIITVIVINTHHRSPSTHVMPNWVRKVFIDTIPNIMFFSTMKRPSREKQDKKIFTEDIDISDISGKPGPPPMGFHSPLIKHPEVKSAIEGIKYIAETMKSDQESNNAAAEWKYVAMVMDHILLGVFMLVCIIGTLAVFAGRLIELNQQG,3.9788107009300617 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+CC(C)(NC(=O)CCNCC(=O)N1CCC[C@H]1C#N)c1ccccc1,MWKRSEQMKIKSGKCNMAAAMETEQLGVEIFETADCEENIESQDRPKLEPFYVERYSWSQLKKLLADTRKYHGYMMAKAPHDFMFVKRNDPDGPHSDRIYYLAMSGENRENTLFYSEIPKTINRAAVLMLSWKPLLDLFQATLDYGMYSREEELLRERKRIGTVGIASYDYHQGSGTFLFQAGSGIYHVKDGGPQGFTQQPLRPNLVETSCPNIRMDPKLCPADPDWIAFIHSNDIWISNIVTREERRLTYVHNELANMEEDARSAGVATFVLQEEFDRYSGYWWCPKAETTPSGGKILRILYEENDESEVEIIHVTSPMLETRRADSFRYPKTGTANPKVTFKMSEIMIDAEGRIIDVIDKELIQPFEILFEGVEYIARAGWTPEGKYAWSILLDRSQTRLQIVLISPELFIPVEDDVMERQRLIESVPDSVTPLIIYEETTDIWINIHDIFHVFPQSHEEEIEFIFASECKTGFRHLYKITSILKESKYKRSSGGLPAPSDFKCPIKEEIAITSGEWEVLGRHGSNIQVDEVRRLVYFEGTKDSPLEHHLYVVSYVNPGEVTRLTDRGYSHSCCISQHCDFFISKYSNQKNPHCVSLYKLSSPEDDPTCKTKEFWATILDSAGPLPDYTPPEIFSFESTTGFTLYGMLYKPHDLQPGKKYPTVLFIYGGPQVQLVNNRFKGVKYFRLNTLASLGYVVVVIDNRGSCHRGLKFEGAFKYKMGQIEIDDQVEGLQYLASRYDFIDLDRVGIHGWSYGGYLSLMALMQRSDIFRVAIAGAPVTLWIFYDTGYTERYMGHPDQNEQGYYLGSVAMQAEKFPSEPNRLLLLHGFLDENVHFAHTSILLSFLVRAGKPYDLQIYPQERHSIRVPESGEHYELHLLHYLQENLGSRIAALKVI,5.078938109209721 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+CS(=O)(=O)N1CCN(Cc2cc3nc(nc(N4CCOCC4)c3s2)-c2cccc3[nH]ncc23)CC1,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,8.522878745280337 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+CC(C)(OCc1cc(-c2cccc(Cl)c2)n(Cc2ccccc2Cl)n1)C(O)=O,MGGAVVDEGPTGVKAPDGGWGWAVLFGCFVITGFSYAFPKAVSVFFKELIQEFGIGYSDTAWISSILLAMLYGTGPLCSVCVNRFGCRPVMLVGGLFASLGMVAASFCRSIIQVYLTTGVITGLGLALNFQPSLIMLNRYFSKRRPMANGLAAAGSPVFLCALSPLGQLLQDRYGWRGGFLILGGLLLNCCVCAALMRPLVVTAQPGSGPPRPSRRLLDLSVFRDRGFVLYAVAASVMVLGLFVPPVFVVSYAKDLGVPDTKAAFLLTILGFIDIFARPAAGFVAGLGKVRPYSVYLFSFSMFFNGLADLAGSTAGDYGGLVVFCIFFGISYGMVGALQFEVLMAIVGTHKFSSAIGLVLLMEAVAVLVGPPSGGKLLDATHVYMYVFILAGAEVLTSSLILLLGNFFCIRKKPKEPQPEVAAAEEEKLHKPPADSGVDLREVEHFLKAEPEKNGEVVHTPETSV,7.6777807052660805 +O=C(OC1CCOC1=O)c1ccc(s1)-c1nc2ccccc2s1,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,5.0227795533646145 +CC(C)CNC(=O)C1CCN(Cc2cccc(NC(=O)c3cccc(n3)C(F)(F)F)c2)C1,MDLHLFDYSEPGNFSDISWPCNSSDCIVVDTVMCPNMPNKSVLLYTLSFIYIFIFVIGMIANSVVVWVNIQAKTTGYDTHCYILNLAIADLWVVLTIPVWVVSLVQHNQWPMGELTCKVTHLIFSINLFGSIFFLTCMSVDRYLSITYFTNTPSSRKKMVRRVVCILVWLLAFCVSLPDTYYLKTVTSASNNETYCRSFYPEHSIKEWLIGMELVSVVLGFAVPFSIIAVFYFLLARAISASSDQEKHSSRKIIFSYVVVFLVCWLPYHVAVLLDIFSILHYIPFTCRLEHALFTALHVTQCLSLVHCCVNPVLYSFINRNYRYELMKAFIFKYSAKTGLTKLIDASRVSETEYSALEQSTK,6.714442690992226 +Cc1[nH]c(C=C2C(=O)NN=C2N)c(C)c1CCO,MAVPFVEDWDLVQTLGEGAYGEVQLAVNRVTEEAVAVKIVDMKRAVDCPENIKKEICINKMLNHENVVKFYGHRREGNIQYLFLEYCSGGELFDRIEPDIGMPEPDAQRFFHQLMAGVVYLHGIGITHRDIKPENLLLDERDNLKISDFGLATVFRYNNRERLLNKMCGTLPYVAPELLKRREFHAEPVDVWSCGIVLTAMLAGELPWDQPSDSCQEYSDWKEKKTYLNPWKKIDSAPLALLHKILVENPSARITIPDIKKDRWYNKPLKKGAKRPRVTSGGVSESPSGFSKHIQSNLDFSPVNSASSEENVKYSSSQPEPRTGLSLWDTSPSYIDKLVQGISFSQPTCPDHMLLNSQLLGTPGSSQNPWQRLVKRMTRFFTKLDADKSYQCLKETCEKLGYQWKKSCMNQVTISTTDRRNNKLIFKVNLLEMDDKILVDFRLSKGDGLEFKRHFLKIKGKLIDIVSSQKIWLPAT,6.400116927926312 +Cn1cc(cn1)-c1cnc2c(cnn2c1)-c1csc(c1)C(=O)NCC(F)(F)F,MVSRDQAHLGPKYVGLWDFKSRTDEELSFRAGDVFHVARKEEQWWWATLLDEAGGAVAQGYVPHNYLAERETVESEPWFFGCISRSEAVRRLQAEGNATGAFLIRVSEKPSADYVLSVRDTQAVRHYKIWRRAGGRLHLNEAVSFLSLPELVNYHRAQSLSHGLRLAAPCRKHEPEPLPHWDDWERPREEFTLCRKLGSGYFGEVFEGLWKDRVQVAIKVISRDNLLHQQMLQSEIQAMKKLRHKHILALYAVVSVGDPVYIITELMAKGSLLELLRDSDEKVLPVSELLDIAWQVAEGMCYLESQNYIHRDLAARNILVGENTLCKVGDFGLARLIKEDVYLSHDHNIPYKWTAPEALSRGHYSTKSDVWSFGILLHEMFSRGQVPYPGMSNHEAFLRVDAGYRMPCPLECPPSVHKLMLTCWCRDPEQRPCFKALRERLSSFTSYENPT,4.0 +N[C@]1(CN(C[C@@H]1CCCB(O)O)C(=O)C1Cc2ccccc2CN1)C(O)=O,MSAKSRTIGIIGAPFSKGQPRGGVEEGPTVLRKAGLLEKLKEQECDVKDYGDLPFADIPNDSPFQIVKNPRSVGKASEQLAGKVAEVKKNGRISLVLGGDHSLAIGSISGHARVHPDLGVIWVDAHTDINTPLTTTSGNLHGQPVSFLLKELKGKIPDVPGFSWVTPCISAKDIVYIGLRDVDPGEHYILKTLGIKYFSMTEVDRLGIGKVMEETLSYLLGRKKRPIHLSFDVDGLDPSFTPATGTPVVGGLTYREGLYITEEIYKTGLLSGLDIMEVNPSLGKTPEEVTRTVNTAVAITLACFGLAREGNHKPIDYLNPPK,6.0 +Fc1ccccc1C1=NC(NC(=O)c2ccccc2)C(=O)Nc2ccccc12,MELLKLNRSVQGTGPGPGASLCRPGAPLLNSSSVGNLSCEPPRIRGAGTRELELAIRITLYAVIFLMSVGGNMLIIVVLGLSRRLRTVTNAFLLSLAVSDLLLAVACMPFTLLPNLMGTFIFGTVICKAVSYLMGVSVSVSTLSLVAIALERYSAICRPLQARVWQTRSHAARVIVATWLLSGLLMVPYPVYTVVQPVGPRVLQCVHRWPSARVRQTWSVLLLLLLFFIPGVVMAVAYGLISRELYLGLRFDGDSDSDSQSRVRNQGGLPGAVHQNGRCRPETGAVGEDSDGCYVQLPRSRPALELTALTAPGPGSGSRPTQAKLLAKKRVVRMLLVIVVLFFLCWLPVYSANTWRAFDGPGAHRALSGAPISFIHLLSYASACVNPLVYCFMHRRFRQACLETCARCCPRPPRARPRALPDEDPPTPSIASLSRLSYTTISTLGPG,4.552841968657781 +CC(=O)N1N=C(CC1c1cccc(OS(N)(=O)=O)c1)c1ccc(Cl)cc1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,7.481486060122112 +CCc1nn(CCCC(=O)NCc2ccccc2Br)c(=O)c2cc3occc3n12,MKLLVLAVLLTVAAADSGISPRAVWQFRKMIKCVIPGSDPFLEYNNYGCYCGLGGSGTPVDELDKCCQTHDNCYDQAKKLDSCKFLLDNPYTHTYSYSCSGSAITCSSKNKECEAFICNCDRNAAICFSKAPYNKAHKNLDTKKYCQS,4.698970004336019 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+CCCCCCCCCCCCCC(OC(=O)C(CCCCN(O)C(C)=O)NC(=O)c1coc(n1)-c1ccccc1O)C(C)C(=O)NC1CCCCN(O)C1=O,MTLHNNSTTSPLFPNISSSWIHSPSDAGLPPGTVTHFGSYNVSRAAGNFSSPDGTTDDPLGGHTVWQVVFIAFLTGILALVTIIGNILVIVSFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLAIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAETENFVHPTGSSRSCSSYELQQQSMKRSNRRKYGRCHFWFTTKSWKPSSEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSTILNSTKLPSSDNLQVPEEELGMVDLERKADKLQAQKSVDDGGSFPKSFSKLPIQLESAVDTAKTSDVNSSVGKSTATLPLSFKEATLAKRFALKTRSQITKRKRMSLVKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTFWNLGYWLCYINSTVNPVCYALCNKTFRTTFKMLLLCQCDKKKRRKQQYQQRQSVIFHKRAPEQAL,6.638272163982407 +Cc1ccc(cc1)-c1cc(nn1-c1ccc(cc1)S(N)(=O)=O)C(F)(F)F,MAPLCPSPWLPLLIPAPAPGLTVQLLLSLLLLVPVHPQRLPRMQEDSPLGGGSSGEDDPLGEEDLPSEEDSPREEDPPGEEDLPGEEDLPGEEDLPEVKPKSEEEGSLKLEDLPTVEAPGDPQEPQNNAHRDKEGDDQSHWRYGGDPPWPRVSPACAGRFQSPVDIRPQLAAFCPALRPLELLGFQLPPLPELRLRNNGHSVQLTLPPGLEMALGPGREYRALQLHLHWGAAGRPGSEHTVEGHRFPAEIHVVHLSTAFARVDEALGRPGGLAVLAAFLEEGPEENSAYEQLLSRLEEIAEEGSETQVPGLDISALLPSDFSRYFQYEGSLTTPPCAQGVIWTVFNQTVMLSAKQLHTLSDTLWGPGDSRLQLNFRATQPLNGRVIEASFPAGVDSSPRAAEPVQLNSCLAAGDILALVFGLLFAVTSVAFLVQMRRQHRRGTKGGVSYRPAEVAETGA,7.795880017344075 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+COC(C)N[Pt](Cl)(Cl)NC(C)OC,MAIDENKQKALAAALGQIEKQFGKGSIMRLGEDRSMDVETISTGSLSLDIALGAGGLPMGRIVEIYGPESSGKTTLTLQVIAAAQREGKTCAFIDAEHALDPIYARKLGVDIDNLLCSQPDTGEQALEICDALARSGAVDVIVVDSVAALTPKAEIEGEIGDSHMGLAARMMSQAMRKLAGNLKQSNTLLIFINQIRMKIGVMFGNPETTTGGNALKFYASVRLDIRRIGAVKEGENVVGSETRVKVVKNKIAAPFKQAEFQILYGEGINFYGELVDLGVKEKLIEKAGAWYSYKGEKIGQGKANATAWLKDNPETAKEIEKKVRELLLSNPNSTPDFSVDDSEGVAETNEDF,3.6989700043360187 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+NS(=O)(=O)c1ccc(cc1)C(=O)NNC(=O)Nc1ccc(Oc2ccccc2)cc1,MAPLCPSPWLPLLIPAPAPGLTVQLLLSLLLLVPVHPQRLPRMQEDSPLGGGSSGEDDPLGEEDLPSEEDSPREEDPPGEEDLPGEEDLPGEEDLPEVKPKSEEEGSLKLEDLPTVEAPGDPQEPQNNAHRDKEGDDQSHWRYGGDPPWPRVSPACAGRFQSPVDIRPQLAAFCPALRPLELLGFQLPPLPELRLRNNGHSVQLTLPPGLEMALGPGREYRALQLHLHWGAAGRPGSEHTVEGHRFPAEIHVVHLSTAFARVDEALGRPGGLAVLAAFLEEGPEENSAYEQLLSRLEEIAEEGSETQVPGLDISALLPSDFSRYFQYEGSLTTPPCAQGVIWTVFNQTVMLSAKQLHTLSDTLWGPGDSRLQLNFRATQPLNGRVIEASFPAGVDSSPRAAEPVQLNSCLAAGDILALVFGLLFAVTSVAFLVQMRRQHRRGTKGGVSYRPAEVAETGA,8.102372908709558 +CN1CC2C(C(=O)N(C)C2=O)C11C(=O)c2ccccc2C1=O,MRPPQCLLHTPSLASPLLLLLLWLLGGGVGAEGREDAELLVTVRGGRLRGIRLKTPGGPVSAFLGIPFAEPPMGPRRFLPPEPKQPWSGVVDATTFQSVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLVWIYGGGFYSGASSLDVYDGRFLVQAERTVLVSMNYRVGAFGFLALPGSREAPGNVGLLDQRLALQWVQENVAAFGGDPTSVTLFGESAGAASVGMHLLSPPSRGLFHRAVLQSGAPNGPWATVGMGEARRRATQLAHLVGCPPGGTGGNDTELVACLRTRPAQVLVNHEWHVLPQESVFRFSFVPVVDGDFLSDTPEALINAGDFHGLQVLVGVVKDEGSYFLVYGAPGFSKDNESLISRAEFLAGVRVGVPQVSDLAAEAVVLHYTDWLHPEDPARLREALSDVVGDHNVVCPVAQLAGRLAAQGARVYAYVFEHRASTLSWPLWMGVPHGYEIEFIFGIPLDPSRNYTAEEKIFAQRLMRYWANFARTGDPNEPRDPKAPQWPPYTAGAQQYVSLDLRPLEVRRGLRAQACAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQDRCSDL,8.67778070526608 +Oc1cc(OCC(=O)OCc2cc(-c3cccc(F)c3)n(n2)-c2ccccc2)cc2oc(cc(=O)c12)-c1ccccc1,MSRSLLLWFLLFLLLLPPLPVLLADPGAPTPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPGLWTWLRNSLRPSPSFTHFLLTHGRWFWEFVNATFIREMLMRLVLTVRSNLIPSPPTYNSAHDYISWESFSNVSYYTRILPSVPKDCPTPMGTKGKKQLPDAQLLARRFLLRRKFIPDPQGTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQVLDGEMYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATLWLREHNRVCDLLKAEHPTWGDEQLFQTTRLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGVQFQYRNRIAMEFNHLYHWHPLMPDSFKVGSQEYSYEQFLFNTSMLVDYGVEALVDAFSRQIAGRIGGGRNMDHHILHVAVDVIRESREMRLQPFNEYRKRFGMKPYTSFQELVGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEIGAPFSLKGLLGNPICSPEYWKPSTFGGEVGFNIVKTATLKKLVCLNTKTCPYVSFRVPDASQDDGPAVERPSTEL,4.364516253185088 +Cn1cc(cn1)-c1cc(-c2ccc(nc2)N2CCC3(CN(C3)C(=O)C3CCCC3)CC2)c2c(cnn2c1)C#N,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,8.10790539730952 +Nc1nc(Nc2ccc(cc2)S(N)(=O)=O)nn1C(=O)c1c(F)cccc1F,MDKYDVIKAIGQGAFGKAYLAKGKSDSKHCVIKEINFEKMPIQEKEASKKEVILLEKMKHPNIVAFFNSFQENGRLFIVMEYCDGGDLMKRINRQRGVLFSEDQILGWFVQISLGLKHIHDRKILHRDIKAQNIFLSKNGMVAKLGDFGIARVLNNSMELARTCIGTPYYLSPEICQNKPYNNKTDIWSLGCVLYELCTLKHPFEGNNLQQLVLKICQAHFAPISPGFSRELHSLISQLFQVSPRDRPSINSILKRPFLENLIPKYLTPEVIQEEFSHMLICRAGAPASRHAGKVVQKCKIQKVRFQGKCPPRSRISVPIKRNAILHRNEWRPPAGAQKARSIKMIERPKIAAVCGHYDYYYAQLDMLRRRAHKPSYHPIPQENTGVEDYGQETRHGPSPSQWPAEYLQRKFEAQQYKLKVEKQLGLRPSSAEPNYNQRQELRSNGEEPRFQELPFRKNEMKEQEYWKQLEEIRQQYHNDMKEIRKKMGREPEENSKISHKTYLVKKSNLPVHQDASEGEAPVQMEFRSCCPGWSAMARSWLTATSASQDIEKDLKQMRLQNTKESKNPEQKYKAKKGVKFEINLDKCISDENILQEEEAMDIPNETLTFEDGMKFKEYECVKEHGDYTDKAFEKLHCPEAGFSTQTVAAVGNRRQWDGGAPQTLLQMMAVADITSTCPTGPDSESVLSVSRQEGKTKDPYSPVLILM,5.0 +Cc1cccc(CN2CCCn3c2nc2n(C)c(=O)n(C)c(=O)c32)c1,MPPYISAFQAAYIGIEVLIALVSVPGNVLVIWAVKVNQALRDATFCFIVSLAVADVAVGALVIPLAILINIGPQTYFHTCLMVACPVLILTQSSILALLAIAVDRYLRVKIPLRYKTVVTQRRAAVAIAGCWILSLVVGLTPMFGWNNLSVVEQDWRANGSVGEPVIKCEFEKVISMEYMVYFNFFVWVLPPLLLMVLIYLEVFYLIRKQLNKKVSASSGDPQKYYGKELKIAKSLALILFLFALSWLPLHILNCITLFCPTCQKPSILIYIAIFLTHGNSAMNPIVYAFRIHKFRVTFLKIWNDHFRCQPKPPIDEDLPEEKAED,5.718966632752272 +O=C(NC1CCOCC1)c1cc(cs1)[C@@H]1C[C@H]1NC1CCC1,SGVEGAAFQSRLPHDRMTSQEAACFPDIISGPQQTQKVFLFIRNRTLQLWLDNPKIQLTFEATLQQLEAPYNSDTVLVHRVHSYLERHGLINFGIYKRIKPLPTKKTGKVIIIGSGVSGLAAARQLQSFGMDVTLLEARDRVGGRVATFRKGNYVADLGAMVVTGLGGNPMAVVSKQVNMELAKIKQKCPLYEANGQAVPKEKDEMVEQEFNRLLEATSYLSHQLDFNVLNNKPVSLGQALEVVIQLQEKHVKDEQIEHWKKIVKTQEELKELLNKMVNLKEKIKELHQQYKEASEVKPPRDITAEFLVKSKHRDLTALCKEYDELAETQGKLEEKLQELEANPPSDVYLSSRDRQILDWHFANLEFANATPLSTLSLKHWDQDDDFEFTGSHLTVRNGYSCVPVALAEGLDIKLNTAVRQVRYTASGCEVIAVNTRSTSQTFIYKCDAVLCTLPLGVLKQQPPAVQFVPPLPEWKTSAVQRMGFGNLNKVVLCFDRVFWDPSVNLFGHVGSTTASRGELFLFWNLYKAPILLALVAGEAAGIMENISDDVIVGRCLAILKGIFGSSAVPQPKETVVSRWRADPWARGSYSYVAAGSSGNDYDLMAQPITPGPSIPGAPQPIPRLFFAGEHTIRNYPATVHGALLSGLREAGRIADQFLGAM,6.698970004336019 +Nc1noc2cccc(C(=O)Nc3cccc(CNC(=O)Nc4ccc(F)c(F)c4)c3)c12,MDRSKENCISGPVKATAPVGGPKRVLVTQQFPCQNPLPVNSGQAQRVLCPSNSSQRVPLQAQKLVSSHKPVQNQKQKQLQATSVPHPVSRPLNNTQKSKQPLPSAPENNPEEELASKQKNEESKKRQWALEDFEIGRPLGKGKFGNVYLAREKQSKFILALKVLFKAQLEKAGVEHQLRREVEIQSHLRHPNILRLYGYFHDATRVYLILEYAPLGTVYRELQKLSKFDEQRTATYITELANALSYCHSKRVIHRDIKPENLLLGSAGELKIADFGWSVHAPSSRRTTLCGTLDYLPPEMIEGRMHDEKVDLWSLGVLCYEFLVGKPPFEANTYQETYKRISRVEFTFPDFVTEGARDLISRLLKHNPSQRPMLREVLEHPWITANSSKPSNCQNKESASKQS,5.320572103387881 +NS(=O)(=O)c1cc(c(NC(=O)CN(CCN(CC(O)=O)CC(O)=O)CC(O)=O)cc1Cl)S(N)(=O)=O,MRLLLALLVLAAAPPQARAASHWCYQIQVKPSNYTCLEPDEWEGSCQNNRQSPVNIVTAKTQLDPNLGRFSFSGYNMKHQWVVQNNGHTVMVLLENKPSIAGGGLSTRYQATQLHLHWSRAMDRGSEHSFDGERFAMEMHIVHEKEKGLSGNASQNQFAEDEIAVLAFMVEDGSKNVNFQPLVEALSDIPRPNMNTTMKEGVSLFDLLPEEESLRHYFRYLGSLTTPTCDEKVVWTVFQKPIQLHRDQILAFSQKLFYDDQQKVNMTDNVRPVQSLGQRQVFRSGAPGLLLAQPLPTLLAPVLACLTVGFLR,6.978810700930062 +Cl.NC(=N)NC(=N)NCCc1ccc(cc1)S(N)(=O)=O,MAPLCPSPWLPLLIPAPAPGLTVQLLLSLLLLVPVHPQRLPRMQEDSPLGGGSSGEDDPLGEEDLPSEEDSPREEDPPGEEDLPGEEDLPGEEDLPEVKPKSEEEGSLKLEDLPTVEAPGDPQEPQNNAHRDKEGDDQSHWRYGGDPPWPRVSPACAGRFQSPVDIRPQLAAFCPALRPLELLGFQLPPLPELRLRNNGHSVQLTLPPGLEMALGPGREYRALQLHLHWGAAGRPGSEHTVEGHRFPAEIHVVHLSTAFARVDEALGRPGGLAVLAAFLEEGPEENSAYEQLLSRLEEIAEEGSETQVPGLDISALLPSDFSRYFQYEGSLTTPPCAQGVIWTVFNQTVMLSAKQLHTLSDTLWGPGDSRLQLNFRATQPLNGRVIEASFPAGVDSSPRAAEPVQLNSCLAAGDILALVFGLLFAVTSVAFLVQMRRQHRRGTKGGVSYRPAEVAETGA,7.698970004336019 +Fc1ccc2c(Cc3c[nH]c4cc(F)ccc34)c[nH]c2c1,MWNSSDANFSCYHESVLGYRYVAVSWGVVVAVTGTVGNVLTLLALAIQPKLRTRFNLLIANLTLADLLYCTLLQPFSVDTYLHLHWRTGATFCRVFGLLLFASNSVSILTLCLIALGRYLLIAHPKLFPQVFSAKGIVLALVSTWVVGVASFAPLWPIYILVPVVCTCSFDRIRGRPYTTILMGIYFVLGLSSVGIFYCLIHRQVKRAAQALDQYKLRQASIHSNHVARTDEAMPGRFQELDSRLASGGPSEGISSEPVSAATTQTLEGDSSEVGDQINSKRAKQMAEKSPPEASAKAQPIKGARRAPDSSSEFGKVTRMCFAVFLCFALSYIPFLLLNILDARVQAPRVVHMLAANLTWLNGCINPVLYAAMNRQFRQAYGSILKRGPRSFHRLH,6.204119982655925 +COc1ccc(Cl)cc1C(=O)N1CCN(C(C)C1)c1ncnc2sc3CCCc3c12,MKWVWALLLLAALGSGRAERDCRVSSFRVKENFDKARFSGTWYAMAKKDPEGLFLQDNIVAEFSVDETGQMSATAKGRVRLLNNWDVCADMVGTFTDTEDPAKFKMKYWGVASFLQKGNDDHWIVDTDYDTYAVQYSCRLLNLDGTCADSYSFVFSRDPNGLPPEAQKIVRQRQEELCLARQYRLIVHNGYCDGRSERNLL,6.080921907623926 +Nc1ccc(cn1)C(O)=O,MWRVRKRGYFGIWSFPLIIAAVCAQSVNDPSNMSLVKETVDRLLKGYDIRLRPDFGGPPVAVGMNIDIASIDMVSEVNMDYTLTMYFQQAWRDKRLSYNVIPLNLTLDNRVADQLWVPDTYFLNDKKSFVHGVTVKNRMIRLHPDGTVLYGLRITTTAACMMDLRRYPLDEQNCTLEIESYGYTTDDIEFYWRGDDNAVTGVTKIELPQFSIVDYKLITKKVVFSTGSYPRLSLSFKLKRNIGYFILQTYMPSILITILSWVSFWINYDASAARVALGITTVLTMTTINTHLRETLPKIPYVKAIDMYLMGCFVFVFMALLEYALVNYIFFGRGPQRQKKAAEKAASANNEKMRLDVNKIFYKDIKQNGTQYRSLWDPTGNLSPTRRTTNYDFSLYTMDPHENILLSTLEIKNEMATSEAVMGLGDPRSTMLAYDASSIQYRKAGLPRHSFGRNALERHVAQKKSRLRRRASQLKITIPDLTDVNAIDRWSRIFFPVVFSFFNIVYWLYYVN,3.4999996786570646 +Cc1nsc(n1)-c1nnc2[C@@H](CCO)N(CCn12)C(=O)c1ccc(F)cc1,MATLPAAETWIDGGGGVGADAVNLTASLAAGAATGAVETGWLQLLDQAGNLSSSPSALGLPVASPAPSQPWANLTNQFVQPSWRIALWSLAYGVVVAVAVLGNLIVIWIILAHKRMRTVTNYFLVNLAFSDASMAAFNTLVNFIYALHSEWYFGANYCRFQNFFPITAVFASIYSMTAIAVDRYMAIIDPLKPRLSATATKIVIGSIWILAFLLAFPQCLYSKTKVMPGRTLCFVQWPEGPKQHFTYHIIVIILVYCFPLLIMGITYTIVGITLWGGEIPGDTCDKYHEQLKAKRKVVKMMIIVVMTFAICWLPYHIYFILTAIYQQLNRWKYIQQVYLASFWLAMSSTMYNPIIYCCLNKRFRAGFKRAFRWCPFIKVSSYDELELKTTRFHPNRQSSMYTVTRMESMTVVFDPNDADTTRSSRKKRATPRDPSFNGCSRRNSKSASATSSFISSPYTSVDEYS,7.136677139879544 +COc1ccccc1N1CCN(CCCCCC(=O)NCc2ccccc2-c2ccccc2Cl)CC1,MSPLNQSAEGLPQEASNRSLNATETSEAWDPRTLQALKISLAVVLSVITLATVLSNAFVLTTILLTRKLHTPANYLIGSLATTDLLVSILVMPISIAYTITHTWNFGQILCDIWLSSDITCCTASILHLCVIALDRYWAITDALEYSKRRTAGHAATMIAIVWAISICISIPPLFWRQAKAQEEMSDCLVNTSQISYTIYSTCGAFYIPSVLLIILYGRIYRAARNRILNPPSLYGKRFTTAHLITGSAGSSLCSLNSSLHEGHSHSAGSPLFFNHVKIKLADSALERKRISAARERKATKILGIILGAFIICWLPFFVVSLVLPICRDSCWIHPALFDFFTWLGYLNSLINPIIYTVFNEEFRQAFQKIVPFRKAS,6.913640169325252 +CNC(=O)c1cccc(Nc2nc(ncc2F)N2CC(C2)Oc2ccc(F)cc2)c1,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,6.468521082957745 +CCc1ccc(OCc2cccc(NC(=O)CC(=O)OC)c2)cc1OC,MPSYTVTVATGSQWFAGTDDYIYLSLIGSAGCSEKHLLDKAFYNDFERGGRDSYDVTVDEELGEIYLVKIEKRKYRLHDDWYLKYITLKTPHDYIEFPCYRWITGEGEIVLRDGCAKLARDDQIHILKQHRRKELETRQKQYRWMEWNPGFPLSIDAKCHKDLPRDIQFDSEKGVDFVLNYSKAMENLFINRFMHMFQSSWHDFADFEKIFVKISNTISERVKNHWQEDLMFGYQFLNGCNPVLIKRCTELPKKLPVTTEMVECSLERQLSLEQEVQEGNIFIVDYELLDGIDANKTDPCTHQFLAAPICLLYKNLANKIVPIAIQLNQTPGEKNPIFLPTDSKYDWLLAKIWVRSSDFHIHQTITHLLRTHLVSEVFGIAMYRQLPAVHPLFKLLVAHVRFTIAINTKAREQLNCEYGLFDKANATGGGGHVQMVQRAVQDLTYSSLCFPEAIKARGMDNTEDIPYYFYRDDGLLVWEAIQSFTTEVVSIYYEDDQVVEEDQELQDFVKDVYVYGMRGRKASGFPKSIKSREKLSEYLTVVIFTASAQHAAVNFGQYDWCSWIPNAPPTMRAPPPTAKGVVTIEQIVDTLPDRGRSCWHLGAVWALSQFQENELFLGMYPEEHFIEKPVKEAMIRFRKNLEAIVSVIAERNKNKKLPYYYLSPDRIPNSVAI,5.342944147142896 +CC(C)Cc1nc(c([nH]1)-c1nc(C)cs1)-c1ccc2ncsc2c1,MEAAVAAPRPRLLLLVLAAAAAAAAALLPGATALQCFCHLCTKDNFTCVTDGLCFVSVTETTDKVIHNSMCIAEIDLIPRDRPFVCAPSSKTGSVTTTYCCNQDHCNKIELPTTVKSSPGLGPVELAAVIAGPVCFVCISLMLMVYICHNRTVIHHRVPNEEDPSLDRPFISEGTTLKDLIYDMTTSGSGSGLPLLVQRTIARTIVLQESIGKGRFGEVWRGKWRGEEVAVKIFSSREERSWFREAEIYQTVMLRHENILGFIAADNKDNGTWTQLWLVSDYHEHGSLFDYLNRYTVTVEGMIKLALSTASGLAHLHMEIVGTQGKPAIAHRDLKSKNILVKKNGTCCIADLGLAVRHDSATDTIDIAPNHRVGTKRYMAPEVLDDSINMKHFESFKRADIYAMGLVFWEIARRCSIGGIHEDYQLPYYDLVPSDPSVEEMRKVVCEQKLRPNIPNRWQSCEALRVMAKIMRECWYANGAARLTALRIKKTLSQLSQQEGIKM,8.045757490560675 +CSCC[C@H](NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@@H](N)Cc1ccccc1)C(=O)N[C@@H](Cc1ccc(OP(O)(O)=O)cc1)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CC(C)C)C(=O)NCC(=O)N[C@@H](CCC(O)=O)C(O)=O,MVRWFHRDLSGLDAETLLKGRGVHGSFLARPSRKNQGDFSLSVRVGDQVTHIRIQNSGDFYDLYGGEKFATLTELVEYYTQQQGVLQDRDGTIIHLKYPLNCSDPTSERWYHGHMSGGQAETLLQAKGEPWTFLVRESLSQPGDFVLSVLSDQPKAGPGSPLRVTHIKVMCEGGRYTVGGLETFDSLTDLVEHFKKTGIEEASGAFVYLRQPYYATRVNAADIENRVLELNKKQESEDTAKAGFWEEFESLQKQEVKNLHQRLEGQRPENKGKNRYKNILPFDHSRVILQGRDSNIPGSDYINANYIKNQLLGPDENAKTYIASQGCLEATVNDFWQMAWQENSRVIVMTTREVEKGRNKCVPYWPEVGMQRAYGPYSVTNCGEHDTTEYKLRTLQVSPLDNGDLIREIWHYQYLSWPDHGVPSEPGGVLSFLDQINQRQESLPHAGPIIVHCSAGIGRTGTIIVIDMLMENISTKGLDCDIDIQKTIQMVRAQRSGMVQTEAQYKFIYVAIAQFIETTKKKLEVLQSQKGQESEYGNITYPPAMKNAHAKASRTSSKHKEDVYENLHTKNKREEKVKKQRSADKEKSKGSLKRK,6.275724130399211 +NS(=O)(=O)c1c(ccc(-c2cnc3cc[nH]c3c2)c1-c1nn[nH]n1)S(=O)(=O)N[C@@H]1CCNC1,MSKLSVFFIFLFCSIATAAESLPDLKIEKLDEGVYVHTSFEEVNGWGVVPKHGLVVLVNAEAYLIDTPFTAKDTEKLVTWFVERGYKIKGSISSHFHSDSTGGIEWLNSRSIPTYASELTNELLKKDGKVQATNSFSGVNYWLVKNKIEVFYPGPGHTPDNVVVWLPERKILFGGCFIKPYGLGNLGDANIEAWPKSAKLLKSKYGKAKLVVPSHSEVGDASLLKLTLEQAVKGLNESKKPSKPSN,8.94692155651658 +CCN1CCN(Cc2ccc(Nc3ncc(F)c(n3)-c3cc(F)c4nc(C)n(C(C)C)c4c3)nc2)CC1,MGTVLSLSPSYRKATLFEDGAATVGHYTAVQNSKNAKDKNLKRHSIISVLPWKRIVAVSAKKKNSKKVQPNSSYQNNITHLNNENLKKSLSCANLSTFAQPPPAQPPAPPASQLSGSQTGGSSSVKKAPHPAVTSAGTPKRVIVQASTSELLRCLGEFLCRRCYRLKHLSPTDPVLWLRSVDRSLLLQGWQDQGFITPANVVFLYMLCRDVISSEVGSDHELQAVLLTCLYLSYSYMGNEISYPLKPFLVESCKEAFWDRCLSVINLMSSKMLQINADPHYFTQVFSDLKNESGQEDKKRLLLGLDR,6.392544976785332 +Cc1nc(nc(C)c1C)N1CC2CN(CC2C1)C(=O)c1ccccc1-c1ncn(C)n1,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,6.505845405981557 +COc1cccc(c1)-n1cc(nc1-c1ccc(C)cc1)C(=O)N1CCN(CC1)c1nc2ccccc2[nH]1,MDVVDSLLVNGSNITPPCELGLENETLFCLDQPRPSKEWQPAVQILLYSLIFLLSVLGNTLVITVLIRNKRMRTVTNIFLLSLAVSDLMLCLFCMPFNLIPNLLKDFIFGSAVCKTTTYFMGTSVSVSTFNLVAISLERYGAICKPLQSRVWQTKSHALKVIAATWCLSFTIMTPYPIYSNLVPFTKNNNQTANMCRFLLPNDVMQQSWHTFLLLILFLIPGIVMMVAYGLISLELYQGIKFEASQKKSAKERKPSTTSSGKYEDSDGCYLQKTRPPRKLELRQLSTGSSSRANRIRSNSSAANLMAKKRVIRMLIVIVVLFFLCWMPIFSANAWRAYDTASAERRLSGTPISFILLLSYTSSCVNPIIYCFMNKRFRLGFMATFPCCPNPGPPGARGEVGEEEEGGTTGASLSRFSYSHMSASVPPQ,7.769551078621726 +COC(=O)NC(C)Cc1ccc(cc1)C#Cc1cnc(NC2CCCC2)nc1,MVLLLCLSCLIFSCLTFSWLKIWGKMTDSKPITKSKSEANLIPSQEPFPASDNSGETPQRNGEGHTLPKTPSQAEPASHKGPKDAGRRRNSLPPSHQKPPRNPLSSSDAAPSPELQANGTGTQGLEATDTNGLSSSARPQGQQAGSPSKEDKKQANIKRQLMTNFILGSFDDYSSDEDSVAGSSRESTRKGSRASLGALSLEAYLTTGEAETRVPTMRPSMSGLHLVKRGREHKKLDLHRDFTVASPAEFVTRFGGDRVIEKVLIANNGIAAVKCMRSIRRWAYEMFRNERAIRFVVMVTPEDLKANAEYIKMADHYVPVPGGPNNNNYANVELIVDIAKRIPVQAVWAGWGHASENPKLPELLCKNGVAFLGPPSEAMWALGDKIASTVVAQTLQVPTLPWSGSGLTVEWTEDDLQQGKRISVPEDVYDKGCVKDVDEGLEAAERIGFPLMIKASEGGGGKGIRKAESAEDFPILFRQVQSEIPGSPIFLMKLAQHARHLEVQILADQYGNAVSLFGRDCSIQRRHQKIVEEAPATIAPLAIFEFMEQCAIRLAKTVGYVSAGTVEYLYSQDGSFHFLELNPRLQVEHPCTEMIADVNLPAAQLQIAMGVPLHRLKDIRLLYGESPWGVTPISFETPSNPPLARGHVIAARITSENPDEGFKPSSGTVQELNFRSSKNVWGYFSVAATGGLHEFADSQFGHCFSWGENREEAISNMVVALKELSIRGDFRTTVEYLINLLETESFQNNDIDTGWLDYLIAEKVQAEKPDIMLGVVCGALNVADAMFRTCMTDFLHSLERGQVLPADSLLNLVDVELIYGGVKYILKVARQSLTMFVLIMNGCHIEIDAHRLNDGGLLLSYNGNSYTTYMKEEVDSYRITIGNKTCVFEKENDPTVLRSPSAGKLTQYTVEDGGHVEAGSSYAEMEVMKMIMTLNVQERGRVKYIKRPGAVLEAGCVVARLELDDPSKVHPAEPFTGELPAQQTLPILGEKLHQVFHSVLENLTNVMSGFCLPEPVFSIKLKEWVQKLMMTLRHPSLPLLELQEIMTSVAGRIPAPVEKSVRRVMAQYASNITSVLCQFPSQQIATILDCHAATLQRKADREVFFINTQSIVQLVQRYRSGIRGYMKTVVLDLLRRYLRVEHHFQQAHYDKCVINLREQFKPDMSQVLDCIFSHAQVAKKNQLVIMLIDELCGPDPSLSDELISILNELTQLSKSEHCKVALRARQILIASHLPSYELRHNQVESIFLSAIDMYGHQFCPENLKKLILSETTIFDVLPTFFYHANKVVCMASLEVYVRRGYIAYELNSLQHRQLPDGTCVVEFQFMLPSSHPNRMTVPISITNPDLLRHSTELFMDSGFSPLCQRMGAMVAFRRFEDFTRNFDEVISCFANVPKDTPLFSEARTSLYSEDDCKSLREEPIHILNVSIQCADHLEDEALVPILRTFVQSKKNILVDYGLRRITFLIAQEKEFPKFFTFRARDEFAEDRIYRHLEPALAFQLELNRMRNFDLTAVPCANHKMHLYLGAAKVKEGVEVTDHRFFIRAIIRHSDLITKEASFEYLQNEGERLLLEAMDELEVAFNNTSVRTDCNHIFLNFVPTVIMDPFKIEESVRYMVMRYGSRLWKLRVLQAEVKINIRQTTTGSAVPIRLFITNESGYYLDISLYKEVTDSRSGNIMFHSFGNKQGPQHGMLINTPYVTKDLLQAKRFQAQTLGTTYIYDFPEMFRQALFKLWGSPDKYPKDILTYTELVLDSQGQLVEMNRLPGGNEVGMVAFKMRFKTQEYPEGRDVIVIGNDITFRIGSFGPGEDLLYLRASEMARAEGIPKIYVAANSGARIGMAEEIKHMFHVAWVDPEDPHKGFKYLYLTPQDYTRISSLNSVHCKHIEEGGESRYMITDIIGKDDGLGVENLRGSGMIAGESSLAYEEIVTISLVTCRAIGIGAYLVRLGQRVIQVENSHIILTGASALNKVLGREVYTSNNQLGGVQIMHYNGVSHITVPDDFEGVYTILEWLSYMPKDNHSPVPIITPTDPIDREIEFLPSRAPYDPRWMLAGRPHPTLKGTWQSGFFDHGSFKEIMAPWAQTVVTGRARLGGIPVGVIAVETRTVEVAVPADPANLDSEAKIIQQAGQVWFPDSAYKTAQAVKDFNREKLPLMIFANWRGFSGGMKDMYDQVLKFGAYIVDGLRQYKQPILIYIPPYAELRGGSWVVIDATINPLCIEMYADKESRGGVLEPEGTVEIKFRKKDLIKSMRRIDPAYKKLMEQLGEPDLSDKDRKDLEGRLKAREDLLLPIYHQVAVQFADFHDTPGRMLEKGVISDILEWKTARTFLYWRLRRLLLEDQVKQEILQASGELSHVHIQSMLRRWFVETEGAVKAYLWDNNQVVVQWLEQHWQAGDGPRSTIRENITYLKHDSVLKTIRGLVEENPEVAVDCVIYLSQHISPAERAQVVHLLSTMDSPAST,6.5376020021010435 +Cc1nn(cc1Nc1ncc(Br)c(NCC(F)F)n1)C(C)(C)C#N,MASGSCQGCEEDEETLKKLIVRLNNVQEGKQIETLVQILEDLLVFTYSERASKLFQGKNIHVPLLIVLDSYMRVASVQQVGWSLLCKLIEVCPGTMQSLMGPQDVGNDWEVLGVHQLILKMLTVHNASVNLSVIGLKTLDLLLTSGKITLLILDEESDIFMLIFDAMHSFPANDEVQKLGCKALHVLFERVSEEQLTEFVENKDYMILLSALTNFKDEEEIVLHVLHCLHSLAIPCNNVEVLMSGNVRCYNIVVEAMKAFPMSERIQEVSCCLLHRLTLGNFFNILVLNEVHEFVVKAVQQYPENAALQISALSCLALLTETIFLNQDLEEKNENQENDDEGEEDKLFWLEACYKALTWHRKNKHVQEAACWALNNLLMYQNSLHEKIGDEDGHFPAHREVMLSMLMHSSSKEVFQASANALSTLLEQNVNFRKILLSKGIHLNVLELMQKHIHSPEVAESGCKMLNHLFEGSNTSLDIMAAVVPKILTVMKRHETSLPVQLEALRAILHFIVPGMPEESREDTEFHHKLNMVKKQCFKNDIHKLVLAALNRFIGNPGIQKCGLKVISSIVHFPDALEMLSLEGAMDSVLHTLQMYPDDQEIQCLGLSLIGYLITKKNVFIGTGHLLAKILVSSLYRFKDVAEIQTKGFQTILAILKLSASFSKLLVHHSFDLVIFHQMSSNIMEQKDQQFLNLCCKCFAKVAMDDYLKNVMLERACDQNNSIMVECLLLLGADANQAKEGSSLICQVCEKESSPKLVELLLNSGSREQDVRKALTISIGKGDSQIISLLLRRLALDVANNSICLGGFCIGKVEPSWLGPLFPDKTSNLRKQTNIASTLARMVIRYQMKSAVEEGTASGSDGNFSEDVLSKFDEWTFIPDSSMDSVFAQSDDLDSEGSEGSFLVKKKSNSISVGEFYRDAVLQRCSPNLQRHSNSLGPIFDHEDLLKRKRKILSSDDSLRSSKLQSHMRHSDSISSLASEREYITSLDLSANELRDIDALSQKCCISVHLEHLEKLELHQNALTSFPQQLCETLKSLTHLDLHSNKFTSFPSYLLKMSCIANLDVSRNDIGPSVVLDPTVKCPTLKQFNLSYNQLSFVPENLTDVVEKLEQLILEGNKISGICSPLRLKELKILNLSKNHISSLSENFLEACPKVESFSARMNFLAAMPFLPPSMTILKLSQNKFSCIPEAILNLPHLRSLDMSSNDIQYLPGPAHWKSLNLRELLFSHNQISILDLSEKAYLWSRVEKLHLSHNKLKEIPPEIGCLENLTSLDVSYNLELRSFPNEMGKLSKIWDLPLDELHLNFDFKHIGCKAKDIIRFLQQRLKKAVPYNRMKLMIVGNTGSGKTTLLQQLMKTKKSDLGMQSATVGIDVKDWPIQIRDKRKRDLVLNVWDFAGREEFYSTHPHFMTQRALYLAVYDLSKGQAEVDAMKPWLFNIKARASSSPVILVGTHLDVSDEKQRKACMSKITKELLNKRGFPAIRDYHFVNATEESDALAKLRKTIINESLNFKIRDQLVVGQLIPDCYVELEKIILSERKNVPIEFPVIDRKRLLQLVRENQLQLDENELPHAVHFLNESGVLLHFQDPALQLSDLYFVEPKWLCKIMAQILTVKVEGCPKHPKGIISRRDVEKFLSKKRKFPKNYMSQYFKLLEKFQIALPIGEEYLLVPSSLSDHRPVIELPHCENSEIIIRLYEMPYFPMGFWSRLINRLLEISPYMLSGRERALRPNRMYWRQGIYLNWSPEAYCLVGSEVLDNHPESFLKITVPSCRKGCILLGQVVDHIDSLMEEWFPGLLEIDICGEGETLLKKWALYSFNDGEEHQKILLDDLMKKAEEGDLLVNPDQPRLTIPISQIAPDLILADLPRNIMLNNDELEFEQAPEFLLGDGSFGSVYRAAYEGEEVAVKIFNKHTSLRLLRQELVVLCHLHHPSLISLLAAGIRPRMLVMELASKGSLDRLLQQDKASLTRTLQHRIALHVADGLRYLHSAMIIYRDLKPHNVLLFTLYPNAAIIAKIADYSIAQYCCRMGIKTSEGTPGFRAPEVARGNVIYNQQADVYSFGLLLYDILTTGGRIVEGLKFPNEFDELEIQGKLPDPVKEYGCAPWPMVEKLIKQCLKENPQERPTSAQVFDILNSAELVCLTRRILLPKNVIVECMVATHHNSRNASIWLGCGHTDRGQLSFLDLNTEGYTSEEVADSRILCLALVHLPVEKESWIVSGTQSGTLLVINTEDGKKRHTLEKMTDSVTCLYCNSFSKQSKQKNFLLVGTADGKLAIFEDKTVKLKGAAPLKILNIGNVSTPLMCLSESTNSTERNVMWGGCGTKIFSFSNDFTIQKLIETRTSQLFSYAAFSDSNIITVVVDTALYIAKQNSPVVEVWDKKTEKLCGLIDCVHFLREVMVKENKESKHKMSYSGRVKTLCLQKNTALWIGTGGGHILLLDLSTRRLIRVIYNFCNSVRVMMTAQLGSLKNVMLVLGYNRKNTEGTQKQKEIQSCLTVWDINLPHEVQNLEKHIEVRKELAEKMRRTSVE,7.522878745280337 +CN1CCN(CC1)c1nc2ccccc2c2-c3ccsc3CCc12,MEEQGIQCAPPPPATSQTGVPLANLSHNCSADDYIYQDSIALPWKVLLVALLALITLATTLSNAFVIATVYRTRKLHTPANYLIASLAVTDLLVSILVMPISTMYTVTGRWTLGQVVCDFWLSSDITCCTASIMHLCVIALDRYWAITDAVDYSAKRTPKRAAIMIVLVWVFSISISLPPFFWRQAKAEEEVLDCFVNTDHVLYTVYSTVGAFYLPTLLLIALYGRIYVEARSRILKQTPNKTGKRLTRAQLITDSPGSTSSVTSINSRVPEVPSESGSPVYVNQVKVRVSDALLEKKKLMAARERKATKTLGIILGAFIVCWLPFFIISLVMPICKDACWFHMAIFDFFNWLGYLNSLINPIIYTMSNEDFKQAFHKLIRFKCTG,5.823908740944319 +CCS(=O)(=O)N[C@@H]1C[C@@]2(C)O[C@]1(C)[C@H]1[C@@H]2C(=O)N(C1=O)c1ccc(C#N)c(c1)C(F)(F)F,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAPPGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLVLDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGPTFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGTSTISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAECKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYKSGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYGDLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGGGGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMDSYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASSTTSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,7.795880017344075 +FC(F)(F)Oc1ccc(C[C@H](NC(=O)c2cnn(n2)C2CCCCC2)C(=O)NC2(CC2)C#N)cc1Cl,MPRTEMVRFVRLPVVLLAMAACLASVALGSLHVEESLEMRFAAFKKKYGKVYKDAKEEAFRFRAFEENMEQAKIQAAANPYATFGVTPFSDMTREEFRARYRNGASYFAAAQKRLRKTVNVTTGRAPAAVDWREKGAVTPVKDQGQCGSCWAFSTIGNIEGQWQVAGNPLVSLSEQMLVSCDTIDFGCGGGLMDNAFNWIVNSNGGNVFTEASYPYVSGNGEQPQCQMNGHEIGAAITDHVDLPQDEDAIAAYLAENGPLAIAVDATSFMDYNGGILTSCTSEQLDHGVLLVGYNDSSNPPYWIIKNSWSNMWGEDGYIRIEKGTNQCLMNQAVSSAVVGGPTPPPPPPPPPSATFTQDFCEGKGCTKGCSHATFPTGECVQTTGVGSVIATCGASNLTQIIYPLSRSCSGLSVPITVPLDKCIPILIGSVEYHCSTNPPTKAARLVPHQ,7.920818753952375 +C[C@@]1(O)C[C@@H](C1)C#Cc1cncc(c1)[C@H]1NC(=O)O[C@@H]1c1cccc(F)c1,MVLLLILSVLLLKEDVRGSAQSSERRVVAHMPGDIIIGALFSVHHQPTVDKVHERKCGAVREQYGIQRVEAMLHTLERINSDPTLLPNITLGCEIRDSCWHSAVALEQSIEFIRDSLISSEEEEGLVRCVDGSSSSFRSKKPIVGVIGPGSSSVAIQVQNLLQLFNIPQIAYSATSMDLSDKTLFKYFMRVVPSDAQQARAMVDIVKRYNWTYVSAVHTEGNYGESGMEAFKDMSAKEGICIAHSYKIYSNAGEQSFDKLLKKLTSHLPKARVVACFCEGMTVRGLLMAMRRLGLAGEFLLLGSDGWADRYDVTDGYQREAVGGITIKLQSPDVKWFDDYYLKLRPETNHRNPWFQEFWQHRFQCRLEGFPQENSKYNKTCNSSLTLKTHHVQDSKMGFVINAIYSMAYGLHNMQMSLCPGYAGLCDAMKPIDGRKLLESLMKTNFTGVSGDTILFDENGDSPGRYEIMNFKEMGKDYFDYINVGSWDNGELKMDDDEVWSKKSNIIRSVCSEPCEKGQIKVIRKGEVSCCWTCTPCKENEYVFDEYTCKACQLGSWPTDDLTGCDLIPVQYLRWGDPEPIAAVVFACLGLLATLFVTVVFIIYRDTPVVKSSSRELCYIILAGICLGYLCTFCLIAKPKQIYCYLQRIGIGLSPAMSYSALVTKTNRIARILAGSKKKICTKKPRFMSACAQLVIAFILICIQLGIIVALFIMEPPDIMHDYPSIREVYLICNTTNLGVVTPLGYNGLLILSCTFYAFKTRNVPANFNEAKYIAFTMYTTCIIWLAFVPIYFGSNYKIITMCFSVSLSATVALGCMFVPKVYIILAKPERNVRSAFTTSTVVRMHVGDGKSSSAASRSSSLVNLWKRRGSSGETLRYKDRRLAQHKSEIECFTPKGSMGNGGRATMSSSNGKSVTWAQNEKSSRGQHLWQRLSIHINKKENPNQTAVIKPFPKSTESRGLGAGAGAGGSAGGVGATGGAGCAGAGPGGPESPDAGPKALYDVAEAEEHFPAPARPRSPSPISTLSHRAGSASRTDDDVPSLHSEPVARSSSSQGSLMEQISSVVTRFTANISELNSMMLSTAAPSPGVGAPLCSSYLIPKEIQLPTTMTTFAEIQPLPAIEVTGGAQPAAGAQAAGDAARESPAAGPEAAAAKPDLEELVALTPPSPFRDSVDSGSTTPNSPVSESALCIPSSPKYDTLIIRDYTQSSSSL,6.522878745280337 +CCn1c(nc2ccccc12)N1CCNCC1,MDPLNLSWYDDDLERQNWSRPFNGSEGKADRPHYNYYAMLLTLLIFIIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMIAIVWVLSFTISCPLLFGLNNTDQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRKRRKRVNTKRSSRAFRANLKTPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRMDAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSNPDSPAKPEKNGHAKIVNPRIAKFFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFMKILHC,6.0 +CC(C)c1c(O)c(O)c(C=O)c2c(O)c(c(C)cc12)-c1c(C)cc2c(C(C)C)c(O)c(O)c(C=O)c2c1O,MFGLKRNAVIGLNLYCGGAGLGAGSGGATRPGGRLLATEKEASARREIGGGEAGAVIGGSAGASPPSTLTPDSRRVARPPPIGAEVPDVTATPARLLFFAPTRRAAPLEEMEAPAADAIMSPEEELDGYEPEPLGKRPAVLPLLELVGESGNNTSTDGSLPSTPPPAEEEEDELYRQSLEIISRYLREQATGAKDTKPMGRSGATSRKALETLRRVGDGVQRNHETAFQGMLRKLDIKNEDDVKSLSRVMIHVFSDGVTNWGRIVTLISFGAFVAKHLKTINQESCIEPLAESITDVLVRTKRDWLVKQRGWDGFVEFFHVEDLEGGIRNVLLAFAGVAGVGAGLAYLIR,5.1842230797016375 +FC(F)(F)c1cccc(Sc2ccc3nnc(-c4ccn[nH]4)n3n2)c1,MASGSCQGCEEDEETLKKLIVRLNNVQEGKQIETLVQILEDLLVFTYSERASKLFQGKNIHVPLLIVLDSYMRVASVQQVGWSLLCKLIEVCPGTMQSLMGPQDVGNDWEVLGVHQLILKMLTVHNASVNLSVIGLKTLDLLLTSGKITLLILDEESDIFMLIFDAMHSFPANDEVQKLGCKALHVLFERVSEEQLTEFVENKDYMILLSALTNFKDEEEIVLHVLHCLHSLAIPCNNVEVLMSGNVRCYNIVVEAMKAFPMSERIQEVSCCLLHRLTLGNFFNILVLNEVHEFVVKAVQQYPENAALQISALSCLALLTETIFLNQDLEEKNENQENDDEGEEDKLFWLEACYKALTWHRKNKHVQEAACWALNNLLMYQNSLHEKIGDEDGHFPAHREVMLSMLMHSSSKEVFQASANALSTLLEQNVNFRKILLSKGIHLNVLELMQKHIHSPEVAESGCKMLNHLFEGSNTSLDIMAAVVPKILTVMKRHETSLPVQLEALRAILHFIVPGMPEESREDTEFHHKLNMVKKQCFKNDIHKLVLAALNRFIGNPGIQKCGLKVISSIVHFPDALEMLSLEGAMDSVLHTLQMYPDDQEIQCLGLSLIGYLITKKNVFIGTGHLLAKILVSSLYRFKDVAEIQTKGFQTILAILKLSASFSKLLVHHSFDLVIFHQMSSNIMEQKDQQFLNLCCKCFAKVAMDDYLKNVMLERACDQNNSIMVECLLLLGADANQAKEGSSLICQVCEKESSPKLVELLLNSGSREQDVRKALTISIGKGDSQIISLLLRRLALDVANNSICLGGFCIGKVEPSWLGPLFPDKTSNLRKQTNIASTLARMVIRYQMKSAVEEGTASGSDGNFSEDVLSKFDEWTFIPDSSMDSVFAQSDDLDSEGSEGSFLVKKKSNSISVGEFYRDAVLQRCSPNLQRHSNSLGPIFDHEDLLKRKRKILSSDDSLRSSKLQSHMRHSDSISSLASEREYITSLDLSANELRDIDALSQKCCISVHLEHLEKLELHQNALTSFPQQLCETLKSLTHLDLHSNKFTSFPSYLLKMSCIANLDVSRNDIGPSVVLDPTVKCPTLKQFNLSYNQLSFVPENLTDVVEKLEQLILEGNKISGICSPLRLKELKILNLSKNHISSLSENFLEACPKVESFSARMNFLAAMPFLPPSMTILKLSQNKFSCIPEAILNLPHLRSLDMSSNDIQYLPGPAHWKSLNLRELLFSHNQISILDLSEKAYLWSRVEKLHLSHNKLKEIPPEIGCLENLTSLDVSYNLELRSFPNEMGKLSKIWDLPLDELHLNFDFKHIGCKAKDIIRFLQQRLKKAVPYNRMKLMIVGNTGSGKTTLLQQLMKTKKSDLGMQSATVGIDVKDWPIQIRDKRKRDLVLNVWDFAGREEFYSTHPHFMTQRALYLAVYDLSKGQAEVDAMKPWLFNIKARASSSPVILVGTHLDVSDEKQRKACMSKITKELLNKRGFPAIRDYHFVNATEESDALAKLRKTIINESLNFKIRDQLVVGQLIPDCYVELEKIILSERKNVPIEFPVIDRKRLLQLVRENQLQLDENELPHAVHFLNESGVLLHFQDPALQLSDLYFVEPKWLCKIMAQILTVKVEGCPKHPKGIISRRDVEKFLSKKRKFPKNYMSQYFKLLEKFQIALPIGEEYLLVPSSLSDHRPVIELPHCENSEIIIRLYEMPYFPMGFWSRLINRLLEISPYMLSGRERALRPNRMYWRQGIYLNWSPEAYCLVGSEVLDNHPESFLKITVPSCRKGCILLGQVVDHIDSLMEEWFPGLLEIDICGEGETLLKKWALYSFNDGEEHQKILLDDLMKKAEEGDLLVNPDQPRLTIPISQIAPDLILADLPRNIMLNNDELEFEQAPEFLLGDGSFGSVYRAAYEGEEVAVKIFNKHTSLRLLRQELVVLCHLHHPSLISLLAAGIRPRMLVMELASKGSLDRLLQQDKASLTRTLQHRIALHVADGLRYLHSAMIIYRDLKPHNVLLFTLYPNAAIIAKIADYGIAQYCCRMGIKTSEGTPGFRAPEVARGNVIYNQQADVYSFGLLLYDILTTGGRIVEGLKFPNEFDELEIQGKLPDPVKEYGCAPWPMVEKLIKQCLKENPQERPTSAQVFDILNSAELVCLTRRILLPKNVIVECMVATHHNSRNASIWLGCGHTDRGQLSFLDLNTEGYTSEEVADSRILCLALVHLPVEKESWIVSGTQSGTLLVINTEDGKKRHTLEKMTDSVTCLYCNSFSKQSKQKNFLLVGTADGKLAIFEDKTVKLKGAAPLKILNIGNVSTPLMCLSESTNSTERNVMWGGCGTKIFSFSNDFTIQKLIETRTSQLFSYAAFSDSNIITVVVDTALYIAKQNSPVVEVWDKKTEKLCGLIDCVHFLREVMVKENKESKHKMSYSGRVKTLCLQKNTALWIGTGGGHILLLDLSTRRLIRVIYNFCNSVRVMMTAQLGSLKNVMLVLGYNRKNTEGTQKQKEIQSCLTVWDINLPHEVQNLEKHIEVRKELAEKMRRTSVE,7.275724130399211 +CCN1CC[C@@]2(Cc3[nH]c(C(=O)N(C)C)c(C)c3C[C@H]2C1)c1cccc(O)c1,MESPIQIFRGDPGPTCSPSACLLPNSSSWFPNWAESDSNGSVGSEDQQLESAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSAVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLASSVGISAIVLGGTKVREDVDVIECSLQFPDDEYSWWDLFMKICVFVFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITKLVLVVVAVFIICWTPIHIFILVEALGSTSHSTAALSSYYFCIALGYTNSSLNPVLYAFLDENFKRCFRDFCFPIKMRMERQSTNRVRNTVQDPASMRDVGGMNKPV,6.0 +COc1cc(Br)c2OC[C@H]3C[C@@H](N)Cc1c23,MALSYRVSELQSTIPEHILQSTFVHVISSNWSGLQTESIPEEMKQIVEEQGNKLHWAALLILMVIIPTIGGNTLVILAVSLEKKLQYATNYFLMSLAVADLLVGLFVMPIALLTIMFEAMWPLPLVLCPAWLFLDVLFSTASIMHLCAISVDRYIAIKKPIQANQYNSRATAFIKITVVWLISIGIAIPVPIKGIETDVDNPNNITCVLTKERFGDFMLFGSLAAFFTPLAIMIVTYFLTIHALQKKAYLVKNKPPQRLTWLTVSTVFQRDETPCSSPEKVAMLDGSRKDKALPNSGDETLMRRTSTIGKKSVQTISNEQRASKVLGIVFFLFLLMWCPFFITNITLVLCDSCNQTTLQMLLEIFVWIGYVSSGVNPLVYTLFNKTFRDAFGRYITCNYRATKSVKTLRKRSSKIYFRNPMAENSKFFKKHGIRNGINPAMYQSPMRLRSSTIQSSSIILLDTLLLTENEGDKTEEQVSYV,6.580044251510242 +COc1ccc(cc1)S(=O)(=O)NC(=O)c1ccc(Cl)cc1Cl,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,6.455931955649724 +Cn1cc(cn1)C(NC(=O)c1ccc2cnc(NC3CCOCC3)nc2c1)c1ccc(OC(F)F)cc1,GAGPEMVRGQVFDVGPRYTNLSYIGEGAYGMVCSAYDNVNKVRVAIKKISPFEHQTYCQRTLREIKILLRFRHENIIGINDIIRAPTIEQMKDVYIVQDLMETDLYKLLKTQHLSNDHICYFLYQILRGLKYIHSANVLHRDLKPSNLLLNTTCDLKICDFGLARVADPDHDHTGFLTEYVATRWYRAPEIMLNSKGYTKSIDIWSVGCILAEMLSNRPIFPGKHYLDQLNHILGILGSPSQEDLNCIINLKARNYLLSLPHKNKVPWNRLFPNADSKALDLLDKMLTFNPHKRIEVEQALAHPYLEQYYDPSDEPIAEAPFKFDMELDDLPKEKLKELIFEETARFQPGYRS,7.91721462968355 +O=C(NCC1CC11CCN(CC1)C(=O)c1n[nH]c2ccccc12)c1cc2ccncc2o1,MNPAAEAEFNILLATDSYKVTHYKQYPPNTSKVYSYFECREKKTENSKLRKVKYEETVFYGLQYILNKYLKGKVVTKEKIQEAKDVYKEHFQDDVFNEKGWNYILEKYDGHLPIEIKAVPEGFVIPRGNVLFTVENTDPECYWLTNWIETILVQSWYPITVATNSREQKKILAKYLLETSGNLDGLEYKLHDFGYRGVSSQETAGIGASAHLVNFKGTDTVAGLALIKKYYGTKDPVPGYSVPAAEHSTITAWGKDHEKDAFEHIVTQFSSVPVSVVSDSYDIYNACEKIWGEDLRHLIVSRSTQAPLIIRPDSGNPLDTVLKVLEILGKKFPVTENSKGYKLLPPYLRVIQGDGVDINTLQEIVEGMKQKMWSIENIAFGSGGGLLQKLTRDLLNCSFKCSYVVTNGLGINVFKDPVADPNKRSKKGRLSLHRTPAGNFVTLEEGKGDLEEYGQDLLHTVFKNGKVTKSYSFDEIRKNAQLNIELEAAHH,7.188424994129407 +C[C@@H]1CC(=O)Nc2cccc(-c3ccc(cc3)C(=O)N3CCCC3)c2N1,STNPPPPETSNPNKPKRQTNQLQYLLRVVLKTLWKHQFAWPFQQPVDAVKLNLPDYYKIIKTPMDMGTIKKRLENNYYWNAQECIQDFNTMFTNCYIYNKPGDDIVLMAEALEKLFLQKINELPTEE,4.758254347429356 +CCCc1sc(nc1CSc1nc(N)cc(N)n1)-c1cc(F)cc(F)c1,MATPPKRFCPSPSTSSEGTRIKKISIEGNIAAGKSTFVNILKQASEDWEVVPEPVARWCNVQSTQEEFEELTTSQKSGGNVLQMMYEKPERWSFTFQSYACLSRIRAQLASLNGKLKDAEKPVLFFERSVYSDRYIFASNLYESDCMNETEWTIYQDWHDWMNSQFGQSLELDGIIYLRATPEKCLNRIYLRGRNEEQGIPLEYLEKLHYKHESWLLHRTLKTSFDYLQEVPVLTLDVNEDFKDKHESLVEKVKEFLSTL,6.414539270491499 +O=C1CC2(CCC(CC2)OCc2ccccc2)OC=C1c1ccccc1,MQWAVGRRWAWAALLLAVAAVLTQVVWLWLGTQSFVFQREEIAQLARQYAGLDHELAFSRLIVELRRLHPGHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSRGHSGRYWAEISDTIISGTFHQWREGTTKSEVFYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLAFALADTVFSTQDFLTLFYTLRSYARGLRLELTTYLFGQDP,5.1249387366083 +NS(=O)(=O)N1CCCCCC1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,6.882728704344236 +CC(O)c1cc(cc2c3CC[C@H](CC(O)=O)c3n(Cc3ccc(Cl)cc3)c12)S(C)(=O)=O,MKETRGYGGDAPFCTRLNHSYTGMWAPERSAEARGNLTRPPGSGEDCGSVSVAFPITMLLTGFVGNALAMLLVSRSYRRRESKRKKSFLLCIGWLALTDLVGQLLTTPVVIVVYLSKQRWEHIDPSGRLCTFFGLTMTVFGLSSLFIASAMAVERALAIRAPHWYASHMKTRATRAVLLGVWLAVLAFALLPVLGVGQYTVQWPGTWCFISTGRGGNGTSSSHNWGNLFFASAFAFLGLLALTVTFSCNLATIKALVSRCRAKATASQSSAQWGRITTETAIQLMGIMCVLSVCWSPLLIMMLKMIFNQTSVEHCKTHTEKQKECNFFLIAVRLASLNQILDPWVYLLLRKILLRKFCQIRYHTNNYASSSTSLPCQCSSTLMWSDHLER,4.698970004336019 +COC(=O)N1CCc2nc(N3CCC(CC3)Oc3ccc(F)cc3F)c(NC(C)C)nc2C1,MNASAASLNDSQVVVVAAEGAAAAATAAGGPDTGEWGPPAAAALGAGGGANGSLELSSQLSAGPPGLLLPAVNPWDVLLCVSGTVIAGENALVVALIASTPALRTPMFVLVGSLATADLLAGCGLILHFVFQYLVPSETVSLLTVGFLVASFAASVSSLLAITVDRYLSLYNALTYYSRRTLLGVHLLLAATWTVSLGLGLLPVLGWNCLAERAACSVVRPLARSHVALLSAAFFMVFGIMLHLYVRICQVVWRHAHQIALQQHCLAPPHLAATRKGVGTLAVVLGTFGASWLPFAIYCVVGSHEDPAVYTYATLLPATYNSMINPIIYAFRNQEIQRALWLLLCGCFQSKVPFRSRSPSEV,3.8877302315827293 +COc1nc(cnc1CNC[C@@H]1CCC(=O)N1)-c1cccc(c1Cl)-c1cccc(c1Cl)-c1cnc(CN2CC[C@H]3CNC(=O)[C@@H]23)c(OC)n1,LDSPDRPWNPPTFSPALLVVTEGDNATFTCSFSNTSESFVLNWYRMSPSNQTDKLAAFPEDRSQPGQDCRFRVTQLPNGRDFHMSVVRARRNDSGTYLCGAISLAPKAQIKESLRAELRVTERRAEVPTAHPSPSPRPAGQFQ,9.468521082957745 +CC[C@H](C)[C@H](NC(=O)[C@@H]1CCCCN1C(=O)[C@@H](C1CCCCC1)c1cc(OC)c(OC)c(OC)c1)C(N)=O,MTTDEGAKNNEESPTATVAEQGEDITSKKDRGVLKIVKRVGNGEETPMIGDKVYVHYKGKLSNGKKFDSSHDRNEPFVFSLGKGQVIKAWDIGVATMKKGEICHLLCKPEYAYGSAGSLPKIPSNATLFFEIELLDFKGEDLFEDGGIIRRTKRKGEGYSNPNEGATVEIHLEGRCGGRMFDCRDVAFTVGEGEDHDIPIGIDKALEKMQREEQCILYLGPRYGFGEAGKPKFGIEPNAELIYEVTLKSFEKAKESWEMDTKEKLEQAAIVKEKGTVYFKGGKYMQAVIQYGKIVSWLEMEYGLSEKESKASESFLLAAFLNLAMCYLKLREYTKAVECCDKALGLDSANEKGLYRRGEAQLLMNEFESAKGDFEKVLEVNPQNKAARLQISMCQKKAKEHNERDRRIYANMFKKFAEQDAKEEANKAMGKKTSEGVTNEKGTDSQAMEEEKPEGHV,5.1487416512809245 +Cn1cc2c(n1)nc(N(C(=O)c1ccccc1)C(=O)c1ccccc1)n1nc(nc21)-c1ccc(Cl)cc1,MLLETQDALYVALELVIAALSVAGNVLVCAAVGTANTLQTPTNYFLVSLAAADVAVGLFAIPFAITISLGFCTDFYGCLFLACFVLVLTQSSIFSLLAVAVDRYLAICVPLRYKSLVTGTRARGVIAVLWVLAFGIGLTPFLGWNSKDSATNNCTEPWDGTTNESCCLVKCLFENVVPMSYMVYFNFFGCVLPPLLIMLVIYIKIFLVACRQLQRTELMDHSRTTLQREIHAAKSLAMIVGIFALCWLPVHAVNCVTLFQPAQGKNKPKWAMNMAILLSHANSVVNPIVYAYRNRDFRYTFHKIISRYLLCQADVKSGNGQAGVQPALGVGL,5.0 +Nc1nc(N)c2nc(-c3cccc(O)c3)c(nc2n1)-c1cccc(O)c1,MEHIQGAWKTISNGFGFKDAVFDGSSCISPTIVQQFGYQRRASDDGKLTDPSKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARLDWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPTMCVDWSNIRQLLLFPNSTIGDSGVPALPSLTMRRMRESVSRMPVSSQHRYSTPHAFTFNTSSPSSEGSLSQRQRSTSTPNVHMVSTTLPVDSRMIEDAIRSHSESASPSALSSSPNNLSPTGWSQPKTPVPAQRERAPVSGTQEKNKIRPRGQRDSSYYWEIEASEVMLSTRIGSGSFGTVYKGKWHGDVAVKILKVVDPTPEQFQAFRNEVAVLRKTRHVNILLFMGYMTKDNLAIVTQWCEGSSLYKHLHVQETKFQMFQLIDIARQTAQGMDYLHAKNIIHRDMKSNNIFLHEGLTVKIGDFGLATVKSRWSGSQQVEQPTGSVLWMAPEVIRMQDNNPFSFQSDVYSYGIVLYELMTGELPYSHINNRDQIIFMVGRGYASPDLSKLYKNCPKAMKRLVADCVKKVKEERPLFPQILSSIELLQHSLPKINRSASEPSLHRAAHTEDINACTLTTSPRLPVF,5.0 +Oc1ccc2c(ccnc2c1)-c1c2CCCn2nc1-c1ccccn1,AVAAPRPRLLLLVLAAAAAAAAALLPGATALQCFCHLCTKDNFTCVTDGLCFVSVTETTDKVIHNSMCIAEIDLIPRDRPFVCAPSSKTGSVTTTYCCNQDHCNKIELPTTVKSSPGLGPVELAAVIAGPVCFVCISLMLMVYICHNRTVIHHRVPNEEDPSLDRPFISEGTTLKDLIYDMTTSGSGSGLPLLVQRTIARDIVLQESIGKGRFGEVWRGKWRGEEVAVKIFSSREERSWFREAEIYQTVMLRHENILGFIAADNKDNGTWTQLWLVSDYHEHGSLFDYLNRYTVTVEGMIKLALSTASGLAHLHMEIVGTQGKPAIAHRDLKSKNILVKKNGTCCIADLGLAVRHDSATDTIDIAPNHRVGTKRYMAPEVLDDSINMKHFESFKRADIYAMGLVFWEIARRCSIGGIHEDYQLPYYDLVPSDPSVEEMRKVVCEQKLRPNIPNRWQSCEALRVMAKIMRECWYANGAARLTALRIKKTLSQLSQQEGIKM,6.7447274948966935 +Cc1ccc(cc1NC(=O)c1cnn(c1N)-c1ccccc1F)C(=O)Nc1ccon1,MNNFILLEEQLIKKSQQKRRTSPSNFKVRFFVLTKASLAYFEDRHGKKRTLKGSIELSRIKCVEIVKSDISIPCHYKYPFQVVHDNYLLYVFAPDRESRQRWVLALKEETRNNNSLVPKYHPNFWMDGKWRCCSQLEKLATGCAQYDPTKNASKKPLPPTPEDNRRPLWEPEETVVIALYDYQTNDPQELALRRNEEYCLLDSSEIHWWRVQDRNGHEGYVPSSYLVEKSPNNLETYEWYNKSISRDKAEKLLLDTGKEGAFMVRDSRTAGTYTVSVFTKAVVSENNPCIKHYHIKETNDNPKRYYVAEKYVFDSIPLLINYHQHNGGGLVTRLRYPVCFGRQKAPVTAGLRYGKWVIDPSELTFVQEIGSGQFGLVHLGYWLNKDKVAIKTIREGAMSEEDFIEEAEVMMKLSHPKLVQLYGVCLEQAPICLVFEFMEHGCLSDYLRTQRGLFAAETLLGMCLDVCEGMAYLEEACVIHRDLAARNCLVGENQVIKVSDFGMTRFVLDDQYTSSTGTKFPVKWASPEVFSFSRYSSKSDVWSFGVLMWEVFSEGKIPYENRSNSEVVEDISTGFRLYKPRLASTHVYQIMNHCWKERPEDRPAFSRLLRQLAEIAESGL,4.301029995663981 +Nc1n[nH]c2cccc(-c3ccc(NS(=O)(=O)c4ccccc4)cc3)c12,MRGARGAWDFLCVLLLLLRVQTGSSQPSVSPGEPSPPSIHPGKSDLIVRVGDEIRLLCTDPGFVKWTFEILDETNENKQNEWITEKAEATNTGKYTCTNKHGLSNSIYVFVRDPAKLFLVDRSLYGKEDNDTLVRCPLTDPEVTNYSLKGCQGKPLPKDLRFIPDPKAGIMIKSVKRAYHRLCLHCSVDQEGKSVLSEKFILKVRPAFKAVPVVSVSKASYLLREGEEFTVTCTIKDVSSSVYSTWKRENSQTKLQEKYNSWHHGDFNYERQATLTISSARVNDSGVFMCYANNTFGSANVTTTLEVVDKGFINIFPMINTTVFVNDGENVDLIVEYEAFPKPEHQQWIYMNRTFTDKWEDYPKSENESNIRYVSELHLTRLKGTEGGTYTFLVSNSDVNAAIAFNVYVNTKPEILTYDRLVNGMLQCVAAGFPEPTIDWYFCPGTEQRCSASVLPVDVQTLNSSGPPFGKLVVQSSIDSSAFKHNGTVECKAYNDVGKTSAYFNFAFKGNNKEQIHPHTLFTPLLIGFVIVAGMMCIIVMILTYKYLQKPMYEVQWKVVEEINGNNYVYIDPTQLPYDHKWEFPRNRLSFGKTLGAGAFGKVVEATAYGLIKSDAAMTVAVKMLKPSAHLTEREALMSELKVLSYLGNHMNIVNLLGACTIGGPTLVITEYCCYGDLLNFLRRKRDSFICSKQEDHAEAALYKNLLHSKESSCSDSTNEYMDMKPGVSYVVPTKADKRRSVRIGSYIERDVTPAIMEDDELALDLEDLLSFSYQVAKGMAFLASKNCIHRDLAARNILLTHGRITKICDFGLARDIKNDSNYVVKGNARLPVKWMAPESIFNCVYTFESDVWSYGIFLWELFSLGSSPYPGMPVDSKFYKMIKEGFRMLSPEHAPAEMYDIMKTCWDADPLKRPTFKQIVQLIEKQISESTNHIYSNLANCSPNRQKPVVDHSVRINSVGSTASSSQPLLVHDDV,4.950781977329818 +CCOc1ccc(cc1)C1=Nn2c(SC1)nnc2-c1ccccc1OC,MDVLSPGQGNNTTSPPAPFETGGNTTGISDVTVSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVKKVEKTGADTRHGASPAPQPKKSVNGESGSRNWRLGVESKAGGALCANGAVRQGDDGAALEVIEVHRVGNSKEHLPLPSEAGPTPCAPASFERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPTLLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRQ,4.6020599913279625 +Oc1ccc2C(=O)\C(Oc2c1)=C\c1ccc(OCCN2CCCC2)cc1,EEDIIITTKNGKVRGMNLPVLGGTVTAFLGIPYAQPPLGRLRFKKPQSLTKWSNIWNATKYANSCYQNTDQSFPGFLGSEMWNPNTELSEDCLYLNVWIPAPKPKNATVMIWIYGGGFQTGTSSLPVYDGKFLARVERVIVVSMNYRVGALGFLALSENPEAPGNMGLFDQQLALQWVQKNIAAFGGNPRSVTLFGESAGAASVSLHLLSPRSQPLFTRAILQSGSSNAPWAVTSLYEARNRTLTLAKRMGCSRDNETEMIKCLRDKDPQEILLNEVFVVPYDTLLSVNFGPTVDGDFLTDMPDTLLQLGQFKRTQILVGVNKDEGTAFLVYGAPGFSKDNNSIITRKEFQEGLKIFFPRVSEFGRESILFHYMDWLDDQRAENYREALDDVVGDYNIICPALEFTRKFSELGNDAFFYYFEHRSTKLPWPEWMGVMHGYEIEFVFGLPLERRVNYTRAEEILSRSIMKRWANFAKYGNPNGTQNNSTRWPVFKSTEQKYLTLNTESPKVYTKLRAQQCRFWTLFFPKVLELTGNIDEAEREWKAGFHRWNNYMMDWKNQFNDYTSKKESCSDF,4.0 +NC(=O)c1cc2cc(Br)c(nc2nc1N)C(F)(F)F,MDSLVVLVLCLSCLLLLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKDISKSLTNLSKVYGPVFTLYFGLKPIVVLHGYEAVKEALIDLGEEFSGRGIFPLAERANRGFGIVFSNGKKWKEIRRFSLMTLRNFGMGKRSIEDRVQEEARCLVEELRKTKASPCDPTFILGCAPCNVICSIIFHKRFDYKDQQFLNLMEKLNENIKILSSPWIQICNNFSPIIDYFPGTHNKLLKNVAFMKSYILEKVKEHQESMDMNNPQDFIDCFLMKMEKEKHNQPSEFTIESLENTAVDLFGAGTETTSTTLRYALLLLLKHPEVTAKVQEEIERVIGRNRSPCMQDRSHMPYTDAVVHEVQRYIDLLPTSLPHAVTCDIKFRNYLIPKGTTILISLTSVLHDNKEFPNPEMFDPHHFLDEGGNFKKSKYFMPFSAGKRICVGEALAGMELFLFLTSILQNFNLKSLVDPKNLDTTPVVNGFASVPPFYQLCFIPV,4.301029995663981 +COc1ccccc1C1C(C(=O)c2cc3ccccc3o2)C(=O)C(=O)N1c1cc(C)on1,MAQRADMLRGLSPRESSLALNYAAGPRGIIDLSQVPHLPVLVPPTPGTPATAMDRLAYLPTAPQPFSSRHSSSPLSPGGPTHLTKPTTTSSSERERDRDRERDRDREREKSILTSTTTVEHAPIWRPGTEQSSGSSGGGGGSSSRPASHSHAHQHSPISPRTQDALQQRPSVLHNTGMKGIITAVEPSTPTVLRSTSTSSPVRPAATFPPATHCPLGGTLDGVYPTLMEPVLLPKEAPRVARPERPRADTGHAFLAKPPARSGLEPASSPSKGSEPRPLVPPVSGHATIARTPAKNLAPHHASPDPPAPPASASDPHREKTQSKPFSIQELELRSLGYHGSSYSPEGVEPVSPVSSPSLTHDKGLPKHLEELDKSHLEGELRPKQPGPVKLGGEAAHLPHLRPLPESQPSSSPLLQTAPGVKGHQRVVTLAQHISEVITQDYTRHHPQQLSAPLPAPLYSFPGASCPVLDLRRPPSDLYLPPPDHGAPARGSPHSEGGKRSPEPNKTSVLGGGEDGIEPVSPPEGMTEPGHSRSAVYPLLYRDGEQTEPSRMGSKSPGNTSQPPAFFSKLTESNSAMVKSKKQEINKKLNTHNRNEPEYNISQPGTEIFNMPAITGTGLMTYRSQAVQEHASTNMGLEAIIRKALMGGGGKAKVSGRPSSRKAKSPAPGLASGDRPPSVSSVHSEGDCNRRTPLTNRVWEDRPSSAGSTPFPYNPLIMRLQAGVMASPPPPGLPAGSGPLAGPHHAWDEEPKPLLCSQYETLSDSE,5.207398218835033 +CN1CCC[C@@H]1Cn1nc(Cc2ccc(Cl)cc2)c2ncccc2c1=O,MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCNDGFCELCGYSRAEVMQRPCTCDFLHGPRTQRRAAAQIAQALLGAEERKVEIAFYRKDGSCFLCLVDVVPVKNEDGAVIMFILNFEVVMEKDMVGSPAHDTNHRGPPTSWLAPGRAKTFRLKLPALLALTARESSVRSGGAGGAGAPGAVVVDVDLTPAAPSSESLALDEVTAMDNHVAGLGPAEERRALVGPGSPPRSAPGQLPSPRAHSLNPDASGSSCSLARTRSRESCASVRRASSADDIEAMRAGVLPPPPRHASTGAMHPLRSGLLNSTSDSDLVRYRTISKIPQITLNFVDLKGDPFLASPTSDREIIAPKIKERTHNVTEKVTQVLSLGADVLPEYKLQAPRIHRWTILHYSPFKAVWDWLILLLVIYTAVFTPYSAAFLLKETEEGPPATECGYACQPLAVVDLIVDIMFIVDILINFRTTYVNANEEVVSHPGRIAVHYFKGWFLIDMVAAIPFDLLIFGSGSEELIGLLKTARLLRLVRVARKLDRYSEYGAAVLFLLMCTFALIAHWLACIWYAIGNMEQPHMDSRIGWLHNLGDQIGKPYNSSGLGGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLIGSLMYASIFGNVSAIIQRLYSGTARYHTQMLRVREFIRFHQIPNPLRQRLEEYFQHAWSYTNGIDMNAVLKGFPECLQADICLHLNRSLLQHCKPFRGATKGCLRALAMKFKTTHAPPGDTLVHAGDLLTALYFISRGSIEILRGDVVVAILGKNDIFGEPLNLYARPGKSNGDVRALTYCDLHKIHRDDLLEVLDMYPEFSDHFWSSLEITFNLRDTNMIPGSPGSTELEGGFSRQRKRKLSFRRRTDKDTEQPGEVSALGPGRAGAGPSSRGRPGGPWGESPSSGPSSPESSEDEGPGRSSSPLRLVPFSSPRPPGEPPGGEPLMEDCEKSSDTCNPLSGAFSGVSNIFSFWGDSRGRQYQELPRCPAPTPSLLNIPLSSPGRRPRGDVESRLDALQRQLNRLETRLSADMATVLQLLQRQMTLVPPAYSAVTTPGPGPTSTSPLLPVSPLPTLTLDSLSQVSQFMACEELPPGAPELPQEGPTRRLSLPGQLGALTSQPLHRHGSDPGS,6.799998134593398 +COc1cc(OC)cc(\C=C\C(=O)c2ccncc2)c1,MALSQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKNPHLALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDGQSLTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELMAGPGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFPILRYLPNPALQRFKAFNQRFLWFLQKTVQEHYQDFDKNSVRDITGALFKHSKKGPRASGNLIPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLSDRPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPELWEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLEFSVPPGVKVDLTPIYGLTMKHARCEHVQARLRFSIN,7.552841968657781 +CC1(C)SSC(C)(C)C(NC(=O)C(N)Cc2ccc(O)cc2)C(=O)NCC(=O)NC(Cc2ccccc2)C(=O)NC1C(O)=O,MELVPSARAELQSSPLVNLSDAFPSAFPSAGANASGSPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKLKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTQPRDGAVVCMLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDINRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRTPCGRQEPGSLRRPRQATTRERVTACTPSDGPGGGAAA,8.468521082957745 +Cc1nc2n(Cc3ccco3)c(=O)n(C)c(=O)c2[nH]1,MALSQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKNPHLALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDGQSLTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELMAGPGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFPILRYLPNPALQRFKAFNQRFLWFLQKTVQEHYQDFDKNSVRDITGALFKHSKKGPRASGNLIPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLSDRPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPELWEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLEFSVPPGVKVDLTPIYGLTMKHARCEHVQARLRFSIN,5.3448615651886175 +CCNC(=O)Nc1cccc(c1)-n1c(nc2cccc(Cl)c2c1=O)[C@H](COCc1ccccc1)Nc1ncnc(N)c1C#N,MELENYKQPVVLREDNCRRRRRMKPRSAAASLSSMELIPIEFVLPTSQRKCKSPETALLHVAGHGNVEQMKAQVWLRALETSVAADFYHRLGPHHFLLLYQKKGQWYEIYDKYQVVQTLDCLRYWKATHRSPGQIHLVQRHPPSEESQAFQRQLTALIGYDVTDVSNVHDDELEFTRRGLVTPRMAEVASRDPKLYAMHPWVTSKPLPEYLWKKIANNCIFIVIHRSTTSQTIKVSPDDTPGAILQSFFTKMAKKKSLMDIPESQSEQDFVLRVCGRDEYLVGETPIKNFQWVRHCLKNGEEIHVVLDTPPDPALDEVRKEEWPLVDDCTGVTGYHEQLTIHGKDHESVFTVSLWDCDRKFRVKIRGIDIPVLPRNTDLTVFVEANIQHGQQVLCQRRTSPKPFTEEVLWNVWLEFSIKIKDLPKGALLNLQIYCGKAPALSSKASAESPSSESKGKVQLLYYVNLLLIDHRFLLRRGEYVLHMWQISGKGEDQGSFNADKLTSATNPDKENSMSISILLDNYCHPIALPKHQPTPDPEGDRVRAEMPNQLRKQLEAIIATDPLNPLTAEDKELLWHFRYESLKHPKAYPKLFSSVKWGQQEIVAKTYQLLARREVWDQSALDVGLTMQLLDCNFSDENVRAIAVQKLESLEDDDVLHYLLQLVQAVKFEPYHDSALARFLLKRGLRNKRIGHFLFWFLRSEIAQSRHYQQRFAVILEAYLRGCGTAMLHDFTQQVQVIEMLQKVTLDIKSLSAEKYDVSSQVISQLKQKLENLQNSQLPESFRVPYDPGLKAGALAIEKCKVMASKKKPLWLEFKCADPTALSNETIGIIFKHGDDLRQDMLILQILRIMESIWETESLDLCLLPYGCISTGDKIGMIEIVKDATTIAKIQQSTVGNTGAFKDEVLNHWLKEKSPTEEKFQAAVERFVYSCAGYCVATFVLGIGDRHNDNIMITETGNLFHIDFGHILGNYKSFLGINKERVPFVLTPDFLFVMGTSGKKTSPHFQKFQDICVKAYLALRHHTNLLIILFSMMLMTGMPQLTSKEDIEYIRDALTVGKNEEDAKKYFLDQIEVCRDKGWTVQFNWFLHLVLGIKQGEKHSA,2.0 +NCc1cccc(Nc2n[nH]c3ncnc(Nc4cccc(O)c4)c23)c1,MHSWERLAVLVLLGAAACAAPPRGRILGGREAEAHARPYMASVQLNGAHLCGGVLVAEQWVLSAAHCLEDAADGKVQVLLGAHSLSQPEPSKRLYDVLRAVPHPDSQPDTIDHDLLLLQLSEKATLGPAVRPLPWQRVDRDVAPGTLCDVAGWGIVNHAGRRPDSLQHVLLPVLDRATCNRRTHHDGAITERLMCAESNRRDSCKGDSGGPLVCGGVLEGVVTSGSRVCGNRKKPGIYTRVASYAAWIDSVLA,4.698970004336019 +COc1cccc(c1)[C@@]1(O)C[C@@H]2CN(C[C@@H]2C1)C(=O)Nc1cc(C)ccc1OC,MKPRAECCSPKFWLVLAVLAVSGSRARSQKSPPSIGIAVILVGTSDEVAIKDAHEKDDFHHLSVVPRVELVAMNETDPKSIITRICDLMSDRKIQGVVFADDTDQEAIAQILDFISAQTLTPILGIHGGSSMIMADKDESSMFFQFGPSIEQQASVMLNIMEEYDWYIFSIVTTYFPGYQDFVNKIRSTIENSFVGWELEEVLLLDMSLDDGDSKIQNQLKKLQSPIILLYCTKEEATYIFEVANSVGLTGYGYTWIVPSLVAGDTDTVPAEFPTGLISVSYDEWDYGLPARVRDGIAIITTAASDMLSEHSFIPEPKSSCYNTHEKRIYQSNMLNRYLINVTFEGRNLSFSEDGYQMHPKLVIILLNKERKWERVGKWKDKSLQMKYYVWPRMCPETEEQEDDHLSIVTLEEAPFVIVESVDPLSGTCMRNTVPCQKRIVTENKTDEEPGYIKKCCKGFCIDILKKISKSVKFTYDLYLVTNGKHGKKINGTWNGMIGEVVMKRAYMAVGSLTINEERSEVVDFSVPFIETGISVMVSRSNGTVSPSAFLEPFSADVWVMMFVMLLIVSAVAVFVFEYFSPVGYNRCLADGREPGGPSFTIGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANLAAFMIQEEYVDQVSGLSDKKFQRPNDFSPPFRFGTVPNGSTERNIRNNYAEMHAYMGKFNQRGVDDALLSLKTGKLDAFIYDAAVLNYMAGRDEGCKLVTIGSGKVFASTGYGIAIQKDSGWKRQVDLAILQLFGDGEMEELEALWLTGICHNEKNEVMSSQLDIDNMAGVFYMLGAAMALSLITFICEHLFYWQFRHCFMGVCSGKPGMVFSISRGIYSCIHGVAIEERQSVMNSPTATMNNTHSNILRLLRTAKNMANLSGVNGSPQSALDFIRRESSVYDISEHRRSFTHSDCKSYNNPPCEENLFSDYISEVERTFGNLQLKDSNVYQDHYHHHHRPHSIGSASSIDGLYDCDNPPFTTQSRSISKKPLDIGLPSSKHSQLSDLYGKFSFKSDRYSGHDDLIRSDVSDISTHTVTYGNIEGNAAKRRKQQYKDSLKKRPASAKSRREFDEIELAYRRRPPRSPDHKRYFRDKEGLRDFYLDQFRTKENSPHWEHVDLTDIYKERSDDFKRDSVSGGGPCTNRSHIKHGTGDKHGVVSGVPAPWEKNLTNVEWEDRSGGNFCRSCPSKLHNYSTTVTGQNSGRQACIRCEACKKAGNLYDISEDNSLQELDQPAAPVAVTSNASTTKYPQSPTNSKAQKKNRNKLRRQHSYDTFVDLQKEEAALAPRSVSLKDKGRFMDGSPYAHMFEMSAGESTFANNKSSVPTAGHHHHNNPGGGYMLSKSLYPDRVTQNPFIPTFGDDQCLLHGSKSYFFRQPTVAGASKARPDFRALVTNKPVVSALHGAVPARFQKDICIGNQSNPCVPNNKNPRAFNGSSNGHVYEKLSSIESDV,5.0 +COC[C@@H](C)Oc1nc(cc(n1)C(=O)N1CC(F)(F)C1)N1CCC(CC1)c1n[nH]c2ncccc12,MAWRCPRMGRVPLAWCLALCGWACMAPRGTQAEESPFVGNPGNITGARGLTGTLRCQLQVQGEPPEVHWLRDGQILELADSTQTQVPLGEDEQDDWIVVSQLRITSLQLSDTGQYQCLVFLGHQTFVSQPGYVGLEGLPYFLEEPEDRTVAANTPFNLSCQAQGPPEPVDLLWLQDAVPLATAPGHGPQRSLHVPGLNKTSSFSCEAHNAKGVTTSRTATITVLPQQPRNLHLVSRQPTELEVAWTPGLSGIYPLTHCTLQAVLSDDGMGIQAGEPDPPEEPLTSQASVPPHQLRLGSLHPHTPYHIRVACTSSQGPSSWTHWLPVETPEGVPLGPPENISATRNGSQAFVHWQEPRAPLQGTLLGYRLAYQGQDTPEVLMDIGLRQEVTLELQGDGSVSNLTVCVAAYTAAGDGPWSLPVPLEAWRPGQAQPVHQLVKEPSTPAFSWPWWYVLLGAVVAAACVLILALFLVHRRKKETRYGEVFEPTVERGELVVRYRVRKSYSRRTTEATLNSLGISEELKEKLRDVMVDRHKVALGKTLGEGEFGAVMEGQLNQDDSILKVAVKTMKIAICTRSELEDFLSEAVCMKEFDHPNVMRLIGVCFQGSERESFPAPVVILPFMKHGDLHSFLLYSRLGDQPVYLPTQMLVKFMADIASGMEYLSTKRFIHRDLAARNCMLNENMSVCVADFGLSKKIYNGDYYRQGRIAKMPVKWIAIESLADRVYTSKSDVWSFGVTMWEIATRGQTPYPGVENSEIYDYLRQGNRLKQPADCLDGLYALMSRCWELNPQDRPSFTELREDLENTLKALPPAQEPDEILYVNMDEGGGYPEPPGAAGGADPPTQPDPKDSCSCLTAAEVHPAGRYVLCPSTTPSPAQPADRGSPAAPGQEDGA,8.732828271596986 +CN(C1CN(C)C1)[C@H]1CCCC[C@@H]1Nc1cc(F)c(cc1Cl)S(=O)(=O)Nc1cccc(F)n1,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,8.271646217978772 +Cc1cn(Cc2ccc(F)cc2F)c2c(cc(F)cc12)-c1cc(NS(C)(=O)=O)on1,MKETRGYGGDAPFCTRLNHSYTGMWAPERSAEARGNLTRPPGSGEDCGSVSVAFPITMLLTGFVGNALAMLLVSRSYRRRESKRKKSFLLCIGWLALTDLVGQLLTTPVVIVVYLSKQRWEHIDPSGRLCTFFGLTMTVFGLSSLFIASAMAVERALAIRAPHWYASHMKTRATRAVLLGVWLAVLAFALLPVLGVGQYTVQWPGTWCFISTGRGGNGTSSSHNWGNLFFASAFAFLGLLALTVTFSCNLATIKALVSRCRAKATASQSSAQWGRITTETAIQLMGIMCVLSVCWSPLLIMMLKMIFNQTSVEHCKTHTEKQKECNFFLIAVRLASLNQILDPWVYLLLRKILLRKFCQIRYHTNNYASSSTSLPCQCSSTLMWSDHLER,4.748361779551788 +CC(C)Cn1cc(cn1)-c1ccc2nc(sc2c1)C(C(=O)NCCS(N)(=O)=O)S(C)(=O)=O,MDTSPLCFSILLVLCIFIQSSALGQSLKPEPFGRRAQAVETNKTLHEMKTRFLLFGETNQGCQIRINHPDTLQECGFNSSLPLVMIIHGWSVDGVLENWIWQMVAALKSQPAQPVNVGLVDWITLAHDHYTIAVRNTRLVGKEVAALLRWLEESVQLSRSHVHLIGYSLGAHVSGFAGSSIGGTHKIGRITGLDAAGPLFEGSAPSNRLSPDDANFVDAIHTFTREHMGLSVGIKQPIGHYDFYPNGGSFQPGCHFLELYRHIAQHGFNAITQTIKCSHERSVHLFIDSLLHAGTQSMAYPCGDMNSFSQGLCLSCKKGRCNTLGYHVRQEPRSKSKRLFLVTRAQSPFKVYHYQFKIQFINQTETPIQTTFTMSLLGTKEKMQKIPITLGKGIASNKTYSFLITLDVDIGELIMIKFKWENSAVWANVWDTVQTIIPWSTGPRHSGLVLKTIRVKAGETQQRMTFCSENTDDLLLRPTQEKIFVKCEIKSKTSKRKIR,7.3872161432802645 +Nc1cc([C@H]2CCN[C@H]3C[C@H](Cc4ccccc4)[C@@H](C3)Oc3cccc(Cn4cc2cn4)c3)c2nn[nH]c2n1,MGVPFFSSLRCMVDLGPCWAGGLTAEMKLLLALAGLLAILATPQPSEGAAPAVLGEVDTSLVLSSMEEAKQLVDKAYKERRESIKQRLRSGSASPMELLSYFKQPVAATRTAVRAADYLHVALDLLERKLRSLWRRPFNVTDVLTPAQLNVLSKSSGCAYQDVGVTCPEQDKYRTITGMCNNRRSPTLGASNRAFVRWLPAEYEDGFSLPYGWTPGVKRNGFPVALARAVSNEIVRFPTDQLTPDQERSLMFMQWGQLLDHDLDFTPEPAARASFVTGVNCETSCVQQPPCFPLKIPPNDPRIKNQADCIPFFRSCPACPGSNITIRNQINALTSFVDASMVYGSEEPLARNLRNMSNQLGLLAVNQRFQDNGRALLPFDNLHDDPCLLTNRSARIPCFLAGDTRSSEMPELTSMHTLLLREHNRLATELKSLNPRWDGERLYQEARKIVGAMVQIITYRDYLPLVLGPTAMRKYLPTYRSYNDSVDPRIANVFTNAFRYGHTLIQPFMFRLDNRYQPMEPNPRVPLSRVFFASWRVVLEGGIDPILRGLMATPAKLNRQNQIAVDEIRERLFEQVMRIGLDLPALNMQRSRDHGLPGYNAWRRFCGLPQPETVGQLGTVLRNLKLARKLMEQYGTPNNIDIWMGGVSEPLKRKGRVGPLLACIIGTQFRKLRDGDRFWWENEGVFSMQQRQALAQISLPRIICDNTGITTVSKNNIFMSNSYPRDFVNCSTLPALNLASWREAS,7.301029995663981 +CNC(=O)c1c(NC(=O)c2nc(cnc2Nc2cncnc2)C(C)C)cnn1C,MRIEERKSQHLTGLTDEKVKAYLSLHPQVLDEFVSESVSAETVEKWLKRKNNKSEDESAPKEVSRYQDTNMQGVVYELNSYIEQRLDTGGDNQLLLYELSSIIKIATKADGFALYFLGECNNSLCIFTPPGIKEGKPRLIPAGPITQGTTVSAYVAKSRKTLLVEDILGDERFPRGTGLESGTRIQSVLCLPIVTAIGDLIGILELYRHWGKEAFCLSHQEVATANLAWASVAIHQVQVCRGLAKQTELNDFLLDVSKTYFDNIVAIDSLLEHIMIYAKNLVNADRCALFQVDHKNKELYSDLFDIGEEKEGKPVFKKTKEIRFSIEKGIAGQVARTGEVLNIPDAYADPRFNREVDLYTGYTTRNILCMPIVSRGSVIGVVQMVNKISGSAFSKTDENNFKMFAVFCALALHCANMYHRIRHSECIYRVTMEKLSYHSICTSEEWQGLMQFTLPVRLCKEIELFHFDIGPFENMWPGIFVYMVHRSCGTSCFELEKLCRFIMSVKKNYRRVPYHNWKHAVTVAHCMYAILQNNHTLFTDLERKGLLIACLCHDLDHRGFSNSYLQKFDHPLAALYSTSTMEQHHFSQTVSILQLEGHNIFSTLSSSEYEQVLEIIRKAIIATDLALYFGNRKQLEEMYQTGSLNLNNQSHRDRVIGLMMTACDLCSVTKLWPVTKLTANDIYAEFWAEGDEMKKLGIQPIPMMDRDKKDEVPQGQLGFYNAVAIPCYTTLTQILPPTEPLLKACRDNLSQWEKVIRGEETATWISSPSVAQKAAASED,7.892790030352131 +COC(=O)c1ccc2C(C(=Nc3ccc(cc3)N(CCN(C)C)C(C)=O)c3ccccc3)C(=O)Nc2c1,MQRGAALCLRLWLCLGLLDGLVSGYSMTPPTLNITEESHVIDTGDSLSISCRGQHPLEWAWPGAQEAPATGDKDSEDTGVVRDCEGTDARPYCKVLLLHEVHANDTGSYVCYYKYIKARIEGTTAASSYVFVRDFEQPFINKPDTLLVNRKDAMWVPCLVSIPGLNVTLRSQSSVLWPDGQEVVWDDRRGMLVSTPLLHDALYLQCETTWGDQDFLSNPFLVHITGNELYDIQLLPRKSLELLVGEKLVLNCTVWAEFNSGVTFDWDYPGKQAERGKWVPERRSQQTHTELSSILTIHNVSQHDLGSYVCKANNGIQRFRESTEVIVHENPFISVEWLKGPILEATAGDELVKLPVKLAAYPPPEFQWYKDGKALSGRHSPHALVLKEVTEASTGTYTLALWNSAAGLRRNISLELVVNVPPQIHEKEASSPSIYSRHSRQALTCTAYGVPLPLSIQWHWRPWTPCKMFAQRSLRRRQQQDLMPQCRDWRAVTTQDAVNPIESLDTWTEFVEGKNKTVSKLVIQNANVSAMYKCVVSNKVGQDERLIYFYVTTIPDGFTIESKPSEELLEGQPVLLSCQADSYKYEHLRWYRLNLSTLHDAHGNPLLLDCKNVHLFATPLAASLEEVAPGARHATLSLSIPRVAPEHEGHYVCEVQDRRSHDKHCHKKYLSVQALEAPRLTQNLTDLLVNVSDSLEMQCLVAGAHAPSIVWYKDERLLEEKSGVDLADSNQKLSIQRVREEDAGRYLCSVCNAKGCVNSSASVAVEGSEDKGSMEIVILVGTGVIAVFFWVLLLLIFCNMRRPAHADIKTGYLSIIMDPGEVPLEEQCEYLSYDASQWEFPRERLHLGRVLGYGAFGKVVEASAFGIHKGSSCDTVAVKMLKEGATASEHRALMSELKILIHIGNHLNVVNLLGACTKPQGPLMVIVEFCKYGNLSNFLRAKRDAFSPCAEKSPEQRGRFRAMVELARLDRRRPGSSDRVLFARFSKTEGGARRASPDQEAEDLWLSPLTMEDLVCYSFQVARGMEFLASRKCIHRDLAARNILLSESDVVKICDFGLARDIYKDPDYVRKGSARLPLKWMAPESIFDKVYTTQSDVWSFGVLLWEIFSLGASPYPGVQINEEFCQRLRDGTRMRAPELATPAIRRIMLNCWSGDPKARPAFSELVEILGDLLQGRGLQEEEEVCMAPRSSQSSEEGSFSQVSTMALHIAQADAEDSPPSLQRHSLAARYYNWVSFPGCLARGAETRGSSRMKTFEEFPMTPTTYKGSVDNQTDSGMVLASEEFEQIESRHRQESGFSCKGPGQNVAVTRAHPDSQGRRRRPERGARGGQVFYNSEYGELSEPSEEDHCSPSARVTFFTDNSY,8.301029995663981 +Clc1cccc(c1)N1CCN(Cc2cncn2Cc2ccc(cc2)C#N)C(=O)C1=O,MAATEGVGEAAQGGEPGQPAQPPPQPHPPPPQQQHKEEMAAEAGEAVASPMDDGFVSLDSPSYVLYRDRAEWADIDPVPQNDGPNPVVQIIYSDKFRDVYDYFRAVLQRDERSERAFKLTRDAIELNAANYTVWHFRRVLLKSLQKDLHEEMNYITAIIEEQPKNYQVWHHRRVLVEWLRDPSQELEFIADILNQDAKNYHAWQHRQWVIQEFKLWDNELQYVDQLLKEDVRNNSVWNQRYFVISNTTGYNDRAVLEREVQYTLEMIKLVPHNESAWNYLKGILQDRGLSKYPNLLNQLLDLQPSHSSPYLIAFLVDIYEDMLENQCDNKEDILNKALELCEILAKEKDTIRKEYWRYIGRSLQSKHSTENDSPTNVQQ,4.958607314841775 +CC(C)(C)NC(=O)C1CCN(Cc2cccc(NC(=O)Cc3cccc(c3Cl)C(F)(F)F)c2)CC1,MDLHLFDYSEPGNFSDISWPCNSSDCIVVDTVMCPNMPNKSVLLYTLSFIYIFIFVIGMIANSVVVWVNIQAKTTGYDTHCYILNLAIADLWVVLTIPVWVVSLVQHNQWPMGELTCKVTHLIFSINLFGSIFFLTCMSVDRYLSITYFTNTPSSRKKMVRRVVCILVWLLAFCVSLPDTYYLKTVTSASNNETYCRSFYPEHSIKEWLIGMELVSVVLGFAVPFSIIAVFYFLLARAISASSDQEKHSSRKIIFSYVVVFLVCWLPYHVAVLLDIFSILHYIPFTCRLEHALFTALHVTQCLSLVHCCVNPVLYSFINRNYRYELMKAFIFKYSAKTGLTKLIDASRVSETEYSALEQSTK,8.698970004336019 +COc1ccc2C(Cc3c(Cl)cncc3Cl)=NN(Cc2c1)S(C)(=O)=O,MKKSRSVMTVMADDNVKDYFECSLSKSYSSSSNTLGIDLWRGRRCCSGNLQLPPLSQRQSERARTPEGDGISRPTTLPLTTLPSIAITTVSQECFDVENGPSPGRSPLDPQASSSAGLVLHATFPGHSQRRESFLYRSDSDYDLSPKAMSRNSSLPSEQHGDDLIVTPFAQVLASLRSVRNNFTILTNLHGTSNKRSPAASQPPVSRVNPQEESYQKLAMETLEELDWCLDQLETIQTYRSVSEMASNKFKRMLNRELTHLSEMSRSGNQVSEYISNTFLDKQNDVEIPSPTQKDREKKKKQQLMTQISGVKKLMHSSSLNNTSISRFGVNTENEDHLAKELEDLNKWGLNIFNVAGYSHNRPLTCIMYAIFQERDLLKTFRISSDTFITYMMTLEDHYHSDVAYHNSLHAADVAQSTHVLLSTPALDAVFTDLEILAAIFAAAIHDVDHPGVSNQFLINTNSELALMYNDESVLENHHLAVGFKLLQEEHCDIFMNLTKKQRQTLRKMVIDMVLATDMSKHMSLLADLKTMVETKKVTSSGVLLLDNYTDRIQVLRNMVHCADLSNPTKSLELYRQWTDRIMEEFFQQGDKERERGMEISPMCDKHTASVEKSQVGFIDYIVHPLWETWADLVQPDAQDILDTLEDNRNWYQSMIPQSPSPPLDEQNRDCQGLMEKFQFELTLDEEDSEGPEKEGEGHSYFSSTKTLCVIDPENRDSLGETDIDIATEDKSPVDT,7.6777807052660805 +Nc1nccc(Nc2ccc(cc2)S(N)(=O)=O)n1,MASPDWGYDDKNGPEQWSKLYPIANGNNQSPVDIKTSETKHDTSLKPISVSYNPATAKEIINVGHSFHVNFEDNDNRSVLKGGPFSDSYRLFQFHFHWGSTNEHGSEHTVDGVKYSAELHVAHWNSAKYSSLAEAASKADGLAVIGVLMKVGEANPKLQKVLDALQAIKTKGKRAPFTNFDPSTLLPSSLDFWTYPGSLTHPPLYESVTWIICKESISVSSEQLAQFRSLLSNVEGDNAVPMQHNNRPTQPLKGRTVRASF,7.022276394711152 +COC(=O)C1NCC(=C1)c1cc2c(ccnc2[nH]1)-c1cc(F)ccc1OC,MAKQYDSVECPFCDEVSKYEKLAKIGQGTFGEVFKARHRKTGQKVALKKVLMENEKEGFPITALREIKILQLLKHENVVNLIEICRTKASPYNRCKGSIYLVFDFCEHDLAGLLSNVLVKFTLSEIKRVMQMLLNGLYYIHRNKILHRDMKAANVLITRDGVLKLADFGLARAFSLAKNSQPNRYTNRVVTLWYRPPELLLGERDYGPPIDLWGAGCIMAEMWTRSPIMQGNTEQHQLALISQLCGSITPEVWPNVDNYELYEKLELVKGQKRKVKDRLKAYVRDPYALDLIDKLLVLDPAQRIDSDDALNHDFFWSDPMPSDLKGMLSTHLTSMFEYLAPPRRKGSQITQQSTNQSRNPATTNQTEFERVF,7.113509274827518 +Nc1ncc(-c2cccc(c2)S(N)(=O)=O)c2scc(-c3ccc(F)c(Cl)c3)c12,MSAAVTAGKLARAPADPGKAGVPGVAAPGAPAAAPPAKEIPEVLVDPRSRRRYVRGRFLGKGGFAKCFEISDADTKEVFAGKIVPKSLLLKPHQREKMSMEISIHRSLAHQHVVGFHGFFEDNDFVFVVLELCRRRSLLELHKRRKALTEPEARYYLRQIVLGCQYLHRNRVIHRDLKLGNLFLNEDLEVKIGDFGLATKVEYDGERKKTLCGTPNYIAPEVLSKKGHSFEVDVWSIGCIMYTLLVGKPPFETSCLKETYLRIKKNEYSIPKHINPVAASLIQKMLQTDPTARPTINELLNDEFFTSGYIPARLPITCLTIPPRFSIAPSSLDPSNRKPLTVLNKGLENPLPERPREKEEPVVRETGEVVDCHLSDMLQQLHSVNASKPSERGLVRQEEAEDPACIPIFWVSKWVDYSDKYGLGYQLCDNSVGVLFNDSTRLILYNDGDSLQYIERDGTESYLTVSSHPNSLMKKITLLKYFRNYMSEHLLKAGANITPREGDELARLPYLRTWFRTRSAIILHLSNGSVQINFFQDHTKLILCPLMAAVTYIDEKRDFRTYRLSLLEEYGCCKELASRLRYARTMVDKLLSSRSASNRLKAS,5.0 +Cc1ccc(c(C)c1)-n1sc2cc(F)ccc2c1=O,MVSEIKTLVTFFGGTGDLAKRKLYPSVFNLYKKGYLQKHFAIVGTARQALNDDEFKQLVRDSIKDFTDDQAQAEAFIEHFSYRAHDVTDAASYAVLKEAIEEAADKFDIDGNRIFYMSVAPRFFGTIAKYLKSEGLLADTGYNRLMIEKPFGTSYDTAAELQNDLENAFDDNQLFRIDHYLGKEMVQNIAALRFGNPIFDAAWNKDYIKNVQVTLSEVLGVEERAGYYDTAGALLDMIQNHTMQIVGWLAMEKPESFTDKDIRAAKNAAFNALKIYDEAEVNKYFVRAQYGAGDSADFKPYLEELDVPADSKNNTFIAGELQFDLPRWEGVPFYVRSGKRLAAKQTRVDIVFKAGTFNFGSEQEAQEAVLSIIIDPKGAIELKLNAKSVEDAFNTRTIDLGWTVSDEDKKNTPEPYERMIHDTMNGDGSNFADWNGVSIAWKFVDAISAVYTADKAPLETYKSGSMGPEASDKLLAANGDAWVFKG,4.6020599913279625 +CCCCN[C@]12Cc3c([nH]c4ccccc34)[C@@H]3Oc4c5c(CC1N(C)CC[C@@]235)ccc4O,MEPAPSAGAELQPPLFANASDAYPSACPSAGANASGPPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKMKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTRPRDGAVVCMLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDIDRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRKPCGRPDPSSFSRAREATARERVTACTPSDGPGGGAAA,8.853871964321762 +COc1ccc(cc1)-c1cnc(nc1-c1ccccc1C)C(=O)N1CCN(CC1)c1cnc2ccccc2c1,MDVVDSLLVNGSNITPPCELGLENETLFCLDQPRPSKEWQPAVQILLYSLIFLLSVLGNTLVITVLIRNKRMRTVTNIFLLSLAVSDLMLCLFCMPFNLIPNLLKDFIFGSAVCKTTTYFMGTSVSVSTFNLVAISLERYGAICKPLQSRVWQTKSHALKVIAATWCLSFTIMTPYPIYSNLVPFTKNNNQTANMCRFLLPNDVMQQSWHTFLLLILFLIPGIVMMVAYGLISLELYQGIKFEASQKKSAKERKPSTTSSGKYEDSDGCYLQKTRPPRKLELRQLSTGSSSRANRIRSNSSAANLMAKKRVIRMLIVIVVLFFLCWMPIFSANAWRAYDTASAERRLSGTPISFILLLSYTSSCVNPIIYCFMNKRFRLGFMATFPCCPNPGPPGARGEVGEEEEGGTTGASLSRFSYSHMSASVPPQ,7.431798275933005 +CC(=O)Nc1cccc(c1)N1CCN(CCCCNS(=O)(=O)CC2CCCCC2)CC1,MEGDSYHNATTVNGTPVNHQPLERHRLWEVITIAAVTAVVSLITIVGNVLVMISFKVNSQLKTVNNYYLLSLACADLIIGIFSMNLYTTYILMGRWALGSLACDLWLALDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTPKRAGIMIGLAWLISFILWAPAILCWQYLVGKRTVPLDECQIQFLSEPTITFGTAIAAFYIPVSVMTILYCRIYRETEKRTKDLADLQGSDSVTKAEKRKPAHRALFRSCLRCPRPTLAQRERNQASWSSSRRSTSTTGKPSQATGPSANWAKAEQLTTCSSYPSSEDEDKPATDPVLQVVYKSQGKESPGEEFSAEETEETFVKAETEKSDYDTPNYLLSPAAAHRPKSQKCVAYKFRLVVKADGNQETNNGCHKVKIMPCPFPVAKEPSTKGLNPNPSHQMTKRKRVVLVKERKAAQTLSAILLAFIITWTPYNIMVLVSTFCDKCVPVTLWHLGYWLCYVNSTVNPICYALCNRTFRKTFKMLLLCRWKKKKVEEKLYWQGNSKLP,5.698970004336019 +CC(=O)N[C@H](CCCNC(N)=N)C(=O)N[C@H]1CC(=O)NCCCC[C@H](NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@@H](Cc2ccccc2)NC(=O)[C@@H]2C[C@@H](Cc3ccccc3)CN2C1=O)C(N)=O,MVNSTHRGMHTSLHLWNRSSYRLHSNASESLGKGYSDGGCYEQLFVSPEVFVTLGVISLLENILVIVAIAKNKNLHSPMYFFICSLAVADMLVSVSNGSETIVITLLNSTDTDAQSFTVNIDNVIDSVICSSLLASICSLLSIAVDRYFTIFYALQYHNIMTVKRVGIIISCIWAACTVSGILFIIYSDSSAVIICLITMFFTMLALMASLYVHMFLMARLHIKRIAVLPGTGAIRQGANMKGAITLTILIGVFVVCWAPFFLHLIFYISCPQNPYCVCFMSHFNLYLILIMCNSIIDPLIYALRSQELRKTFKEIICCYPLGGLCDLSSRY,8.698970004336019 +CN[C@@H](C)C(=O)N[C@H]1CN(C(=O)c2cccc3[nH]ncc23)c2ccccc2N(Cc2c(C)ccc3ccccc23)C1=O,MRHHHHHHRSDAVSSDRNFPNSTNLPRNPSMADYEARIFTFGTWIYSVNKEQLARAGFYALGEGDKVKCFHCGGGLTDWKPSEDPWEQHAKWYPGCKYLLEQKGQEYINNIHLTHSLEECLVRTT,4.261219441515631 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+[O-][N+](=O)c1cccc(c1)C#CCO[N-][C+]1CN2CCC1C2,MTLHSNSTTSPLFPNISSSWVHSPSEAGLPLGTVTQLGSYNISQETGNFSSNDTSSDPLGGHTIWQVVFIAFLTGFLALVTIIGNILVIVAFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLSIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAEAENFVHPTGSSRSCSSYELQQQGVKRSSRRKYGRCHFWFTTKSWKPSAEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSSILNSTKLPSSDNLQVSNEDLGTVDVERNAHKLQAQKSMGDGDNCQKDFTKLPIQLESAVDTGKTSDTNSSADKTTATLPLSFKEATLAKRFALKTRSQITKRKRMSLIKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTYWNLGYWLCYINSTVNPVCYALCNKTFRTTFKTLLLCQCDKRKRRKQQYQQRQSVIFHKRVPEQAL,5.193887889830909 +Cc1cc(=O)n(cc1-c1ccnnc1)-c1ccc(Cl)cc1,MDYLLMIFSLLFVACQGAPETAVLGAELSAVGENGGEKPTPSPPWRLRRSKRCSCSSLMDKECVYFCHLDIIWVNTPEHVVPYGLGSPRSKRALENLLPTKATDRENRCQCASQKDKKCWNFCQAGKELRAEDIMEKDWNNHKKGKDCSKLGKKCIYQQLVRGRKIRRSSEEHLRQTRSETMRNSVKSSFHDPKLKGKPSRERYVTHNRAHW,3.6989700043360187 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+CN1CCN2C(C1)c1sccc1Cc1ccccc21,MGSLQPDAGNASWNGTEAPGGGARATPYSLQVTLTLVCLAGLLMLFTVFGNVLVIIAVFTSRALKAPQNLFLVSLASADILVATLVIPFSLANEVMGYWYFGKAWCEIYLALDVLFCTSSIVHLCAISLDRYWSITQAIEYNLKRTPRRIKAIIVTVWVISAVISFPPLISFEKKRGRSGQPSAEPRCEINDQKWYVISSSIGSFFAPCLIMILVYVRIYQIAKRRTRVPPSRRGPDATAAELPGSAERRPNGLGPERGGVGPVGAEVESLQVQLNGAPGEPAPAGAGADALDLEESSSSEHAERPPGSRRSERGPRAKGKARASQVKPGDSLPRRGPGATGLGAPTAGPAEERSGGGAKASRWRGRQNREKRFTFVLAVVIGVFVVCWFPFFFTYTLTAIGCPVPPTLFKFFFWFGYCNSSLNPVIYTIFNHDFRRAFKKILCRGDRKRIV,8.522878745280337 +FC(F)(F)Oc1cccc(COc2ccc(Br)cc2OC2CNC2)c1,MMDVNSSGRPDLYGHLRSLILPEVGRGLQDLSPDGGAHPVVSSWMPHLLSGFLEVTASPAPTWDAPPDNVSGCGEQINYGRVEKVVIGSILTLITLLTIAGNCLVVISVCFVKKLRQPSNYLIVSLALADLSVAVAVMPFVSVTDLIGGKWIFGHFFCNVFIAMDVMCCTASIMTLCVISIDRYLGITRPLTYPVRQNGKCMAKMILSVWLLSASITLPPLFGWAQNVNDDKVCLISQDFGYTIYSTAVAFYIPMSVMLFMYYQIYKAARKSAAKHKFPGFPRVQPESVISLNGVVKLQKEVEECANLSRLLKHERKNISIFKREQKAATTLGIIVGAFTVCWLPFFLLSTARPFICGTSCSCIPLWVERTCLWLGYANSLINPFIYAFFNRDLRTTYRSLLQCQYRNINRKLSAAGMHEALKLAERPERSEFVLQNSDHCGKKGHDT,8.0 +CC(=O)Nc1ccc(cc1)-c1nc2c(OC3CCN(C3)C(=O)OC(C)(C)C)ncnc2n1C,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,6.853871964321762 +CN(c1ccc2c(C)n(C)nc2c1)c1ccnc(Nc2ccc(C)c(c2)S(N)(=O)=O)n1,MGDEKDSWKVKTLDEILQEKKRRKEQEEKAEIKRLKNSDDRDSKRDSLEEGELRDHCMEITIRNSPYRREDSMEDRGEEDDSLAIKPPQQMSRKEKVHHRKDEKRKEKWKHARVKEREHERRKRHREEQDKARREWERQKRREMAREHSRRERDRLEQLERKRERERKMREQQKEQREQKERERRAEERRKEREARREVSAHHRTMREDYSDKVKASHWSRSPPRPPRERFELGDGRKPGEARPAPAQKPAQLKEEKMEERDLLSDLQDISDSERKTSSAESSSAESGSGSEEEEEEEEEEEEEGSTSEESEEEEEEEEEEEEETGSNSEEASEQSAEEVSEEEMSEDEERENENHLLVVPESRFDRDSGESEEAEEEVGEGTPQSSALTEGDYVPDSPALLPIELKQELPKYLPALQGCRSVEEFQCLNRIEEGTYGVVYRAKDKKTDEIVALKRLKMEKEKEGFPITSLREINTILKAQHPNIVTVREIVVGSNMDKIYIVMNYVEHDLKSLMETMKQPFLPGEVKTLMIQLLRGVKHLHDNWILHRDLKTSNLLLSHAGILKVGDFGLAREYGSPLKAYTPVVVTQWYRAPELLLGAKEYSTAVDMWSVGCIFGELLTQKPLFPGNSEIDQINKVFKELGTPSEKIWPGYSELPVVKKMTFSEHPYNNLRKRFGALLSDQGFDLMNKFLTYFPGRRISAEDGLKHEYFRETPLPIDPSMFPTWPAKSEQQRVKRGTSPRPPEGGLGYSQLGDDDLKETGFHLTTTNQGASAAGPGFSLKF,5.886056647693163 +CNc1ncc(-c2cc(F)c(O)c(F)c2)c(n1)-c1ccc(C)cc1,MPLAQLADPWQKMAVESPSDSAENGQQIMDEPMGEEEINPQTEEGSIKEIAITHHVKEGHEKADPSQFELLKVLGQGSFGKVFLVKKISGSDARQLYAMKVLKKATLKVRDRVRTKMERDILVEVNHPFIVKLHYAFQTEGKLYLILDFLRGGDLFTRLSKEVMFTEEDVKFYLAELALALDHLHSLGIIYRDLKPENILLDEEGHIKLTDFGLSKESIDHEKKAYSFCGTVEYMAPEVVNRRGHTQSADWWSFGVLMFEMLTGTLPFQGKDRKETMTMILKAKLGMPQFLSPEAQSLLRMLFKRNPANRLGAGPDGVEEIKRHSFFSTIDWNKLYRREIHPPFKPATGRPEDTFYFDPEFTAKTPKDSPGIPPSANAHQLFRGFSFVAITSDDESQAMQTVGVHSIVQQLHRNSIQFTDGYEVKEDIGVGSYSVCKRCIHKATNMEFAVKIIDKSKRDPTEEIEILLRYGQHPNIITLKDVYDDGKYVYVVTELMKGGELLDKILRQKFFSEREASAVLFTITKTVEYLHAQGVVHRDLKPSNILYVDESGNPESIRICDFGFAKQLRAENGLLMTPCYTANFVAPEVLKRQGYDAACDIWSLGVLLYTMLTGYTPFANGPDDTPEEILARIGSGKFSLSGGYWNSVSDTAKDLVSKMLHVDPHQRLTAALVLRHPWIVHWDQLPQYQLNRQDAPHLVKGAMAATYSALNRNQSPVLEPVGRSTLAQRRGIKKITSTAL,6.161150909262744 +Cc1cn([C@@H]2O[C@H](CO[Si](C)(C)C(C)(C)C)[C@@]3(OS(=O)(=O)C=C3N)[C@H]2O[Si](C)(C)C(C)(C)C)c(=O)n(CCO)c1=O,PISPIETVPVKLKPGMDGPKVKQWPLTEEKIKALVEICTEMEKEGKISKIGPENPYNTPVFAIKKKDSTKWRKLVDFRELNKRTQDFWEVQLGIPHPAGLKKRKSVTVLDVGDAYFSVPLDEDFRKYTAFTIPSINNETPGIRYQYNVLPQGWKGSPAIFQSSMTKILEPFRKQNPDIVIYQYMDDLYVGSDLEIGQHRTKIEELRQHLLRWGLTTPDKKHQKEPPFLWMGYELHPDKWTVQPIVLPEKDSWTVNDIQKLVGKLNWASQIYPGIRVRQLCKLLRGTKALTEVIPLTEEAELELAENREILKEPVHGVYYDPSKDLIAEIQKQGQGQWTYQIYQEPFKNLRTGKYARMRGAHTNDVKQLTEAVQKITTESIVIWGKTPKFKLPIQKETWETWWTEYWQATWIPEWEFVNTPPLVKLWYQLEKEPIVGAETFYVDGAANRETKLGKAGYVTNRGRQKVVTLTDTTNQKTELQAIYLALQDSGLEVNIVTDSQYALGIIQAQPDQSESELVNQIIEQLIKKEKVYLAWVPAHKGIGGNEQVDKLVSAGIRKVLFLDGID,5.508638306165727 +CCOC(=O)C(C)(C)Oc1ccc(Cl)cc1,MNFSGKYQVQSQENFEPFMKAMGLPEDLIQKGKDIKGVSEIVHEGKKVKLTITYGSKVIHNEFTLGEECELETMTGEKVKAVVKMEGDNKMVTTFKGIKSVTEFNGDTITNTMTLGDIVYKRVSKRI,5.221848749616356 +NS(=O)(=O)c1ccc(NC(=O)N2CCN(CC2)c2ncccc2C(F)(F)F)cc1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,8.387216143280265 +C[C@@]12CN(c3ccccc3)c3ccccc3[C@@H]1CCN2,MANFTPVNGSSGNQSVRLVTSSSHNRYETVEMVFIATVTGSLSLVTVVGNILVMLSIKVNRQLQTVNNYFLFSLACADLIIGAFSMNLYTVYIIKGYWPLGAVVCDLWLALDYVVSNASVMNLLIISFDRYFCVTKPLTYPARRTTKMAGLMIAAAWVLSFVLWAPAILFWQFVVGKRTVPDNQCFIQFLSNPAVTFGTAIAAFYLPVVIMTVLYIHISLASRSRVHKHRPEGPKEKKAKTLAFLKSPLMKQSVKKPPPGEAAREELRNGKLEEAPPPALPPPPRPVADKDTSNESSSGSATQNTKERPATELSTTEATTPAMPAPPLQPRALNPASRWSKIQIVTKQTGNECVTAIEIVPATPAGMRPAANVARKFASIARNQVRKKRQMAARERKVTRTIFAILLAFILTWTPYNVMVLVNTFCQSCIPDTVWSIGYWLCYVNSTINPACYALCNATFKKTFRHLLLCQYRNIGTAR,5.0 +CN1CCN(CC(O)CN2CCc3ccccc3C2)C(=O)C1,MAAMAVGGAGGSRVSSGRDLNCVPEIADTLGAVAKQGFDFLCMPVFHPRFKREFIQEPAKNRPGPQTRSDLLLSGRDWNTLIVGKLSPWIRPDSKVEKIRRNSEAAMLQELNFGAYLGLPAFLLPLNQEDNTNLARVLTNHIHTGHHSSMFWMRVPLVAPEDLRDDIIENAPTTHTEEYSGEEKTWMWWHNFRTLCDYSKRIAVALEIGADLPSNHVIDRWLGEPIKAAILPTSIFLTNKKGFPVLSKMHQRLIFRLLKLEVQFIITGTNHHSEKEFCSYLQYLEYLSQNRPPPNAYELFAKGYEDYLQSPLQPLMDNLESQTYEVFEKDPIKYSQYQQAIYKCLLDRVPEEEKDTNVQVLMVLGAGRGPLVNASLRAAKQADRRIKLYAVEKNPNAVVTLENWQFEEWGSQVTVVSSDMREWVAPEKADIIVSELLGSFADNELSPECLDGAQHFLKDDGVSIPGEYTSFLAPISSSKLYNEVRACREKDRDPEAQFEMPYVVRLHNFHQLSAPQPCFTFSHPNRDPMIDNNRYCTLEFPVEVNTVLHGFAGYFETVLYQDITLSIRPETHSPGMFSWFPILFPIKQPITVREGQTICVRFWRCSNSKKVWYEWAVTAPVCSAIHNPTGRSYTIGL,4.301029995663981 +Cc1n[nH]c(C)c1-c1cccc2c(CCCOc3cc(C)c(Cl)c(C)c3)c([nH]c12)C(=O)NCc1ccc(CO)o1,MFGLKRNAVIGLNLYCGGAGLGAGSGGATRPGGRLLATEKEASARREIGGGEAGAVIGGSAGASPPSTLTPDSRRVARPPPIGAEVPDVTATPARLLFFAPTRRAAPLEEMEAPAADAIMSPEEELDGYEPEPLGKRPAVLPLLELVGESGNNTSTDGSLPSTPPPAEEEEDELYRQSLEIISRYLREQATGAKDTKPMGRSGATSRKALETLRRVGDGVQRNHETAFQGMLRKLDIKNEDDVKSLSRVMIHVFSDGVTNWGRIVTLISFGAFVAKHLKTINQESCIEPLAESITDVLVRTKRDWLVKQRGWDGFVEFFHVEDLEGGIRNVLLAFAGVAGVGAGLAYLIR,7.1249387366083 +CCCC[C@H](NC(=O)O[C@H]1C[C@@H](C)C[C@@H](C)C1)C(=O)C(=O)N[C@H](C)c1ccccc1,MKRLVCVLLVCSSAVAQLHKDPTLDHHWHLWKKTYGKQYKEKNEEAVRRLIWEKNLKFVMLHNLEHSMGMHSYDLGMNHLGDMTSEEVMSLMSSLRVPSQWQRNITYKSNPNRILPDSVDWREKGCVTEVKYQGSCGACWAFSAVGALEAQLKLKTGKLVSLSAQNLVDCSTEKYGNKGCNGGFMTTAFQYIIDNKGIDSDASYPYKAMDQKCQYDSKYRAATCSKYTELPYGREDVLKEAVANKGPVSVGVDARHPSFFLYRSGVYYEPSCTQNVNHGVLVVGYGDLNGKEYWLVKNSWGHNFGEEGYIRMARNKGNHCGIASFPSYPEI,7.200659450546418 +COc1ccc(cc1)S(=O)(=O)N(Cc1ccccc1)c1cccc(C)c1C(=O)NO,MSLWQPLVLVLLVLGCCFAAPRQRQSTLVLFPGDLRTNLTDRQLAEEYLYRYGYTRVAEMRGESKSLGPALLLLQKQLSLPETGELDSATLKAMRTPRCGVPDLGRFQTFEGDLKWHHHNITYWIQNYSEDLPRAVIDDAFARAFALWSAVTPLTFTRVYSRDADIVIQFGVAEHGDGYPFDGKDGLLAHAFPPGPGIQGDAHFDDDELWSLGKGVVVPTRFGNADGAACHFPFIFEGRSYSACTTDGRSDGLPWCSTTANYDTDDRFGFCPSERLYTQDGNADGKPCQFPFIFQGQSYSACTTDGRSDGYRWCATTANYDRDKLFGFCPTRADSTVMGGNSAGELCVFPFTFLGKEYSTCTSEGRGDGRLWCATTSNFDSDKKWGFCPDQGYSLFLVAAHEFGHALGLDHSSVPEALMYPMYRFTEGPPLHKDDVNGIRHLYGPRPEPEPRPPTTTTPQPTAPPTVCPTGPPTVHPSERPTAGPTGPPSAGPTGPPTAGPSTATTVPLSPVDDACNVNIFDAIAEIGNQLYLFKDGKYWRFSEGRGSRPQGPFLIADKWPALPRKLDSVFEERLSKKLFFFSGRQVWVYTGASVLGPRRLDKLGLGADVAQVTGALRSGRGKMLLFSGRRLWRFDVKAQMVDPRSASEVDRMFPGVPLDTHDVFQYREKAYFCQDRFYWRVSSRSELNQVDQVGYVTYDILQCPED,6.356547323513812 +ONC(=O)c1ccccc1S(=O)(=O)Nc1ccc(Oc2ccccc2)cc1,MHSFPPLLLLLFWGVVSHSFPATLETQEQDVDLVQKYLEKYYNLKNDGRQVEKRRNSGPVVEKLKQMQEFFGLKVTGKPDAETLKVMKQPRCGVPDVAQFVLTEGNPRWEQTHLTYRIENYTPDLPRADVDHAIEKAFQLWSNVTPLTFTKVSEGQADIMISFVRGDHRDNSPFDGPGGNLAHAFQPGPGIGGDAHFDEDERWTNNFREYNLHRVAAHELGHSLGLSHSTDIGALMYPSYTFSGDVQLAQDDIDGIQAIYGRSQNPVQPIGPQTPKACDSKLTFDAITTIRGEVMFFKDRFYMRTNPFYPEVELNFISVFWPQLPNGLEAAYEFADRDEVRFFKGNKYWAVQGQNVLHGYPKDIYSSFGFPRTVKHIDAALSEENTGKTYFFVANKYWRYDEYKRSMDPGYPKMIAHDFPGIGHKVDAVFMKDGFFYFFHGTRQYKFDPKTKRILTLQKANSWFNCRKN,5.0 +CONc1nc(nc2n(cnc12)[C@@H]1O[C@H](CO)[C@@H](O)[C@H]1O)C#Cc1ccc(OC)cc1,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,5.7495799976911055 +Cn1cnc2ncn(Cc3nc(no3)[C@H]3[C@@H]4CC(=C[C@H]34)c3cccc(F)c3)c(=O)c12,MKRSLRKMWRPGEKKEPQGVVYEDVPDDTEDFKESLKVVFEGSAYGLQNFNKQKKLKRCDDMDTFFLHYAAAEGQIELMEKITRDSSLEVLHEMDDYGNTPLHCAVEKNQIESVKFLLSRGANPNLRNFNMMAPLHIAVQGMNNEVMKVLLEHRTIDVNLEGENGNTAVIIACTTNNSEALQILLKKGAKPCKSNKWGCFPIHQAAFSGSKECMEIILRFGEEHGYSRQLHINFMNNGKATPLHLAVQNGDLEMIKMCLDNGAQIDPVEKGRCTAIHFAATQGATEIVKLMISSYSGSVDIVNTTDGCHETMLHRASLFDHHELADYLISVGADINKIDSEGRSPLILATASASWNIVNLLLSKGAQVDIKDNFGRNFLHLTVQQPYGLKNLRPEFMQMQQIKELVMDEDNDGCTPLHYACRQGGPGSVNNLLGFNVSIHSKSKDKKSPLHFAASYGRINTCQRLLQDISDTRLLNEGDLHGMTPLHLAAKNGHDKVVQLLLKKGALFLSDHNGWTALHHASMGGYTQTMKVILDTNLKCTDRLDEDGNTALHFAAREGHAKAVALLLSHNADIVLNKQQASFLHLALHNKRKEVVLTIIRSKRWDECLKIFSHNSPGNKCPITEMIEYLPECMKVLLDFCMLHSTEDKSCRDYYIEYNFKYLQCPLEFTKKTPTQDVIYEPLTALNAMVQNNRIELLNHPVCKEYLLMKWLAYGFRAHMMNLGSYCLGLIPMTILVVNIKPGMAFNSTGIINETSDHSEILDTTNSYLIKTCMILVFLSSIFGYCKEAGQIFQQKRNYFMDISNVLEWIIYTTGIIFVLPLFVEIPAHLQWQCGAIAVYFYWMNFLLYLQRFENCGIFIVMLEVILKTLLRSTVVFIFLLLAFGLSFYILLNLQDPFSSPLLSIIQTFSMMLGDINYRESFLEPYLRNELAHPVLSFAQLVSFTIFVPIVLMNLLIGLAVGDIAEVQKHASLKRIAMQVELHTSLEKKLPLWFLRKVDQKSTIVYPNKPRSGGMLFHIFCFLFCTGEIRQEIPNADKSLEMEILKQKYRLKDLTFLLEKQHELIKLIIQKMEIISETEDDDSHCSFQDRFKKEQMEQRNSRWNTVLRAVKAKTHHLEP,8.011887159731648 +FC(F)(F)c1cnc(NC2CC(F)(F)CC2NC(=O)c2ccccc2-n2nccn2)cn1,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,6.924453038607469 +COC(CCc1ccc(C[C@H](C[C@H](O)[C@H](Cc2ccccc2)NC(=O)OC(C)(C)C)C(=O)N[C@@H]2[C@H](O)Cc3ccccc23)cc1)OC,PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMNLPGRWKPKMIGGIGGFIKVRQYDQILIEICGHKAIGTVLVGPTPVNIIGRNLLTQIGCTLNF,10.096910013008056 +Fc1ccc(cc1)C1CNC(=O)C11CCN(CC1)C1(CCCCC1)c1ccc(F)cc1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,5.0 +COc1cc2c(ncnc2cc1OCCCN1CCCCC1)N1CCN(CC1)C(=O)Nc1ccc(OC(C)C)cc1,HHSTVADGLITTLHYPAPKRNKPTVYGVSPNYDKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSAMEYLEKKNVIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQES,5.154901959985743 +C\C=C1/NC(=O)[C@H](CS)NC(=O)[C@H](NC(=O)C[C@H](OC(=O)[C@@H](NC1=O)C(C)C)\C=C\CCS)C(C)C,MDLRVGQRPPVEPPPEPTLLALQRPQRLHHHLFLAGLQQQRSVEPMRLSMDTPMPELQVGPQEQELRQLLHKDKSKRSAVASSVVKQKLAEVILKKQQAALERTVHPNSPGIPYRTLEPLETEGATRSMLSSFLPPVPSLPSDPPEHFPLRKTVSEPNLKLRYKPKKSLERRKNPLLRKESAPPSLRRRPAETLGDSSPSSSSTPASGCSSPNDSEHGPNPILGSEALLGQRLRLQETSVAPFALPTVSLLPAITLGLPAPARADSDRRTHPTLGPRGPILGSPHTPLFLPHGLEPEAGGTLPSRLQPILLLDPSGSHAPLLTVPGLGPLPFHFAQSLMTTERLSGSGLHWPLSRTRSEPLPPSATAPPPPGPMQPRLEQLKTHVQVIKRSAKPSEKPRLRQIPSAEDLETDGGGPGQVVDDGLEHRELGHGQPEARGPAPLQQHPQVLLWEQQRLAGRLPRGSTGDTVLLPLAQGGHRPLSRAQSSPAAPASLSAPEPASQARVLSSSETPARTLPFTTGLIYDSVMLKHQCSCGDNSRHPEHAGRIQSIWSRLQERGLRSQCECLRGRKASLEELQSVHSERHVLLYGTNPLSRLKLDNGKLAGLLAQRMFVMLPCGGVGVDTDTIWNELHSSNAARWAAGSVTDLAFKVASRELKNGFAVVRPPGHHADHSTAMGFCFFNSVAIACRQLQQQSKASKILIVDWDVHHGNGTQQTFYQDPSVLYISLHRHDDGNFFPGSGAVDEVGAGSGEGFNVNVAWAGGLDPPMGDPEYLAAFRIVVMPIAREFSPDLVLVSAGFDAAEGHPAPLGGYHVSAKCFGYMTQQLMNLAGGAVVLALEGGHDLTAICDASEACVAALLGNRVDPLSEEGWKQKPNLNAIRSLEAVIRVHSKYWGCMQRLASCPDSWVPRVPGADKEEVEAVTALASLSVGILAEDRPSEQLVEEEEPMNL,5.7544873321858505 +CNS(=O)(=O)Cc1ccc2[nH]cc(CCN(C)C)c2c1,MSPLNQSAEGLPQEASNRSLNATETSEAWDPRTLQALKISLAVVLSVITLATVLSNAFVLTTILLTRKLHTPANYLIGSLATTDLLVSILVMPISIAYTITHTWNFGQILCDIWLSSDITCCTASILHLCVIALDRYWAITDALEYSKRRTAGHAATMIAIVWAISICISIPPLFWRQAKAQEEMSDCLVNTSQISYTIYSTCGAFYIPSVLLIILYGRIYRAARNRILNPPSLYGKRFTTAHLITGSAGSSLCSLNSSLHEGHSHSAGSPLFFNHVKIKLADSALERKRISAARERKATKILGIILGAFIICWLPFFVVSLVLPICRDSCWIHPALFDFFTWLGYLNSLINPIIYTVFNEEFRQAFQKIVPFRKAS,7.522878745280337 +CC(C)Oc1cc(OCCCN2CCCC2)cc2ncnc(Nc3c4OCOc4ccc3Cl)c12,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,5.920818753952375 +[O-][N+](=O)c1ccc(cc1)C(=O)Nc1ccccc1-c1nnn(n1)-c1ccc(Cl)cc1,MSSSNVEVFIPVSQGNTNGFPATASNDLKAFTEGAVLSFHNICYRVKLKSGFLPCRKPVEKEILSNINGIMKPGLNAILGPTGGGKSSLLDVLAARKDPSGLSGDVLINGAPRPANFKCNSGYVVQDDVVMGTLTVRENLQFSAALRLATTMTNHEKNERINRVIQELGLDKVADSKVGTQFIRGVSGGERKRTSIGMELITDPSILFLDEPTTGLDSSTANAVLLLLKRMSKQGRTIIFSIHQPRYSIFKLFDSLTLLASGRLMFHGPAQEALGYFESAGYHCEAYNNPADFFLDIINGDSTAVALNREEDFKATEIIEPSKQDKPLIEKLAEIYVNSSFYKETKAELHQLSGGEKKKKITVFKEISYTTSFCHQLRWVSKRSFKNLLGNPQASIAQIIVTVVLGLVIGAIYFGLKNDSTGIQNRAGVLFFLTTNQCFSSVSAVELFVVEKKLFIHEYISGYYRVSSYFLGKLLSDLLPMRMLPSIIFTCIVYFMLGLKPKADAFFVMMFTLMMVAYSASSMALAIAAGQSVVSVATLLMTICFVFMMIFSGLLVNLTTIASWLSWLQYFSIPRYGFTALQHNEFLGQNFCPGLNATGNNPCNYATCTGEEYLVKQGIDLSPWGLWKNHVALACMIVIFLTIAYLKLLFLKKYS,5.0 +COc1ccc(CCC2CCc3cc(ccc3C2)[C@H]2CC[C@@](N)(COP(O)(O)=O)C2)cc1,MPSTDLLMLKAFEPYLEILEVYSTKAKNYVNGHCTKYEPWQLIAWSVVWTLLIVWGYEFVFQPESLWSRFKKKCFKLTRKMPIIGRKIQDKLNKTKDDISKNMSFLKVDKEYVKALPSQGLSSSAVLEKLKEYSSMDAFWQEGRASGTVYSGEEKLTELLVKAYGDFAWSNPLHPDIFPGLRKIEAEIVRIACSLFNGGPDSCGCVTSGGTESILMACKAYRDLAFEKGIKTPEIVAPQSAHAAFNKAASYFGMKIVRVPLTKMMEVDVRAMRRAISRNTAMLVCSTPQFPHGVIDPVPEVAKLAVKYKIPLHVDACLGGFLIVFMEKAGYPLEHPFDFRVKGVTSISADTHKYGYAPKGSSLVLYSDKKYRNYQFFVDTDWQGGIYASPTIAGSRPGGISAACWAALMHFGENGYVEATKQIIKTARFLKSELENIKGIFVFGNPQLSVIALGSRDFDIYRLSNLMTAKGWNLNQLQFPPSIHFCITLLHARKRVAIQFLKDIRESVTQIMKNPKAKTTGMGAIYGMAQTTVDRNMVAELSSVFLDSLYSTDTVTQGSQMNGSPKPH,7.259637310505756 +Fc1ccc(C(=O)NOCC2CC2)c(Nc2ccc(I)cc2Cl)c1F,MSDGLDNEEKPPAPPLRMNSNNRDSSALNHSSKPLPMAPEEKNKKARLRSIFPGGGDKTNKKKEKERPEISLPSDFEHTIHVGFDAVTGEFTPDLYGSQMCPGKLPEGIPEQWARLLQTSNITKLEQKKNPQAVLDVLKFYDSKETVNNQKYMSFTSGDKSAHGYIAAHPSSTKTASEPPLAPPVSEEEDEEEEEEEDENEPPPVIAPRPEHTKSIYTRSVVESIASPAVPNKEVTPPSAENANSSTLYRNTDRQRKKSKMTDEEILEKLRSIVSVGDPKKKYTRFEKIGQGASGTVYTALDIATGQEVAIKQMNLQQQPKKELIINEILVMRENKNPNIVNYLDSYLVGDELWVVMEYLAGGSLTDVVTETCMDEGQIAAVCRECLQALDFLHSNQVIHRDIKSDNILLGMDGSVKLTDFGFCAQITPEQSKRSTMVGTPYWMAPEVVTRKAYGPKVDIWSLGIMAIEMVEGEPPYLNENPLRALYLIATNGTPELQNPERLSAVFRDFLNRCLEMDVDRRGSAKELLQHPFLKLAKPLSSLTPLIIAAKEAIKNSSR,5.0 +NC(=O)Cn1cc(cn1)-c1cnc2ncc(Cc3ccc4ncccc4c3)n2n1,MKAPAVLAPGILVLLFTLVQRSNGECKEALAKSEMNVNMKYQLPNFTAETPIQNVILHEHHIFLGATNYIYVLNEEDLQKVAEYKTGPVLEHPDCFPCQDCSSKANLSGGVWKDNINMALVVDTYYDDQLISCGSVNRGTCQRHVFPHNHTADIQSEVHCIFSPQIEEPSQCPDCVVSALGAKVLSSVKDRFINFFVGNTINSSYFPDHPLHSISVRRLKETKDGFMFLTDQSYIDVLPEFRDSYPIKYVHAFESNNFIYFLTVQRETLDAQTFHTRIIRFCSINSGLHSYMEMPLECILTEKRKKRSTKKEVFNILQAAYVSKPGAQLARQIGASLNDDILFGVFAQSKPDSAEPMDRSAMCAFPIKYVNDFFNKIVNKNNVRCLQHFYGPNHEHCFNRTLLRNSSGCEARRDEYRTEFTTALQRVDLFMGQFSEVLLTSISTFIKGDLTIANLGTSEGRFMQVVVSRSGPSTPHVNFLLDSHPVSPEVIVEHTLNQNGYTLVITGKKITKIPLNGLGCRHFQSCSQCLSAPPFVQCGWCHDKCVRSEECLSGTWTQQICLPAIYKVFPNSAPLEGGTRLTICGWDFGFRRNNKFDLKKTRVLLGNESCTLTLSESTMNTLKCTVGPAMNKHFNMSIIISNGHGTTQYSTFSYVDPVITSISPKYGPMAGGTLLTLTGNYLNSGNSRHISIGGKTCTLKSVSNSILECYTPAQTISTEFAVKLKIDLANRETSIFSYREDPIVYEIHPTKSFISGGSTITGVGKNLNSVSVPRMVINVHEAGRNFTVACQHRSNSEIICCTTPSLQQLNLQLPLKTKAFFMLDGILSKYFDLIYVHNPVFKPFEKPVMISMGNENVLEIKGNDIDPEAVKGEVLKVGNKSCENIHLHSEAVLCTVPNDLLKLNSELNIEWKQAISSTVLGKVIVQPDQNFTGLIAGVVSISTALLLLLGFFLWLKKRKQIKDLGSELVRYDARVHTPHLDRLVSARSVSPTTEMVSNESVDYRATFPEDQFPNSSQNGSCRQVQYPLTDMSPILTSGDSDISSPLLQNTVHIDLSALNPELVQAVQHVVIGPSSLIVHFNEVIGRGHFGCVYHGTLLDNDGKKIHCAVKSLNRITDIGEVSQFLTEGIIMKDFSHPNVLSLLGICLRSEGSPLVVLPYMKHGDLRNFIRNETHNPTVKDLIGFGLQVAKGMKYLASKKFVHRDLAARNCMLDEKFTVKVADFGLARDMYDKEYYSVHNKTGAKLPVKWMALESLQTQKFTTKSDVWSFGVLLWELMTRGAPPYPDVNTFDITVYLLQGRRLLQPEYCPDPLYEVMLKCWHPKAEMRPSFSELVSRISAIFSTFIGEHYVHVNATYVNVKCVAPYPSLLSSEDNADDEVDTRPASFWETS,6.301029995663981 +Fc1cccc(C[C@H](NC(=O)c2cc3ccccc3[nH]2)C(=O)N[C@@H](C[C@@H]2CCNC2=O)C=O)c1,MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHLKDGTCGLVEVEKGVLPQLEQPYVFIKRSDARTAPHGHVMVELVAELEGIQYGRSGETLGVLVPHVGEIPVAYRKVLLRKNGNKGAGGHSYGADLKSFDLGDELGTDPYEDFQENWNTKHSSGVTRELMRELNGGAYTRYVDNNFCGPDGYPLECIKDLLARAGKASCTLSEQLDFIDTKRGVYCCREHEHEIAWYTERSEKSYELQTPFEIKLAKKFDTFNGECPNFVFPLNSIIKTIQPRVEKKKLDGFMGRIRSVYPVASPNECNQMCLSTLMKCDHCGETSWQTGDFVKATCEFCGTENLTKEGATTCGYLPQNAVVKIYCPACHNSEVGPEHSLAEYHNESGLKTILRKGGRTIAFGGCVFSYVGCHNKCAYWVPRASANIGCNHTGVVGEGSEGLNDNLLEILQKEKVNINIVGDFKLNEEIAIILASFSASTSAFVETVKGLDYKAFKQIVESCGNFKVTKGKAKKGAWNIGEQKSILSPLYAFASEAARVVRSIFSRTLETAQNSVRVLQKAAITILDGISQYSLRLIDAMMFTSDLATNNLVVMAYITGGVVQLTSQWLTNIFGTVYEKLKPVLDWLEEKFKEGVEFLRDGWEIVKFISTCACEIVGGQIVTCAKEIKESVQTFFKLVNKFLALCADSIIIGGAKLKALNLGETFVTHSKGLYRKCVKSREETGLLMPLKAPKEIIFLEGETLPTEVLTEEVVLKTGDLQPLEQPTSEAVEAPLVGTPVCINGLMLLEIKDTEKYCALAPNMMVTNNTFTLKGGAPTKVTFGDDTVIEVQGYKSVNITFELDERIDKVLNEKCSAYTVELGTEVNEFACVVADAVIKTLQPVSELLTPLGIDLDEWSMATYYLFDESGEFKLASHMYCSFYPPDEDEEEGDCEEEEFEPSTQYEYGTEDDYQGKPLEFGATSAALQPEEEQEEDWLDDDSQQTVGQQDGSEDNQTTTIQTIVEVQPQLEMELTPVVQTIEVNSFSGYLKLTDNVYIKNADIVEEAKKVKPTVVVNAANVYLKHGGGVAGALNKATNNAMQVESDDYIATNGPLKVGGSCVLSGHNLAKHCLHVVGPNVNKGEDIQLLKSAYENFNQHEVLLAPLLSAGIFGADPIHSLRVCVDTVRTNVYLAVFDKNLYDKLVSSFLEMKSEKQVEQKIAEIPKEEVKPFITESKPSVEQRKQDDKKIKACVEEVTTTLEETKFLTENLLLYIDINGNLHPDSATLVSDIDITFLKKDAPYIVGDVVQEGVLTAVVIPTKKAGGTTEMLAKALRKVPTDNYITTYPGQGLNGYTVEEAKTVLKKCKSAFYILPSIISNEKQEILGTVSWNLREMLAHAEETRKLMPVCVETKAIVSTIQRKYKGIKIQEGVVDYGARFYFYTSKTTVASLINTLNDLNETLVTMPLGYVTHGLNLEEAARYMRSLKVPATVSVSSPDAVTAYNGYLTSSSKTPEEHFIETISLAGSYKDWSYSGQSTQLGIEFLKRGDKSVYYTSNPTTFHLDGEVITFDNLKTLLSLREVRTIKVFTTVDNINLHTQVVDMSMTYGQQFGPTYLDGADVTKIKPHNSHEGKTFYVLPNDDTLRVEAFEYYHTTDPSFLGRYMSALNHTKKWKYPQVNGLTSIKWADNNCYLATALLTLQQIELKFNPPALQDAYYRARAGEAANFCALILAYCNKTVGELGDVRETMSYLFQHANLDSCKRVLNVVCKTCGQQQTTLKGVEAVMYMGTLSYEQFKKGVQIPCTCGKQATKYLVQQESPFVMMSAPPAQYELKHGTFTCASEYTGNYQCGHYKHITSKETLYCIDGALLTKSSEYKGPITDVFYKENSYTTTIKPVTYKLDGVVCTEIDPKLDNYYKKDNSYFTEQPIDLVPNQPYPNASFDNFKFVCDNIKFADDLNQLTGYKKPASRELKVTFFPDLNGDVVAIDYKHYTPSFKKGAKLLHKPIVWHVNNATNKATYKPNTWCIRCLWSTKPVETSNSFDVLKSEDAQGMDNLACEDLKPVSEEVVENPTIQKDVLECNVKTTEVVGDIILKPANNSLKITEEVGHTDLMAAYVDNSSLTIKKPNELSRVLGLKTLATHGLAAVNSVPWDTIANYAKPFLNKVVSTTTNIVTRCLNRVCTNYMPYFFTLLLQLCTFTRSTNSRIKASMPTTIAKNTVKSVGKFCLEASFNYLKSPNFSKLINIIIWFLLLSVCLGSLIYSTAALGVLMSNLGMPSYCTGYREGYLNSTNVTIATYCTGSIPCSVCLSGLDSLDTYPSLETIQITISSFKWDLTAFGLVAEWFLAYILFTRFFYVLGLAAIMQLFFSYFAVHFISNSWLMWLIINLVQMAPISAMVRMYIFFASFYYVWKSYVHVVDGCNSSTCMMCYKRNRATRVECTTIVNGVRRSFYVYANGGKGFCKLHNWNCVNCDTFCAGSTFISDEVARDLSLQFKRPINPTDQSSYIVDSVTVKNGSIHLYFDKAGQKTYERHSLSHFVNLDNLRANNTKGSLPINVIVFDGKSKCEESSAKSASVYYSQLMCQPILLLDQALVSDVGDSAEVAVKMFDAYVNTFSSTFNVPMEKLKTLVATAEAELAKNVSLDNVLSTFISAARQGFVDSDVETKDVVECLKLSHQSDIEVTGDSCNNYMLTYNKVENMTPRDLGACIDCSARHINAQVAKSHNIALIWNVKDFMSLSEQLRKQIRSAAKKNNLPFKLTCATTRQVVNVVTTKIALKGGKIVNNWLKQLIKVTLVFLFVAAIFYLITPVHVMSKHTDFSSEIIGYKAIDGGVTRDIASTDTCFANKHADFDTWFSQRGGSYTNDKACPLIAAVITREVGFVVPGLPGTILRTTNGDFLHFLPRVFSAVGNICYTPSKLIEYTDFATSACVLAAECTIFKDASGKPVPYCYDTNVLEGSVAYESLRPDTRYVLMDGSIIQFPNTYLEGSVRVVTTFDSEYCRHGTCERSEAGVCVSTSGRWVLNNDYYRSLPGVFCGVDAVNLLTNMFTPLIQPIGALDISASIVAGGIVAIVVTCLAYYFMRFRRAFGEYSHVVAFNTLLFLMSFTVLCLTPVYSFLPGVYSVIYLYLTFYLTNDVSFLAHIQWMVMFTPLVPFWITIAYIICISTKHFYWFFSNYLKRRVVFNGVSFSTFEEAALCTFLLNKEMYLKLRSDVLLPLTQYNRYLALYNKYKYFSGAMDTTSYREAACCHLAKALNDFSNSGSDVLYQPPQTSITSAVLQSGFRKMAFPSGKVEGCMVQVTCGTTTLNGLWLDDVVYCPRHVICTSEDMLNPNYEDLLIRKSNHNFLVQAGNVQLRVIGHSMQNCVLKLKVDTANPKTPKYKFVRIQPGQTFSVLACYNGSPSGVYQCAMRPNFTIKGSFLNGSCGSVGFNIDYDCVSFCYMHHMELPTGVHAGTDLEGNFYGPFVDRQTAQAAGTDTTITVNVLAWLYAAVINGDRWFLNRFTTTLNDFNLVAMKYNYEPLTQDHVDILGPLSAQTGIAVLDMCASLKELLQNGMNGRTILGSALLEDEFTPFDVVRQCSGVTFQSAVKRTIKGTHHWLLLTILTSLLVLVQSTQWSLFFFLYENAFLPFAMGIIAMSAFAMMFVKHKHAFLCLFLLPSLATVAYFNMVYMPASWVMRIMTWLDMVDTSLSGFKLKDCVMYASAVVLLILMTARTVYDDGARRVWTLMNVLTLVYKVYYGNALDQAISMWALIISVTSNYSGVVTTVMFLARGIVFMCVEYCPIFFITGNTLQCIMLVYCFLGYFCTCYFGLFCLLNRYFRLTLGVYDYLVSTQEFRYMNSQGLLPPKNSIDAFKLNIKLLGVGGKPCIKVATVQSKMSDVKCTSVVLLSVLQQLRVESSSKLWAQCVQLHNDILLAKDTTEAFEKMVSLLSVLLSMQGAVDINKLCEEMLDNRATLQAIASEFSSLPSYAAFATAQEAYEQAVANGDSEVVLKKLKKSLNVAKSEFDRDAAMQRKLEKMADQAMTQMYKQARSEDKRAKVTSAMQTMLFTMLRKLDNDALNNIINNARDGCVPLNIIPLTTAAKLMVVIPDYNTYKNTCDGTTFTYASALWEIQQVVDADSKIVQLSEISMDNSPNLAWPLIVTALRANSAVKLQNNELSPVALRQMSCAAGTTQTACTDDNALAYYNTTKGGRFVLALLSDLQDLKWARFPKSDGTGTIYTELEPPCRFVTDTPKGPKVKYLYFIKGLNNLNRGMVLGSLAATVRLQAGNATEVPANSTVLSFCAFAVDAAKAYKDYLASGGQPITNCVKMLCTHTGTGQAITVTPEANMDQESFGGASCCLYCRCHIDHPNPKGFCDLKGKYVQIPTTCANDPVGFTLKNTVCTVCGMWKGYGCSCDQLREPMLQSADAQSFLNRVCGVSAARLTPCGTGTSTDVVYRAFDIYNDKVAGFAKFLKTNCCRFQEKDEDDNLIDSYFVVKRHTFSNYQHEETIYNLLKDCPAVAKHDFFKFRIDGDMVPHISRQRLTKYTMADLVYALRHFDEGNCDTLKEILVTYNCCDDDYFNKKDWYDFVENPDILRVYANLGERVRQALLKTVQFCDAMRNAGIVGVLTLDNQDLNGNWYDFGDFIQTTPGSGVPVVDSYYSLLMPILTLTRALTAESHVDTDLTKPYIKWDLLKYDFTEERLKLFDRYFKYWDQTYHPNCVNCLDDRCILHCANFNVLFSTVFPPTSFGPLVRKIFVDGVPFVVSTGYHFRELGVVHNQDVNLHSSRLSFKELLVYAADPAMHAASGNLLLDKRTTCFSVAALTNNVAFQTVKPGNFNKDFYDFAVSKGFFKEGSSVELKHFFFAQDGNAAISDYDYYRYNLPTMCDIRQLLFVVEVVDKYFDCYDGGCINANQVIVNNLDKSAGFPFNKWGKARLYYDSMSYEDQDALFAYTKRNVIPTITQMNLKYAISAKNRARTVAGVSICSTMTNRQFHQKLLKSIAATRGATVVIGTSKFYGGWHNMLKTVYSDVENPHLMGWDYPKCDRAMPNMLRIMASLVLARKHTTCCSLSHRFYRLANECAQVLSEMVMCGGSLYVKPGGTSSGDATTAYANSVFNICQAVTANVNALLSTDGNKIADKYVRNLQHRLYECLYRNRDVDTDFVNEFYAYLRKHFSMMILSDDAVVCFNSTYASQGLVASIKNFKSVLYYQNNVFMSEAKCWTETDLTKGPHEFCSQHTMLVKQGDDYVYLPYPDPSRILGAGCFVDDIVKTDGTLMIERFVSLAIDAYPLTKHPNQEYADVFHLYLQYIRKLHDELTGHMLDMYSVMLTNDNTSRYWEPEFYEAMYTPHTVLQAVGACVLCNSQTSLRCGACIRRPFLCCKCCYDHVISTSHKLVLSVNPYVCNAPGCDVTDVTQLYLGGMSYYCKSHKPPISFPLCANGQVFGLYKNTCVGSDNVTDFNAIATCDWTNAGDYILANTCTERLKLFAAETLKATEETFKLSYGIATVREVLSDRELHLSWEVGKPRPPLNRNYVFTGYRVTKNSKVQIGEYTFEKGDYGDAVVYRGTTTYKLNVGDYFVLTSHTVMPLSAPTLVPQEHYVRITGLYPTLNISDEFSSNVANYQKVGMQKYSTLQGPPGTGKSHFAIGLALYYPSARIVYTACSHAAVDALCEKALKYLPIDKCSRIIPARARVECFDKFKVNSTLEQYVFCTVNALPETTADIVVFDEISMATNYDLSVVNARLRAKHYVYIGDPAQLPAPRTLLTKGTLEPEYFNSVCRLMKTIGPDMFLGTCRRCPAEIVDTVSALVYDNKLKAHKDKSAQCFKMFYKGVITHDVSSAINRPQIGVVREFLTRNPAWRKAVFISPYNSQNAVASKILGLPTQTVDSSQGSEYDYVIFTQTTETAHSCNVNRFNVAITRAKVGILCIMSDRDLYDKLQFTSLEIPRRNVATLQAENVTGLFKDCSKVITGLHPTQAPTHLSVDTKFKTEGLCVDIPGIPKDMTYRRLISMMGFKMNYQVNGYPNMFITREEAIRHVRAWIGFDVEGCHATREAVGTNLPLQLGFSTGVNLVAVPTGYVDTPNNTDFSRVSAKPPPGDQFKHLIPLMYKGLPWNVVRIKIVQMLSDTLKNLSDRVVFVLWAHGFELTSMKYFVKIGPERTCCLCDRRATCFSTASDTYACWHHSIGFDYVYNPFMIDVQQWGFTGNLQSNHDLYCQVHGNAHVASCDAIMTRCLAVHECFVKRVDWTIEYPIIGDELKINAACRKVQHMVVKAALLADKFPVLHDIGNPKAIKCVPQADVEWKFYDAQPCSDKAYKIEELFYSYATHSDKFTDGVCLFWNCNVDRYPANSIVCRFDTRVLSNLNLPGCDGGSLYVNKHAFHTPAFDKSAFVNLKQLPFFYYSDSPCESHGKQVVSDIDYVPLKSATCITRCNLGGAVCRHHANEYRLYLDAYNMMISAGFSLWVYKQFDTYNLWNTFTRLQSLENVAFNVVNKGHFDGQQGEVPVSIINNTVYTKVDGVDVELFENKTTLPVNVAFELWAKRNIKPVPEVKILNNLGVDIAANTVIWDYKRDAPAHISTIGVCSMTDIAKKPTETICAPLTVFFDGRVDGQVDLFRNARNGVLITEGSVKGLQPSVGPKQASLNGVTLIGEAVKTQFNYYKKVDGVVQQLPETYFTQSRNLQEFKPRSQMEIDFLELAMDEFIERYKLEGYAFEHIVYGDFSHSQLGGLHLLIGLAKRFKESPFELEDFIPMDSTVKNYFITDAQTGSSKCVCSVIDLLLDDFVEIIKSQDLSVVSKVVKVTIDYTEISFMLWCKDGHVETFYPKLQSSQAWQPGVAMPNLYKMQRMLLEKCDLQNYGDSATLPKGIMMNVAKYTQLCQYLNTLTLAVPYNMRVIHFGAGSDKGVAPGTAVLRQWLPTGTLLVDSDLNDFVSDADSTLIGDCATVHTANKWDLIISDMYDPKTKNVTKENDSKEGFFTYICGFIQQKLALGGSVAIKITEHSWNADLYKLMGHFAWWTAFVTNVNASSSEAFLIGCNYLGKPREQIDGYVMHANYIFWRNTNPIQLSSYSLFDMSKFPLKLRGTAVMSLKEGQINDMILSLLSKGRLIIRENNRVVISSDVLVNN,6.481486060122112 +Cn1cc(cc(NC(=O)N2CCC(CC2)n2c3cccnc3[nH]c2=O)c1=O)-c1ccccc1F,MEKKCTLNFLVLLPFFMILVTAELEESPEDSIQLGVTRNKIMTAQYECYQKIMQDPIQQAEGVYCNRTWDGWLCWNDVAAGTESMQLCPDYFQDFDPSEKVTKICDQDGNWFRHPASNRTWTNYTQCNVNTHEKVKTALNLFYLTIIGHGLSIASLLISLGIFFYFKSLSCQRITLHKNLFFSFVCNSVVTIIHLTAVANNQALVATNPVSCKVSQFIHLYLMGCNYFWMLCEGIYLHTLIVVAVFAEKQHLMWYYFLGWGFPLIPACIHAIARSLYYNDNCWISSDTHLLYIIHGPICAALLVNLFFLLNIVRVLITKLKVTHQAESNLYMKAVRATLILVPLLGIEFVLIPWRPEGKIAEEVYDYIMHILMHFQGLLVSTIFCFFNGEVQAILRRNWNQYKIQFGNSFSNSEALRSASYTVSTISDGPGYSHDCPSEHLNGKSIHDIENVLLKPENLYN,6.321481620959886 +COc1cccc(F)c1C1CCCC(=O)N1Cc1ccc(OC(F)(F)F)cc1,MSGTKLEDSPPCRNWSSASELNETQEPFLNPTDYDDEEFLRYLWREYLHPKEYEWVLIAGYIIVFVVALIGNVLVCVAVWKNHHMRTVTNYFIVNLSLADVLVTITCLPATLVVDITETWFFGQSLCKVIPYLQTVSVSVSVLTLSCIALDRWYAICHPLMFKSTAKRARNSIVIIWIVSCIIMIPQAIVMECSTVFPGLANKTTLFTVCDERWGGEIYPKMYHICFFLVTYMAPLCLMVLAYLQIFRKLWCRQIPGTSSVVQRKWKPLQPVSQPRGPGQPTKSRMSAVAAEIKQIRARRKTARMLMIVLLVFAICYLPISILNVLKRVFGMFAHTEDRETVYAWFTFSHWLVYANSAANPIIYNFLSGKFREEFKAAFSCCCLGVHHRQEDRLTRGRTSTESRKSLTTQISNFDNISKLSEQVVLTSISTLPAANGAGPLQNW,6.79317412396815 +Cc1nnc2ccc3n(Cc4ccccc4)c(cc3n12)C(=O)NC1CCC1,MLQNVTPHNKLPGEGNAGLLGLGPEAAAPGKRIRKPSLLYEGFESPTMASVPALQLTPANPPPPEVSNPKKPGRVTNQLQYLHKVVMKALWKHQFAWPFRQPVDAVKLGLPDYHKIIKQPMDMGTIKRRLENNYYWAASECMQDFNTMFTNCYIYNKPTDDIVLMAQTLEKIFLQKVASMPQEEQELVVTIPKNSHKKGAKLAALQGSVTSAHQVPAVSSVSHTALYTPPPEIPTTVLNIPHPSVISSPLLKSLHSAGPPLLAVTAAPPAQPLAKKKGVKRKADTTTPTPTAILAPGSPASPPGSLEPKAARLPPMRRESGRPIKPPRKDLPDSQQQHQSSKKGKLSEQLKHCNGILKELLSKKHAAYAWPFYKPVDASALGLHDYHDIIKHPMDLSTVKRKMENRDYRDAQEFAADVRLMFSNCYKYNPPDHDVVAMARKLQDVFEFRYAKMPDEPLEPGPLPVSTAMPPGLAKSSSESSSEESSSESSSEEEEEEDEEDEEEEESESSDSEEERAHRLAELQEQLRAVHEQLAALSQGPISKPKRKREKKEKKKKRKAEKHRGRAGADEDDKGPRAPRPPQPKKSKKASGSGGGSAALGPSGFGPSGGSGTKLPKKATKTAPPALPTGYDSEEEEESRPMSYDEKRQLSLDINKLPGEKLGRVVHIIQAREPSLRDSNPEEIEIDFETLKPSTLRELERYVLSCLRKKPRKPYTIKKPVGKTKEELALEKKRELEKRLQDVSGQLNSTKKPPKKANEKTESSSAQQVAVSRLSASSSSSDSSSSSSSSSSSDTSDSDSG,6.0 +OC(=O)c1cccc(Nc2ccc(cc2)[N+]([O-])=O)c1,MDSKHQCVKLNDGHFMPVLGFGTYAPPEVPRSKALEVTKLAIEAGFRHIDSAHLYNNEEQVGLAIRSKIADGSVKREDIFYTSKLWSTFHRPELVRPALENSLKKAQLDYVDLYLIHSPMSLKPGEELSPTDENGKVIFDIVDLCTTWEAMEKCKDAGLAKSIGVSNFNRRQLEMILNKPGLKYKPVCNQVECHPYFNRSKLLDFCKSKDIVLVAYSALGSQRDKRWVDPNSPVLLEDPVLCALAKKHKRTPALIALRYQLQRGVVVLAKSYNEQRIRQNVQVFEFQLTAEDMKAIDGLDRNLHYFNSDSFASHPNYPYSDEY,7.522878745280337 +Fc1ccc(cc1)-n1ccc(OCCOc2cc(Cl)ccn2)cc1=O,MKMLTRLQILMLALFSKGFLLSLGDHNFMRREIKIEGDLVLGGLFPINEKGTGTEECGRINEDRGIQRLEAMLFAIDEINKDNYLLPGVKLGVHILDTCSRDTYALEQSLEFVRASLTKVDEAEYMCPDGSYAIQENIPLLIAGVIGGSYSSVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFYQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFEQEARLRNICIATAEKVGRSNIRKSYDSVIRELLQKPNARVVVLFMRSDDSRELIAAANRVNASFTWVASDGWGAQESIVKGSEHVAYGAITLELASHPVRQFDRYFQSLNPYNNHRNPWFRDFWEQKFQCSLQNKRNHRQVCDKHLAIDSSNYEQESKIMFVVNAVYAMAHALHKMQRTLCPNTTKLCDAMKILDGKKLYKEYLLKINFTAPFNPNKGADSIVKFDTFGDGMGRYNVFNLQQTGGKYSYLKVGHWAETLSLDVDSIHWSRNSVPTSQCSDPCAPNEMKNMQPGDVCCWICIPCEPYEYLVDEFTCMDCGPGQWPTADLSGCYNLPEDYIKWEDAWAIGPVTIACLGFLCTCIVITVFIKHNNTPLVKASGRELCYILLFGVSLSYCMTFFFIAKPSPVICALRRLGLGTSFAICYSALLTKTNCIARIFDGVKNGAQRPKFISPSSQVFICLGLILVQIVMVSVWLILETPGTRRYTLPEKRETVILKCNVKDSSMLISLTYDVVLVILCTVYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCISVSLSGFVVLGCLFAPKVHIVLFQPQKNVVTHRLHLNRFSVSGTATTYSQSSASTYVPTVCNGREVLDSTTSSL,5.840132152907433 +COc1cc(C=CC(=O)CC(=O)C=Cc2ccc(O)c(OC)c2)ccc1O,MVVFNGLLKIKICEAVSLKPTAWSLRHAVGPRPQTFLLDPYIALNVDDSRIGQTATKQKTNSPAWHDEFVTDVCNGRKIELAVFHDAPIGYDDFVANCTIQFEELLQNGSRHFEDWIDLEPEGRVYVIIDLSGSSGEAPKDNEERVFRERMRPRKRQGAVRRRVHQVNGHKFMATYLRQPTYCSHCRDFIWGVIGKQGYQCQVCTCVVHKRCHELIITKCAGLKKQETPDQVGSQRFSVNMPHKFGIHNYKVPTFCDHCGSLLWGLLRQGLQCKVCKMNVHRRCETNVAPNCGVDARGIAKVLADLGVTPDKITNSGQRRKKLIAGAESPQPASGSSPSEEDRSKSAPTSPCDQEIKELENNIRKALSFDNRGEEHRAASSPDGQLMSPGENGEVRQGQAKRLGLDEFNFIKVLGKGSFGKVMLAELKGKDEVYAVKVLKKDVILQDDDVDCTMTEKRILALARKHPYLTQLYCCFQTKDRLFFVMEYVNGGDLMFQIQRSRKFDEPRSRFYAAEVTSALMFLHQHGVIYRDLKLDNILLDAEGHCKLADFGMCKEGILNGVTTTTFCGTPDYIAPEILQELEYGPSVDWWALGVLMYEMMAGQPPFEADNEDDLFESILHDDVLYPVWLSKEAVSILKAFMTKNPHKRLGCVASQNGEDAIKQHPFFKEIDWVLLEQKKIKPPFKPRIKTKRDVNNFDQDFTREEPVLTLVDEAIVKQINQEEFKGFSYFGEDLMP,5.055024091587952 +Cc1cc(COc2ccc(CC3C(CCS3(=O)=O)C(=O)NO)cc2)c2ccccc2n1,MSLWQPLVLVLLVLGCCFAAPRQRQSTLVLFPGDLRTNLTDRQLAEEYLYRYGYTRVAEMRGESKSLGPALLLLQKQLSLPETGELDSATLKAMRTPRCGVPDLGRFQTFEGDLKWHHHNITYWIQNYSEDLPRAVIDDAFARAFALWSAVTPLTFTRVYSRDADIVIQFGVAEHGDGYPFDGKDGLLAHAFPPGPGIQGDAHFDDDELWSLGKGVVVPTRFGNADGAACHFPFIFEGRSYSACTTDGRSDGLPWCSTTANYDTDDRFGFCPSERLYTQDGNADGKPCQFPFIFQGQSYSACTTDGRSDGYRWCATTANYDRDKLFGFCPTRADSTVMGGNSAGELCVFPFTFLGKEYSTCTSEGRGDGRLWCATTSNFDSDKKWGFCPDQGYSLFLVAAHEFGHALGLDHSSVPEALMYPMYRFTEGPPLHKDDVNGIRHLYGPRPEPEPRPPTTTTPQPTAPPTVCPTGPPTVHPSERPTAGPTGPPSAGPTGPPTAGPSTATTVPLSPVDDACNVNIFDAIAEIGNQLYLFKDGKYWRFSEGRGSRPQGPFLIADKWPALPRKLDSVFEERLSKKLFFFSGRQVWVYTGASVLGPRRLDKLGLGADVAQVTGALRSGRGKMLLFSGRRLWRFDVKAQMVDPRSASEVDRMFPGVPLDTHDVFQYREKAYFCQDRFYWRVSSRSELNQVDQVGYVTYDILQCPED,5.672028376376989 +O=C(CCc1ccccc1)Nc1cccc(Cc2n[nH]c(=O)c3CCCCc23)c1,MAESSDKLYRVEYAKSGRASCKKCSESIPKDSLRMAIMVQSPMFDGKVPHWYHFSCFWKVGHSIRHPDVEVDGFSELRWDDQQKVKKTAEAGGVTGKGQDGIGSKAEKTLGDFAAEYAKSNRSTCKGCMEKIEKGQVRLSKKMVDPEKPQLGMIDRWYHPGCFVKNREELGFRPEYSASQLKGFSLLATEDKEALKKQLPGVKSEGKRKGDEVDGVDEVAKKKSKKEKDKDSKLEKALKAQNDLIWNIKDELKKVCSTNDLKELLIFNKQQVPSGESAILDRVADGMVFGALLPCEECSGQLVFKSDAYYCTGDVTAWTKCMVKTQTPNRKEWVTPKEFREISYLKKLKVKKQDRIFPPETSASVAATPPPSTASAPAAVNSSASADKPLSNMKILTLGKLSRNKDEVKAMIEKLGGKLTGTANKASLCISTKKEVEKMNKKMEEVKEANIRVVSEDFLQDVSASTKSLQELFLAHILSPWGAEVKAEPVEVVAPRGKSGAALSKKSKGQVKEEGINKSEKRMKLTLKGGAAVDPDSGLEHSAHVLEKGGKVFSATLGLVDIVKGTNSYYKLQLLEDDKENRYWIFRSWGRVGTVIGSNKLEQMPSKEDAIEHFMKLYEEKTGNAWHSKNFTKYPKKFYPLEIDYGQDEEAVKKLTVNPGTKSKLPKPVQDLIKMIFDVESMKKAMVEYEIDLQKMPLGKLSKRQIQAAYSILSEVQQAVSQGSSDSQILDLSNRFYTLIPHDFGMKKPPLLNNADSVQAKVEMLDNLLDIEVAYSLLRGGSDDSSKDPIDVNYEKLKTDIKVVDRDSEEAEIIRKYVKNTHATTHNAYDLEVIDIFKIEREGECQRYKPFKQLHNRRLLWHGSRTTNFAGILSQGLRIAPPEAPVTGYMFGKGIYFADMVSKSANYCHTSQGDPIGLILLGEVALGNMYELKHASHISKLPKGKHSVKGLGKTTPDPSANISLDGVDVPLGTGISSGVNDTSLLYNEYIVYDIAQVNLKYLLKLKFNFKTSLW,7.107905397309519 +NS(=O)(=O)c1ccc(OCC#C)cc1,MRMLLALLALSAARPSASAESHWCYEVQAESSNYPCLVPVKWGGNCQKDRQSPINIVTTKAKVDKKLGRFFFSGYDKKQTWTVQNNGHSVMMLLENKASISGGGLPAPYQAKQLHLHWSDLPYKGSEHSLDGEHFAMEMHIVHEKEKGTSRNVKEAQDPEDEIAVLAFLVEAGTQVNEGFQPLVEALSNIPKPEMSTTMAESSLLDLLPKEEKLRHYFRYLGSLTTPTCDEKVVWTVFREPIQLHREQILAFSQKLYYDKEQTVSMKDNVRPLQQLGQRTVIKSGAPGRPLPWALPALLGPMLACLLAGFLR,5.760700520873107 +COc1cc2c(cc1-c1c(C)noc1C)[nH]c1nc(C)nc(-c3ccc(C(=O)NC4CCN(CC4)C4COC4)c4ccccc34)c21,WKHQFAWPFRQPVDAVKLGLPDYHKIIKQPMDMGTIKRRLENNYYWAASECMQDFNTMFTNCYIYNKPTDDIV,8.207608310501746 +OC(c1cc(F)cc(OCc2ccc3c(cc(=O)oc3c2)-c2ccc(F)cc2)c1)(C(F)(F)F)C(F)(F)F,MPSYTVTVATGSQWFAGTDDYIYLSLVGSAGCSEKHLLDKPFYNDFERGAVDSYDVTVDEELGEIQLVRIEKRKYWLNDDWYLKYITLKTPHGDYIEFPCYRWITGDVEVVLRDGRAKLARDDQIHILKQHRRKELETRQKQYRWMEWNPGFPLSIDAKCHKDLPRDIQFDSEKGVDFVLNYSKAMENLFINRFMHMFQSSWNDFADFEKIFVKISNTISERVMNHWQEDLMFGYQFLNGCNPVLIRRCTELPEKLPVTTEMVECSLERQLSLEQEVQQGNIFIVDFELLDGIDANKTDPCTLQFLAAPICLLYKNLANKIVPIAIQLNQIPGDENPIFLPSDAKYDWLLAKIWVRSSDFHVHQTITHLLRTHLVSEVFGIAMYRQLPAVHPIFKLLVAHVRFTIAINTKAREQLICECGLFDKANATGGGGHVQMVQRAMKDLTYASLCFPEAIKARGMESKEDIPYYFYRDDGLLVWEAIRTFTAEVVDIYYEGDQVVEEDPELQDFVNDVYVYGMRGRKSSGFPKSVKSREQLSEYLTVVIFTASAQHAAVNFGQYDWCSWIPNAPPTMRAPPPTAKGVVTIEQIVDTLPDRGRSCWHLGAVWALSQFQENELFLGMYPEEHFIEKPVKEAMARFRKNLEAIVSVIAERNKKKQLPYYYLSPDRIPNSVAI,7.259637310505756 +CS(=O)(=O)Nc1nnc2cc(OCC34CC5CC(CC(C5)C3)C4)c(Br)cn12,MAMLPPPGPQSFVHFTKQSLALIEQRIAERKSKEPKEEKKDDDEEAPKPSSDLEAGKQLPFIYGDIPPGMVSEPLEDLDPYYADKKTFIVLNKGKTIFRFNATPALYMLSPFSPLRRISIKILVHSLFSMLIMCTILTNCIFMTMNNPPDWTKNVEYTFTGIYTFESLVKILARGFCVGEFTFLRDPWNWLDFVVIVFAYLTEFVNLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLKHKCFRNSLENNETLESIMNTLESEEDFRKYFYYLEGSKDALLCGFSTDSGQCPEGYTCVKIGRNPDYGYTSFDTFSWAFLALFRLMTQDYWENLYQQTLRAAGKTYMIFFVVVIFLGSFYLINLILAVVAMAYEEQNQANIEEAKQKELEFQQMLDRLKKEQEEAEAIAAAAAEYTSIRRSRIMGLSESSSETSKLSSKSAKERRNRRKKKNQKKLSSGEEKGDAEKLSKSESEDSIRRKSFHLGVEGHRRAHEKRLSTPNQSPLSIRGSLFSARRSSRTSLFSFKGRGRDIGSETEFADDEHSIFGDNESRRGSLFVPHRPQERRSSNISQASRSPPMLPVNGKMHSAVDCNGVVSLVDGRSALMLPNGQLLPEVIIDKATSDDSGTTNQIHKKRRCSSYLLSEDMLNDPNLRQRAMSRASILTNTVEELEESRQKCPPWWYRFAHKFLIWNCSPYWIKFKKCIYFIVMDPFVDLAITICIVLNTLFMAMEHHPMTEEFKNVLAIGNLVFTGIFAAEMVLKLIAMDPYEYFQVGWNIFDSLIVTLSLVELFLADVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINDDCTLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLIVYMMVMVIGNLVVLNLFLALLLSSFSSDNLTAIEEDPDANNLQIAVTRIKKGINYVKQTLREFILKAFSKKPKISREIRQAEDLNTKKENYISNHTLAEMSKGHNFLKEKDKISGFGSSVDKHLMEDSDGQSFIHNPSLTVTVPIAPGESDLENMNAEELSSDSDSEYSKVRLNRSSSSECSTVDNPLPGEGEEAEAEPMNSDEPEACFTDGCVWRFSCCQVNIESGKGKIWWNIRKTCYKIVEHSWFESFIVLMILLSSGALAFEDIYIERKKTIKIILEYADKIFTYIFILEMLLKWIAYGYKTYFTNAWCWLDFLIVDVSLVTLVANTLGYSDLGPIKSLRTLRALRPLRALSRFEGMRVVVNALIGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYECINTTDGSRFPASQVPNRSECFALMNVSQNVRWKNLKVNFDNVGLGYLSLLQVATFKGWTIIMYAAVDSVNVDKQPKYEYSLYMYIYFVVFIIFGSFFTLNLFIGVIIDNFNQQKKKLGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKIQGCIFDLVTNQAFDISIMVLICLNMVTMMVEKEGQSQHMTEVLYWINVVFIILFTGECVLKLISLRHYYFTVGWNIFDFVVVIISIVGMFLADLIETYFVSPTLFRVIRLARIGRILRLVKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEDGINDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPKKVHPGSSVEGDCGNPSVGIFYFVSYIIISFLVVVNMYIAVILENFSVATEESTEPLSEDDFEMFYEVWEKFDPDATQFIEFSKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDSLRSQMEERFMSANPSKVSYEPITTTLKRKQEDVSATVIQRAYRRYRLRQNVKNISSIYIKDGDRDDDLLNKKDMAFDNVNENSSPEKTDATSSTTSPPSYDSVTKPDKEKYEQDRTEKEDKGKDSKESKK,7.552841968657781 +Cc1cc2nc([nH]c2cc1C)[C@@H]1CC(=C)CN1C(=O)c1ccccc1-n1nccn1,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,7.292429823902063 +CC(C)Cc1cc(ccc1C(O)=O)-c1ccc(CCNC[C@H](O)c2cnccc2N)cc1,MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL,5.494850021680094 +CCCCCCCC(=O)OC1CC2CC(OC(C)=O)C(C1)N2C,MTLHNNSTTSPLFPNISSSWIHSPSDAGLPPGTVTHFGSYNVSRAAGNFSSPDGTTDDPLGGHTVWQVVFIAFLTGILALVTIIGNILVIVSFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLAIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAETENFVHPTGSSRSCSSYELQQQSMKRSNRRKYGRCHFWFTTKSWKPSSEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSTILNSTKLPSSDNLQVPEEELGMVDLERKADKLQAQKSVDDGGSFPKSFSKLPIQLESAVDTAKTSDVNSSVGKSTATLPLSFKEATLAKRFALKTRSQITKRKRMSLVKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTFWNLGYWLCYINSTVNPVCYALCNKTFRTTFKMLLLCQCDKKKRRKQQYQQRQSVIFHKRAPEQAL,-4.999999999999996 +Oc1cccc(c1)C(=O)c1ccc(s1)-c1ccc(O)c(O)c1,MARTVVLITGCSSGIGLHLAVRLASDPSQSFKVYATLRDLKTQGRLWEAARALACPPGSLETLQLDVRDSKSVAAARERVTEGRVDVLVCNAGLGLLGPLEALGEDAVASVLDVNVVGTVRMLQAFLPDMKRRGSGRVLVTGSVGGLMGLPFNDVYCASKFALEGLCESLAVLLLPFGVHLSLIECGPVHTAFMEKVLGSPEEVLDRTDIHTFHRFYQYLAHSKQVFREAAQNPEEVAEVFLTALRAPKPTLRYFTTERFLPLLRMRLDDPSGSNYVTAMHREVFGDVPAKAEAGAEAGGGAGPGAEDEAGRGAVGDPELGDPPAAPQ,7.0655015487564325 +CN(C)Cc1cncc(c1)-c1cnc2[nH]nc(-c3nc4c(cncc4[nH]3)-c3cncc(c3)C(F)(F)F)c2c1,MAAASYDQLLKQVEALKMENSNLRQELEDNSNHLTKLETEASNMKEVLKQLQGSIEDEAMASSGQIDLLERLKELNLDSSNFPGVKLRSKMSLRSYGSREGSVSSRSGECSPVPMGSFPRRGFVNGSRESTGYLEELEKERSLLLADLDKEEKEKDWYYAQLQNLTKRIDSLPLTENFSLQTDMTRRQLEYEARQIRVAMEEQLGTCQDMEKRAQRRIARIQQIEKDILRIRQLLQSQATEAERSSQNKHETGSHDAERQNEGQGVGEINMATSGNGQGSTTRMDHETASVLSSSSTHSAPRRLTSHLGTKVEMVYSLLSMLGTHDKDDMSRTLLAMSSSQDSCISMRQSGCLPLLIQLLHGNDKDSVLLGNSRGSKEARARASAALHNIIHSQPDDKRGRREIRVLHLLEQIRAYCETCWEWQEAHEPGMDQDKNPMPAPVEHQICPAVCVLMKLSFDEEHRHAMNELGGLQAIAELLQVDCEMYGLTNDHYSITLRRYAGMALTNLTFGDVANKATLCSMKGCMRALVAQLKSESEDLQQVIASVLRNLSWRADVNSKKTLREVGSVKALMECALEVKKESTLKSVLSALWNLSAHCTENKADICAVDGALAFLVGTLTYRSQTNTLAIIESGGGILRNVSSLIATNEDHRQILRENNCLQTLLQHLKSHSLTIVSNACGTLWNLSARNPKDQEALWDMGAVSMLKNLIHSKHKMIAMGSAAALRNLMANRPAKYKDANIMSPGSSLPSLHVRKQKALEAELDAQHLSETFDNIDNLSPKASHRSKQRHKQSLYGDYVFDTNRHDDNRSDNFNTGNMTVLSPYLNTTVLPSSSSSRGSLDSSRSEKDRSLERERGIGLGNYHPATENPGTSSKRGLQISTTAAQIAKVMEEVSAIHTSQEDRSSGSTTELHCVTDERNALRRSSAAHTHSNTYNFTKSENSNRTCSMPYAKLEYKRSSNDSLNSVSSSDGYGKRGQMKPSIESYSEDDESKFCSYGQYPADLAHKIHSANHMDDNDGELDTPINYSLKYSDEQLNSGRQSPSQNERWARPKHIIEDEIKQSEQRQSRNQSTTYPVYTESTDDKHLKFQPHFGQQECVSPYRSRGANGSETNRVGSNHGINQNVSQSLCQEDDYEDDKPTNYSERYSEEEQHEEEERPTNYSIKYNEEKRHVDQPIDYSLKYATDIPSSQKQSFSFSKSSSGQSSKTEHMSSSSENTSTPSSNAKRQNQLHPSSAQSRSGQPQKAATCKVSSINQETIQTYCVEDTPICFSRCSSLSSLSSAEDEIGCNQTTQEADSANTLQIAEIKEKIGTRSAEDPVSEVPAVSQHPRTKSSRLQGSSLSSESARHKAVEFSSGAKSPSKSGAQTPKSPPEHYVQETPLMFSRCTSVSSLDSFESRSIASSVQSEPCSGMVSGIISPSDLPDSPGQTMPPSRSKTPPPPPQTAQTKREVPKNKAPTAEKRESGPKQAAVNAAVQRVQVLPDADTLLHFATESTPDGFSCSSSLSALSLDEPFIQKDVELRIMPPVQENDNGNETESEQPKESNENQEKEAEKTIDSEKDLLDDSDDDDIEILEECIISAMPTKSSRKAKKPAQTASKLPPPVARKPSQLPVYKLLPSQNRLQPQKHVSFTPGDDMPRVYCVEGTPINFSTATSLSDLTIESPPNELAAGEGVRGGAQSGEFEKRDTIPTEGRSTDEAQGGKTSSVTIPELDDNKAEEGDILAECINSAMPKGKSHKPFRVKKIMDQVQQASASSSAPNKNQLDGKKKKPTSPVKPIPQNTEYRTRVRKNADSKNNLNAERVFSDNKDSKKQNLKNNSKVFNDKLPNNEDRVRGSFAFDSPHHYTPIEGTPYCFSRNDSLSSLDFDDDDVDLSREKAELRKAKENKESEAKVTSHTELTSNQQSANKTQAIAKQPINRGQPKPILQKQSTFPQSSKDIPDRGAATDEKLQNFAIENTPVCFSHNSSLSSLSDIDQENNNKENEPIKETEPPDSQGEPSKPQASGYAPKSFHVEDTPVCFSRNSSLSSLSIDSEDDLLQECISSAMPKKKKPSRLKGDNEKHSPRNMGGILGEDLTLDLKDIQRPDSEHGLSPDSENFDWKAIQEGANSIVSSLHQAAAAACLSRQASSDSDSILSLKSGISLGSPFHLTPDQEEKPFTSNKGPRILKPGEKSTLETKKIESESKGIKGGKKVYKSLITGKVRSNSEISGQMKQPLQANMPSISRGRTMIHIPGVRNSSSSTSPVSKKGPPLKTPASKSPSEGQTATTSPRGAKPSVKSELSPVARQTSQIGGSSKAPSRSGSRDSTPSRPAQQPLSRPIQSPGRNSISPGRNGISPPNKLSQLPRTSSPSTASTKSSGSGKMSYTSPGRQMSQQNLTKQTGLSKNASSIPRSESASKGLNQMNNGNGANKKVELSRMSSTKSSGSESDRSERPVLVRQSTFIKEAPSPTLRRKLEESASFESLSPSSRPASPTRSQAQTPVLSPSLPDMSLSTHSSVQAGGWRKLPPNLSPTIEYNDGRPAKRHDIARSHSESPSRLPINRSGTWKREHSKHSSSLPRVSTWRRTGSSSSILSASSESSEKAKSEDEKHVNSISGTKQSKENQVSAKGTWRKIKENEFSPTNSTSQTVSSGATNGAESKTLIYQMAPAVSKTEDVWVRIEDCPINNPRSGRSPTGNTPPVIDSVSEKANPNIKDSKDNQAKQNVGNGSVPMRTVGLENRLNSFIQVDAPDQKGTEIKPGQNNPVPVSETNESSIVERTPFSSSSSSKHSSPSGTVAARVTPFNYNPSPRKSSADSTSARPSQIPTPVNNNTKKRDSKTDSTESSGTQSPKRHSGSYLVTSV,5.0 +CCCCN1CCC2(CC1)OC(CCCF)c1ccccc21,MQWAVGRRWLWVALFLAAVAVLTQIVWLWLGTQNFVFQREEIAQLARQYAGLDHELAFSKLIVELRRLHPVHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSPRHSGRYWAEISDTIISGTFHQWREGTTKSEVFYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLGFALADTVFSTQDFLTLFYTLRVYARALQLELTTYLFGQDP,8.346787486224656 +CNC(=O)[C@H](CO)NCc1ccc(OCc2cccc(F)c2)cc1,MAQALLVPPGPESFRLFTRESLAAIEKRAAEEKAKKPKKEQDIDDENKPKPNSDLEAGKNLPFIYGDIPPEMVSEPLEDLDPYYVSKKTFVVLNKGKAIFRFSATSALYILTPLNPVRKIAIKILVHSLFSMLIMCTILTNCVFMTLSNPPDWTKNVEYTFTGIYTFESLIKILARGFCLEDFTFLRDPWNWLDFSVIVMAYVTEFVDLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLRNKCSQWPPSDSAFETNTTSYFNGTMDSNGTFVNVTMSTFNWKDYIADDSHFYVLDGQKDPLLCGNGSDAGQCPEGYICVKAGRNPNYGYTSFDTFSWAFLSLFRLMTQDYWENLYQLTLRAAGKTYMIFFVLVIFLGSFYLVNLILAVVAMAYEEQNQATLEEAEQKEAEFQQMLEQLKKQQEEAQAVAAASAASRDFSGIGGLGELLESSSEASKLSSKSAKEWRNRRKKRRQREHLEGNHRADGDRFPKSESEDSVKRRSFLLSLDGNPLTGDKKLCSPHQSLLSIRGSLFSPRRNSKTSIFSFRGRAKDVGSENDFADDEHSTFEDSESRRDSLFVPHRPGERRNSNGTTTETEVRKRRLSSYQISMEMLEDSSGRQRSMSIASILTNTMEELEESRQKCPPCWYRFANVFLIWDCCDAWLKVKHLVNLIVMDPFVDLAITICIVLNTLFMAMEHYPMTQQFSSVLTVGNLVFTGIFTAEMVLKIIAMDPYYYFQEGWNIFDGIIVSLSLMELGLANVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKECVCKINVDCKLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQTMCLIVFMLVMVIGNLVVLNLFLALLLSSFSSDNLAATDDDNEMNNLQIAVGRMQKGIDFVKNKIRECFRKAFFRKPKVIEIQEGNKIDSCMSNNTGIEISKELNYLKDGNGTTSGVGTGSSVEKYVIDENDYMSFINNPSLTVTVPIAVGESDFENLNTEEFSSESELEESKEKLNATSSSEGSTVDVAPPREGEQAEIEPEEDLKPEACFTEGCIKKFPFCQVSTEEGKGKIWWNLRKTCYSIVEHNWFETFIVFMILLSSGALAFEDIYIEQRKTIKTMLEYADKVFTYIFILEMLLKWVAYGFQTYFTNAWCWLDFLIVDVSLVSLVANALGYSELGAIKSLRTLRALRPLRALSRFEGMRVVVNALVGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYHCVNTTTGNMFEIKEVNNFSDCQALGKQARWKNVKVNFDNVGAGYLALLQVATFKGWMDIMYAAVDSRDVKLQPIYEENLYMYLYFVIFIIFGSFFTLNLFIGVIIDNFNQQKKKFGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPANKFQGMVFDFVTRQVFDISIMILICLNMVTMMVETDDQSKYMTLVLSRINLVFIVLFTGEFLLKLISLRYYYFTIGWNIFDFVVVILSIVGMFLAELIEKYFVSPTLFRVIRLARIGRILRLIKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKKEAGIDDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSAPPDCDPDAIHPGSSVKGDCGNPSVGIFFFVSYIIISFLVVVNMYIAVILENFSVATEESAEPLSEDDFEMFYEVWEKFDPDATQFIEFCKLSDFAAALDPPLLIAKPNKVQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDALRIQMEDRFMASNPSKVSYEPITTTLKRKQEEVSAAIIQRNYRCYLLKQRLKNISSKYDKETIKGRIDLPIKGDMVIDKLNGNSTPEKTDGSSSTTSPPSYDSVTKPDKEKFEKDKPEKEIKGKEVRENQK,3.5228787452803374 +O=C(N(C1CCN(Cc2ccccc2)CC1)c1ccn(n1)-c1cccc(c1)C#N)c1cccs1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,7.0 +OC(=O)[C@H](Cc1ccc(OCCCNc2ccccn2)cc1)NC(=O)CC(c1ccccc1)(c1ccccc1)c1ccccc1,MCNTNMSVPTDGAVTTSQIPASEQETLVRPKPLLLKLLKSVGAQKDTYTMKEVLFYLGQYIMTKRLYDEKQQHIVYCSNDLLGDLFGVPSFSVKEHRKIYTMIYRNLVVVNQQESSDSGTSVSENRCHLEGGSDQKDLVQELQEEKPSSSHLVSRPSTSSRRRAISETEENSDELSGERQRKRHKSDSISLSFDESLALCVIREICCERSSSSESTGTPSNPDLDAGVSEHSGDWLDQDSVSDQFSVEFEVESLDSEDYSLSEEGQELSDEDDEVYQVTVYQAGESDTDSFEEDPEISLADYWKCTSCNEMNPPLPSHCNRCWALRENWLPEDKGKDKGEISEKAKLENSTQAEEGFDVPDCKKTIVNDSRESCVEENDDKITQASQSQESEDYSQPSTSSSIIYSSQEDVKEFEREETQDKEESVESSLPLNAIEPCVICQGRPKNGCIVHGKTGHLMACFTCAKKLKKRNKPCPVCRQPIQMIVLTYFP,7.026872146400302 +CN(C1CCCC1)C(=O)[C@H](CC#Cc1cccnc1)NS(=O)(=O)c1ccc2ccccc2c1,MAHVRGLQLPGCLALAALCSLVHSQHVFLAPQQARSLLQRVRRANTFLEEVRKGNLERECVEETCSYEEAFEALESSTATDVFWAKYTACETARTPRDKLAACLEGNCAEGLGTNYRGHVNITRSGIECQLWRSRYPHKPEINSTTHPGADLQENFCRNPDSSTTGPWCYTTDPTVRRQECSIPVCGQDQVTVAMTPRSEGSSVNLSPPLEQCVPDRGQQYQGRLAVTTHGLPCLAWASAQAKALSKHQDFNSAVQLVENFCRNPDGDEEGVWCYVAGKPGDFGYCDLNYCEEAVEEETGDGLDEDSDRAIEGRTATSEYQTFFNPRTFGSGEADCGLRPLFEKKSLEDKTERELLESYIDGRIVEGSDAEIGMSPWQVMLFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTENDLLVRIGKHSRTRYERNIEKISMLEKIYIHPRYNWRENLDRDIALMKLKKPVAFSDYIHPVCLPDRETAASLLQAGYKGRVTGWGNLKETWTANVGKGQPSVLQVVNLPIVERPVCKDSTRIRITDNMFCAGYKPDEGKRGDACEGDSGGPFVMKSPFNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWIQKVIDQFGE,5.6020599913279625 +CC(C)Oc1ncc(cc1N1CCOCC1)-c1cc(NC(=O)c2ccnc(c2)C(C)(F)F)ccc1C,MAALSGGGGGGAEPGQALFNGDMEPEAGAGAGAAASSAADPAIPEEVWNIKQMIKLTQEHIEALLDKFGGEHNPPSIYLEAYEEYTSKLDALQQREQQLLESLGNGTDFSVSSSASMDTVTSSSSSSLSVLPSSLSVFQNPTDVARSNPKSPQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQDGEKKPIGWDTDISWLTGEELHVEVLENVPLTTHNFVRKTFFTLAFCDFCRKLLFQGFRCQTCGYKFHQRCSTEVPLMCVNYDQLDLLFVSKFFEHHPIPQEEASLAETALTSGSSPSAPASDSIGPQILTSPSPSKSIPIPQPFRPADEDHRNQFGQRDRSSSAPNVHINTIEPVNIDDLIRDQGFRGDGGSTTGLSATPPASLPGSLTNVKALQKSPGPQRERKSSSSSEDRNRMKTLGRRDSSDDWEIPDGQITVGQRIGSGSFGTVYKGKWHGDVAVKMLNVTAPTPQQLQAFKNEVGVLRKTRHVNILLFMGYSTKPQLAIVTQWCEGSSLYHHLHIIETKFEMIKLIDIARQTAQGMDYLHAKSIIHRDLKSNNIFLHEDLTVKIGDFGLATEKSRWSGSHQFEQLSGSILWMAPEVIRMQDKNPYSFQSDVYAFGIVLYELMTGQLPYSNINNRDQIIFMVGRGYLSPDLSKVRSNCPKAMKRLMAECLKKKRDERPLFPQILASIELLARSLPKIHRSASEPSLNRAGFQTEDFSLYACASPKTPIQAGGYGAFPVH,8.869666231504993 +Cn1cc(cn1)-c1ccc2cnc(NC(=O)C3CCN(Cc4cnccn4)CC3)cc2c1,MSGRPRTTSFAESCKPVQQPSAFGSMKVSRDKDGSKVTTVVATPGQGPDRPQEVSYTDTKVIGNGSFGVVYQAKLCDSGELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDEVYLNLVLDYVPETVYRVARHYSRAKQTLPVIYVKLYMYQLFRSLAYIHSFGICHRDIKPQNLLLDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFRPRTPPEAIALCSRLLEYTPTARLTPLEACAHSFFDELRDPNVKLPNGRDTPALFNFTTQELSSNPPLATILIPPHARIQAAASTPTNATAASDANTGDRGQTNNAASASASNST,7.431798275933005 +CCCC(=O)N[C@H]1CC[C@H](CCN2CCC(CC2)c2cccc3OCCc23)CC1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,6.705974905904677 +CCCc1nc(CC)c(C(=O)OCCC(=O)Nc2ccccc2)n1Cc1ccc(cc1F)-c1ccccc1S(=O)(=O)NC(=O)OCCC(C)C,MILNSSTEDGIKRIQDDCPKAGRHNYIFVMIPTLYSIIFVVGIFGNSLVVIVIYFYMKLKTVASVFLLNLALADLCFLLTLPLWAVYTAMEYRWPFGNYLCKIASASVSFNLYASVFLLTCLSIDRYLAIVHPMKSRLRRTMLVAKVTCIIIWLLAGLASLPAIIHRNVFFIENTNITVCAFHYESQNSTLPIGLGLTKNILGFLFPFLIILTSYTLIWKALKKAYEIQKNKPRNDDIFKIIMAIVLFFFFSWIPHQIFTFLDVLIQLGIIRDCRIADIVDTAMPITICIAYFNNCLNPLFYGFLGKKFKRYFLQLLKYIPPKAKSHSNLSTKMSTLSYRPSDNVSSSTKKPAPCFEVE,10.0 +COc1ncc(cc1-c1cnc(nc1CN1[C@@H](C)[C@H](OC1=O)c1cc(cc(c1)C(F)(F)F)C(F)(F)F)N1CC(F)(F)C1)-c1c(C)n[nH]c1C,MLAATVLTLALLGNAHACSKGTSHEAGIVCRITKPALLVLNHETAKVIQTAFQRASYPDITGEKAMMLLGQVKYGLHNIQISHLSIASSQVELVEAKSIDVSIQNVSVVFKGTLKYGYTTAWWLGIDQSIDFEIDSAIDLQINTQLTCDSGRVRTDAPDCYLSFHKLLLHLQGEREPGWIKQLFTNFISFTLKLVLKGQICKEINVISNIMADFVQTRAASILSDGDIGVDISLTGDPVITASYLESHHKGHFIYKNVSEDLPLPTFSPTLLGDSRMLYFWFSERVFHSLAKVAFQDGRLMLSLMGDEFKAVLETWGFNTNQEIFQEVVGGFPSQAQVTVHCLKMPKISCQNKGVVVNSSVMVKFLFPRPDQQHSVAYTFEEDIVTTVQASYSKKKLFLSLLDFQITPKTVSNLTESSSESVQSFLQSMITAVGIPEVMSRLEVVFTALMNSKGVSLFDIINPEIITRDGFLLLQMDFGFPEHLLVDFLQSLS,7.823908740944319 +CC(C)(C#N)c1cc(ccn1)C(=O)Nc1c[nH]c(=O)c(c1)-c1ccnc(c1)N1CCOCC1,MAALSGGGGGGAEPGQALFNGDMEPEAGAGAGAAASSAADPAIPEEVWNIKQMIKLTQEHIEALLDKFGGEHNPPSIYLEAYEEYTSKLDALQQREQQLLESLGNGTDFSVSSSASMDTVTSSSSSSLSVLPSSLSVFQNPTDVARSNPKSPQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQDGEKKPIGWDTDISWLTGEELHVEVLENVPLTTHNFVRKTFFTLAFCDFCRKLLFQGFRCQTCGYKFHQRCSTEVPLMCVNYDQLDLLFVSKFFEHHPIPQEEASLAETALTSGSSPSAPASDSIGPQILTSPSPSKSIPIPQPFRPADEDHRNQFGQRDRSSSAPNVHINTIEPVNIDDLIRDQGFRGDGGSTTGLSATPPASLPGSLTNVKALQKSPGPQRERKSSSSSEDRNRMKTLGRRDSSDDWEIPDGQITVGQRIGSGSFGTVYKGKWHGDVAVKMLNVTAPTPQQLQAFKNEVGVLRKTRHVNILLFMGYSTKPQLAIVTQWCEGSSLYHHLHIIETKFEMIKLIDIARQTAQGMDYLHAKSIIHRDLKSNNIFLHEDLTVKIGDFGLATEKSRWSGSHQFEQLSGSILWMAPEVIRMQDKNPYSFQSDVYAFGIVLYELMTGQLPYSNINNRDQIIFMVGRGYLSPDLSKVRSNCPKAMKRLMAECLKKKRDERPLFPQILASIELLARSLPKIHRSASEPSLNRAGFQTEDFSLYACASPKTPIQAGGYGAFPVH,4.730603817305009 +CC1CC(CCC1Nc1ncnc2ccc(cc12)C#N)N1CCOCC1,MNKPITPSTYVRCLNVGLIRKLSDFIDPQEGWKKLAVAIKKPSGDDRYNQFHIRRFEALLQTGKSPTSELLFDWGTTNCTVGDLVDLLIQNEFFAPASLLLPDAVPKTANTLPSKEAITVQQKQMPFCDKDRTLMTPVQNLEQSYMPPDSSSPENKSLEVSDTRFHSFSFYELKNVTNNFDERPISVGGNKMGEGGFGVVYKGYVNNTTVAVKKLAAMVDITTEELKQQFDQEIKVMAKCQHENLVELLGFSSDGDDLCLVYVYMPNGSLLDRLSCLDGTPPLSWHMRCKIAQGAANGINFLHENHHIHRDIKSANILLDEAFTAKISDFGLARASEKFAQTVMTSRIVGTTAYMAPEALRGEITPKSDIYSFGVVLLEIITGLPAVDEHREPQLLLDIKEEIEDEEKTIEDYIDKKMNDADSTSVEAMYSVASQCLHEKKNKRPDIKKVQQLLQEMTAS,7.585026652029182 +CCOc1ccccc1O[C@@H]1CCCN(C1)c1ncc(cn1)C(=O)NCc1cc(ccc1OC)C(O)=O,MKTLIAAYSGVLRGERQAEADRSQRSHGGPALSREGSGRWGTGSSILSALQDLFSVTWLNRSKVEKQLQVISVLQWVLSFLVLGVACSAILMYIFCTDCWLIAVLYFTWLVFDWNTPKKGGRRSQWVRNWAVWRYFRDYFPIQLVKTHNLLTTRNYIFGYHPHGIMGLGAFCNFSTEATEVSKKFPGIRPYLATLAGNFRMPVLREYLMSGGICPVSRDTIDYLLSKNGSGNAIIIVVGGAAESLSSMPGKNAVTLRNRKGFVKLALRHGADLVPIYSFGENEVYKQVIFEEGSWGRWVQKKFQKYIGFAPCIFHGRGLFSSDTWGLVPYSKPITTVVGEPITIPKLEHPTQQDIDLYHTMYMEALVKLFDKHKTKFGLPETEVLEVN,6.913640169325252 +OC(=O)C(F)(F)F.OC(=O)C(F)(F)F.CC(C)(C)CNc1nccc(n1)N1CCc2nc[nH]c2C1,MERAPPDGPLNASGALAGEAAAAGGARGFSAAWTAVLAALMALLIVATVLGNALVMLAFVADSSLRTQNNFFLLNLAISDFLVGAFCIPLYVPYVLTGRWTFGRGLCKLWLVVDYLLCTSSAFNIVLISYDRFLSVTRAVSYRAQQGDTRRAVRKMLLVWVLAFLLYGPAILSWEYLSGGSSIPEGHCYAEFFYNWYFLITASTLEFFTPFLSVTFFNLSIYLNIQRRTRLRLDGAREAAGPEPPPEAQPSPPPPPGCWGCWQKGHGEAMPLHRYGVGEAAVGAEAGEATLGGGGGGGSVASPTSSSGSSSRGTERPRSLKRGSKPSASSASLEKRMKMVSQSFTQRFRLSRDRKVAKSLAVIVSIFGLCWAPYTLLMIIRAACHGHCVPDYWYETSFWLLWANSAVNPVLYPLCHHSFRRAFTKLLCPQKLKIQPHSSLEHCWK,8.481486060122112 +CC1(C)CC(=O)C2=C(C1)N=C1SCCC(=O)N1C2c1ccc(cc1)C(F)(F)F,MALRGFCSADGSDPLWDWNVTWNTSNPDFTKCFQNTVLVWVPCFYLWACFPFYFLYLSRHDRGYIQMTPLNKTKTALGFLLWIVCWADLFYSFWERSRGIFLAPVFLVSPTLLGITMLLATFLIQLERRKGVQSSGIMLTFWLVALVCALAILRSKIMTALKEDAQVDLFRDITFYVYFSLLLIQLVLSCFSDRSPLFSETIHDPNPCPESSASFLSRITFWWITGLIVRGYRQPLEGSDLWSLNKEDTSEQVVPVLVKNWKKECAKTRKQPVKVVYSSKDPAQPKESSKVDANEEVEALIVKSPQKEWNPSLFKVLYKTFGPYFLMSFFFKAIHDLMMFSGPQILKLLIKFVNDTKAPDWQGYFYTVLLFVTACLQTLVLHQYFHICFVSGMRIKTAVIGAVYRKALVITNSARKSSTVGEIVNLMSVDAQRFMDLATYINMIWSAPLQVILALYLLWLNLGPSVLAGVAVMVLMVPVNAVMAMKTKTYQVAHMKSKDNRIKLMNEILNGIKVLKLYAWELAFKDKVLAIRQEELKVLKKSAYLSAVGTFTWVCTPFLVALCTFAVYVTIDENNILDAQTAFVSLALFNILRFPLNILPMVISSIVQASVSLKRLRIFLSHEELEPDSIERRPVKDGGGTNSITVRNATFTWARSDPPTLNGITFSIPEGALVAVVGQVGCGKSSLLSALLAEMDKVEGHVAIKGSVAYVPQQAWIQNDSLRENILFGCQLEEPYYRSVIQACALLPDLEILPSGDRTEIGEKGVNLSGGQKQRVSLARAVYSNADIYLFDDPLSAVDAHVGKHIFENVIGPKGMLKNKTRILVTHSMSYLPQVDVIIVMSGGKISEMGSYQELLARDGAFAEFLRTYASTEQEQDAEENGVTGVSGPGKEAKQMENGMLVTDSAGKQLQRQLSSSSSYSGDISRHHNSTAELQKAEAKKEETWKLMEADKAQTGQVKLSVYWDYMKAIGLFISFLSIFLFMCNHVSALASNYWLSLWTDDPIVNGTQEHTKVRLSVYGALGISQGIAVFGYSMAVSIGGILASRCLHVDLLHSILRSPMSFFERTPSGNLVNRFSKELDTVDSMIPEVIKMFMGSLFNVIGACIVILLATPIAAIIIPPLGLIYFFVQRFYVASSRQLKRLESVSRSPVYSHFNETLLGVSVIRAFEEQERFIHQSDLKVDENQKAYYPSIVANRWLAVRLECVGNCIVLFAALFAVISRHSLSAGLVGLSVSYSLQVTTYLNWLVRMSSEMETNIVAVERLKEYSETEKEAPWQIQETAPPSSWPQVGRVEFRNYCLRYREDLDFVLRHINVTINGGEKVGIVGRTGAGKSSLTLGLFRINESAEGEIIIDGINIAKIGLHDLRFKITIIPQDPVLFSGSLRMNLDPFSQYSDEEVWTSLELAHLKDFVSALPDKLDHECAEGGENLSVGQRQLVCLARALLRKTKILVLDEATAAVDLETDDLIQSTIRTQFEDCTVLTIAHRLNTIMDYTRVIVLDKGEIQEYGAPSDLLQQRGLFYSMAKDAGLV,5.186352304653103 +Cc1cc(O)cc(C)c1C[C@H](N)C(=O)N1Cc2ccccc2C[C@H]1C(=O)NCCCC[C@H](N)c1nc2ccccc2[nH]1,MEPVPSARAELQFSLLANVSDTFPSAFPSASANASGSPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKLKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTQPRDGAVVCTLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDINRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRAPCGGQEPGSLRRPRQATARERVTACTPSDGPGGGAAA,8.578396073130168 +OC(=O)[C@H]1CC[C@@H](CC1)NC(=O)[C@H](C1CCCCC1)n1c(nc2cc(F)c(F)cc12)-c1ccc(Cl)cc1,MGLEALVPLAVIVAIFLLLVDLMHRRQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQLRRRFGDVFSLQLAWTPVVVLNGLAAVREALVTHGEDTADRPPVPITQILGFGPRSQGVFLARYGPAWREQRRFSVSTLRNLGLGKKSLEQWVTEEAACLCAAFANHSGRPFRPNGLLDKAVSNVIASLTCGRRFEYDDPRFLRLLDLAQEGLKEESGFLREVLNAVPVLLHIPALAGKVLRFQKAFLTQLDELLTEHRMTWDPAQPPRDLTEAFLAEMEKAKGNPESSFNDENLRIVVADLFSAGMVTTSTTLAWGLLLMILHPDVQRRVQQEIDDVIGQVRRPEMGDQAHMPYTTAVIHEVQRFGDIVPLGVTHMTSRDIEVQGFRIPKGTTLITNLSSVLKDEAVWEKPFRFHPEHFLDAQGHFVKPEAFLPFSAGRRACLGEPLARMELFLFFTSLLQHFSFSVPTGQPRPSHHGVFAFLVSPSPYELCAVPR,4.301029995663981 +CCN[C@H](CN[C@H](CN[C@H](CN[C@H](CN[C@@H](CN[C@H](CN)Cc1ccc(O)cc1)[C@@H](C)O)Cc1ccccc1)Cc1ccc(O)cc1)Cc1ccc(O)cc1)Cc1ccc(O)cc1,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,6.698970004336019 +CCc1c(C)c(cn2ncnc12)-c1[nH]c2ccc(cc2c1C(C)C)C1CCNCC1,MGFCRSALHPLSLLVQAIMLAMTLALGTLPAFLPCELQPHGLVNCNWLFLKSVPHFSMAAPRGNVTSLSLSSNRIHHLHDSDFAHLPSLRHLNLKWNCPPVGLSPMHFPCHMTIEPSTFLAVPTLEELNLSYNNIMTVPALPKSLISLSLSHTNILMLDSASLAGLHALRFLFMDGNCYYKNPCRQALEVAPGALLGLGNLTHLSLKYNNLTVVPRNLPSSLEYLLLSYNRIVKLAPEDLANLTALRVLDVGGNCRRCDHAPNPCMECPRHFPQLHPDTFSHLSRLEGLVLKDSSLSWLNASWFRGLGNLRVLDLSENFLYKCITKTKAFQGLTQLRKLNLSFNYQKRVSFAHLSLAPSFGSLVALKELDMHGIFFRSLDETTLRPLARLPMLQTLRLQMNFINQAQLGIFRAFPGLRYVDLSDNRISGASELTATMGEADGGEKVWLQPGDLAPAPVDTPSSEDFRPNCSTLNFTLDLSRNNLVTVQPEMFAQLSHLQCLRLSHNCISQAVNGSQFLPLTGLQVLDLSHNKLDLYHEHSFTELPRLEALDLSYNSQPFGMQGVGHNFSFVAHLRTLRHLSLAHNNIHSQVSQQLCSTSLRALDFSGNALGHMWAEGDLYLHFFQGLSGLIWLDLSQNRLHTLLPQTLRNLPKSLQVLRLRDNYLAFFKWWSLHFLPKLEVLDLAGNQLKALTNGSLPAGTRLRRLDVSCNSISFVAPGFFSKAKELRELNLSANALKTVDHSWFGPLASALQILDVSANPLHCACGAAFMDFLLEVQAAVPGLPSRVKCGSPGQLQGLSIFAQDLRLCLDEALSWDCFALSLLAVALGLGVPMLHHLCGWDLWYCFHLCLAWLPWRGRQSGRDEDALPYDAFVVFDKTQSAVADWVYNELRGQLEECRGRWALRLCLEERDWLPGKTLFENLWASVYGSRKTLFVLAHTDRVSGLLRASFLLAQQRLLEDRKDVVVLVILSPDGRRSRYVRLRQRLCRQSVLLWPHQPSGQRSFWAQLGMALTRDNHHFYNRNFCQGPTAE,5.755475488429916 +CNCCC(Oc1ccc(cc1)C(F)(F)F)c1ccccc1,MAPNTSTMDEAGLPAERDFSFRILTACFLSLLILSTLLGNTLVCAAVIRFRHLRSKVTNFFVISLAVSDLLVAVLVMPWKAVAEIAGFWPLGPFCNIWVAFDIMCSTASILNLCVISVDRYWAISSPFQYERKMTPKAAFILISVAWTLSVLISFIPVQLSWHKAKPTWPLDGNFTSLEDTEDDNCDTRLSRTYAISSSLISFYIPVAIMIVTYTSIYRIAQKQIRRISALERAAVHAKNCQTTAGNGNPVECAQSESSFKMSFKRETKVLKTLSVIMGVFVCCWLPFFISNCMVPFCGSEETQPFCIDSITFDVFVWFGWANSSLNPIIYAFNADFQKAFSTLLGCYRLCPTTNNAIETVSINNNGAVVFSSHHEPRGSISKDCNLVYLIPHAVGSSEDLKKEEAGGIAKPLEKLSPALSVILDYDTDVSLEKIQPVTHSGQHST,5.0 +O=C(CNC(=O)Cc1ccccc1)N\N=C1/C(=O)N(Cc2ccc3OCOc3c2)c2ccccc12,MPMILGYWDIRGLAHAIRLLLEYTDSSYEEKKYTMGDAPDYDRSQWLNEKFKLGLDFPNLPYLIDGAHKITQSNAILCYIARKHNLCGETEEEKIRVDILENQTMDNHMQLGMICYNPEFEKLKPKYLEELPEKLKLYSEFLGKRPWFAGNKITFVDFLVYDVLDLHRIFEPKCLDAFPNLKDFISRFEGLEKISAYMKSSRFLPRPVFSKMAVWGNK,4.9222688203476075 +CCc1cnc(cc1Nc1ccncc1C(=O)NC[C@H](C)O)-c1cc(Cl)ccc1F,MAESAGASSFFPLVVLLLAGSGGSGPRGVQALLCACTSCLQANYTCETDGACMVSIFNLDGMEHHVRTCIPKVELVPAGKPFYCLSSEDLRNTHCCYTDYCNRIDLRVPSGHLKEPEHPSMWGPVELVGIIAGPVFLLFLIIIIVFLVINYHQRVYHNRQRLDMEDPSCEMCLSKDKTLQDLVYDLSTSGSGSGLPLFVQRTVARTIVLQEIIGKGRFGEVWRGRWRGGDVAVKIFSSREERSWFREAEIYQTVMLRHENILGFIAADNKDNGTWTQLWLVSDYHEHGSLFDYLNRYTVTIEGMIKLALSAASGLAHLHMEIVGTQGKPGIAHRDLKSKNILVKKNGMCAIADLGLAVRHDAVTDTIDIAPNQRVGTKRYMAPEVLDETINMKHFDSFKCADIYALGLVYWEIARRCNSGGVHEEYQLPYYDLVPSDPSIEEMRKVVCDQKLRPNIPNWWQSYEALRVMGKMMRECWYANGAARLTALRIKKTLSQLSVQEDVKI,7.061480274823508 +CCOC(=O)c1c(OCC)[nH]c2c1cc(O)c1ccccc21,MFGLKRNAVIGLNLYCGGAGLGAGSGGATRPGGRLLATEKEASARREIGGGEAGAVIGGSAGASPPSTLTPDSRRVARPPPIGAEVPDVTATPARLLFFAPTRRAAPLEEMEAPAADAIMSPEEELDGYEPEPLGKRPAVLPLLELVGESGNNTSTDGSLPSTPPPAEEEEDELYRQSLEIISRYLREQATGAKDTKPMGRSGATSRKALETLRRVGDGVQRNHETAFQGMLRKLDIKNEDDVKSLSRVMIHVFSDGVTNWGRIVTLISFGAFVAKHLKTINQESCIEPLAESITDVLVRTKRDWLVKQRGWDGFVEFFHVEDLEGGIRNVLLAFAGVAGVGAGLAYLIR,6.028994484402068 +CC(=O)c1ccc(OCCCN2CC[C@@H](C2)NC(=O)c2ccc(cc2)C#N)cc1,MSLPNSSCLLEDKMCEGNKTTMASPQLMPLVVVLSTICLVTVGLNLLVLYAVRSERKLHTVGNLYIVSLSVADLIVGAVVMPMNILYLLMSKWSLGRPLCLFWLSMDYVASTASIFSVFILCIDRYRSVQQPLRYLKYRTKTRASATILGAWFLSFLWVIPILGWNHFMQQTSVRREDKCETDFYDVTWFKVMTAIINFYLPTLLMLWFYAKIYKAVRQHCQHRELINRSLPSFSEIKLRPENPKGDAKKPGKESPWEVLKRKPKDAGGGSVLKSPSQTPKEMKSPVVFSQEDDREVDKLYCFPLDIVHMQAAAEGSSRDYVAVNRSHGQLKTDEQGLNTHGASEISEDQMLGDSQSFSRTDSDTTTETAPGKGKLRSGSNTGLDYIKFTWKRLRSHSRQYVSGLHMNRERKAAKQLGFIMAAFILCWIPYFIFFMVIAFCKNCCNEHLHMFTIWLGYINSTLNPLIYPLCNENFKKTFKRILHIRS,4.886056647693163 +CCn1nnc(n1)[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1cnc2c(N)nc(Cl)nc12,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,7.6777807052660805 +NC(=N)c1ccc(Nc2ncnc(Nc3ccc(cc3)C#N)c2[N+]([O-])=O)cc1,MAAAAAAVGPGAGGAGSAVPGGAGPCATVSVFPGARLLTIGDANGEIQRHAEQQALRLEVRAGPDSAGIALYSHEDVCVFKCSVSRETECSRVGKQSFIITLGCNSVLIQFATPNDFCSFYNILKTCRGHTLERSVFSERTEESSAVQYFQFYGYLSQQQNMMQDYVRTGTYQRAILQNHTDFKDKIVLDVGCGSGILSFFAAQAGARKIYAVEASTMAQHAEVLVKSNNLTDRIVVIPGKVEEVSLPEQVDIIISEPMGYMLFNERMLESYLHAKKYLKPSGNMFPTIGDVHLAPFTDEQLYMEQFTKANFWYQPSFHGVDLSALRGAAVDEYFRQPVVDTFDIRILMAKSVKYTVNFLEAKEGDLHRIEIPFKFHMLHSGLVHGLAFWFDVAFIGSIMTVWLSTAPTEPLTHWYQVRCLFQSPLFAKAGDTLSGTCLLIANKRQSYDISIVAQVDQTGSKSSNLLDLKNPFFRYTGTTPSPPPGSHYTSPSENMWNTGSTYNLSSGMAVAGMPTAYDLSSVIASGSSVGHNNLIPLANTGIVNHTHSRMGSIMSTGIVQGSSGAQGSGGGSTSAHYAVNSQFTMGGPAISMASPMSIPTNTMHYGS,5.0 +CN1CCCC[C@H]1CC=C1c2ccccc2Cc2ccccc12,MNTSAPPAVSPNITVLAPGKGPWQVAFIGITTGLLSLATVTGNLLVLISFKVNTELKTVNNYFLLSLACADLIIGTFSMNLYTTYLLMGHWALGTLACDLWLALDYVASNASVMNLLLISFDRYFSVTRPLSYRAKRTPRRAALMIGLAWLVSFVLWAPAILFWQYLVGERTVLAGQCYIQFLSQPIITFGTAMAAFYLPVTVMCTLYWRIYRETENRARELAALQGSETPGKGGGSSSSSERSQPGAEGSPETPPGRCCRCCRAPRLLQAYSWKEEEEEDEGSMESLTSSEGEEPGSEVVIKMPMVDPEAQAPTKQPPRSSPNTVKRPTKKGRDRAGKGQKPRGKEQLAKRKTFSLVKEKKAARTLSAILLAFILTWTPYNIMVLVSTFCKDCVPETLWELGYWLCYVNSTINPMCYALCNKAFRDTFRLLLLCRWDKRRWRKIPKRPGSVHRTPSRQC,7.619788758288394 +CC(C)[C@H](NC(=O)[C@H](C)NC(=O)[C@H](Cc1c[nH]c2ccccc12)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](C)c1ccccc1)C(=O)N[C@H](C)C(=O)N[C@@H](Cc1cnc[nH]1)C(=O)N1CCC[C@@H]1CN[C@@H](Cc1ccccc1)C(N)=O,MAPNNCSHLNLDVDPFLSCNDTFNQSLSPPKMDNWFHPGFIYVIPAVYGLIIVIGLIGNITLIKIFCTVKSMRNVPNLFISSLALGDLLLLVTCAPVDASKYLADRWLFGRIGCKLIPFIQLTSVGVSVFTLTALSADRYKAIVRPMDIQASHALMKICLKAALIWIVSMLLAIPEAVFSDLHPFHVKDTNQTFISCAPYPHSNELHPKIHSMASFLVFYVIPLAIISVYYYFIARNLIQSAYNLPVEGNIHVKKQIESRKRLAKTVLVFVGLFAFCWLPNHVIYLYRSYHYSEVDTSMLHFVTSICARLLAFTNSCVNPFALYLLSKSFRKQFNTQLLCCQPGLMNRSHSTGRSTTCMTSFKSTNPSATFSLINRNICHEGYV,8.522878745280337 +Clc1ccc(NC(=S)NCCc2occc2C#N)nc1,PISPIETVPVKLKPGMDGPKVKQWPLTEEKIKALVEICTEMEKEGKISKIGPENPYNTPVFAIKKKDSTKWRKLVDFRELNKRTQDFWEVQLGIPHPAGLKKKKSVTVLDVGDAYFSVPLDEDFRKYTAFTIPSINNETPGIRYQYNVLPQGWKGSPAIFQSSMTKILEPFRKQNPDIVIYQYMDDLYVGSDLEIGQHRTKIEELRQHLLRWGLTTPDKKHQKEPPFLWMGYELHPDKWTVQPIVLPEKDSWTVNDIQKLVGKLNWASQIYPGIKVRQLXKLLRGTKALTEVIPLTEEAELELAENREILKEPVHGVYYDPSKDLIAEIQKQGQGQWTYQIYQEPFKNLKTGKYARMRGAHTNDVKQLTEAVQKITTESIVIWGKTPKFKLPIQKETWETWWTEYWQATWIPEWEFVNTPPLVKLWYQLEKEPIVGAETFYVDGAANRETKLGKAGYVTNRGRQKVVTLTDTTNQKTELQAIYLALQDSGLEVNIVTDSQYALGIIQAQPDQSESELVNQIIEQLIKKEKVYLAWVPAHKGIGGNEQVDKLVSAGIRKVL,7.221848749616356 +C[C@H]1CN(CCCc2cccc(Cl)c2)CC[C@@]1(C)c1cccc(O)c1,MGRRRQGPAQPASELPARNACLLPNGSAWLPGWAEPDGNGSAGPQDEQLEPAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSTVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLSSSVGISAIILGGTKVREDVDIIECSLQFPDDDYSWWDLFMKICVFVFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITRLVLVVVAVFIICWTPIHIFILVEALGSTSHSTAALSSYYFCIALGYTNSSLNPILYAFLDENFKRCFRDFCFPIKMRMERQSTSRVRNTVQDPAYMRNVDGVNKPV,7.721246399047171 +COc1ccc(cc1)N1CCN(CCCNC(=O)c2ccccn2)CC1,MEILCEDNISLSSIPNSLMQLGDGPRLYHNDFNSRDANTSEASNWTIDAENRTNLSCEGYLPPTCLSILHLQEKNWSALLTTVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAIWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVAFFIPLTIMVITYFLTIKSLQKEATLCVSDLSTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYAGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNENVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENRKPLQLILVNTIPALAYKSSQLQVGQKKNSQEDAEQTVDDCSMVTLGKQQSEENCTDNIETVNEKVSCV,5.0 +CCN(C1CCOCC1)c1cc(cc(C(=O)NCc2c(C)c(F)c(C)[nH]c2=O)c1C)-c1ccc(CN2CCOCC2)cc1,MGQTGKKSEKGPVCWRKRVKSEYMRLRQLKRFRRADEVKSMFSSNRQKILERTEILNQEWKQRRIQPVHILTSVSSLRGTRECSVTSDLDFPTQVIPLKTLNAVASVPIMYSWSPLQQNFMVEDETVLHNIPYMGDEVLDQDGTFIEELIKNYDGKVHGDRECGFINDEIFVELVNALGQYNDDDDDDDGDDPEEREEKQKDLEDHRDDKESRPPRKFPSDKIFEAISSMFPDKGTAEELKEKYKELTEQQLPGALPPECTPNIDGPNAKSVQREQSLHSFHTLFCRRCFKYDCFLHPFHATPNTYKRKNTETALDNKPCGPQCYQHLEGAKEFAAALTAERIKTPPKRPGGRRRGRLPNNSSRPSTPTINVLESKDTDSDREAGTETGGENNDKEEEEKKDETSSSSEANSRCQTPIKMKPNIEPPENVEWSGAEASMFRVLIGTYYDNFCAIARLIGTKTCRQVYEFRVKESSIIAPAPAEDVDTPPRKKKRKHRLWAAHCRKIQLKKDGSSNHVYNYQPCDHPRQPCDSSCPCVIAQNFCEKFCQCSSECQNRFPGCRCKAQCNTKQCPCYLAVRECDPDLCLTCGAADHWDSKNVSCKNCSIQRGSKKHLLLAPSDVAGWGIFIKDPVQKNEFISEYCGEIISQDEADRRGKVYDKYMCSFLFNLNNDFVVDATRKGNKIRFANHSVNPNCYAKVMMVNGDHRIGIFAKRAIQTGEELFFDYRYSQADALKYVGIEREMEIP,6.61253898367965 +Cc1cc(Cl)cc(C)c1C(=O)c1sc2cc(O)ccc2c1Oc1ccc(\C=C\C(O)=O)cc1,MTMTLHTKASGMALLHQIQGNELEPLNRPQLKIPLERPLGEVYLDSSKPAVYNYPEGAAYEFNAAAAANAQVYGQTGLPYGPGSEAAAFGSNGLGGFPPLNSVSPSPLMLLHPPPQLSPFLQPHGQQVPYYLENEPSGYTVREAGPPAFYRPNSDNRRQGGRERLASTNDKGSMAMESAKETRYCAVCNDYASGYHYGVWSCEGCKAFFKRSIQGHNDYMCPATNQCTIDKNRRKSCQACRLRKCYEVGMMKGGIRKDRRGGRMLKHKRQRDDGEGRGEVGSAGDMRAANLWPSPLMIKRSKKNSLALSLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNLADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLLLDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSLEEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMKCKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAEGFPATV,9.244125144327509 +COc1cccc(CNC(=O)c2cc3ccc(nc3[nH]2)-c2cn[nH]c2C)c1,MSRPPPTGKMPGAPETAPGDGAGASRQRKLEALIRDPRSPINVESLLDGLNSLVLDLDFPALRKNKNIDNFLNRYEKIVKKIRGLQMKAEDYDVVKVIGRGAFGEVQLVRHKASQKVYAMKLLSKFEMIKRSDSAFFWEERDIMAFANSPWVVQLFYAFQDDRYLYMVMEYMPGGDLVNLMSNYDVPEKWAKFYTAEVVLALDAIHSMGLIHRDVKPDNMLLDKHGHLKLADFGTCMKMDETGMVHCDTAVGTPDYISPEVLKSQGGDGFYGRECDWWSVGVFLYEMLVGDTPFYADSLVGTYSKIMDHKNSLCFPEDAEISKHAKNLICAFLTDREVRLGRNGVEEIRQHPFFKNDQWHWDNIRETAAPVVPELSSDIDSSNFDDIEDDKGDVETFPIPKAFVGNQLPFIGFTYYRENLLLSDSPSCRETDSIQSRKNEESQEIQKKLYTLEEHLSNEMQAKEELEQKCKSVNTRLEKTAKELEEEITLRKSVESALRQLEREKALLQHKNAEYQRKADHEADKKRNLENDVNSLKDQLEDLKKRNQNSQISTEKVNQLQRQLDETNALLRTESDTAARLRKTQAESSKQIQQLESNNRDLQDKNCLLETAKLKLEKEFINLQSALESERRDRTHGSEIINDLQGRICGLEEDLKNGKILLAKVELEKRQLQERFTDLEKEKSNMEIDMTYQLKVIQQSLEQEEAEHKATKARLADKNKIYESIEEAKSEAMKEMEKKLLEERTLKQKVENLLLEAEKRCSLLDCDLKQSQQKINELLKQKDVLNEDVRNLTLKIEQETQKRCLTQNDLKMQTQQVNTLKMSEKQLKQENNHLMEMKMNLEKQNAELRKERQDADGQMKELQDQLEAEQYFSTLYKTQVRELKEECEEKTKLGKELQQKKQELQDERDSLAAQLEITLTKADSEQLARSIAEEQYSDLEKEKIMKELEIKEMMARHKQELTEKDATIASLEETNRTLTSDVANLANEKEELNNKLKDVQEQLSRLKDEEISAAAIKAQFEKQLLTERTLKTQAVNKLAEIMNRKEPVKRGNDTDVRRKEKENRKLHMELKSEREKLTQQMIKYQKELNEMQAQIAEESQIRIELQMTLDSKDSDIEQLRSQLQALHIGLDSSSIGSGPGDAEADDGFPESRLEGWLSLPVRNNTKKFGWVKKYVIVSSKKILFYDSEQDKEQSNPYMVLDIDKLFHVRPVTQTDVYRADAKEIPRIFQILYANEGESKKEQEFPVEPVGEKSNYICHKGHEFIPTLYHFPTNCEACMKPLWHMFKPPPALECRRCHIKCHKDHMDKKEEIIAPCKVYYDISTAKNLLLLANSTEEQQKWVSRLVKKIPKKPPAPDPFARSSPRTSMKIQQNQSIRRPSRQLAPNKPS,8.301029995663981 +Fc1cccc(CNc2ncnc3n(CC(Cl)c4ccccc4)ncc23)c1,MLEICLKLVGCKSKKGLSSSSSCYLEEALQRPVASDFEPQGLSEAARWNSKENLLAGPSENDPNLFVALYDFVASGDNTLSITKGEKLRVLGYNHNGEWCEAQTKNGQGWVPSNYITPVNSLEKHSWYHGPVSRNAAEYLLSSGINGSFLVRESESSPGQRSISLRYEGRVYHYRINTASDGKLYVSSESRFNTLAELVHHHSTVADGLITTLHYPAPKRNKPTVYGVSPNYDKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSAMEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQESSISDEVEKELGKQGVRGAVSTLLQAPELPTKTRTSRRAAEHRDTTDVPEMPHSKGQGESDPLDHEPAVSPLLPRKERGPPEGGLNEDERLLPKDKKTNLFSALIKKKKKTAPTPPKRSSSFREMDGQPERRGAGEEEGRDISNGALAFTPLDTADPAKSPKPSNGAGVPNGALRESGGSGFRSPHLWKKSSTLTSSRLATGEEEGGGSSSKRFLRSCSASCVPHGAKDTEWRSVTLPRDLQSTGRQFDSSTFGGHKSEKPALPRKRAGENRSDQVTRGTVTPPPRLVKKNEEAADEVFKDIMESSPGSSPPNLTPKPLRRQVTVAPASGLPHKEEAGKGSALGTPAAAEPVTPTSKAGSGAPGGTSKGPAEESRVRRHKHSSESPGRDKGKLSRLKPAPPPPPAASAGKAGGKPSQSPSQEAAGEAVLGAKTKATSLVDAVNSDAAKPSQPGEGLKKPVLPATPKPQSAKPSGTPISPAPVPSTLPSASSALAGDQPSSTAFIPLISTRVSLRKTRQPPERIASGAITKGVVLDSTEALCLAISRNSEQMASHSAVLEAGKNLYTFCVSYVDSIQQMRNKFAFREAINKLENNLRELQICPATAGSGPAATQDFSKLLSSVKEISDIVQR,7.3979400086720375 +COc1ccc(CN2CCN(CC2)c2ccc(cn2)-c2cc(cn3ncc(C#N)c23)-c2cnc(C)s2)cn1,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,7.928117992693874 +S=c1[nH]nc(-c2cccs2)n1C1CCCCC1,MSKLSVFFIFLFCSIATAAESLPDLKIEKLDEGVYVHTSFEEVNGWGVVPKHGLVVLVNAEAYLIDTPFTAKDTEKLVTWFVERGYKIKGSISSHFHSDSTGGIEWLNSRSIPTYASELTNELLKKDGKVQATNSFSGVNYWLVKNKIEVFYPGPGHTPDNVVVWLPERKILFGGCFIKPYGLGNLGDANIEAWPKSAKLLKSKYGKAKLVVPSHSEVGDASLLKLTLEQAVKGLNESKKPSKPSN,4.224462365219043 +CN1CCN(CC1)C1=c2ccccc2=Nc2ccc(Cl)cc2N1,MSLPNSSCLLEDKMCEGNKTTMASPQLMPLVVVLSTICLVTVGLNLLVLYAVRSERKLHTVGNLYIVSLSVADLIVGAVVMPMNILYLLMSKWSLGRPLCLFWLSMDYVASTASIFSVFILCIDRYRSVQQPLRYLKYRTKTRASATILGAWFLSFLWVIPILGWNHFMQQTSVRREDKCETDFYDVTWFKVMTAIINFYLPTLLMLWFYAKIYKAVRQHCQHRELINRSLPSFSEIKLRPENPKGDAKKPGKESPWEVLKRKPKDAGGGSVLKSPSQTPKEMKSPVVFSQEDDREVDKLYCFPLDIVHMQAAAEGSSRDYVAVNRSHGQLKTDEQGLNTHGASEISEDQMLGDSQSFSRTDSDTTTETAPGKGKLRSGSNTGLDYIKFTWKRLRSHSRQYVSGLHMNRERKAAKQLGFIMAAFILCWIPYFIFFMVIAFCKNCCNEHLHMFTIWLGYINSTLNPLIYPLCNENFKKTFKRILHIRS,8.787812395596042 +NCCS(=O)(=O)c1ccc(-c2ccc3[nH]c(=O)oc3c2)c(-c2nnn[nH]2)c1S(N)(=O)=O,MLKVISSLLVYMTASVMAVASPLAHSGEPSGEYPTVNEIPVGEVRLYQIADGVWSHIATQSFDGAVYPSNGLIVRDGDELLLIDTAWGAKNTAALLAEIEKQIGLPVTRAVSTHFHDDRVGGVDVLRAAGVATYASPSTRRLAEAEGNEIPTHSLEGLSSSGDAVRFGPVELFYPGAAHSTDNLVVYVPSANVLYGGCAVHELSSTSAGNVADADLAEWPTSVERIQKHYPEAEVVIPGHGLPGGLDLLQHTANVVKAHKNRSVAE,9.539102157243452 +OC(=O)COc1ccc(Cl)cc1[C@H]1N(CCc2ncsc12)C(=O)OCc1ccccc1,MSANATLKPLCPILEQMSRLQSHSNTSIRYIDHAAVLLHGLASLLGLVENGVILFVVGCRMRQTVVTTWVLHLALSDLLASASLPFFTYFLAVGHSWELGTTFCKLHSSIFFLNMFASGFLLSAISLDRCLQVVRPVWAQNHRTVAAAHKVCLVLWALAVLNTVPYFVFRDTISRLDGRIMCYYNVLLLNPGPDRDATCNSRQVALAVSKFLLAFLVPLAIIASSHAAVSLRLQHRGRRRPGRFVRLVAAVVAAFALCWGPYHVFSLLEARAHANPGLRPLVWRGLPFVTSLAFFNSVANPVLYVLTCPDMLRKLRRSLRTVLESVLVDDSELGGAGSSRRRRTSSTARSASPLALCSRPEEPRGPARLLGWLLGSCAASPQTGPLNRALSSTSS,8.638272163982407 +CN(C)S(=O)(=O)c1cccc(c1)C(=O)N1CCN(CC1)c1cccc(C)c1C,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,4.494850021680094 +NC(=O)C(Cc1ccccc1)NC(=O)c1ccccc1\C=C\c1cccc2ccccc12,MWQLWASLCCLLVLANARSRPSFHPLSDELVNYVNKRNTTWQAGHNFYNVDMSYLKRLCGTFLGGPKPPQRVMFTEDLKLPASFDAREQWPQCPTIKEIRDQGSCGSCWAFGAVEAISDRICIHTNAHVSVEVSAEDLLTCCGSMCGDGCNGGYPAEAWNFWTRKGLVSGGLYESHVGCRPYSIPPCEHHVNGSRPPCTGEGDTPKCSKICEPGYSPTYKQDKHYGYNSYSVSNSEKDIMAEIYKNGPVEGAFSVYSDFLLYKSGVYQHVTGEMMGGHAIRILGWGVENGTPYWLVANSWNTDWGDNGFFKILRGQDHCGIESEVVAGIPRTDQYWEKI,7.00436480540245 +Cc1ccc(NC(=O)CCc2nnc(CCCC(C)(C)C)n2C2CC2)c(C)c1,MDRAPQRHHRTSRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQQCNVAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQQQQQEQVAKTPPAGSRGADTLTYTLGLSDGQLPLGASPDLPEASACPPGLLRASGSGPPYSNTLAKTEVQGASCHLEYSPERGKAEGRDSIYSTDGQLTLGRCGLRFEETRHPELGEPEQGPDSHCIPSFCSAPEVPYASLTDIEYLVQNVCKSFRETCQLRLEDLLRQRTNLFSREEVTSYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIILLTAGAMEVVLVRMCRAYNANNHTVFFEGKYGGVELFRALGCSELISSIFDFSHFLSALCFSEDEIALYTALVLINANRPGLQEKRRVEHLQYNLELAFHHHLCKTHRQGLLAKLPPKGKLRSLCSQHVEKLQIFQHLHPIVVQAAFPPLYKELFSTDVESPEGLSK,5.886056647693163 +NCCCOc1cccc2n(c(nc12)C(F)F)-c1nc(nc(n1)N1CCOCC1)N1CCOCC1,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,7.552841968657781 +CS(=O)(=O)c1ccc(NC(=O)Nc2ccccc2)cc1,MLARALLLCAAVVCGAANPCCSHPCQNRGVCMSVGFDQYKCDCTRTGFYGENCTTPEFLTRIKLLLKPTPDTVHYILTHFKGVWNIVNKISFLRNMIMRYVLTSRSHLIESPPTYNVHYSYKSWEAFSNLSYYTRALPPVPDDCPTPMGVKGRKELPDSKEVVKKVLLRRKFIPDPQGTNLMFAFFAQHFTHQFFKTDIERGPAFTKGKNHGVDLSHVYGESLERQHNRRLFKDGKMKYQMINGEMYPPTVKDTQVEMIYPPHIPEHLKFAVGQEVFGLVPGLMMYATIWLREHNRVCDVLKQEHPEWGDEQLFQTSRLILIGETIKIVIEDYVQHLSGYHFKLKFDPELLFNQQFQYQNRIAAEFNTLYHWHPLLPDVFQIDGQEYNYQQFIYNNSVLLEHGVTQFVESFTRQIAGRVAGRRNLPAAVEKVSKASLDQSREMKYQSFNEYRKRFLLKPYESFEELTGEKEMAAELEALYGDIDAMELYPALLVEKPAPDAIFGETMVEAGAPFSLKGLMGNPICSPEYWKPSTFGGEVGFKIINTASIQSLICSNVKGCPFTSFSVQDAHLTKTVTINASSSHSGLDDINPTVLLKERSTEL,6.769551078621726 +Cl.CN1CCN(CC1)c1nc(C)nc2n(C3CCOCC3)c(nc12)-c1ccccc1C#N,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,3.0 +O[C@@H]1[C@H](O)[C@]2(CCP([O-])([O-])=O)C[C@@H]2[C@H]1n1ccc(=O)[nH]c1=O,MAADLGPWNDTINGTWDGDELGYRCRFNEDFKYVLLPVSYGVVCVPGLCLNAVALYIFLCRLKTWNASTTYMFHLAVSDALYAASLPLLVYYYARGDHWPFSTVLCKLVRFLFYTNLYCSILFLTCISVHRCLGVLRPLRSLRWGRARYARRVAGAVWVLVLACQAPVLYFVTTSARGGRVTCHDTSAPELFSRFVAYSSVMLGLLFAVPFAVILVCYVLMARRLLKPAYGTSGGLPRAKRKSVRTIAVVLAVFALCFLPFHVTRTLYYSFRSLDLSCHTLNAINMAYKVTRPLASANSCLDPVLYFLAGQRLVRFARDAKPPTGPSPATPARRRLGLRRSDRTDMQRIEDVLGSSEDSRRTESTPAGSENTKDIRL,5.3979400086720375 +CCOCCn1cc(C2CCN(Cc3ccc(F)c(c3)C(O)=O)CC2)c2ccccc12,MSFLPGMTPVTLSNFSWALEDRMLEGNSTTTPTRQLMPLVVVLSSVSLVTVALNLLVLYAVRSERKLHTVGNLYIVSLSVADLIVGAVVMPMSILYLHRSAWILGRPLCLFWLSMDYVASTASIFSVFILCIDRYRSVQQPLRYLRYRTKTRASATILGAWLLSFLWVIPILGWHHFMAPTSEPREKKCETDFYDVTWFKVMTAIINFYLPTLLMLWFYIRIYKAVRRHCQHRQLINSSLPSFSEMKLKLENAKVDTRRMGKESPWEDPKRCSKDASGVHTPMPSSQHLVDMPCAAVLSEDEGGEVGTRQMPMLAVGDGRCCEALNHMHSQLELSGQSRATHSISARPEEWTVVDGQSFPITDSDTSTEAAPMGGQPRSGSNSGLDYIKFTWRRLRSHSRQYTSGLHLNRERKAAKQLGCIMAAFILCWIPYFVFFMVIAFCKSCSNEPVHMFTIWLGYLNSTLNPLIYPLCNENFRKTFKRILRIPP,6.522878745280337 +NS(=O)(=O)c1ccc(CCNC(=O)c2ccc(NC(=O)Nc3ccc(Cl)c(c3)C(F)(F)F)cc2)cc1,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,5.575118363368933 +CCOc1ccc(cc1)-c1ccc(CN(Cc2cccc(NCC(O)=O)n2)S(=O)(=O)c2ccccn2)cc1,MGNASNDSQSEDCETRQWLPPGESPAISSVMFSAGVLGNLIALALLARRWRGDVGCSAGRRSSLSLFHVLVTELVFTDLLGTCLISPVVLASYARNQTLVALAPESRACTYFAFAMTFFSLATMLMLFAMALERYLSIGHPYFYQRRVSRSGGLAVLPVIYAVSLLFCSLPLLDYGQYVQYCPGTWCFIRHGRTAYLQLYATLLLLLIVSVLACNFSVILNLIRMHRRSRRSRCGPSLGSGRGGPGARRRGERVSMAEETDHLILLAIMTITFAVCSLPFTIFAYMNETSSRKEKWDLQALRFLSINSIIDPWVFAILRPPVLRLMRSVLCCRISLRTQDATQTSCSTQSDASKQADL,8.0 +COc1ccccc1Nc1ncc(Br)c(Nc2cccc(NC(=O)C=C)c2)n1,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,6.698970004336019 +Cc1cccc(NC(=S)NNc2ncc(cc2Cl)C(F)(F)F)c1,MEEGGDFDNYYGADNQSECEYTDWKSSGALIPAIYMLVFLLGTTGNGLVLWTVFRSSREKRRSADIFIASLAVADLTFVVTLPLWATYTYRDYDWPFGTFFCKLSSYLIFVNMYASVFCLTGLSFDRYLAIVRPVANARLRLRVSGAVATAVLWVLAALLAMPVMVLRTTGDLENTTKVQCYMDYSMVATVSSEWAWEVGLGVSSTTVGFVVPFTIMLTCYFFIAQTIAGHFRKERIEGLRKRRRLLSIIVVLVVTFALCWMPYHLVKTLYMLGSLLHWPCDFDLFLMNIFPYCTCISYVNSCLNPFLYAFFDPRFRQACTSMLCCGQSRCAGTSHSSSGEKSASYSSGHSQGPGPNMGKGGEQMHEKSIPYSQETLVVD,4.818156412055227 +OC(=O)C[C@H](CN1CC[C@@H](CCc2ccc3CCCNc3n2)C1)c1cccc(O[C@H]2CCOC2)c1,MAFPPRRRLRLGPRGLPLLLSGLLLPLCRAFNLDVDSPAEYSGPEGSYFGFAVDFFVPSASSRMFLLVGAPKANTTQPGIVEGGQVLKCDWSSTRRCQPIEFDATGNRDYAKDDPLEFKSHQWFGASVRSKQDKILACAPLYHWRTEMKQEREPVGTCFLQDGTKTVEYAPCRSQDIDADGQGFCQGGFSIDFTKADRVLLGGPGSFYWQGQLISDQVAEIVSKYDPNVYSIKYNNQLATRTAQAIFDDSYLGYSVAVGDFNGDGIDDFVSGVPRAARTLGMVYIYDGKNMSSLYNFTGEQMAAYFGFSVAATDINGDDYADVFIGAPLFMDRGSDGKLQEVGQVSVSLQRASGDFQTTKLNGFEVFARFGSAIAPLGDLDQDGFNDIAIAAPYGGEDKKGIVYIFNGRSTGLNAVPSQILEGQWAARSMPPSFGYSMKGATDIDKNGYPDLIVGAFGVDRAILYRARPVITVNAGLEVYPSILNQDNKTCSLPGTALKVSCFNVRFCLKADGKGVLPRKLNFQVELLLDKLKQKGAIRRALFLYSRSPSHSKNMTISRGGLMQCEELIAYLRDESEFRDKLTPITIFMEYRLDYRTAADTTGLQPILNQFTPANISRQAHILLDCGEDNVCKPKLEVSVDSDQKKIYIGDDNPLTLIVKAQNQGEGAYEAELIVSIPLQADFIGVVRNNEALARLSCAFKTENQTRQVVCDLGNPMKAGTQLLAGLRFSVHQQSEMDTSVKFDLQIQSSNLFDKVSPVVSHKVDLAVLAAVEIRGVSSPDHVFLPIPNWEHKENPETEEDVGPVVQHIYELRNNGPSSFSKAMLHLQWPYKYNNNTLLYILHYDIDGPMNCTSDMEINPLRIKISSLQTTEKNDTVAGQGERDHLITKRDLALSEGDIHTLGCGVAQCLKIVCQVGRLDRGKSAILYVKSLLWTETFMNKENQNHSYSLKSSASFNVIEFPYKNLPIEDITNSTLVTTNVTWGIQPAPMPVPVWVIILAVLAGLLLLAVLVFVMYRMGFFKRVRPPQEEQEREQLQPHENGEGNSET,10.39999691337226 +Cc1ccc2oc(=O)c(cc2c1)C(=O)Nc1ccccc1,MILFKQATYFISLFATVSCGCLTQLYENAFFRGGDVASMYTPNAQYCQMRCTFHPRCLLFSFLPASSINDMEKRFGCFLKDSVTGTLPKVHRTGAVSGHSLKQCGHQISACHRDIYKGVDMRGVNFNVSKVSSVEECQKRCTNNIRCQFFSYATQTFHKAEYRNNCLLKYSPGGTPTAIKVLSNVESGFSLKPCALSEIGCHMNIFQHLAFSDVDVARVLTPDAFVCRTICTYHPNCLFFTFYTNVWKIESQRNVCLLKTSESGTPSSSTPQENTISGYSLLTCKRTLPEPCHSKIYPGVDFGGEELNVTFVKGVNVCQETCTKMIRCQFFTYSLLPEDCKEEKCKCFLRLSMDGSPTRIAYGTQGSSGYSLRLCNTGDNSVCTTKTSTRIVGGTNSSWGEWPWQVSLQVKLTAQRHLCGGSLIGHQWVLTAAHCFDGLPLQDVWRIYSGILNLSDITKDTPFSQIKEIIIHQNYKVSEGNHDIALIKLQAPLNYTEFQKPICLPSKGDTSTIYTNCWVTGWGFSKEKGEIQNILQKVNIPLVTNEECQKRYQDYKITQRMVCAGYKEGGKDACKGDSGGPLVCKHNGMWRLVGITSWGEGCARREQPGVYTKVAEYMDWILEKTQSSDGKAQMQSPA,4.301029995663981 +CCN(CC)CCNC(=O)OCC1CN(C1)C(=O)O[C@@H]1CC[C@]2(CO2)[C@H]([C@@H]1OC)[C@@]1(C)O[C@@H]1CC=C(C)C,MAGVEEVAASGSHLNGDLDPDDREEGAASTAEEAAKKKRRKKKKSKGPSAAGEQEPDKESGASVDEVARQLERSALEDKERDEDDEDGDGDGDGATGKKKKKKKKKRGPKVQTDPPSVPICDLYPNGVFPKGQECEYPPTQDGRTAAWRTTSEEKKALDQASEEIWNDFREAAEAHRQVRKYVMSWIKPGMTMIEICEKLEDCSRKLIKENGLNAGLAFPTGCSLNNCAAHYTPNAGDTTVLQYDDICKIDFGTHISGRIIDCAFTVTFNPKYDTLLKAVKDATNTGIKCAGIDVRLCDVGEAIQEVMESYEVEIDGKTYQVKPIRNLNGHSIGQYRIHAGKTVPIVKGGEATRMEEGEVYAIETFGSTGKGVVHDDMECSHYMKNFDVGHVPIRLPRTKHLLNVINENFGTLAFCRRWLDRLGESKYLMALKNLCDLGIVDPYPPLCDIKGSYTAQFEHTILLRPTCKEVVSRGDDY,7.301029995663981 +COc1ccc2[nH]c3nc(SCc4nnc(o4)-c4ccc(C)cc4)nnc3c2c1,MTMTLHTKASGMALLHQIQGNELEPLNRPQLKIPLERPLGEVYLDSSKPAVYNYPEGAAYEFNAAAAANAQVYGQTGLPYGPGSEAAAFGSNGLGGFPPLNSVSPSPLMLLHPPPQLSPFLQPHGQQVPYYLENEPSGYTVREAGPPAFYRPNSDNRRQGGRERLASTNDKGSMAMESAKETRYCAVCNDYASGYHYGVWSCEGCKAFFKRSIQGHNDYMCPATNQCTIDKNRRKSCQACRLRKCYEVGMMKGGIRKDRRGGRMLKHKRQRDDGEGRGEVGSAGDMRAANLWPSPLMIKRSKKNSLALSLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNLADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLLLDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSLEEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMKCKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAEGFPATV,5.164938183916401 +CNC(=O)COc1ccc(cn1)C(=O)Nc1ccc(F)cc1,MEDFNMESDSFEDFWKGEDLSNYSYSSTLPPFLLDAAPCEPESLEINKYFVVIIYALVFLLSLLGNSLVMLVILYSRVGRSVTDVYLLNLALADLLFALTLPIWAASKVNGWIFGTFLCKVVSLLKEVNFYSGILLLACISVDRYLAIVHATRTLTQKRYLVKFICLSIWGLSLLLALPVLLFRRTVYSSNVSPACYEDMGNNTANWRMLLRILPQSFGFIVPLLIMLFCYGFTLRTLFKAHMGQKHRAMRVIFAVVLIFLLCWLPYNLVLLADTLMRTQVIQETCERRNHIDRALDATEILGILHSCLNPLIYAFIGQKFRHGLLKILAIHGLISKDSLPKDSRPSFVGSSSGHTSTTL,4.698970004336019 +NNC(=O)NCCCCCC(=O)Nc1ccccc1,MAQTQGTRRKVCYYYDGDVGNYYYGQGHPMKPHRIRMTHNLLLNYGLYRKMEIYRPHKANAEEMTKYHSDDYIKFLRSIRPDNMSEYSKQMQRFNVGEDCPVFDGLFEFCQLSTGGSVASAVKLNKQQTDIAVNWAGGLHHAKKSEASGFCYVNDIVLAILELLKYHQRVLYIDIDIHHGDGVEEAFYTTDRVMTVSFHKYGEYFPGTGDLRDIGAGKGKYYAVNYPLRDGIDDESYEAIFKPVMSKVMEMFQPSAVVLQCGSDSLSGDRLGCFNLTIKGHAKCVEFVKSFNLPMLMLGGGGYTIRNVARCWTYETAVALDTEIPNELPYNDYFEYFGPDFKLHISPSNMTNQNTNEYLEKIKQRLFENLRMLPHAPGVQMQAIPEDAIPEESGDEDEDDPDKRISICSSDKRIACEEEFSDSEEEGEGGRKNSSNFKKAKRVKTEDEKEKDPEEKKEVTEEEKTKEEKPEAKGVKEEVKLA,3.8239087409443187 +O=C(CSc1nnc([nH]1)-c1cccnc1)Nc1ccnc2ccccc12,MFAVHLMAFYFSKLKEDQIKKVDRFLYHMRLSDDTLLDIMRRFRAEMEKGLAKDTNPTAAVKMLPTFVRAIPDGSENGEFLSLDLGGSKFRVLKVQVAEEGKRHVQMESQFYPTPNEIIRGNGTELFEYVADCLADFMKTKDLKHKKLPLGLTFSFPCRQTKLEEGVLLSWTKKFKARGVQDTDVVSRLTKAMRRHKDMDVDILALVNDTVGTMMTCAYDDPYCEVGVIIGTGTNACYMEDMSNIDLVEGDEGRMCINTEWGAFGDDGALEDIRTEFDRELDLGSLNPGKQLFEKMISGLYLGELVRLILLKMAKAGLLFGGEKSSALHTKGKIETRHVAAMEKYKEGLANTREILVDLGLEPSEADCIAVQHVCTIVSFRSANLCAAALAAILTRLRENKKVERLRTTVGMDGTLYKIHPQYPKRLHKVVRKLVPSCDVRFLLSESGSTKGAAMVTAVASRVQAQRKQIDRVLALFQLTREQLVDVQAKMRAELEYGLKKKSHGLATVRMLPTYVCGLPDGTEKGKFLALDLGGTNFRVLLVKIRSGRRSVRMYNKIFAIPLEIMQGTGEELFDHIVQCIADFLDYMGLKGASLPLGFTFSFPCRQMSIDKGTLIGWTKGFKATDCEGEDVVDMLREAIKRRNEFDLDIVAVVNDTVGTMMTCGYEDPNCEIGLIAGTGSNMCYMEDMRNIEMVEGGEGKMCINTEWGGFGDNGCIDDIRTRYDTEVDEGSLNPGKQRYEKMTSGMYLGEIVRQILIDLTKQGLLFRGQISERLRTRGIFETKFLSQIESDRLALLQVRRILQQLGLDSTCEDSIVVKEVCGAVSRRAAQLCGAGLAAIVEKRREDQGLEHLRITVGVDGTLYKLHPHFSRILQETVKELAPRCDVTFMLSEDGSGKGAALITAVAKRLQQAQKEN,4.882728704344236 +NC(=N)NCCC[C@@H]1NC(=O)[C@@H](Cc2ccccc2)NC(=O)[C@H](Cc2c[nH]cn2)NC(=O)C2(CCCCC2)NC(=O)CC[C@H](NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC1=O)C(N)=O,MNSSFHLHFLDLNLNATEGNLSGPNVKNKSSPCEDMGIAVEVFLTLGVISLLENILVIGAIVKNKNLHSPMYFFVCSLAVADMLVSMSSAWETITIYLLNNKHLVIADAFVRHIDNVFDSMICISVVASMCSLLAIAVDRYVTIFYALRYHHIMTARRSGAIIAGIWAFCTGCGIVFILYSESTYVILCLISMFFAMLFLLVSLYIHMFLLARTHVKRIAALPGASSARQRTSMQGAVTVTMLLGVFTVCWAPFFLHLTLMLSCPQNLYCSRFMSHFNMYLILIMCNSVMDPLIYAFRSQEMRKTFKEIICCRGFRIACSFPRRD,6.200659450546418 +Nc1ccc(cc1)-c1nnc(SCC(O)=O)n1-c1ccc(Cl)c(Cl)c1,MVGQLSEGAIAAIMQKGDTNIKPILQVINIRPITTGNSPPRYRLLMSDGLNTLSSFMLATQLNPLVEEEQLSSNCVCQIHRFIVNTLKDGRRVVILMELEVLKSAEAVGVKIGNPVPYNEGLGQPQVAPPAPAASPAASSRPQPQNGSSGMGSTVSKAYGASKTFGKAAGPSLSHTSGGTQSKVVPIASLTPYQSKWTICARVTNKSQIRTWSNSRGEGKLFSLELVDESGEIRATAFNEQVDKFFPLIEVNKVYYFSKGTLKIANKQFTAVKNDYEMTFNNETSVMPCEDDHHLPTVQFDFTGIDDLENKSKDSLVDIIGICKSYEDATKITVRSNNREVAKRNIYLMDTSGKVVTATLWGEDADKFDGSRQPVLAIKGARVSDFGGRSLSVLSSSTIIANPDIPEAYKLRGWFDAEGQALDGVSISDLKSGGVGGSNTNWKTLYEVKSENLGQGDKPDYFSSVATVVYLRKENCMYQACPTQDCNKKVIDQQNGLYRCEKCDTEFPNFKYRMILSVNIADFQENQWVTCFQESAEAILGQNAAYLGELKDKNEQAFEEVFQNANFRSFIFRVRVKVETYNDESRIKATVMDVKPVDYREYGRRLVMSIRRSALM,3.962573502059376 +NC1=N[C@@](CF)(C[C@H](O1)C(F)(F)F)c1cc(Nc2nccc3cc(cnc23)C#CC2CC2)ccc1F,MQPSSLLPLALCLLAAPASALVRIPLHKFTSIRRTMSEVGGSVEDLIAKGPVSKYSQAVPAVTEGPIPEVLKNYMDAQYYGEIGIGTPPQCFTVVFDTGSSNLWVPSIHCKLLDIACWIHHKYNSDKSSTYVKNGTSFDIHYGSGSLSGYLSQDTVSVPCQSASSASALGGVKVERQVFGEATKQPGITFIAAKFDGILGMAYPRISVNNVLPVFDNLMQQKLVDQNIFSFYLSRDPDAQPGGELMLGGTDSKYYKGSLSYLNVTRKAYWQVHLDQVEVASGLTLCKEGCEAIVDTGTSLMVGPVDEVRELQKAIGAVPLIQGEYMIPCEKVSTLPAITLKLGGKGYKLSPEDYTLKVSQAGKTLCLSGFMGMDIPPPSGPLWILGDVFIGRYYTVFDRDNNRVGFAEAARL,3.3979400086720375 +CCCCCCC(C)(C)c1ccc([C@H]2C[C@@H](O)CC[C@@H]2CCCO)c(O)c1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNSPLVPAGDTTNITEFYNKSLSSFKENEENIQCGENFMDMECFMILNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFVDFHVFHRKDSPNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCKKLQSVCSDIFPLIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNTASMHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,9.236572006437063 +C(CNc1ccnc2oc(c(-c3ccccc3)c12)-c1ccc(OCCN2CCCCC2)cc1)Cn1ccnc1,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,5.769551078621726 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+C[C@@H]1C[C@H](N)C[C@@H](C1)c1ccncc1NC(=O)c1ccc(F)c2cc(cnc12)N1CCSCC1,MLLSKINSLAHLRAAPCNDLHATKLAPGKEKEPLESQYQVGPLLGSGGFGSVYSGIRVSDNLPVAIKHVEKDRISDWGELPNGTRVPMEVVLLKKVSSGFSGVIRLLDWFERPDSFVLILERPEPVQDLFDFITERGALQEELARSFFWQVLEAVRHCHNCGVLHRDIKDENILIDLNRGELKLIDFGSGALLKDTVYTDFDGTRVYSPPEWIRYHRYHGRSAAVWSLGILLYDMVCGDIPFEHDEEIIRGQVFFRQRVSSECQHLIRWCLALRPSDRPTFEEIQNHPWMQDVLLPQETAEIHLHSLSPGPSK,8.0 +COc1cc(nc(OC)n1)-c1cnc(o1)C(=O)CCCCCCc1ccccc1,MRSSCVLLTALVALAAYYVYIPLPGSVSDPWKLMLLDATFRGAQQVSNLIHYLGLSHHLLALNFIIVSFGKKSAWSSAQVKVTDTDFDGVEVRVFEGPPKPEEPLKRSVVYIHGGGWALASAKIRYYDELCTAMAEELNAVIVSIEYRLVPKVYFPEQIHDVVRATKYFLKPEVLQKYMVDPGRICISGDSAGGNLAAALGQQFTQDASLKNKLKLQALIYPVLQALDFNTPSYQQNVNTPILPRYVMVKYWVDYFKGNYDFVQAMIVNNHTSLDVEEAAAVRARLNWTSLLPASFTKNYKPVVQTTGNARIVQELPQLLDARSAPLIADQAVLQLLPKTYILTCEHDVLRDDGIMYAKRLESAGVEVTLDHFEDGFHGCMIFTSWPTNFSVGIRTRNSYIKWLDQNL,4.0 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+CN(C)c1nc(nnc1-c1ccccc1)-c1ccccn1,MEGAGGANDKKKISSERRKEKSRDAARSRRSKESEVFYELAHQLPLPHNVSSHLDKASVMRLTISYLRVRKLLDAGDLDIEDDMKAQMNCFYLKALDGFVMVLTDDGDMIYISDNVNKYMGLTQFELTGHSVFDFTHPCDHEEMREMLTHRNGLVKKGKEQNTQRSFFLRMKCTLTSRGRTMNIKSATWKVLHCTGHIHVYDTNSNQPQCGYKKPPMTCLVLICEPIPHPSNIEIPLDSKTFLSRHSLDMKFSYCDERITELMGYEPEELLGRSIYEYYHALDSDHLTKTHHDMFTKGQVTTGQYRMLAKRGGYVWVETQATVIYNTKNSQPQCIVCVNYVVSGIIQHDLIFSLQQTECVLKPVESSDMKMTQLFTKVESEDTSSLFDKLKKEPDALTLLAPAAGDTIISLDFGSNDTETDDQQLEEVPLYNDVMLPSPNEKLQNINLAMSPLPTAETPKPLRSSADPALNQEVALKLEPNPESLELSFTMPQIQDQTPSPSDGSTRQSSPEPNSPSEYCFYVDSDMVNEFKLELVEKLFAEDTEAKNPFSTQDTDLDLEMLAPYIPMDDDFQLRSFDQLSPLESSSASPESASPQSTVTVFQQTQIQEPTANATTTTATTDELKTVTKDRMEDIKILIASPSPTHIHKETTSATSSPYRDTQSRTASPNRAGKGVIEQTEKSHPRSPNVLSVALSQRTTVPEEELNPKILALQNAQRKRKMEHDGSLFQAVGIGTLLQQPDDHAATTSLSWKRVKGCKSSEQNGMEQKTIILIPSDLACRLLGQSMDESGLPQLTSYDCEVNAPIQGSRNLLQGEELLRALDQVN,5.00788851221305 +CC(C)CC(C1CCCCN1)c1ccc(Cl)c(Cl)c1,MSKSKCSVGLMSSVVAPAKEPNAVGPKEVELILVKEQNGVQLTSSTLTNPRQSPVEAQDRETWGKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPILKGVGFTVILISLYVGFFYNVIIAWALHYLFSSFTTELPWIHCNNSWNSPNCSDAHPGDSSGDSSGLNDTFGTTPAAEYFERGVLHLHQSHGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAIDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIVTTSINSLTSFSSGFVVFSFLGYMAQKHSVPIGDVAKDGPGLIFIIYPEAIATLPLSSAWAVVFFIMLLTLGIDSAMGGMESVITGLIDEFQLLHRHRELFTLFIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVGQFSDDIQQMTGQRPSLYWRLCWKLVSPCFLLFVVVVSIVTFRPPHYGAYIFPDWANALGWVIATSSMAMVPIYAAYKFCSLPGSFREKLAYAIAPEKDRELVDRGEVRQFTLRHWLKV,7.886056647693163 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+[I-].C[n+]1c(\C=C\c2ccc(O)cc2)ccc2ccccc12,MRPPQCLLHTPSLASPLLLLLLWLLGGGVGAEGREDAELLVTVRGGRLRGIRLKTPGGPVSAFLGIPFAEPPMGPRRFLPPEPKQPWSGVVDATTFQSVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLVWIYGGGFYSGASSLDVYDGRFLVQAERTVLVSMNYRVGAFGFLALPGSREAPGNVGLLDQRLALQWVQENVAAFGGDPTSVTLFGESAGAASVGMHLLSPPSRGLFHRAVLQSGAPNGPWATVGMGEARRRATQLAHLVGCPPGGTGGNDTELVACLRTRPAQVLVNHEWHVLPQESVFRFSFVPVVDGDFLSDTPEALINAGDFHGLQVLVGVVKDEGSYFLVYGAPGFSKDNESLISRAEFLAGVRVGVPQVSDLAAEAVVLHYTDWLHPEDPARLREALSDVVGDHNVVCPVAQLAGRLAAQGARVYAYVFEHRASTLSWPLWMGVPHGYEIEFIFGIPLDPSRNYTAEEKIFAQRLMRYWANFARTGDPNEPRDPKAPQWPPYTAGAQQYVSLDLRPLEVRRGLRAQACAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQDRCSDL,5.7447274948966935 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+CNc1nccc(n1)-c1cccnc1Oc1ccc(NC(=O)Nc2ccccc2)c2ccccc12,MAQKENSYPWPYGRQTAPSGLSTLPQRVLRKEPVTPSALVLMSRSNVQPTAAPGQKVMENSSGTPDILTRHFTIDDFEIGRPLGKGKFGNVYLAREKKSHFIVALKVLFKSQIEKEGVEHQLRREIEIQAHLHHPNILRLYNYFYDRRRIYLILEYAPRGELYKELQKSCTFDEQRTATIMEELADALMYCHGKKVIHRDIKPENLLLGLKGELKIADFGWSVHAPSLRRKTMCGTLDYLPPEMIEGRMHNEKVDLWCIGVLCYELLVGNPPFESASHNETYRRIVKVDLKFPASVPMGAQDLISKLLRHNPSERLPLAQVSAHPWVRANSRRVLPPSALQSVA,7.638272163982407 +CC1COCC(C[N+](C)(C)C)O1,MNNSTNSSNNSLALTSPYKTFEVVFIVLVAGSLSLVTIIGNILVMVSIKVNRHLQTVNNYFLFSLACADLIIGVFSMNLYTLYTVIGYWPLGPVVCDLWLALDYVVSNASVMNLLIISFDRYFCVTKPLTYPVKRTTKMAGMMIAAAWVLSFILWAPAILFWQFIVGVRTVEDGECYIQFFSNAAVTFGTAIAAFYLPVIIMTVLYWHISRASKSRIKKDKKEPVANQDPVSPSLVQGRIVKPNNNNMPSSDDGLEHNKIQNGKAPRDPVTENCVQGEEKESSNDSTSVSAVASNMRDDEITQDENTVSTSLGHSKDENSKQTCIRIGTKTPKSDSCTPTNTTVEVVGSSGQNGDEKQNIVARKIVKMTKQPAKKKPPPSREKKVTRTILAILLAFIITWAPYNVMVLINTFCAPCIPNTVWTIGYWLCYINSTINPACYALCNATFKKTFKHLLMCHYKNIGATR,-4.309999999999993 +NC(=O)c1csc(n1)[C@@H]1O[C@H](COP(O)(=O)CC(=O)NC[C@@H]2O[C@@H]([C@@H](O)[C@H]2O)n2cnc3c(N)ncnc23)[C@@H](O)[C@H]1O,MADYLISGGTSYVPDDGLTAQQLFNCGDGLTYNDFLILPGYIDFTADQVDLTSALTKKITLKTPLVSSPMDTVTEAGMAIAMALTGGIGFIHHNCTPEFQANEVRKVKKYEQGFITDPVVLSPKDRVRDVFEAKARHGFCGIPITDTGRMGSRLVGIISSRDIDFLKEEEHDCFLEEIMTKREDLVVAPAGITLKEANEILQRSKKGKLPIVNEDDELVAIIARTDLKKNRDYPLASKDAKKQLLCGAAIGTHEDDKYRLDLLAQAGVDVVVLDSSQGNSIFQINMIKYIKDKYPNLQVIGGNVVTAAQAKNLIDAGVDALRVGMGSGSICITQEVLACGRPQATAVYKVSEYARRFGVPVIADGGIQNVGHIAKALALGASTVMMGSLLAATTEAPGEYFFSDGIRLKKYRGMGSLDAMDKHLSSQNRYFSEADKIKVAQGVSGAVQDKGSIHKFVPYLIAGIQHSCQDIGAKSLTQVRAMMYSGELKFEKRTSSAQVEGGVHSLHSYEKRLF,5.180456064458132 +Clc1cccc(N2CCN(CCCCOc3ccc4CCC(=O)Nc4c3)CC2)c1Cl,MSLPNSSCLLEDKMCEGNKTTMASPQLMPLVVVLSTICLVTVGLNLLVLYAVRSERKLHTVGNLYIVSLSVADLIVGAVVMPMNILYLLMSKWSLGRPLCLFWLSMDYVASTASIFSVFILCIDRYRSVQQPLRYLKYRTKTRASATILGAWFLSFLWVIPILGWNHFMQQTSVRREDKCETDFYDVTWFKVMTAIINFYLPTLLMLWFYAKIYKAVRQHCQHRELINRSLPSFSEIKLRPENPKGDAKKPGKESPWEVLKRKPKDAGGGSVLKSPSQTPKEMKSPVVFSQEDDREVDKLYCFPLDIVHMQAAAEGSSRDYVAVNRSHGQLKTDEQGLNTHGASEISEDQMLGDSQSFSRTDSDTTTETAPGKGKLRSGSNTGLDYIKFTWKRLRSHSRQYVSGLHMNRERKAAKQLGFIMAAFILCWIPYFIFFMVIAFCKNCCNEHLHMFTIWLGYINSTLNPLIYPLCNENFKKTFKRILHIRS,7.527243550682788 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+OC1(CCN(CCCC(=O)c2ccc(F)cc2)CC1)c1ccc(Cl)cc1,MEPSSPQDEGLRKKQPKKPVPEILPRPPRALFCLTLENPLRKACISIVEWKPFETIILLTIFANCVALAVYLPMPEDDNNSLNLGLEKLEYFFLIVFSIEAAMKIIAYGFLFHQDAYLRSGWNVLDFTIVFLGVFTVILEQVNVIQSHTAPMSSKGAGLDVKALRAFRVLRPLRLVSGVPSLQVVLNSIFKAMLPLFHIALLVLFMVIIYAIIGLELFKGKMHKTCYFIGTDIVATVENEEPSPCARTGSGRRCTINGSECRGGWPGPNHGITHFDNFGFSMLTVYQCITMEGWTDVLYWVNDAIGNEWPWIYFVTLILLGSFFILNLVLGVLSGEFTKEREKAKSRGTFQKLREKQQLDEDLRGYMSWITQGEVMDVEDFREGKLSLDEGGSDTESLYEIAGLNKIIQFIRHWRQWNRIFRWKCHDIVKSKVFYWLVILIVALNTLSIASEHHNQPLWLTRLQDIANRVLLSLFTTEMLMKMYGLGLRQYFMSIFNRFDCFVVCSGILEILLVESGAMTPLGISVLRCIRLLRIFKITKYWTSLSNLVASLLNSIRSIASLLLLLFLFIVIFALLGMQLFGGRYDFEDTEVRRSNFDNFPQALISVFQVLTGEDWTSMMYNGIMAYGGPSYPGMLVCIYFIILFVCGNYILLNVFLAIAVDNLAEAESLTSAQKAKAEEKKRRKMSKGLPDKSEEEKSTMAKKLEQKPKGEGIPTTAKLKIDEFESNVNEVKDPYPSADFPGDDEEDEPEIPLSPRPRPLAELQLKEKAVPIPEASSFFIFSPTNKIRVLCHRIVNATWFTNFILLFILLSSAALAAEDPIRADSMRNQILKHFDIGFTSVFTVEIVLKMTTYGAFLHKGSFCRNYFNMLDLLVVAVSLISMGLESSAISVVKILRVLRVLRPLRAINRAKGLKHVVQCMFVAISTIGNIVLVTTLLQFMFACIGVQLFKGKFFRCTDLSKMTEEECRGYYYVYKDGDPMQIELRHREWVHSDFHFDNVLSAMMSLFTVSTFEGWPQLLYKAIDSNAEDVGPIYNNRVEMAIFFIIYIILIAFFMMNIFVGFVIVTFQEQGETEYKNCELDKNQRQCVQYALKARPLRCYIPKNPYQYQVWYIVTSSYFEYLMFALIMLNTICLGMQHYNQSEQMNHISDILNVAFTIIFTLEMILKLMAFKARGYFGDPWNVFDFLIVIGSIIDVILSEIDTFLASSGGLYCLGGGCGNVDPDESARISSAFFRLFRVMRLIKLLSRAEGVRTLLWTFIKSFQALPYVALLIVMLFFIYAVIGMQMFGKIALVDGTQINRNNNFQTFPQAVLLLFRCATGEAWQEILLACSYGKLCDPESDYAPGEEYTCGTNFAYYYFISFYMLCAFLVINLFVAVIMDNFDYLTRDWSILGPHHLDEFKAIWAEYDPEAKGRIKHLDVVTLLRRIQPPLGFGKFCPHRVACKRLVGMNMPLNSDGTVTFNATLFALVRTALKIKTEGNFEQANEELRAIIKKIWKRTSMKLLDQVIPPIGDDEVTVGKFYATFLIQEHFRKFMKRQEEYYGYRPKKDIVQIQAGLRTIEEEAAPEICRTVSGDLAAEEELERAMVEAAMEEGIFRRTGGLFGQVDNFLERTNSLPPVMANQRPLQFAEIEMEEMESPVFLEDFPQDPRTNPLARANTNNANANVAYGNSNHSNSHVFSSVHYEREFPEETETPATRGRALGQPCRVLGPHSKPCVEMLKGLLTQRAMPRGQAPPAPCQCPRVESSMPEDRKSSTPGSLHEETPHSRSTRENTSRCSAPATALLIQKALVRGGLGTLAADANFIMATGQALADACQMEPEEVEIMATELLKGREAPEGMASSLGCLNLGSSLGSLDQHQGSQETLIPPRL,5.886056647693163 +Oc1cc(O)cc(c1)C(=O)NN=Cc1cn(Cc2cccc(F)c2)c2ccccc12,MQGPWVLLLLGLRLQLSLGVIPAEEENPAFWNRQAAEALDAAKKLQPIQKVAKNLILFLGDGLGVPTVTATRILKGQKNGKLGPETPLAMDRFPYLALSKTYNVDRQVPDSAATATAYLCGVKANFQTIGLSAAARFNQCNTTRGNEVISVMNRAKQAGKSVGVVTTTRVQHASPAGTYAHTVNRNWYSDADMPASARQEGCQDIATQLISNMDIDVILGGGRKYMFPMGTPDPEYPADASQNGIRLDGKNLVQEWLAKHQGAWYVWNRTELMQASLDQSVTHLMGLFEPGDTKYEIHRDPTLDPSLMEMTEAALRLLSRNPRGFYLFVEGGRIDHGHHEGVAYQALTEAVMFDDAIERAGQLTSEEDTLTLVTADHSHVFSFGGYTLRGSSIFGLAPSKAQDSKAYTSILYGNGPGYVFNSGVRPDVNESESGSPDYQQQAAVPLSSETHGGEDVAVFARGPQAHLVHGVQEQSFVAHVMAFAACLEPYTACDLAPPACTTDAAHPVAASLPLLAGTLLLLGASAAP,4.0 +CC(C)[C@@]1(CC[C@H](C1)N1CCC(CC1)c1cccc(c1)C(O)=O)C(=O)NCc1cc(cc(c1)C(F)(F)F)C(F)(F)F,MLSTSRSRFIRNTNESGEEVTTFFDYDYGAPCHKFDVKQIGAQLLPPLYSLVFIFGFVGNMLVVLILINCKKLKCLTDIYLLNLAISDLLFLITLPLWAHSAANEWVFGNAMCKLFTGLYHIGYFGGIFFIILLTIDRYLAIVHAVFALKARTVTFGVVTSVITWLVAVFASVPGIIFTKCQKEDSVYVCGPYFPRGWNNFHTIMRNILGLVLPLLIMVICYSGILKTLLRCRNEKKRHRAVRVIFTIMIVYFLFWTPYNIVILLNTFQEFFGLSNCESTSQLDQATQVTETLGMTHCCINPIIYAFVGEKFRSLFHIALGCRIAPLQKPVCGGPGVRPGKNVKVTTQGLLDGRGKGKSIGRAPEASLQDKEGA,7.207608310501746 +CCn1c(cc2sccc12)C(=O)N1CCC(CC1)C(=O)NCc1ccc2OCOc2c1,MDVLSPGQGNNTTSPPAPFETGGNTTGISDVTVSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVKKVEKTGADTRHGASPAPQPKKSVNGESGSRNWRLGVESKAGGALCANGAVRQGDDGAALEVIEVHRVGNSKEHLPLPSEAGPTPCAPASFERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPTLLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRQ,4.00436480540245 +CCOP(=O)(Cc1ccc(C[C@H](NC(=O)[C@H](CCCNC(N)=N)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](N)CO)[C@@H](C)CC)C(=O)N[C@@H]([C@@H](C)CC)C(N)=O)cc1)OCC,MRSPSAAWLLGAAILLAASLSCSGTIQGTNRSSKGRSLIGKVDGTSHVTGKGVTVETVFSVDEFSASVLTGKLTTVFLPIVYTIVFVVGLPSNGMALWVFLFRTKKKHPAVIYMANLALADLLSVIWFPLKIAYHIHGNNWIYGEALCNVLIGFFYGNMYCSILFMTCLSVQRYWVIVNPMGHSRKKANIAIGISLAIWLLILLVTIPLYVVKQTIFIPALNITTCHDVLPEQLLVGDMFNYFLSLAIGVFLFPAFLTASAYVLMIRMLRSSAMDENSEKKRKRAIKLIVTVLAMYLICFTPSNLLLVVHYFLIKSQGQSHVYALYIVALCLSTLNSCIDPFVYYFVSHDFRDHAKNALLCRSVRTVKQMQVSLTSKKHSRKSSSYSSSSTTVKTSY,5.886056647693163 +CN1CCN(CCCNC(=O)c2cc(-c3ccc4ccccc4c3)n(c2C)-c2ccc(cc2)S(N)(=O)=O)CC1,MAPLCPSPWLPLLIPAPAPGLTVQLLLSLLLLVPVHPQRLPRMQEDSPLGGGSSGEDDPLGEEDLPSEEDSPREEDPPGEEDLPGEEDLPGEEDLPEVKPKSEEEGSLKLEDLPTVEAPGDPQEPQNNAHRDKEGDDQSHWRYGGDPPWPRVSPACAGRFQSPVDIRPQLAAFCPALRPLELLGFQLPPLPELRLRNNGHSVQLTLPPGLEMALGPGREYRALQLHLHWGAAGRPGSEHTVEGHRFPAEIHVVHLSTAFARVDEALGRPGGLAVLAAFLEEGPEENSAYEQLLSRLEEIAEEGSETQVPGLDISALLPSDFSRYFQYEGSLTTPPCAQGVIWTVFNQTVMLSAKQLHTLSDTLWGPGDSRLQLNFRATQPLNGRVIEASFPAGVDSSPRAAEPVQLNSCLAAGDILALVFGLLFAVTSVAFLVQMRRQHRRGTKGGVSYRPAEVAETGA,6.8326826652518236 +COc1ccc(cc1NC(C)=O)S(=O)(=O)Nc1ccccc1C(=O)NC1CC1,MAKQPSDVSSECDREGRQLQPAERPPQLRPGAPTSLQTEPQGNPEGNHGGEGDSCPHGSPQGPLAPPASPGPFATRSPLFIFMRRSSLLSRSSSGYFSFDTDRSPAPMSCDKSTQTPSPPCQAFNHYLSAMASMRQAEPADMRPEIWIAQELRRIGDEFNAYYARRVFLNNYQAAEDHPRMVILRLLRYIVRLVWRMH,3.4559319556497243 +CCCCC1Oc2ccc(C)cc2-c2ccc3NC(C)(C)C=C(C)c3c12,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAPPGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLVLDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGPTFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGTSTISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAECKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYKSGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYGDLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGGGGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMDSYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASSTTSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,6.044312249686494 +COc1cccc(c1)-c1ncc([nH]1)C(F)(F)F,MKFSELWLREWVNPAIDSDALANQITMAGLEVDGVEPVAGSFHGVVVGEVVECAQHPNADKLRVTKVNVGGDRLLDIVCGAPNCRQGLRVAVATIGAVLPGDFKIKAAKLRGEPSEGMLCSFSELGISDDHSGIIELPADAPIGTDIREYLKLDDNTIEISVTPNRADCLGIIGVARDVAVLNQLPLVQPEIVPVGATIDDTLPITVEAPEACPRYLGRVVKGINVKAPTPLWMKEKLRRCGIRSIDAVVDVTNYVLLELGQPMHAFDKDRIEGGIVVRMAKEGETLVLLDGTEAKLNADTLVIADHNKALAMGGIFGGEHSGVNDETQNVLLECAFFSPLSITGRARRHGLHTDASHRYERGVDPALQHKAMERATRLLIDICGGEAGPVIDITNEATLPKRATITLRRSKLDRLIGHHIADEQVTDILRRLGCEVTEGKDEWQAVAPSWRFDMEIEEDLVEEVARVYGYNNIPDEPVQASLIMGTHREADLSLKRVKTLLNDKGYQEVITYSFVDPKVQQMIHPGVEALLLPSPISVEMSAMRLSLWTGLLATVVYNQNRQQNRVRIFESGLRFVPDTQAPLGIRQDLMLAGVICGNRYEEHWNLAKETVDFYDLKGDLESVLDLTGKLNEVEFRAEANPALHPGQSAAIYLKGERIGFVGVVHPELERKLDLNGRTLVFELEWNKLADRVVPQAREISRFPANRRDIAVVVAENVPAADILSECKKVGVNQVVGVNLFDVYRGKGVAEGYKSLAISLILQDTSRTLEEEEIAATVAKCVEALKERFQASLRD,4.795880017344075 +CN(C)c1ccc(cc1)C(=O)NCCCCCC(=O)NO,MGTALVYHEDMTATRLLWDDPECEIERPERLTAALDRLRQRGLEQRCLRLSAREASEEELGLVHSPEYVSLVRETQVLGKEELQALSGQFDAIYFHPSTFHCARLAAGAGLQLVDAVLTGAVQNGLALVRPPGHHGQRAAANGFCVFNNVAIAAAHAKQKHGLHRILVVDWDVHHGQGIQYLFEDDPSVLYFSWHRYEHGRFWPFLRESDADAVGRGQGLGFTVNLPWNQVGMGNADYVAAFLHLLLPLAFEFDPELVLVSAGFDSAIGDPEGQMQATPECFAHLTQLLQVLAGGRVCAVLEGGYHLESLAESVCMTVQTLLGDPAPPLSGPMAPCQSALESIQSARAAQAPHWKSLQQQDVTAVPMSPSSHSPEGRPPPLLPGGPVCKAAASAPSSLLDQPCLCPAPSVRTAVALTTPDITLVLPPDVIQQEASALREETEAWARPHESLAREEALTALGKLLYLLDGMLDGQVNSGIAATPASAAAATLDVAVRRGLSHGAQRLLCVALGQLDRPPDLAHDGRSLWLNIRGKEAAALSMFHVSTPLPVMTGGFLSCILGLVLPLAYGFQPDLVLVALGPGHGLQGPHAALLAAMLRGLAGGRVLALLEENSTPQLAGILARVLNGEAPPSLGPSSVASPEDVQALMYLRGQLEPQWKMLQCHPHLVA,6.61261017366127 +Fc1ccc(CN2CCN(CC2)C(=O)c2ccc(nc2)C(=O)Nc2ccc(OCc3ccccc3)cc2)cc1,MAEKQKHDGRVKIGHYVLGDTLGVGTFGKVKIGEHQLTGHKVAVKILNRQKIRSLDVVGKIKREIQNLKLFRHPHIIKLYQVISTPTDFFMVMEYVSGGELFDYICKHGRVEEMEARRLFQQILSAVDYCHRHMVVHRDLKPENVLLDAHMNAKIADFGLSNMMSDGEFLRTSCGSPNYAAPEVISGRLYAGPEVDIWSCGVILYALLCGTLPFDDEHVPTLFKKIRGGVFYIPEYLNRSVATLLMHMLQVDPLKRATIKDIREHEWFKQDLPSYLFPEDPSYDANVIDDEAVKEVCEKFECTESEVMNSLYSGDPQDQLAVAYHLIIDNRRIMNQASEFYLASSPPSGSFMDDSAMHIPPGLKPHPERMPPLIADSPKARCPLDALNTTKPKSLAVKKAKWHLGIRSQSKPYDIMAEVYRAMKQLDFEWKVVNAYHLRVRRKNPVTGNYVKMSLQLYLVDNRSYLLDFKSIDDEVVEQRSGSSTPQRSCSAAGLHRPRSSFDSTTAESHSLSGSLTGSLTGSTLSSVSPRLGSHTMDFFEMCASLITTLAR,6.1249387366083 +Cc1nccc(c1C)-c1ccc(C[C@H](NC(=O)[C@@H]2Cc3cc4OC[C@@H](Oc4cc3CN2C(=O)NC2(C)CCCCC2)c2ccc(OCc3ccc(Cl)c(Cl)c3)cc2)C(O)=O)cc1,MAGAPGPLRLALLLLGMVGRAGPRPQGATVSLWETVQKWREYRRQCQRSLTEDPPPATDLFCNRTFDEYACWPDGEPGSFVNVSCPWYLPWASSVPQGHVYRFCTAEGLWLQKDNSSLPWRDLSECEESKRGERSSPEEQLLFLYIIYTVGYALSFSALVIASAILLGFRHLHCTRNYIHLNLFASFILRALSVFIKDAALKWMYSTAAQQHQWDGLLSYQDSLSCRLVFLLMQYCVAANYYWLLVEGVYLYTLLAFSVLSEQWIFRLYVSIGWGVPLLFVVPWGIVKYLYEDEGCWTRNSNMNYWLIIRLPILFAIGVNFLIFVRVICIVVSKLKANLMCKTDIKCRLAKSTLTLIPLLGTHEVIFAFVMDEHARGTLRFIKLFTELSFTSFQGLMVAILYCFVNNEVQLEFRKSWERWRLEHLHIQRDSSMKPLKCPTSSLSSGATAGSSMYTATCQASCS,7.431798275933005 +CC1=CC(=O)N(CC(=O)c2cccc(c2)[N+]([O-])=O)S(=O)(=O)O1,MASPDWGYDDKNGPEQWSKLYPIANGNNQSPVDIKTSETKHDTSLKPISVSYNPATAKEIINVGHSFHVNFEDNDNRSVLKGGPFSDSYRLFQFHFHWGSTNEHGSEHTVDGVKYSAELHVAHWNSAKYSSLAEAASKADGLAVIGVLMKVGEANPKLQKVLDALQAIKTKGKRAPFTNFDPSTLLPSSLDFWTYPGSLTHPPLYESVTWIICKESISVSSEQLAQFRSLLSNVEGDNAVPMQHNNRPTQPLKGRTVRASF,5.886056647693163 +COc1ccccc1N1CCN(Cc2c[nH]c3ncccc23)CC1,MMDVNSSGRPDLYGHLRSFLLPEVGRGLPDLSPDGGADPVAGSWAPHLLSEVTASPAPTWDAPPDNASGCGEQINYGRVEKVVIGSILTLITLLTIAGNCLVVISVCFVKKLRQPSNYLIVSLALADLSVAVAVMPFVSVTDLIGGKWIFGHFFCNVFIAMDVMCCTASIMTLCVISIDRYLGITRPLTYPVRQNGKCMAKMILSVWLLSASITLPPLFGWAQNVNDDKVCLISQDFGYTIYSTAVAFYIPMSVMLFMYYQIYKAARKSAAKHKFPGFPRVEPDSVIALNGIVKLQKEVEECANLSRLLKHERKNISIFKREQKAATTLGIIVGAFTVCWLPFFLLSTARPFICGTSCSCIPLWVERTFLWLGYANSLINPFIYAFFNRDLRTTYRSLLQCQYRNINRKLSAAGMHEALKLAERPERPEFVLRACTRRVLLRPEKRPPVSVWVLQSPDHHNWLADKMLTTVEKKVMIHD,6.987162775294828 +Clc1cccc(\C=C\S(=O)(=O)NCC2CCN(C2)C(=O)C2CCN(CC2)c2ccncc2)c1,MGRPLHLVLLSASLAGLLLLGESLFIRREQANNILARVTRANSFLEEMKKGHLERECMEETCSYEEAREVFEDSDKTNEFWNKYKDGDQCETSPCQNQGKCKDGLGEYTCTCLEGFEGKNCELFTRKLCSLDNGDCDQFCHEEQNSVVCSCARGYTLADNGKACIPTGPYPCGKQTLERRKRSVAQATSSSGEAPDSITWKPYDAADLDPTENPFDLLDFNQTQPERGDNNLTRIVGGQECKDGECPWQALLINEENEGFCGGTILSEFYILTAAHCLYQAKRFKVRVGDRNTEQEEGGEAVHEVEVVIKHNRFTKETYDFDIAVLRLKTPITFRMNVAPACLPERDWAESTLMTQKTGIVSGFGRTHEKGRQSTRLKMLEVPYVDRNSCKLSSSFIITQNMFCAGYDTKQEDACQGDSGGPHVTRFKDTYFVTGIVSWGEGCARKGKYGIYTKVTAFLKWIDRSMKTRGLPKAKSHAPEVITSSPLK,5.366531544420414 +CCNC(=O)[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1cnc2c(N)ncnc12,MPPSISAFQAAYIGIEVLIALVSVPGNVLVIWAVKVNQALRDATFCFIVSLAVADVAVGALVIPLAILINIGPQTYFHTCLMVACPVLILTQSSILALLAIAVDRYLRVKIPLRYKMVVTPRRAAVAIAGCWILSFVVGLTPMFGWNNLSAVERAWAANGSMGEPVIKCEFEKVISMEYMVYFNFFVWVLPPLLLMVLIYLEVFYLIRKQLNKKVSASSGDPQKYYGKELKIAKSLALILFLFALSWLPLHILNCITLFCPSCHKPSILTYIAIFLTHGNSAMNPIVYAFRIQKFRVTFLKIWNDHFRCQPAPPIDEDLPEERPDD,8.167491087293763 +Clc1cccc(c1)-c1ccccc1C(=O)NCC1CCNCC1,MNTSAPPAVSPNITVLAPGKGPWQVAFIGITTGLLSLATVTGNLLVLISFKVNTELKTVNNYFLLSLACADLIIGTFSMNLYTTYLLMGHWALGTLACDLWLALDYVASNASVMNLLLISFDRYFSVTRPLSYRAKRTPRRAALMIGLAWLVSFVLWAPAILFWQYLVGERTVLAGQCYIQFLSQPIITFGTAMAAFYLPVTVMCTLYWRIYRETENRARELAALQGSETPGKGGGSSSSSERSQPGAEGSPETPPGRCCRCCRAPRLLQAYSWKEEEEEDEGSMESLTSSEGEEPGSEVVIKMPMVDPEAQAPTKQPPRSSPNTVKRPTKKGRDRAGKGQKPRGKEQLAKRKTFSLVKEKKAARTLSAILLAFILTWTPYNIMVLVSTFCKDCVPETLWELGYWLCYVNSTINPMCYALCNKAFRDTFRLLLLCRWDKRRWRKIPKRPGSVHRTPSRQC,7.199970640755866 +OC(=O)CCC(NC(=O)c1cc(Cl)cc(Cl)c1)C(=O)NC1CCC2(CCCCC2)CC1,MSHSPARQHLVESSRMDVVDSLLMNGSNITPPCELGLENETLFCLDQPQPSKEWQSALQILLYSIIFLLSVLGNTLVITVLIRNKRMRTVTNIFLLSLAVSDLMLCLFCMPFNLIPNLLKDFIFGSAVCKTTTYFMGTSVSVSTFNLVAISLERYGAICRPLQSRVWQTKSHALKVIAATWCLSFTIMTPYPIYSNLVPFTKNNNQTANMCRFLLPSDAMQQSWQTFLLLILFLLPGIVMVVAYGLISLELYQGIKFDASQKKSAKEKKPSTGSSTRYEDSDGCYLQKSRPPRKLELQQLSSGSGGSRLNRIRSSSSAANLIAKKRVIRMLIVIVVLFFLCWMPIFSANAWRAYDTVSAEKHLSGTPISFILLLSYTSSCVNPIIYCFMNKRFRLGFMATFPCCPNPGPPGVRGEVGEEEDGRTIRALLSRYSYSHMSTSAPPP,4.5638373529592435 +Fc1ccc2NC(=O)C(c2c1)c1[nH]c2ccc(F)cc2c1N=O,MPRERRERDAKERDTMKEDGGAEFSARSRKRKANVTVFLQDPDEEMAKIDRTARDQCGSQPWDNNAVCADPCSLIPTPDKEDDDRVYPNSTCKPRIIAPSRGSPLPVLSWANREEVWKIMLNKEKTYLRDQHFLEQHPLLQPKMRAILLDWLMEVCEVYKLHRETFYLAQDFFDRYMATQENVVKTLLQLIGISSLFIAAKLEEIYPPKLHQFAYVTDGACSGDEILTMELMIMKALKWRLSPLTIVSWLNVYMQVAYLNDLHEVLLPQYPQQIFIQIAELLDLCVLDVDCLEFPYGILAASALYHFSSSELMQKVSGYQWCDIENCVKWMVPFAMVIRETGSSKLKHFRGVADEDAHNIQTHRDSLDLLDKARAKKAMLSEQNRASPLPSGLLTPPQSGKKQSSGPEMA,8.744727494896694 +Cc1cncc(n1)-c1cc2n(ncc2cn1)-c1cccc(n1)C(=O)N1CCC[C@@H](N)C1,MLTKPLQGPPAPPGTPTPPPGGKDREAFEAEYRLGPLLGKGGFGTVFAGHRLTDRLQVAIKVIPRNRVLGWSPLSDSVTCPLEVALLWKVGAGGGHPGVIRLLDWFETQEGFMLVLERPLPAQDLFDYITEKGPLGEGPSRCFFGQVVAAIQHCHSRGVVHRDIKDENILIDLRRGCAKLIDFGSGALLHDEPYTDFDGTRVYSPPEWISRHQYHALPATVWSLGILLYDMVCGDIPFERDQEILEAELHFPAHVSPDCCALIRRCLAPKPSSRPSLEEILLDPWMQTPAEDVPLNPSKGGPAPLAWSLLP,6.714442690992226 +Clc1ccc(OC(C2CNC2)c2ccc3ccccc3c2)cc1Cl,MSKSKCSVGLMSSVVAPAKEPNAVGPKEVELILVKEQNGVQLTSSTLTNPRQSPVEAQDRETWGKKIDFLLSVIGFAVDLANVWRFPYLCYKNGGGAFLVPYLLFMVIAGMPLFYMELALGQFNREGAAGVWKICPILKGVGFTVILISLYVGFFYNVIIAWALHYLFSSFTTELPWIHCNNSWNSPNCSDAHPGDSSGDSSGLNDTFGTTPAAEYFERGVLHLHQSHGIDDLGPPRWQLTACLVLVIVLLYFSLWKGVKTSGKVVWITATMPYVVLTALLLRGVTLPGAIDGIRAYLSVDFYRLCEASVWIDAATQVCFSLGVGFGVLIAFSSYNKFTNNCYRDAIVTTSINSLTSFSSGFVVFSFLGYMAQKHSVPIGDVAKDGPGLIFIIYPEAIATLPLSSAWAVVFFIMLLTLGIDSAMGGMESVITGLIDEFQLLHRHRELFTLFIVLATFLLSLFCVTNGGIYVFTLLDHFAAGTSILFGVLIEAIGVAWFYGVGQFSDDIQQMTGQRPSLYWRLCWKLVSPCFLLFVVVVSIVTFRPPHYGAYIFPDWANALGWVIATSSMAMVPIYAAYKFCSLPGSFREKLAYAIAPEKDRELVDRGEVRQFTLRHWLKV,7.267606240177031 +CS(=O)c1ccc(CSc2nc(c([nH]2)-c2ccc(Cl)cc2)-c2ccncc2)cc1,MSQERPTFYRQELNKTIWEVPERYQNLSPVGSGAYGSVCAAFDTKTGLRVAVKKLSRPFQSIIHAKRTYRELRLLKHMKHENVIGLLDVFTPARSLEEFNDVYLVTHLMGADLNNIVKCQKLTDDHVQFLIYQILRGLKYIHSADIIHRDLKPSNLAVNEDCELKILDFGLARHTDDEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLTGRTLFPGTDHIDQLKLILRLVGTPGAELLKKISSESARNYIQSLTQMPKMNFANVFIGANPLAVDLLEKMLVLDSDKRITAAQALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES,5.853871964321762 +COCc1cc(=O)oc2cc3occ(C)c3cc12,MGQGDESERIVINVGGTRHQTYRSTLRTLPGTRLAWLAEPDAHSHFDYDPRADEFFFDRHPGVFAHILNYYRTGKLHCPADVCGPLYEEELAFWGIDETDVEPCCWMTYRQHRDAEEALDSFGGAPLDNSADDADADGPGDSGDGEDELEMTKRLALSDSPDGRPGGFWRRWQPRIWALFEDPYSSRYARYVAFASLFFILVSITTFCLETHERFNPIVNKTEIENVRNGTQVRYYREAETEAFLTYIEGVCVVWFTFEFLMRVIFCPNKVEFIKNSLNIIDFVAILPFYLEVGLSGLSSKAAKDVLGFLRVVRFVRILRIFKLTRHFVGLRVLGHTLRASTNEFLLLIIFLALGVLIFATMIYYAERIGAQPNDPSASEHTHFKNIPIGFWWAVVTMTTLGYGDMYPQTWSGMLVGALCALAGVLTIAMPVPVIVNNFGMYYSLAMAKQKLPKKKKKHIPRPPQLGSPNYCKSVVNSPHHSTQSDTCPLAQEEILEINRAGRKPLRGMSI,3.671620396561262 +CC(C)(C)OC(=O)NCc1nc2c(cc(cc2[nH]1)C(F)(F)F)C(F)(F)F,MTEGARAADEVRVPLGAPPPGPAALVGASPESPGAPGREAERGSELGVSPSESPAAERGAELGADEEQRVPYPALAATVFFCLGQTTRPRSWCLRLVCNPWFEHVSMLVIMLNCVTLGMFRPCEDVECGSERCNILEAFDAFIFAFFAVEMVIKMVALGLFGQKCYLGDTWNRLDFFIVVAGMMEYSLDGHNVSLSAIRTVRVLRPLRAINRVPSMRILVTLLLDTLPMLGNVLLLCFFVFFIFGIVGVQLWAGLLRNRCFLDSAFVRNNNLTFLRPYYQTEEGEENPFICSSRRDNGMQKCSHIPGRRELRMPCTLGWEAYTQPQAEGVGAARNACINWNQYYNVCRSGDSNPHNGAINFDNIGYAWIAIFQVITLEGWVDIMYYVMDAHSFYNFIYFILLIIVGSFFMINLCLVVIATQFSETKQRESQLMREQRARHLSNDSTLASFSEPGSCYEELLKYVGHIFRKVKRRSLRLYARWQSRWRKKVDPSAVQGQGPGHRQRRAGRHTASVHHLVYHHHHHHHHHYHFSHGSPRRPGPEPGACDTRLVRAGAPPSPPSPGRGPPDAESVHSIYHADCHIEGPQERARVAHAAATAAASLRLATGLGTMNYPTILPSGVGSGKGSTSPGPKGKWAGGPPGTGGHGPLSLNSPDPYEKIPHVVGEHGLGQAPGHLSGLSVPCPLPSPPAGTLTCELKSCPYCTRALEDPEGELSGSESGDSDGRGVYEFTQDVRHGDRWDPTRPPRATDTPGPGPGSPQRRAQQRAAPGEPGWMGRLWVTFSGKLRRIVDSKYFSRGIMMAILVNTLSMGVEYHEQPEELTNALEISNIVFTSMFALEMLLKLLACGPLGYIRNPYNIFDGIIVVISVWEIVGQADGGLSVLRTFRLLRVLKLVRFLPALRRQLVVLVKTMDNVATFCTLLMLFIFIFSILGMHLFGCKFSLKTDTGDTVPDRKNFDSLLWAIVTVFQILTQEDWNVVLYNGMASTSSWAALYFVALMTFGNYVLFNLLVAILVEGFQAEGDANRSDTDEDKTSVHFEEDFHKLRELQTTELKMCSLAVTPNGHLEGRGSLSPPLIMCTAATPMPTPKSSPFLDAAPSLPDSRRGSSSSGDPPLGDQKPPASLRSSPCAPWGPSGAWSSRRSSWSSLGRAPSLKRRGQCGERESLLSGEGKGSTDDEAEDGRAAPGPRATPLRRAESLDPRPLRPAALPPTKCRDRDGQVVALPSDFFLRIDSHREDAAELDDDSEDSCCLRLHKVLEPYKPQWCRSREAWALYLFSPQNRFRVSCQKVITHKMFDHVVLVFIFLNCVTIALERPDIDPGSTERVFLSVSNYIFTAIFVAEMMVKVVALGLLSGEHAYLQSSWNLLDGLLVLVSLVDIVVAMASAGGAKILGVLRVLRLLRTLRPLRVISRAPGLKLVVETLISSLRPIGNIVLICCAFFIIFGILGVQLFKGKFYYCEGPDTRNISTKAQCRAAHYRWVRRKYNFDNLGQALMSLFVLSSKDGWVNIMYDGLDAVGVDQQPVQNHNPWMLLYFISFLLIVSFFVLNMFVGVVVENFHKCRQHQEAEEARRREEKRLRRLERRRRSTFPSPEAQRRPYYADYSPTRRSIHSLCTSHYLDLFITFIICVNVITMSMEHYNQPKSLDEALKYCNYVFTIVFVFEAALKLVAFGFRRFFKDRWNQLDLAIVLLSLMGITLEEIEMSAALPINPTIIRIMRVLRIARVLKLLKMATGMRALLDTVVQALPQVGNLGLLFMLLFFIYAALGVELFGRLECSEDNPCEGLSRHATFSNFGMAFLTLFRVSTGDNWNGIMKDTLRECSREDKHCLSYLPALSPVYFVTFVLVAQFVLVNVVVAVLMKHLEESNKEAREDAELDAEIELEMAQGPGSARRVDADRPPLPQESPGARDAPNLVARKVSVSRMLSLPNDSYMFRPVVPASAPHPRPLQEVEMETYGAGTPLGSVASVHSPPAESCASLQIPLAVSSPARSGEPLHALSPRGTARSPSLSRLLCRQEAVHTDSLEGKIDSPRDTLDPAEPGEKTPVRPVTQGGSLQSPPRSPRPASVRTRKHTFGQRCVSSRPAAPGGEEAEASDPADEEVSHITSSACPWQPTAEPHGPEASPVAGGERDLRRLYSVDAQGFLDKPGRADEQWRPSAELGSGEPGEAKAWGPEAEPALGARRKKKMSPPCISVEPPAEDEGSARPSAAEGGSTTLRRRTPSCEATPHRDSLEPTEGSGAGGDPAAKGERWGQASCRAEHLTVPSFAFEPLDLGVPSGDPFLDGSHSVTPESRASSSGAIVPLEPPESEPPMPVGDPPEKRRGLYLTVPQCPLEKPGSPSATPAPGGGADDPV,5.0 +CC1(C)C(=O)Nc2nc(nnc12)-c1nn(Cc2ccccc2F)c2nc(ccc12)C(F)(F)F,MERAGPSFGQQRQQQQPQQQKQQQRDQDSVEAWLDDHWDFTFSYFVRKATREMVNAWFAERVHTIPVCKEGIRGHTESCSCPLQQSPRADNSAPGTPTRKISASEFDRPLRPIVVKDSEGTVSFLSDSEKKEQMPLTPPRFDHDEGDQCSRLLELVKDISSHLDVTALCHKIFLHIHGLISADRYSLFLVCEDSSNDKFLISRLFDVAEGSTLEEVSNNCIRLEWNKGIVGHVAALGEPLNIKDAYEDPRFNAEVDQITGYKTQSILCMPIKNHREEVVGVAQAINKKSGNGGTFTEKDEKDFAAYLAFCGIVLHNAQLYETSLLENKRNQVLLDLASLIFEEQQSLEVILKKIAATIISFMQVQKCTIFIVDEDCSDSFSSVFHMECEELEKSSDTLTREHDANKINYMYAQYVKNTMEPLNIPDVSKDKRFPWTTENTGNVNQQCIRSLLCTPIKNGKKNKVIGVCQLVNKMEENTGKVKPFNRNDEQFLEAFVIFCGLGIQNTQMYEAVERAMAKQMVTLEVLSYHASAAEEETRELQSLAAAVVPSAQTLKITDFSFSDFELSDLETALCTIRMFTDLNLVQNFQMKHEVLCRWILSVKKNYRKNVAYHNWRHAFNTAQCMFAALKAGKIQNKLTDLEILALLIAALSHDLDHRGVNNSYIQRSEHPLAQLYCHSIMEHHHFDQCLMILNSPGNQILSGLSIEEYKTTLKIIKQAILATDLALYIKRRGEFFELIRKNQFNLEDPHQKELFLAMLMTACDLSAITKPWPIQQRIAELVATEFFDQGDRERKELNIEPTDLMNREKKNKIPSMQVGFIDAICLQLYEALTHVSEDCFPLLDGCRKNRQKWQALAEQQEKMLINGESGQAKRN,7.42021640338319 +Cc1cccc(C)c1NC(=O)c1ccc(o1)-c1cc(Cl)ccc1Cl,MGPTSVPLVKAHRSSVSDYVNYDIIVRHYNYTGKLNISADKENSIKLTSVVFILICCFIILENIFVLLTIWKTKKFHRPMYYFIGNLALSDLLAGVAYTANLLLSGATTYKLTPAQWFLREGSMFVALSASVFSLLAIAIERYITMLKMKLHNGSNNFRLFLLISACWVISLILGGLPIMGWNCISALSSCSTVLPLYHKHYILFCTTVFTLLLLSIVILYCRIYSLVRTRSRRLTFRKNISKASRSSEKSLALLKTVIIVLSVFIACWAPLFILLLLDVGCKVKTCDILFRAEYFLVLAVLNSGTNPIIYTLTNKEMRRAFIRIMSCCKCPSGDSAGKFKRPIIAGMEFSRSKSDNSSHPQKDEGDNPETIMSSGNVNSSS,4.698970004336019 +OC(=O)C(F)(F)F.OC(=O)C(F)(F)F.CC(=O)N[C@@H](CCCNC(N)=N)C(=O)NCCCCC1CCN(CC(=O)N2c3ccccc3NC(=O)c3ccccc23)CC1,MNNSTNSSNNSLALTSPYKTFEVVFIVLVAGSLSLVTIIGNILVMVSIKVNRHLQTVNNYFLFSLACADLIIGVFSMNLYTLYTVIGYWPLGPVVCDLWLALDYVVSNASVMNLLIISFDRYFCVTKPLTYPVKRTTKMAGMMIAAAWVLSFILWAPAILFWQFIVGVRTVEDGECYIQFFSNAAVTFGTAIAAFYLPVIIMTVLYWHISRASKSRIKKDKKEPVANQDPVSPSLVQGRIVKPNNNNMPSSDDGLEHNKIQNGKAPRDPVTENCVQGEEKESSNDSTSVSAVASNMRDDEITQDENTVSTSLGHSKDENSKQTCIRIGTKTPKSDSCTPTNTTVEVVGSSGQNGDEKQNIVARKIVKMTKQPAKKKPPPSREKKVTRTILAILLAFIITWAPYNVMVLINTFCAPCIPNTVWTIGYWLCYINSTINPACYALCNATFKKTFKHLLMCHYKNIGATR,7.958607314841775 +OC1=CC\C(C=C1)=C1/Oc2cc(O)cc(O)c2C1=O,MNPNQKIITIGSICLVVGLISLILQIGNIISIWISHSIQTGSQNHTGICNQNIITYKNSTWVKDTTSVILTGNSSLCPIRGWAIYSKDNSIRIGSKGDVFVIREPFISCSHLECRTFFLTQGALLNDKHSNGTVKDRSPYRALMSCPVGEAPSPYNSRFESVAWSASACHDGMGWLTIGISGPDNGAVAVLKYNGIITETIKSWRKKILRTQESECACVNGSCFTIMTDGPSDGLASYKIFKIEKGKVTKSIELNAPNSHYEECSCYPDTGKVMCVCRDNWHGSNRPWVSFDQNLDYQIGYICSGVFGDNPRPEDGTGSCGPVYVDGANGVKGFSYRYGNGVWIGRTKSHSSRHGFEMIWDPNGWTETDSKFSVRQDVVAMTDWSGYSGSFVQHPELTGLDCMRPCFWVELIRGRPKEKTIWTSASSISFCGVNSDTVDWSWPDGAELPFSIDK,4.573488738635425 +COc1cc(cn2ncnc12)-c1[nH]c2ccc(nc2c1C(C)C)C1CCC(CC1)N1CCCC1,MVFPMWTLKRQILILFNIILISKLLGARWFPKTLPCDVTLDVPKNHVIVDCTDKHLTEIPGGIPTNTTNLTLTINHIPDISPASFHRLDHLVEIDFRCNCVPIPLGSKNNMCIKRLQIKPRSFSGLTYLKSLYLDGNQLLEIPQGLPPSLQLLSLEANNIFSIRKENLTELANIEILYLGQNCYYRNPCYVSYSIEKDAFLNLTKLKVLSLKDNNVTAVPTVLPSTLTELYLYNNMIAKIQEDDFNNLNQLQILDLSGNCPRCYNAPFPCAPCKNNSPLQIPVNAFDALTELKVLRLHSNSLQHVPPRWFKNINKLQELDLSQNFLAKEIGDAKFLHFLPSLIQLDLSFNFELQVYRASMNLSQAFSSLKSLKILRIRGYVFKELKSFNLSPLHNLQNLEVLDLGTNFIKIANLSMFKQFKRLKVIDLSVNKISPSGDSSEVGFCSNARTSVESYEPQVLEQLHYFRYDKYARSCRFKNKEASFMSVNESCYKYGQTLDLSKNSIFFVKSSDFQHLSFLKCLNLSGNLISQTLNGSEFQPLAELRYLDFSNNRLDLLHSTAFEELHKLEVLDISSNSHYFQSEGITHMLNFTKNLKVLQKLMMNDNDISSSTSRTMESESLRTLEFRGNHLDVLWREGDNRYLQLFKNLLKLEELDISKNSLSFLPSGVFDGMPPNLKNLSLAKNGLKSFSWKKLQCLKNLETLDLSHNQLTTVPERLSNCSRSLKNLILKNNQIRSLTKYFLQDAFQLRYLDLSSNKIQMIQKTSFPENVLNNLKMLLLHHNRFLCTCDAVWFVWWVNHTEVTIPYLATDVTCVGPGAHKGQSVISLDLYTCELDLTNLILFSLSISVSLFLMVMMTASHLYFWDVWYIYHFCKAKIKGYQRLISPDCCYDAFIVYDTKDPAVTEWVLAELVAKLEDPREKHFNLCLEERDWLPGQPVLENLSQSIQLSKKTVFVMTDKYAKTENFKIAFYLSHQRLMDEKVDVIILIFLEKPFQKSKFLQLRKRLCGSSVLEWPTNPQAHPYFWQCLKNALATDNHVAYSQVFKETV,8.508638306165727 +CC(=O)Nc1cc(ccn1)-c1cnc(N)c(c1)S(=O)(=O)Cc1ccc(Cl)cc1,MGEAEKFHYIYSCDLDINVQLKIGSLEGKREQKSYKAVLEDPMLKFSGLYQETCSDLYVTCQVFAEGKPLALPVRTSYKAFSTRWNWNEWLKLPVKYPDLPRNAQVALTIWDVYGPGKAVPVGGTTVSLFGKYGMFRQGMHDLKVWPNVEADGSEPTKTPGRTSSTLSEDQMSRLAKLTKAHRQGHMVKVDWLDRLTFREIEMINESEKRSSNFMYLMVEFRCVKCDDKEYGIVYYEKDGDESSPILTSFELVKVPDPQMSMENLVESKHHKLARSLRSGPSDHDLKPNAATRDQLNIIVSYPPTKQLTYEEQDLVWKFRYYLTNQEKALTKFLKCVNWDLPQEAKQALELLGKWKPMDVEDSLELLSSHYTNPTVRRYAVARLRQADDEDLLMYLLQLVQALKYENFDDIKNGLEPTKKDSQSSVSENVSNSGINSAEIDSSQIITSPLPSVSSPPPASKTKEVPDGENLEQDLCTFLISRACKNSTLANYLYWYVIVECEDQDTQQRDPKTHEMYLNVMRRFSQALLKGDKSVRVMRSLLAAQQTFVDRLVHLMKAVQRESGNRKKKNERLQALLGDNEKMNLSDVELIPLPLEPQVKIRGIIPETATLFKSALMPAQLFFKTEDGGKYPVIFKHGDDLRQDQLILQIISLMDKLLRKENLDLKLTPYKVLATSTKHGFMQFIQSVPVAEVLDTEGSIQNFFRKYAPSENGPNGISAEVMDTYVKSCAGYCVITYILGVGDRHLDNLLLTKTGKLFHIDFGYILGRDPKPLPPPMKLNKEMVEGMGGTQSEQYQEFRKQCYTAFLHLRRYSNLILNLFSLMVDANIPDIALEPDKTVKKVQDKFRLDLSDEEAVHYMQSLIDESVHALFAAVVEQIHKFAQYWRK,7.522878745280337 +O=C1CC(CC(=O)C1)c1ccco1,MKPHFRNTVERMYRDTFSYNFYNRPILSRRNTVWLCYEVKTKGPSRPPLDAKIFRGQVYSELKYHPEMRFFHWFSKWRKLHRDQEYEVTWYISWSPCTKCTRDMATFLAEDPKVTLTIFVARLYYFWDPDYQEALRSLCQKRDGPRATMKIMNYDEFQHCWSKFVYSQRELFEPWNNLPKYYILLHIMLGEILRHSMDPPTFTFNFNNEPWVRGRHETYLCYEVERMHNDTWVLLNQRRGFLCNQAPHKHGFLEGRHAELCFLDVIPFWKLDLDQDYRVTCFTSWSPCFSCAQEMAKFISKNKHVSLCIFTARIYDDQGRCQEGLRTLAEAGAKISIMTYSEFKHCWDTFVDHQGCPFQPWDGLDEHSQDLSGRLRAILQNQEN,4.425968732272281 +COc1ccc(CCC(=O)NC(N=C(NC#N)Nc2ccccc2C)C(C)(C)C)cc1OC,MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY,6.698970004336019 +CC(C)CC(NS(=O)(=O)c1ccc(C)cc1)C(=O)Nc1ccc(cc1)C(N)=N,MRALLARLLLCVLVVSDSKGSNELHQVPSNCDCLNGGTCVSNKYFSNIHWCNCPKKFGGQHCEIDKSKTCYEGNGHFYRGKASTDTMGRPCLPWNSATVLQQTYHAHRSDALQLGLGKHNYCRNPDNRRRPWCYVQVGLKPLVQECMVHDCADGKKPSSPPEELKFQCGQKTLRPRFKIIGGEFTTIENQPWFAAIYRRHRGGSVTYVCGGSLISPCWVISATHCFIDYPKKEDYIVYLGRSRLNSNTQGEMKFEVENLILHKDYSADTLAHHNDIALLKIRSKEGRCAQPSRTIQTICLPSMYNDPQFGTSCEITGFGKENSTDYLYPEQLKMTVVKLISHRECQQPHYYGSEVTTKMLCAADPQWKTDSCQGDSGGPLVCSLQGRMTLTGIVSWGRGCALKDKPGVYTRVSHFLPWIRSHTKEENGLAL,4.958607314841775 +Cc1cccc(Nc2ccnc(SCC(O)=O)n2)c1C,MGETLGDSPIDPESDSFTDTLSANISQEMTMVDTEMPFWPTNFGISSVDLSVMEDHSHSFDIKPFTTVDFSSISTPHYEDIPFTRTDPVVADYKYDLKLQEYQSAIKVEPASPPYYSEKTQLYNKPHEEPSNSLMAIECRVCGDKASGFHYGVHACEGCKGFFRRTIRLKLIYDRCDLNCRIHKKSRNKCQYCRFQKCLAVGMSHNAIRFGRMPQAEKEKLLAEISSDIDQLNPESADLRALAKHLYDSYIKSFPLTKAKARAILTGKTTDKSPFVIYDMNSLMMGEDKIKFKHITPLQEQSKEVAIRIFQGCQFRSVEAVQEITEYAKSIPGFVNLDLNDQVTLLKYGVHEIIYTMLASLMNKDGVLISEGQGFMTREFLKSLRKPFGDFMEPKFEFAVKFNALELDDSDLAIFIAVIILSGDRPGLLNVKPIEDIQDNLLQALELQLKLNHPESSQLFAKLLQKMTDLRQIVTEHVQLLQVIKKTETDMSLHPLLQEIYKDLY,4.443697499232712 +C[C@H]1C[C@H]2CSC(N)=N[C@]2(CO1)c1nc(NC(=O)c2cnc(cn2)C(F)(F)F)cs1,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,6.714442690992226 +CC(C)(Cc1nc2cc(OCc3ccc4ccccc4n3)ccc2n1Cc1ccc(cc1)C(F)(F)F)C(O)=O,MDQETVGNVVLLAIVTLISVVQNGFFAHKVEHESRTQNGRSFQRTGTLAFERVYTANQNCVDAYPTFLAVLWSAGLLCSQVPAAFAGLMYLFVRQKYFVGYLGERTQSTPGYIFGKRIILFLFLMSVAGIFNYYLIFFFGSDFENYIKTISTTISPLLLIP,6.769551078621726 +CCCc1nc2c(cc(cc2n1-c1ccnc2c(F)ccc(F)c12)N1CCOCC1)-c1ccn[nH]1,MAGPEGFQYRALYPFRRERPEDLELLPGDVLVVSRAALQALGVAEGGERCPQSVGWMPGLNERTRQRGDFPGTYVEFLGPVALARPGPRPRGPRPLPARPRDGAPEPGLTLPDLPEQFSPPDVAPPLLVKLVEAIERTGLDSESHYRPELPAPRTDWSLSDVDQWDTAALADGIKSFLLALPAPLVTPEASAEARRALREAAGPVGPALEPPTLPLHRALTLRFLLQHLGRVASRAPALGPAVRALGATFGPLLLRAPPPPSSPPPGGAPDGSEPSPDFPALLVEKLLQEHLEEQEVAPPALPPKPPKAKPASTVLANGGSPPSLQDAEWYWGDISREEVNEKLRDTPDGTFLVRDASSKIQGEYTLTLRKGGNNKLIKVFHRDGHYGFSEPLTFCSVVDLINHYRHESLAQYNAKLDTRLLYPVSKYQQDQIVKEDSVEAVGAQLKVYHQQYQDKSREYDQLYEEYTRTSQELQMKRTAIEAFNETIKIFEEQGQTQEKCSKEYLERFRREGNEKEMQRILLNSERLKSRIAEIHESRTKLEQQLRAQASDNREIDKRMNSLKPDLMQLRKIRDQYLVWLTQKGARQKKINEWLGIKNETEDQYALMEDEDDLPHHEERTWYVGKINRTQAEEMLSGKRDGTFLIRESSQRGCYACSVVVDGDTKHCVIYRTATGFGFAEPYNLYGSLKELVLHYQHASLVQHNDALTVTLAHPVRAPGPGPPPAAR,7.795880017344075 +O=C(NCC1CCC1)c1nccnc1NC(=O)c1ccc(Cn2ccnn2)c2ccccc12,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,8.09151498112135 +Cc1nc2ccc(CN(CC#C)c3ccc(cc3)S(=O)c3ccccc3C)cc2c(=O)[nH]1,MPVAGSELPRRPLPPAAQERDAEPRPPHGELQYLGQIQHILRCGVRKDDRTGTGTLSVFGMQARYSLRDEFPLLTTKRVFWKGVLEELLWFIKGSTNAKELSSKGVKIWDANGSRDFLDSLGFSTREEGDLGPVYGFQWRHFGAEYRDMESDYSGQGVDQLQRVIDTIKTNPDDRRIIMCAWNPRDLPLMALPPCHALCQFYVVNSELSCQLYQRSGDMGLGVPFNIASYALLTYMIAHITGLKPGDFIHTLGDAHIYLNHIEPLKIQLQREPRPFPKLRILRKVEKIDDFKAEDFQIEGYNPHPTIKMEMAV,7.113509274827518 +COc1cccc(OC)c1-n1c(NS(=O)(=O)[C@@H](C)[C@H](C)c2ncc(F)cn2)nnc1-c1cccc(=O)[nH]1,MEEGGDFDNYYGADNQSECEYTDWKSSGALIPAIYMLVFLLGTTGNGLVLWTVFRSSREKRRSADIFIASLAVADLTFVVTLPLWATYTYRDYDWPFGTFFCKLSSYLIFVNMYASVFCLTGLSFDRYLAIVRPVANARLRLRVSGAVATAVLWVLAALLAMPVMVLRTTGDLENTTKVQCYMDYSMVATVSSEWAWEVGLGVSSTTVGFVVPFTIMLTCYFFIAQTIAGHFRKERIEGLRKRRRLLSIIVVLVVTFALCWMPYHLVKTLYMLGSLLHWPCDFDLFLMNIFPYCTCISYVNSCLNPFLYAFFDPRFRQACTSMLCCGQSRCAGTSHSSSGEKSASYSSGHSQGPGPNMGKGGEQMHEKSIPYSQETLVVD,6.958607314841775 +CCc1ccccc1NC(=O)c1c(C)nsc1Nc1nccc(OC)n1,MENFQKVEKIGEGTYGVVYKARNKLTGEVVALKKIRLDTETEGVPSTAIREISLLKELNHPNIVKLLDVIHTENKLYLVFEFLHQDLKKFMDASALTGIPLPLIKSYLFQLLQGLAFCHSHRVLHRDLKPQNLLINTEGAIKLADFGLARAFGVPVRTYTHEVVTLWYRAPEILLGCKYYSTAVDIWSLGCIFAEMVTRRALFPGDSEIDQLFRIFRTLGTPDEVVWPGVTSMPDYKPSFPKWARQDFSKVVPPLDEDGRSLLSQMLHYDPNKRISAKAALAHPFFQDVTKPVPHLRL,4.698970004336019 +CCCN(CCC)C(=O)C(=O)c1c([nH]c2ccccc12)-c1ccc(Cl)cc1,MSQSWVPAVGLTLVPSLGGFMGAYFVRGEGLRWYASLQKPSWHPPRWTLAPIWGTLYSAMGYGSYIIWKELGGFTEEAMVPLGLYTGQLALNWAWPPIFFGARQMGWALVDLMLVSGVATATTLAWHRVSPPAARLLYPYLAWLAFATMLNYYVWRDNSGRRGGSRLTE,8.332547047110046 +OC(c1ccc2N([C@H](Cc3nnc(CC#N)o3)CCc2c1)S(=O)(=O)c1ccc(F)cc1)(C(F)(F)F)C(F)(F)F,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,7.6777807052660805 +FC(F)(F)c1ccc(Nc2ccc(nc2)[C@@H]2CNCCO2)cc1,MHLCHNSANISHTNSNWSRDVRASLYSLISLIILTTLVGNLIVIISISHFKQLHTPTNWLLHSMAVVDFLLGCLVMPYSMVRTVEHCWYFGELFCKLHTSTDIMLSSASILHLAFISIDRYYAVCDPLRYKAKINLAAIFVMILISWSLPAVFAFGMIFLELNLEGVEELYHNQVFCLRGCFPFFSKVSGVLAFMTSFYIPGSVMLFVYYRIYFIAKGQARSINRANLQVGLEGESRAPQSKETKAAKTLGIMVGVFLLCWCPFFFCMVLDPFLGYVIPPTLNDTLNWFGYLNSAFNPMVYAFFYPWFRRALKMVLFGKIFQKDSSRSKLFL,8.494850021680094 +O[C@H]1[C@H](Oc2cc3oc(cc(=O)c3c(O)c2O)-c2ccccc2)O[C@@H]([C@@H](O)[C@@H]1O)C(O)=O,MNPLLILTFVAAALAAPFDDDDKIVGGYNCEENSVPYQVSLNSGYHFCGGSLINEQWVVSAGHCYKSRIQVRLGEHNIEVLEGNEQFINAAKIIRHPQYDRKTLNNDIMLIKLSSRAVINARVSTISLPTAPPATGTKCLISGWGNTASSGADYPDELQCLDAPVLSQAKCEASYPGKITSNMFCVGFLEGGKDSCQGDSGGPVVCNGQLQGVVSWGDGCAQKNKPGVYTKVYNYVKWIKNTIAANS,3.0 +COc1ccc(CNC(=O)[C@@H](NC(=O)[C@H](NCc2ccc(cc2)C(C)C)[C@H](O)[C@H](Cc2ccccc2)NC(=O)[C@@H](NC(=O)OCc2ccccc2)C(C)(C)C)C(C)C)c(O)c1,MSYDRAITVFSPDGHLFQVEYAQEAVKKGSTAVGVRGRDIVVLGVEKKSVAKLQDERTVRKICALDDNVCMAFAGLTADARIVINRARVECQSHRLTVEDPVTVEYITRYIASLKQRYTQSNGRRPFGISALIVGFDFDGTPRLYQTDPSGTYHAWKANAIGRGAKSVREFLEKNYTDEAIETDDLTIKLVIKALLEVVQSGGKNIELAVMRRDQSLKILNPEEIEKYVAEIEKEKEENEKKKQKKAS,5.795880017344075 +NS(=O)(=O)c1cc(Cl)c(Cl)c(c1)S(N)(=O)=O,MSHHWGYGKHNGPEHWHKDFPIAKGERQSPVDIDTHTAKYDPSLKPLSVSYDQATSLRILNNGHAFNVEFDDSQDKAVLKGGPLDGTYRLIQFHFHWGSLDGQGSEHTVDKKKYAAELHLVHWNTKYGDFGKAVQQPDGLAVLGIFLKVGSAKPGLQKVVDVLDSIKTKGKSADFTNFDPRGLLPESLDYWTYPGSLTTPPLLECVTWIVLKEPISVSSEQVLKFRKLNFNGEGEPEELMVDNWRPAQPLKNRQIKASFK,7.42021640338319 +Clc1ccc2c(c1)nc1CCCCCn1c2=N,MRPPWYPLHTPSLASPLLFLLLSLLGGGARAEGREDPQLLVRVRGGQLRGIRLKAPGGPVSAFLGIPFAEPPVGSRRFMPPEPKRPWSGILDATTFQNVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLIWIYGGGFYSGASSLDVYDGRFLAQVEGTVLVSMNYRVGTFGFLALPGSREAPGNVGLLDQRLALQWVQENIAAFGGDPMSVTLFGESAGAASVGMHILSLPSRSLFHRAVLQSGTPNGPWATVSAGEARRRATLLARLVGCPPGGAGGNDTELISCLRTRPAQDLVDHEWHVLPQESIFRFSFVPVVDGDFLSDTPDALINTGDFQDLQVLVGVVKDEGSYFLVYGVPGFSKDNESLISRAQFLAGVRIGVPQASDLAAEAVVLHYTDWLHPEDPAHLRDAMSAVVGDHNVVCPVAQLAGRLAAQGARVYAYIFEHRASTLTWPLWMGVPHGYEIEFIFGLPLDPSLNYTVEERIFAQRLMQYWTNFARTGDPNDPRDSKSPRWPPYTTAAQQYVSLNLKPLEVRRGLRAQTCAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQERCSDL,4.444905551421681 +COc1ccc(cc1OC1CCCC1)C1(Cc2ccccc2)CCN(C(=O)OC(C)(C)C)C1=O,MENLGVGEGAEACSRLSRSRGRHSMTRAPKHLWRQPRRPIRIQQRFYSDPDKSAGCRERDLSPRPELRKSRLSWPVSSCRRFDLENGLSCGRRALDPQSSPGLGRIMQAPVPHSQRRESFLYRSDSDYELSPKAMSRNSSVASDLHGEDMIVTPFAQVLASLRTVRSNVAALARQQCLGAAKQGPVGNPSSSNQLPPAEDTGQKLALETLDELDWCLDQLETLQTRHSVGEMASNKFKRILNRELTHLSETSRSGNQVSEYISRTFLDQQTEVELPKVTAEEAPQPMSRISGLHGLCHSASLSSATVPRFGVQTDQEEQLAKELEDTNKWGLDVFKVAELSGNRPLTAIIFSIFQERDLLKTFQIPADTLATYLLMLEGHYHANVAYHNSLHAADVAQSTHVLLATPALEAVFTDLEILAALFASAIHDVDHPGVSNQFLINTNSELALMYNDASVLENHHLAVGFKLLQAENCDIFQNLSAKQRLSLRRMVIDMVLATDMSKHMNLLADLKTMVETKKVTSLGVLLLDNYSDRIQVLQNLVHCADLSNPTKPLPLYRQWTDRIMAEFFQQGDRERESGLDISPMCDKHTASVEKSQVGFIDYIAHPLWETWADLVHPDAQDLLDTLEDNREWYQSKIPRSPSDLTNPERDGPDRFQFELTLEEAEEEDEEEEEEGEETALAKEALELPDTELLSPEAGPDPGDLPLDNQRT,5.523458190972571 +CCN1C(=O)N(Cc2cnc3[nH]ncc3c12)c1c(F)c(OC)cc(OC)c1F,MVSWGRFICLVVVTMATLSLARPSFSLVEDTTLEPEEPPTKYQISQPEVYVAAPGESLEVRCLLKDAAVISWTKDGVHLGPNNRTVLIGEYLQIKGATPRDSGLYACTASRTVDSETWYFMVNVTDAISSGDDEDDTDGAEDFVSENSNNKRAPYWTNTEKMEKRLHAVPAANTVKFRCPAGGNPMPTMRWLKNGKEFKQEHRIGGYKVRNQHWSLIMESVVPSDKGNYTCVVENEYGSINHTYHLDVVERSPHRPILQAGLPANASTVVGGDVEFVCKVYSDAQPHIQWIKHVEKNGSKYGPDGLPYLKVLKAAGVNTTDKEIEVLYIRNVTFEDAGEYTCLAGNSIGISFHSAWLTVLPAPGREKEITASPDYLEIAIYCIGVFLIACMVVTVILCRMKNTTKKPDFSSQPAVHKLTKRIPLRRQVTVSAESSSSMNSNTPLVRITTRLSSTADTPMLAGVSEYELPEDPKWEFPRDKLTLGKPLGEGCFGQVVMAEAVGIDKDKPKEAVTVAVKMLKDDATEKDLSDLVSEMEMMKMIGKHKNIINLLGACTQDGPLYVIVEYASKGNLREYLRARRPPGMEYSYDINRVPEEQMTFKDLVSCTYQLARGMEYLASQKCIHRDLAARNVLVTENNVMKIADFGLARDINNIDYYKKTTNGRLPVKWMAPEALFDRVYTHQSDVWSFGVLMWEIFTLGGSPYPGIPVEELFKLLKEGHRMDKPANCTNELYMMMRDCWHAVPSQRPTFKQLVEDLDRILTLTTNEEYLDLSQPLEQYSPSYPDTRSSCSSGDDSVFSPDPMPYEPCLPQYPHINGSVKT,7.0 +Cc1nc2cc(ccc2n1-c1ccc(s1)C(=O)NC1CC1)C(F)(F)F,MISKLKPQFMFLPKKHILSYCRKDVLNLFEQKFYYTSKRKESNNMKNESLLRLINYNRYYNKIDSNNYYNGGKILSNDRQYIYSPLCEYKKKINDISSYVSVPFKINIRNLGTSNFVNNKKDVLDNDYIYENIKKEKSKHKKIIFLLFVSLFGLYGFFESYNPEFFLYDIFLKFCLKYIDGEICHDLFLLLGKYNILPYDTSNDSIYACTNIKHLDFINPFGVAAGFDKNGVCIDSILKLGFSFIEIGTITPRGQTGNAKPRIFRDVESRSIINSCGFNNMGCDKVTENLILFRKRQEEDKLLSKHIVGVSIGKNKDTVNIVDDLKYCINKIGRYADYIAINVSSPNTPGLRDNQEAGKLKNIILSVKEEIDNLEKNNIMNDESTYNEDNKIVEKKNNFNKNNSHMMKDAKDNFLWFNTTKKKPLVFVKLAPDLNQEQKKEIADVLLETNIDGMIISNTTTQINDIKSFENKKGGVSGAKLKDISTKFICEMYNYTNKQIPIIASGGIFSGLDALEKIEAGASVCQLYSCLVFNGMKSAVQIKRELNHLLYQRGYYNLKEAIGRKHSKS,7.3872161432802645 +Clc1ccccc1C1=C(N2CCc3ccccc23)C(=O)NC1=O,MSGGGPSGGGPGGSGRARTSSFAEPGGGGGGGGGGPGGSASGPGGTGGGKASVGAMGGGVGASSSGGGPGGSGGGGSGGPGAGTSFPPPGVKLGRDSGKVTTVVATLGQGPERSQEVAYTDIKVIGNGSFGVVYQARLAETRELVAIKKVLQDKRFKNRELQIMRKLDHCNIVRLRYFFYSSGEKKDELYLNLVLEYVPETVYRVARHFTKAKLTIPILYVKVYMYQLFRSLAYIHSQGVCHRDIKPQNLLVDPDTAVLKLCDFGSAKQLVRGEPNVSYICSRYYRAPELIFGATDYTSSIDVWSAGCVLAELLLGQPIFPGDSGVDQLVEIIKVLGTPTREQIREMNPNYTEFKFPQIKAHPWTKVFKSRTPPEAIALCSSLLEYTPSSRLSPLEACAHSFFDELRCLGTQLPNNRPLPPLFNFSAGELSIQPSLNAILIPPHLRSPAGTTTLTPSSQALTETPTSSDWQSTDATPTLTNSS,6.4723700991286615 +Cc1nnn(C)c1-c1cnc2c(c1)n([C@@H](C1CCOCC1)c1ccccc1)c1c(Cl)ncc(Cl)c21,NPPPPETSNPNKPKRQTNQLQYLLRVVLKTLWKHQFAWPFQQPVDAVKLNLPDYYKIIKTPMDMGTIKKRLENNYYWNAQECIQDFNTMFTNCYIYNKPGDDIVLMAEALEKLFLQKINELPTEE,9.0 +CCCCN1C[C@H]2Cc3c([nH]c4ccccc34)[C@H](N2C1)c1ccc(OC)cc1,MERAGPGSARPQQQWDQDSVEAWLDDHWDFTFSYFVRKGTREMVNAWFAERVHTIPVCKEGIKGHTESCSCPLQPSPRAESSVPGTPTRKISASEFDRPLRPIVIKDSEGTVSFLSDSDKKEQMPLTSPRFDNDEGDQCSRLLELVKDISSHLDVTALCHKIFLHIHGLISADRYSLFLVCEDSSNDKFLISRLFDVAEGSTLEEASNNCIRLEWNKGIVGHVAAFGEPLNIKDAYEDPRFNAEVDQITGYKTQSILCMPIKNHREEVVGVAQAINKKSGNGGTFTEKDEKDFAAYLAFCGIVLHNAQLYETSLLENKRNQVLLDLASLIFEEQQSLEVILKKIAATIISFMQVQKCTIFIVDEDCSDSFSSVFHMECEELEKSSDTLTRERDANRINYMYAQYVKNTMEPLNIPDVSKDKRFPWTNENMGNINQQCIRSLLCTPIKNGKKNKVIGVCQLVNKMEETTGKVKAFNRNDEQFLEAFVIFCGLGIQNTQMYEAVERAMAKQMVTLEVLSYHASAAEEETRELQSLAAAVVPSAQTLKITDFSFSDFELSDLETALCTIRMFTDLNLVQNFQMKHEVLCKWILSVKKNYRKNVAYHNWRHAFNTAQCMFAALKAGKIQKRLTDLEILALLIAALSHDLDHRGVNNSYIQRSEHPLAQLYCHSIMEHHHFDQCLMILNSPGNQILSGLSIEEYKTTLKIIKQAILATDLALYIKRRGEFFELIMKNQFNLEDPHQKELFLAMLMTACDLSAITKPWPIQQRIAELVATEFFDQGDRERKELNIEPADLMNREKKNKIPSMQVGFIDAICLQLYEALTHVSEDCFPLLDGCRKNRQKWQALAEQQEKTLINGESSQTKRN,5.0 +CO[C@@H]1[C@@H](C)C[C@]2(Cc3ccc(cc3[C@]22N=C(N)N(CC3(F)CCOCC3)C2=O)C#N)C[C@H]1C,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,7.920818753952375 +Cn1c2c(Oc3ccc(NC(=O)Nc4cccc(SC(F)(F)F)c4)c4ccccc34)ccnc2[nH]c1=O,MAALSGGGGGGAEPGQALFNGDMEPEAGAGAGAAASSAADPAIPEEVWNIKQMIKLTQEHIEALLDKFGGEHNPPSIYLEAYEEYTSKLDALQQREQQLLESLGNGTDFSVSSSASMDTVTSSSSSSLSVLPSSLSVFQNPTDVARSNPKSPQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQDGEKKPIGWDTDISWLTGEELHVEVLENVPLTTHNFVRKTFFTLAFCDFCRKLLFQGFRCQTCGYKFHQRCSTEVPLMCVNYDQLDLLFVSKFFEHHPIPQEEASLAETALTSGSSPSAPASDSIGPQILTSPSPSKSIPIPQPFRPADEDHRNQFGQRDRSSSAPNVHINTIEPVNIDDLIRDQGFRGDGGSTTGLSATPPASLPGSLTNVKALQKSPGPQRERKSSSSSEDRNRMKTLGRRDSSDDWEIPDGQITVGQRIGSGSFGTVYKGKWHGDVAVKMLNVTAPTPQQLQAFKNEVGVLRKTRHVNILLFMGYSTKPQLAIVTQWCEGSSLYHHLHIIETKFEMIKLIDIARQTAQGMDYLHAKSIIHRDLKSNNIFLHEDLTVKIGDFGLATVKSRWSGSHQFEQLSGSILWMAPEVIRMQDKNPYSFQSDVYAFGIVLYELMTGQLPYSNINNRDQIIFMVGRGYLSPDLSKVRSNCPKAMKRLMAECLKKKRDERPLFPQILASIELLARSLPKIHRSASEPSLNRAGFQTEDFSLYACASPKTPIQAGGYGAFPVH,7.619788758288394 +Cc1ccccc1C(=O)NCC(=O)Nc1ccc(C)c(c1)S(=O)(=O)N1CCCCCC1,MVVLRSSLELHNHSAASATGSLDLSSDFLSLEHIGRRRLRSAGAAQKKPAATTAKAGDGSSVKEVETYHRTRALRSLRKDAQNSSDSSFEKNVEITEQLANGRHFTRQLARQQADKKKEEHREDKVIPVTRSLRARNIVQSTEHLHEDNGDVEVRRSCRIRSRYSGVNQSMLFDKLITNTAEAVLQKMDDMKKMRRQRMRELEDLGVFNETEESNLNMYTRGKQKDIQRTDEETTDNQEGSVESSEEGEDQEHEDDGEDEDDEDDDDDDDDDDDDDDEDDEDEEDGEEENQKRYYLRQRKATVYYQAPLEKPRHQRKPNIFYSGPASPARPRYRLSSAGPRSPYCKRMNRRRHAIHSSDSTSSSSSEDEQHFERRRKRSRNRAINRCLPLNFRKDELKGIYKDRMKIGASLADVDPMQLDSSVRFDSVGGLSNHIAALKEMVVFPLLYPEVFEKFKIQPPRGCLFYGPPGTGKTLVARALANECSQGDKRVAFFMRKGADCLSKWVGESERQLRLLFDQAYQMRPSIIFFDEIDGLAPVRSSRQDQIHSSIVSTLLALMDGLDSRGEIVVIGATNRLDSIDPALRRPGRFDREFLFSLPDKEARKEILKIHTRDWNPKPLDTFLEELAENCVGYCGADIKSICAEAALCALRRRYPQIYTTSEKLQLDLSSINISAKDFEVAMQKMIPASQRAVTSPGQALSTVVKPLLQNTVDKILEALQRVFPHAEFRTNKTLDSDISCPLLESDLAYSDDDVPSVYENGLSQKSSHKAKDNFNFLHLNRNACYQPMSFRPRILIVGEPGFGQGSHLAPAVIHALEKFTVYTLDIPVLFGVSTTSPEETCAQVIREAKRTAPSIVYVPHIHVWWEIVGPTLKATFTTLLQNIPSFAPVLLLATSDKPHSALPEEVQELFIRDYGEIFNVQLPDKEERTKFFEDLILKQAAKPPISKKKAVLQALEVLPVAPPPEPRSLTAEEVKRLEEQEEDTFRELRIFLRNVTHRLAIDKRFRVFTKPVDPDEVPDYVTVIKQPMDLSSVISKIDLHKYLTVKDYLRDIDLICSNALEYNPDRDPGDRLIRHRACALRDTAYAIIKEELDEDFEQLCEEIQESRKKRGCSSSKYAPSYYHVMPKQNSTLVGDKRSDPEQNEKLKTPSTPVACSTPAQLKRKIRKKSNWYLGTIKKRRKISQAKDDSQNAIDHKIESDTEETQDTSVDHNETGNTGESSVEENEKQQNASESKLELRNNSNTCNIENELEDSRKTTACTELRDKIACNGDASSSQIIHISDENEGKEMCVLRMTRARRSQVEQQQLITVEKALAILSQPTPSLVVDHERLKNLLKTVVKKSQNYNIFQLENLYAVISQCIYRHRKDHDKTSLIQKMEQEVENFSCSR,4.900008766455316 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+C[C@H](Cn1nncc1CCCCn1ccc(=O)[nH]c1=O)c1cccc(OCC2CC2)c1,MTPLCPRPALCYHFLTSLLRSAMQNARGARQRAEAAVLSGPGPPLGRAAQHGIPRPLSSAGRLSQGCRGASTVGAAGWKGELPKAGGSPAPGPETPAISPSKRARPAEVGGMQLRFARLSEHATAPTRGSARAAGYDLYSAYDYTIPPMEKAVVKTDIQIALPSGCYGRVAPRSGLAAKHFIDVGAGVIDEDYRGNVGVVLFNFGKEKFEVKKGDRIAQLICERIFYPEIEEVQALDDTERGSGGFGSTGKN,6.060480747381382 +Clc1ccc(cc1)S(=O)(=O)N1C(=O)NC(=O)C11CCCc2ccccc12,MASHLELNNGTKMPTLGLGTWKSPPGQVTEAVKVAIDMGYRHIDCAQVYQNEKEVGVALQEKLKEQVVKRQDLFIVSKLWCTFHDQSMVKGACQKTLSDLQLDYLDLYLIHWPTGFKPGPDYFPLDASGNVIPSDTDFVDTWTAMEQLVDEGLVKAIGVSNFNPLQIERILNKPGLKYKPAVNQIECHPYLTQEKLIEYCHCKGIVVTAYSPLGSPDRPWAKPEDPSLLEDPRIKEIAAKYNKTTAQVLIRFPIQRNLVVIPKSVTPARIAENFKVFDFELSNEDMATLLSYNRNWRVCALMSCAKHKDYPFHAEV,5.413412695328245 +Cn1nc(cc1C(=O)N[C@H](CCC(=O)NC1CCCC1)C(O)=O)-c1ccccc1,MADEEKLPPGWEKRMSRSSGRVYYFNHITNASQWERPSGNSSSGGKNGQGEPARVRCSHLLVKHSQSRRPSSWRQEKITRTKEEALELINGYIQKIKSGEEDFESLASQFSDCSSAKARGDLGAFSRGQMQKPFEDASFALRTGEMSGPVFTDSGIHIILRTE,4.0 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+Oc1ccc(-c2nc3ccc(O)cc3o2)c(O)c1,MDIKNSPSSLNSPSSYNCSQSILPLEHGSIYIPSSYVDSHHEYPAMTFYSPAVMNYSIPSNVTNLEGGPGRQTTSPNVLWPTPGHLSPLVVHRQLSHLYAEPQKSPWCEARSLEHTLPVNRETLKRKVSGNRCASPVTGPGSKRDAHFCAVCSDYASGYHYGVWSCEGCKAFFKRSIQGHNDYICPATNQCTIDKNRRKSCQACRLRKCYEVGMVKCGSRRERCGYRLVRRQRSADEQLHCAGKAKRSGGHAPRVRELLLDALSPEQLVLTLLEAEPPHVLISRPSAPFTEASMMMSLTKLADKELVHMISWAKKIPGFVELSLFDQVRLLESCWMEVLMMGLMWRSIDHPGKLIFAPDLVLDRDEGKCVEGILEIFDMLLATTSRFRELKLQHKEYLCVKAMILLNSSMYPLVTATQDADSSRKLAHLLNAVTDALVWVIAKSGISSQQQSMRLANLLMLLSHVRHASNKGMEHLLNMKCKNVVPVYDLLLEMLNAHVLRGCKSSITGSECSPAEDSKSKEGSQNPQSQ,8.522878745280337 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+OC[C@H]1O[C@H]([C@H](O)[C@@H](O)[C@@H]1O)c1ccc(Cl)c(Cc2ccc(nn2)-c2ccco2)c1,MEEHTEAGSAPEMGAQKALIDNPADILVIAAYFLLVIGVGLWSMCRTNRGTVGGYFLAGRSMVWWPVGASLFASNIGSGHFVGLAGTGAASGLAVAGFEWNALFVVLLLGWLFAPVYLTAGVITMPQYLRKRFGGRRIRLYLSVLSLFLYIFTKISVDMFSGAVFIQQALGWNIYASVIALLGITMIYTVTGGLAALMYTDTVQTFVILGGACILMGYAFHEVGGYSGLFDKYLGAATSLTVSEDPAVGNISSFCYRPRPDSYHLLRHPVTGDLPWPALLLGLTIVSGWYWCSDQVIVQRCLAGKSLTHIKAGCILCGYLKLTPMFLMVMPGMISRILYPDEVACVVPEVCRRVCGTEVGCSNIAYPRLVVKLMPNGLRGLMLAVMLAALMSSLASIFNSSSTLFTMDIYTRLRPRAGDRELLLVGRLWVVFIVVVSVAWLPVVQAAQGGQLFDYIQAVSSYLAPPVSAVFVLALFVPRVNEQGAFWGLIGGLLMGLARLIPEFSFGSGSCVQPSACPAFLCGVHYLYFAIVLFFCSGLLTLTVSLCTAPIPRKHLHRLVFSLRHSKEEREDLDADEQQGSSLPVQNGCPESAMEMNEPQAPAPSLFRQCLLWFCGMSRGGVGSPPPLTQEEAAAAARRLEDISEDPSWARVVNLNALLMMAVAVFLWGFYA,7.191789027075778 +CCCC[C@H](NC(=O)[C@@H](Cc1ccc(cc1)C(F)(F)F)NC(=O)[C@H](Cc1cnc[nH]1)NC(C)=O)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(N)=O,MAVQGSQRRLLGSLNSTPTAIPQLGLAANQTGARCLEVSISDGLFLSLGLVSLVENALVVATIAKNRNLHSPMYCFICCLALSDLLVSGSNVLETAVILLLEAGALVARAAVLQQLDNVIDVITCSSMLSSLCFLGAIAVDRYISIFYALRYHSIVTLPRARRAVAAIWVASVVFSTLFIAYYDHVAVLLCLVVFFLAMLVLMAVLYVHMLARACQHAQGIARLHKRQRPVHQGFGLKGAVTLTILLGIFFLCWGPFFLHLTLIVLCPEHPTCGCIFKNFNLFLALIICNAIIDPLIYAFHSQELRRTLKEVLTCSW,8.0 +COCCN1C[C@@H]([C@H](C1)C(=O)Nc1ccc(cc1F)-n1ccccc1=O)C(=O)Nc1ccc(Cl)cc1,MGRPLHLVLLSASLAGLLLLGESLFIRREQANNILARVTRANSFLEEMKKGHLERECMEETCSYEEAREVFEDSDKTNEFWNKYKDGDQCETSPCQNQGKCKDGLGEYTCTCLEGFEGKNCELFTRKLCSLDNGDCDQFCHEEQNSVVCSCARGYTLADNGKACIPTGPYPCGKQTLERRKRSVAQATSSSGEAPDSITWKPYDAADLDPTENPFDLLDFNQTQPERGDNNLTRIVGGQECKDGECPWQALLINEENEGFCGGTILSEFYILTAAHCLYQAKRFKVRVGDRNTEQEEGGEAVHEVEVVIKHNRFTKETYDFDIAVLRLKTPITFRMNVAPACLPERDWAESTLMTQKTGIVSGFGRTHEKGRQSTRLKMLEVPYVDRNSCKLSSSFIITQNMFCAGYDTKQEDACQGDSGGPHVTRFKDTYFVTGIVSWGEGCARKGKYGIYTKVTAFLKWIDRSMKTRGLPKAKSHAPEVITSSPLK,7.356547323513812 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+Brc1ccc(cc1)C(=O)CSc1nnc(CCNC(=O)c2cccs2)n1CC=C,MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL,8.26121944151563 +CCCCN(C)c1ncc2c(cn([C@H]3CC[C@H](O)CC3)c2n1)-c1ccc(CN2CCN(C)CC2)cc1,MGPAPLPLLLGLFLPALWRRAITEAREEAKPYPLFPGPFPGSLQTDHTPLLSLPHASGYQPALMFSPTQPGRPHTGNVAIPQVTSVESKPLPPLAFKHTVGHIILSEHKGVKFNCSISVPNIYQDTTISWWKDGKELLGAHHAITQFYPDDEVTAIIASFSITSVQRSDNGSYICKMKINNEEIVSDPIYIEVQGLPHFTKQPESMNVTRNTAFNLTCQAVGPPEPVNIFWVQNSSRVNEQPEKSPSVLTVPGLTEMAVFSCEAHNDKGLTVSKGVQINIKAIPSPPTEVSIRNSTAHSILISWVPGFDGYSPFRNCSIQVKEADPLSNGSVMIFNTSALPHLYQIKQLQALANYSIGVSCMNEIGWSAVSPWILASTTEGAPSVAPLNVTVFLNESSDNVDIRWMKPPTKQQDGELVGYRISHVWQSAGISKELLEEVGQNGSRARISVQVHNATCTVRIAAVTRGGVGPFSDPVKIFIPAHGWVDYAPSSTPAPGNADPVLIIFGCFCGFILIGLILYISLAIRKRVQETKFGNAFTEEDSELVVNYIAKKSFCRRAIELTLHSLGVSEELQNKLEDVVIDRNLLILGKILGEGEFGSVMEGNLKQEDGTSLKVAVKTMKLDNSSQREIEEFLSEAACMKDFSHPNVIRLLGVCIEMSSQGIPKPMVILPFMKYGDLHTYLLYSRLETGPKHIPLQTLLKFMVDIALGMEYLSNRNFLHRDLAARNCMLRDDMTVCVADFGLSKKIYSGDYYRQGRIAKMPVKWIAIESLADRVYTSKSDVWAFGVTMWEIATRGMTPYPGVQNHEMYDYLLHGHRLKQPEDCLDELYEIMYSCWRTDPLDRPTFSVLRLQLEKLLESLPDVRNQADVIYVNTQLLESSEGLAQGSTLAPLDLNIDPDSIIASCTPRAAISVVTAEVHDSKPHEGRYILNGGSEEWEDLTSAPSAAVTAEKNSVLPGERLVRNGVSWSHSSMLPLGSSLPDELLFADDSSEGSEVLM,6.400116927926312 +CCN(CC)CCOC(=O)C(O)(c1ccccc1)c1c(C)cccc1C,MTLHNNSTTSPLFPNISSSWIHSPSDAGLPPGTVTHFGSYNVSRAAGNFSSPDGTTDDPLGGHTVWQVVFIAFLTGILALVTIIGNILVIVSFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLAIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAETENFVHPTGSSRSCSSYELQQQSMKRSNRRKYGRCHFWFTTKSWKPSSEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSTILNSTKLPSSDNLQVPEEELGMVDLERKADKLQAQKSVDDGGSFPKSFSKLPIQLESAVDTAKTSDVNSSVGKSTATLPLSFKEATLAKRFALKTRSQITKRKRMSLVKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTFWNLGYWLCYINSTVNPVCYALCNKTFRTTFKMLLLCQCDKKKRRKQQYQQRQSVIFHKRAPEQAL,8.602059991327963 +CCc1ccc(cc1-c1cnc(NC(=O)c2cncc(F)c2C)cn1)-c1nnn(C)n1,MYRMQLLSCIALSLALVTNSAPTSSSTKKTQLQLEHLLLDLQMILNGINNYKNPKLTRMLTFKFYMPKKATELKHLQCLEEELKPLEEVLNLAQSKNFHLRPRDLISNINVIVLELKGSETTFMCEYADETATIVEFLNRWITFCQSIISTLT,7.585026652029182 +CC(C)c1[nH]nc2c(NCc3cccc(O)c3)ncnc12,MALLRRPTVSSDLENIDTGVNSKVKSHVTIRRTVLEEIGNRVTTRAAQVAKKAQNTKVPVQPTKTTNVNKQLKPTASVKPVQMEKLAPKGPSPTPEDVSMKEENLCQAFSDALLCKIEDIDNEDWENPQLCSDYVKDIYQYLRQLEVLQSINPHFLDGRDINGRMRAILVDWLVQVHSKFRLLQETLYMCVGIMDRFLQVQPVSRKKLQLVGITALLLASKYEEMFSPNIEDFVYITDNAYTSSQIREMETLILKELKFELGRPLPLHFLRRASKAGEVDVEQHTLAKYLMELTLIDYDMVHYHPSKVAAAASCLSQKVLGQGKWNLKQQYYTGYTENEVLEVMQHMAKNVVKVNENLTKFIAIKNKYASSKLLKISMIPQLNSKAVKDLASPLIGRS,8.769551078621726 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+CN(C)S(=O)(=O)c1c(Cl)ccc(Nc2c(NC(c3ccc(C)o3)C3(C)COC3)c(=O)c2=O)c1O,MVLEVSDHQVLNDAEVAALLENFSSSYDYGENESDSCCTSPPCPQDFSLNFDRAFLPALYSLLFLLGLLGNGAVAAVLLSRRTALSSTDTFLLHLAVADTLLVLTLPLWAVDAAVQWVFGSGLCKVAGALFNINFYAGALLLACISFDRYLNIVHATQLYRRGPPARVTLTCLAVWGLCLLFALPDFIFLSAHHDERLNATHCQYNFPQVGRTALRVLQLVAGFLLPLLVMAYCYAHILAVLLVSRGQRRLRAMRLVVVVVVAFALCWTPYHLVVLVDILMDLGALARNCGRESRVDVAKSVTSGLGYMHCCLNPLLYAFVGVKFRERMWMLLLRLGCPNQRGLQRQPSSSRRDSSWSETSEASYSGL,5.481486060122112 +COc1cc2ncnc(Oc3cccc(NC(=O)Nc4cc(on4)C(C)C)c3)c2cc1OC,MEHIQGAWKTISNGFGFKDAVFDGSSCISPTIVQQFGYQRRASDDGKLTDPSKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARLDWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPTMCVDWSNIRQLLLFPNSTIGDSGVPALPSLTMRRMRESVSRMPVSSQHRYSTPHAFTFNTSSPSSEGSLSQRQRSTSTPNVHMVSTTLPVDSRMIEDAIRSHSESASPSALSSSPNNLSPTGWSQPKTPVPAQRERAPVSGTQEKNKIRPRGQRDSSYYWEIEASEVMLSTRIGSGSFGTVYKGKWHGDVAVKILKVVDPTPEQFQAFRNEVAVLRKTRHVNILLFMGYMTKDNLAIVTQWCEGSSLYKHLHVQETKFQMFQLIDIARQTAQGMDYLHAKNIIHRDMKSNNIFLHEGLTVKIGDFGLATVKSRWSGSQQVEQPTGSVLWMAPEVIRMQDNNPFSFQSDVYSYGIVLYELMTGELPYSHINNRDQIIFMVGRGYASPDLSKLYKNCPKAMKRLVADCVKKVKEERPLFPQILSSIELLQHSLPKINRSASEPSLHRAAHTEDINACTLTTSPRLPVF,6.6020599913279625 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+C(CCc1nc2ccccc2s1)CN1Cc2ccccc2C1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,6.00436480540245 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+COc1ccc(cc1)-n1nc2CCCC(=O)c2c1-c1ccc(Cl)c(Cl)c1,MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGERLQIVNNTEGDWWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAENPRGTFLVRESETTKGAYCLSVSDFDNAKGLNVKHYKIRKLDSGGFYITSRTQFNSLQQLVAYYSKHADGLCHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWNGTTRVAIKTLKPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLLDFLKGETGKYLRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGLARLIEDNEYTARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMVNREVLDQVERGYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQYQPGENL,3.8239087409443187 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+Cc1ccc(c(C)c1)S(=O)(=O)N1CCN(CC(=O)NC2CCCc3ccccc23)CC1,MQGPWVLLLLGLRLQLSLGIIPVEEENPDFWNRQAAEALGAAKKLQPAQTAAKNLIIFLGDGMGVSTVTAARILKGQKKDKLGPETFLAMDRFPYVALSKTYSVDKHVPDSGATATAYLCGVKGNFQTIGLSAAARFNQCNTTRGNEVISVMNRAKKAGKSVGVVTTTRVQHASPAGAYAHTVNRNWYSDADVPASARQEGCQDIATQLISNMDIDVILGGGRKYMFPMGTPDPEYPDDYSQGGTRLDGKNLVQEWLAKHQGARYVWNRTELLQASLDPSVTHLMGLFEPGDMKYEIHRDSTLDPSLMEMTEAALLLLSRNPRGFFLFVEGGRIDHGHHESRAYRALTETIMFDDAIERAGQLTSEEDTLSLVTADHSHVFSFGGYPLRGSSIFGLAPGKARDRKAYTVLLYGNGPGYVLKDGARPDVTESESGSPEYRQQSAVPLDGETHAGEDVAVFARGPQAHLVHGVQEQTFIAHVMAFAACLEPYTACDLAPRAGTTDAAHPGPSVVPALLPLLAGTLLLLGTATAP,3.0004345117740177 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+FC(F)(F)c1ccc(CN2CCC(CC2)Oc2ccc(cc2Cl)S(=O)(=O)Nc2nccs2)cc1,MEQTVLVPPGPDSFNFFTRESLAAIERRIAEEKAKNPKPDKKDDDENGPKPNSDLEAGKNLPFIYGDIPPEMVSEPLEDLDPYYINKKTFIVLNKGKAIFRFSATSALYILTPFNPLRKIAIKILVHSLFSMLIMCTILTNCVFMTMSNPPDWTKNVEYTFTGIYTFESLIKIIARGFCLEDFTFLRDPWNWLDFTVITFAYVTEFVDLGNVSALRTFRVLRALKTISVIPGLKTIVGALIQSVKKLSDVMILTVFCLSVFALIGLQLFMGNLRNKCIQWPPTNASLEEHSIEKNITVNYNGTLINETVFEFDWKSYIQDSRYHYFLEGFLDALLCGNSSDAGQCPEGYMCVKAGRNPNYGYTSFDTFSWAFLSLFRLMTQDFWENLYQLTLRAAGKTYMIFFVLVIFLGSFYLINLILAVVAMAYEEQNQATLEEAEQKEAEFQQMIEQLKKQQEAAQQAATATASEHSREPSAAGRLSDSSSEASKLSSKSAKERRNRRKKRKQKEQSGGEEKDEDEFQKSESEDSIRRKGFRFSIEGNRLTYEKRYSSPHQSLLSIRGSLFSPRRNSRTSLFSFRGRAKDVGSENDFADDEHSTFEDNESRRDSLFVPRRHGERRNSNLSQTSRSSRMLAVFPANGKMHSTVDCNGVVSLVGGPSVPTSPVGQLLPEVIIDKPATDDNGTTTETEMRKRRSSSFHVSMDFLEDPSQRQRAMSIASILTNTVEELEESRQKCPPCWYKFSNIFLIWDCSPYWLKVKHVVNLVVMDPFVDLAITICIVLNTLFMAMEHYPMTDHFNNVLTVGNLVFTGIFTAEMFLKIIAMDPYYYFQEGWNIFDGFIVTLSLVELGLANVEGLSVLRSFRLLRVFKLAKSWPTLNMLIKIIGNSVGALGNLTLVLAIIVFIFAVVGMQLFGKSYKDCVCKIASDCQLPRWHMNDFFHSFLIVFRVLCGEWIETMWDCMEVAGQAMCLTVFMMVMVIGNLVVLNLFLALLLSSFSADNLAATDDDNEMNNLQIAVDRMHKGVAYVKRKIYEFIQQSFIRKQKILDEIKPLDDLNNKKDSCMSNHTAEIGKDLDYLKDVNGTTSGIGTGSSVEKYIIDESDYMSFINNPSLTVTVPIAVGESDFENLNTEDFSSESDLEESKEKLNESSSSSEGSTVDIGAPVEEQPVVEPEETLEPEACFTEGCVQRFKCCQINVEEGRGKQWWNLRRTCFRIVEHNWFETFIVFMILLSSGALAFEDIYIDQRKTIKTMLEYADKVFTYIFILEMLLKWVAYGYQTYFTNAWCWLDFLIVDVSLVSLTANALGYSELGAIKSLRTLRALRPLRALSRFEGMRVVVNALLGAIPSIMNVLLVCLIFWLIFSIMGVNLFAGKFYHCINTTTGDRFDIEDVNNHTDCLKLIERNETARWKNVKVNFDNVGFGYLSLLQVATFKGWMDIMYAAVDSRNVELQPKYEESLYMYLYFVIFIIFGSFFTLNLFIGVIIDNFNQQKKKFGGQDIFMTEEQKKYYNAMKKLGSKKPQKPIPRPGNKFQGMVFDFVTRQVFDISIMILICLNMVTMMVETDDQSEYVTTILSRINLVFIVLFTGECVLKLISLRHYYFTIGWNIFDFVVVILSIVGMFLAELIEKYFVSPTLFRVIRLARIGRILRLIKGAKGIRTLLFALMMSLPALFNIGLLLFLVMFIYAIFGMSNFAYVKREVGIDDMFNFETFGNSMICLFQITTSAGWDGLLAPILNSKPPDCDPNKVNPGSSVKGDCGNPSVGIFFFVSYIIISFLVVVNMYIAVILENFSVATEESAEPLSEDDFEMFYEVWEKFDPDATQFMEFEKLSQFAAALEPPLNLPQPNKLQLIAMDLPMVSGDRIHCLDILFAFTKRVLGESGEMDALRIQMEERFMASNPSKVSYQPITTTLKRKQEEVSAVIIQRAYRRHLLKRTVKQASFTYNKNKIKGGANLLIKEDMIIDRINENSITEKTDLTMSTAACPPSYDRVTKPIVEKHEQEGKDEKAKGK,4.522878745280337 +COc1ccc(C(=O)\C=C\c2cccc(CC=C(C)C)c2)c(O)c1,MVLEMLNPIHYNITSIVPEAMPAATMPVLLLTGLFLLVWNYEGTSSIPGPGYCMGIGPLISHGRFLWMGIGSACNYYNRVYGEFMRVWISGEETLIISKSSSMFHIMKHNHYSSRFGSKLGLQCIGMHEKGIIFNNNPELWKTTRPFFMKALSGPGLVRMVTVCAESLKTHLDRLEEVTNESGYVDVLTLLRRVMLDTSNTLFLRIPLDESAIVVKIQGYFDAWQALLIKPDIFFKISWLYKKYEKSVKDLKDAIEVLIAEKRRRISTEEKLEECMDFATELILAEKRGDLTRENVNQCILEMLIAAPDTMSVSLFFMLFLIAKHPNVEEAIIKEIQTVIGERDIKIDDIQKLKVMENFIYESMRYQPVVDLVMRKALEDDVIDGYPVKKGTNIILNIGRMHRLEFFPKPNEFTLENFAKNVPYRYFQPFGFGPRGCAGKYIAMVMMKAILVTLLRRFHVKTLQGQCVESIQKIHDLSLHPDETKNMLEMIFTPRNSDRCLEH,3.5083582065224137 +CC(C)[C@H](NC(=O)[C@@H]1CSSC(C)(C)[C@@H](NC(=O)[C@@H](N)CCCCN)C(=O)N[C@@H](Cc2ccccc2)C(=O)N[C@@H](Cc2c[nH]c3ccccc23)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](Cc2ccc(O)cc2)C(=O)N1)C(O)=O,MALTPESPSSFPGLAATGSSVPEPPGGPNATLNSSWASPTEPSSLEDLVATGTIGTLLSAMGVVGVVGNAYTLVVTCRSLRAVASMYVYVVNLALADLLYLLSIPFIVATYVTKEWHFGDVGCRVLFGLDFLTMHASIFTLTVMSSERYAAVLRPLDTVQRPKGYRKLLALGTWLLALLLTLPVMLAMRLVRRGPKSLCLPAWGPRAHRAYLTLLFATSIAGPGLLIGLLYARLARAYRRSQRASFKRARRPGARALRLVLGIVLLFWACFLPFWLWQLLAQYHQAPLAPRTARIVNYLTTCLTYGNSCANPFLYTLLTRNYRDHLRGRVRGPGSGGGRGPVPSLQPRARFQRCSGRSLSSCSPQPTDSLVLAPAAPARPAPEGPRAPA,8.0301183562535 +CC(C)[C@@H]1CN(CCN1C(=O)OC(C)(C)C)c1ccc(F)c(c1)S(C)(=O)=O,MSLWLGAPVPDIPPDSAVELWKPGAQDASSQAQGGSSCILREEARMPHSAGGTAGVGLEAAEPTALLTRAEPPSEPTEIRPQKRKKGPAPKMLGNELCSVCGDKASGFHYNVLSCEGCKGFFRRSVIKGAHYICHSGGHCPMDTYMRRKCQECRLRKCRQAGMREECVLSEEQIRLKKLKRQEEEQAHATSLPPRASSPPQILPQLSPEQLGMIEKLVAAQQQCNRRSFSDRLRVTPWPMAPDPHSREARQQRFAHFTELAIVSVQEIVDFAKQLPGFLQLSREDQIALLKTSAIEVMLLETSRRYNPGSESITFLKDFSYNREDFAKAGLQVEFINPIFEFSRAMNELQLNDAEFALLIAISIFSADRPNVQDQLQVERLQHTYVEALHAYVSIHHPHDRLMFPRMLMKLVSLRTLSSVHSEQVFALRLQDKKLPPLLSEIWDVHE,6.045275209020937 +Cn1c(cccc1=O)C(O)c1ccc(F)c(c1)-c1ncnc2cc(ccc12)N1CCOCC1,MAGSGAGVRCSLLRLQETLSAADRCGAALAGHQLIRGLGQECVLSSSPAVLALQTSLVFSRDFGLLVFVRKSLNSIEFRECREEILKFLCIFLEKMGQKIAPYSVEIKNTCTSVYTKDRAAKCKIPALDLLIKLLQTFRSSRLMDEFKIGELFSKFYGELALKKKIPDTVLEKVYELLGLLGEVHPSEMINNAENLFRAFLGELKTQMTSAVREPKLPVLAGCLKGLSSLLCNFTKSMEEDPQTSREIFNFVLKAIRPQIDLKRYAVPSAGLRLFALHASQFSTCLLDNYVSLFEVLLKWCAHTNVELKKAALSALESFLKQVSNMVAKNAEMHKNKLQYFMEQFYGIIRNVDSNNKELSIAIRGYGLFAGPCKVINAKDVDFMYVELIQRCKQMFLTQTDTGDDRVYQMPSFLQSVASVLLYLDTVPEVYTPVLEHLVVMQIDSFPQYSPKMQLVCCRAIVKVFLALAAKGPVLRNCISTVVHQGLIRICSKPVVLPKGPESESEDHRASGEVRTGKWKVPTYKDYVDLFRHLLSSDQMMDSILADEAFFSVNSSSESLNHLLYDEFVKSVLKIVEKLDLTLEIQTVGEQENGDEAPGVWMIPTSDPAANLHPAKPKDFSAFINLVEFCREILPEKQAEFFEPWVYSFSYELILQSTRLPLISGFYKLLSITVRNAKKIKYFEGVSPKSLKHSPEDPEKYSCFALFVKFGKEVAVKMKQYKDELLASCLTFLLSLPHNIIELDVRAYVPALQMAFKLGLSYTPLAEVGLNALEEWSIYIDRHVMQPYYKDILPCLDGYLKTSALSDETKNNWEVSALSRAAQKGFNKVVLKHLKKTKNLSSNEAISLEEIRIRVVQMLGSLGGQINKNLLTVTSSDEMMKSYVAWDREKRLSFAVPFREMKPVIFLDVFLPRVTELALTASDRQTKVAACELLHSMVMFMLGKATQMPEGGQGAPPMYQLYKRTFPVLLRLACDVDQVTRQLYEPLVMQLIHWFTNNKKFESQDTVALLEAILDGIVDPVDSTLRDFCGRCIREFLKWSIKQITPQQQEKSPVNTKSLFKRLYSLALHPNAFKRLGASLAFNNIYREFREEESLVEQFVFEALVIYMESLALAHADEKSLGTIQQCCDAIDHLCRIIEKKHVSLNKAKKRRLPRGFPPSASLCLLDLVKWLLAHCGRPQTECRHKSIELFYKFVPLLPGNRSPNLWLKDVLKEEGVSFLINTFEGGGCGQPSGILAQPTLLYLRGPFSLQATLCWLDLLLAALECYNTFIGERTVGALQVLGTEAQSSLLKAVAFFLESIAMHDIIAAEKCFGTGAAGNRTSPQEGERYNYSKCTVVVRIMEFTTTLLNTSPEGWKLLKKDLCNTHLMRVLVQTLCEPASIGFNIGDVQVMAHLPDVCVNLMKALKMSPYKDILETHLREKITAQSIEELCAVNLYGPDAQVDRSRLAAVVSACKQLHRAGLLHNILPSQSTDLHHSVGTELLSLVYKGIAPGDERQCLPSLDLSCKQLASGLLELAFAFGGLCERLVSLLLNPAVLSTASLGSSQGSVIHFSHGEYFYSLFSETINTELLKNLDLAVLELMQSSVDNTKMVSAVLNGMLDQSFRERANQKHQGLKLATTILQHWKKCDSWWAKDSPLETKMAVLALLAKILQIDSSVSFNTSHGSFPEVFTTYISLLADTKLDLHLKGQAVTLLPFFTSLTGGSLEELRRVLEQLIVAHFPMQSREFPPGTPRFNNYVDCMKKFLDALELSQSPMLLELMTEVLCREQQHVMEELFQSSFRRIARRGSCVTQVGLLESVYEMFRKDDPRLSFTRQSFVDRSLLTLLWHCSLDALREFFSTIVVDAIDVLKSRFTKLNESTFDTQITKKMGYYKILDVMYSRLPKDDVHAKESKINQVFHGSCITEGNELTKTLIKLCYDAFTENMAGENQLLERRRLYHCAAYNCAISVICCVFNELKFYQGFLFSEKPEKNLLIFENLIDLKRRYNFPVEVEVPMERKKKYIEIRKEAREAANGDSDGPSYMSSLSYLADSTLSEEMSQFDFSTGVQSYSYSSQDPRPATGRFRRREQRDPTVHDDVLELEMDELNRHECMAPLTALVKHMHRSLGPPQGEEDSVPRDLPSWMKFLHGKLGNPIVPLNIRLFLAKLVINTEEVFRPYAKHWLSPLLQLAASENNGGEGIHYMVVEIVATILSWTGLATPTGVPKDEVLANRLLNFLMKHVFHPKRAVFRHNLEIIKTLVECWKDCLSIPYRLIFEKFSGKDPNSKDNSVGIQLLGIVMANDLPPYDPQCGIQSSEYFQALVNNMSFVRYKEVYAAAAEVLGLILRYVMERKNILEESLCELVAKQLKQHQNTMEDKFIVCLNKVTKSFPPLADRFMNAVFFLLPKFHGVLKTLCLEVVLCRVEGMTELYFQLKSKDFVQVMRHRDDERQKVCLDIIYKMMPKLKPVELRELLNPVVEFVSHPSTTCREQMYNILMWIHDNYRDPESETDNDSQEIFKLAKDVLIQGLIDENPGLQLIIRNFWSHETRLPSNTLDRLLALNSLYSPKIEVHFLSLATNFLLEMTSMSPDYPNPMFEHPLSECEFQEYTIDSDWRFRSTVLTPMFVETQASQGTLQTRTQEGSLSARWPVAGQIRATQQQHDFTLTQTADGRSSFDWLTGSSTDPLVDHTSPSSDSLLFAHKRSERLQRAPLKSVGPDFGKKRLGLPGDEVDNKVKGAAGRTDLLRLRRRFMRDQEKLSLMYARKGVAEQKREKEIKSELKMKQDAQVVLYRSYRHGDLPDIQIKHSSLITPLQAVAQRDPIIAKQLFSSLFSGILKEMDKFKTLSEKNNITQKLLQDFNRFLNTTFSFFPPFVSCIQDISCQHAALLSLDPAAVSAGCLASLQQPVGIRLLEEALLRLLPAELPAKRVRGKARLPPDVLRWVELAKLYRSIGEYDVLRGIFTSEIGTKQITQSALLAEARSDYSEAAKQYDEALNKQDWVDGEPTEAEKDFWELASLDCYNHLAEWKSLEYCSTASIDSENPPDLNKIWSEPFYQETYLPYMIRSKLKLLLQGEADQSLLTFIDKAMHGELQKAILELHYSQELSLLYLLQDDVDRAKYYIQNGIQSFMQNYSSIDVLLHQSRLTKLQSVQALTEIQEFISFISKQGNLSSQVPLKRLLNTWTNRYPDAKMDPMNIWDDIITNRCFFLSKIEEKLTPLPEDNSMNVDQDGDPSDRMEVQEQEEDISSLIRSCKFSMKMKMIDSARKQNNFSLAMKLLKELHKESKTRDDWLVSWVQSYCRLSHCRSRSQGCSEQVLTVLKTVSLLDENNVSSYLSKNILAFRDQNILLGTTYRIIANALSSEPACLAEIEEDKARRILELSGSSSEDSEKVIAGLYQRAFQHLSEAVQAAEEEAQPPSWSCGPAAGVIDAYMTLADFCDQQLRKEEENASVIDSAELQAYPALVVEKMLKALKLNSNEARLKFPRLLQIIERYPEETLSLMTKEISSVPCWQFISWISHMVALLDKDQAVAVQHSVEEITDNYPQAIVYPFIISSESYSFKDTSTGHKNKEFVARIKSKLDQGGVIQDFINALDQLSNPELLFKDWSNDVRAELAKTPVNKKNIEKMYERMYAALGDPKAPGLGAFRRKFIQTFGKEFDKHFGKGGSKLLRMKLSDFNDITNMLLLKMNKDSKPPGNLKECSPWMSDFKVEFLRNELEIPGQYDGRGKPLPEYHVRIAGFDERVTVMASLRRPKRIIIRGHDEREHPFLVKGGEDLRQDQRVEQLFQVMNGILAQDSACSQRALQLRTYSVVPMTSRLGLIEWLENTVTLKDLLLNTMSQEEKAAYLSDPRAPPCEYKDWLTKMSGKHDVGAYMLMYKGANRTETVTSFRKRESKVPADLLKRAFVRMSTSPEAFLALRSHFASSHALICISHWILGIGDRHLNNFMVAMETGGVIGIDFGHAFGSATQFLPVPELMPFRLTRQFINLMLPMKETGLMYSIMVHALRAFRSDPGLLTNTMDVFVKEPSFDWKNFEQKMLKKGGSWIQEINVAEKNWYPRQKICYAKRKLAGANPAVITCDELLLGHEKAPAFRDYVAVARGSKDHNIRAQEPESGLSEETQVKCLMDQATDPNILGRTWEGWEPWM,8.522878745280337 +NC(=O)c1cccc(c1)-c1cccc(OC(=O)NC2CCCCC2)c1,MVLSEVWTTLSGVSGVCLACSLLSAAVVLRWTGRQKARGAATRARQKQRASLETMDKAVQRFRLQNPDLDSEALLTLPLLQLVQKLQSGELSPEAVFFTYLGKAWEVNKGTNCVTSYLTDCETQLSQAPRQGLLYGVPVSLKECFSYKGHDSTLGLSLNEGMPSESDCVVVQVLKLQGAVPFVHTNVPQSMLSFDCSNPLFGQTMNPWKSSKSPGGSSGGEGALIGSGGSPLGLGTDIGGSIRFPSAFCGICGLKPTGNRLSKSGLKGCVYGQTAVQLSLGPMARDVESLALCLKALLCEHLFTLDPTVPPLPFREEVYRSSRPLRVGYYETDNYTMPSPAMRRALIETKQRLEAAGHTLIPFLPNNIPYALEVLSAGGLFSDGGRSFLQNFKGDFVDPCLGDLILILRLPSWFKRLLSLLLKPLFPRLAAFLNSMRPRSAEKLWKLQHEIEMYRQSVIAQWKAMNLDVLLTPMLGPALDLNTPGRATGAISYTVLYNCLDFPAGVVPVTTVTAEDDAQMELYKGYFGDIWDIILKKAMKNSVGLPVAVQCVALPWQEELCLRFMREVEQLMTPQKQPS,7.318758762624412 +CCCCCCCCCCCCCCC(=O)N1CCC(CC1)C1CCNCC1,MGCTLSAEERAALERSKAIEKNLKEDGISAAKDVKLLLLGAGESGKSTIVKQMKIIHEDGFSGEDVKQYKPVVYSNTIQSLAAIVRAMDTLGIEYGDKERKADAKMVCDVVSRMEDTEPFSAELLSAMMRLWGDSGIQECFNRSREYQLNDSAKYYLDSLDRIGAADYQPTEQDILRTRVKTTGIVETHFTFKNLHFRLFDVGGQRSERKKWIHCFEDVTAIIFCVALSGYDQVLHEDETTNRMHESLMLFDSICNNKFFIDTSIILFLNKKDLFGEKIKKSPLTICFPEYTGPNTYEDAAAYIQAQFESKNRSPNKEIYCHMTCATDTNNIQVVFDAVTDIIIANNLRGCGLY,5.251811972993799 +CSc1cc(ccc1C#N)-c1ccc(C[C@H](NC(=O)[C@@H]2CCCCN2)C#N)cc1,MKRLVCVLLVCSSAVAQLHKDPTLDHHWHLWKKTYGKQYKEKNEEAVRRLIWEKNLKFVMLHNLEHSMGMHSYDLGMNHLGDMTSEEVMSLMSSLRVPSQWQRNITYKSNPNRILPDSVDWREKGCVTEVKYQGSCGACWAFSAVGALEAQLKLKTGKLVSLSAQNLVDCSTEKYGNKGCNGGFMTTAFQYIIDNKGIDSDASYPYKAMDQKCQYDSKYRAATCSKYTELPYGREDVLKEAVANKGPVSVGVDARHPSFFLYRSGVYYEPSCTQNVNHGVLVVGYGDLNGKEYWLVKNSWGHNFGEEGYIRMARNKGNHCGIASFPSYPEI,5.0 +OC(CN1CCc2ccccc2C1)Cn1cnc(cc1=O)C(=O)NC1CCOCC1,MAAMAVGGAGGSRVSSGRDLNCVPEIADTLGAVAKQGFDFLCMPVFHPRFKREFIQEPAKNRPGPQTRSDLLLSGRDWNTLIVGKLSPWIRPDSKVEKIRRNSEAAMLQELNFGAYLGLPAFLLPLNQEDNTNLARVLTNHIHTGHHSSMFWMRVPLVAPEDLRDDIIENAPTTHTEEYSGEEKTWMWWHNFRTLCDYSKRIAVALEIGADLPSNHVIDRWLGEPIKAAILPTSIFLTNKKGFPVLSKMHQRLIFRLLKLEVQFIITGTNHHSEKEFCSYLQYLEYLSQNRPPPNAYELFAKGYEDYLQSPLQPLMDNLESQTYEVFEKDPIKYSQYQQAIYKCLLDRVPEEEKDTNVQVLMVLGAGRGPLVNASLRAAKQADRRIKLYAVEKNPNAVVTLENWQFEEWGSQVTVVSSDMREWVAPEKADIIVSELLGSFADNELSPECLDGAQHFLKDDGVSIPGEYTSFLAPISSSKLYNEVRACREKDRDPEAQFEMPYVVRLHNFHQLSAPQPCFTFSHPNRDPMIDNNRYCTLEFPVEVNTVLHGFAGYFETVLYQDITLSIRPETHSPGMFSWFPILFPIKQPITVREGQTICVRFWRCSNSKKVWYEWAVTAPVCSAIHNPTGRSYTIGL,5.259637310505756 +Cc1cnccc1-c1nnc2c(C)nc3ccc(Cl)cc3n12,MRIEERKSQHLTGLTDEKVKAYLSLHPQVLDEFVSESVSAETVEKWLKRKNNKSEDESAPKEVSRYQDTNMQGVVYELNSYIEQRLDTGGDNQLLLYELSSIIKIATKADGFALYFLGECNNSLCIFTPPGIKEGKPRLIPAGPITQGTTVSAYVAKSRKTLLVEDILGDERFPRGTGLESGTRIQSVLCLPIVTAIGDLIGILELYRHWGKEAFCLSHQEVATANLAWASVAIHQVQVCRGLAKQTELNDFLLDVSKTYFDNIVAIDSLLEHIMIYAKNLVNADRCALFQVDHKNKELYSDLFDIGEEKEGKPVFKKTKEIRFSIEKGIAGQVARTGEVLNIPDAYADPRFNREVDLYTGYTTRNILCMPIVSRGSVIGVVQMVNKISGSAFSKTDENNFKMFAVFCALALHCANMYHRIRHSECIYRVTMEKLSYHSICTSEEWQGLMQFTLPVRLCKEIELFHFDIGPFENMWPGIFVYMVHRSCGTSCFELEKLCRFIMSVKKNYRRVPYHNWKHAVTVAHCMYAILQNNHTLFTDLERKGLLIACLCHDLDHRGFSNSYLQKFDHPLAALYSTSTMEQHHFSQTVSILQLEGHNIFSTLSSSEYEQVLEIIRKAIIATDLALYFGNRKQLEEMYQTGSLNLNNQSHRDRVIGLMMTACDLCSVTKLWPVTKLTANDIYAEFWAEGDEMKKLGIQPIPMMDRDKKDEVPQGQLGFYNAVAIPCYTTLTQILPPTEPLLKACRDNLSQWEKVIRGEETATWISSPSVAQKAAASED,6.133122185662501 +CCCCCn1cc(C(=O)NC2CCCCC2)c(=O)c2cc(Br)ccc12,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,6.045757490560675 +COc1cc2CCN(CCc3ccc(NC(=O)c4cc(OC)c(OC)cc4NC(=O)c4cnc5ccccc5c4)cc3)Cc2cc1OC,MDLEGDRNGGAKKKNFFKLNNKSEKDKKEKKPTVSVFSMFRYSNWLDKLYMVVGTLAAIIHGAGLPLMMLVFGEMTDIFANAGNLEDLMSNITNRSDINDTGFFMNLEEDMTRYAYYYSGIGAGVLVAAYIQVSFWCLAAGRQIHKIRKQFFHAIMRQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQSMATFFTGFIVGFTRGWKLTLVILAISPVLGLSAAVWAKILSSFTDKELLAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNKNLEEAKRIGIKKAITANISIGAAFLLIYASYALAFWYGTTLVLSGEYSIGQVLTVFFSVLIGAFSVGQASPSIEAFANARGAAYEIFKIIDNKPSIDSYSKSGHKPDNIKGNLEFRNVHFSYPSRKEVKILKGLNLKVQSGQTVALVGNSGCGKSTTVQLMQRLYDPTEGMVSVDGQDIRTINVRFLREIIGVVSQEPVLFATTIAENIRYGRENVTMDEIEKAVKEANAYDFIMKLPHKFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQVALDKARKGRTTIVIAHRLSTVRNADVIAGFDDGVIVEKGNHDELMKEKGIYFKLVTMQTAGNEVELENAADESKSEIDALEMSSNDSRSSLIRKRSTRRSVRGSQAQDRKLSTKEALDESIPPVSFWRIMKLNLTEWPYFVVGVFCAIINGGLQPAFAIIFSKIIGVFTRIDDPETKRQNSNLFSLLFLALGIISFITFFLQGFTFGKAGEILTKRLRYMVFRSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGAIGSRLAVITQNIANLGTGIIISFIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENFRTVVSLTQEQKFEHMYAQSLQVPYRNSLRKAHIFGITFSFTQAMMYFSYAGCFRFGAYLVAHKLMSFEDVLLVFSAVVFGAMAVGQVSSFAPDYAKAKISAAHIIMIIEKTPLIDSYSTEGLMPNTLEGNVTFGEVVFNYPTRPDIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPLAGKVLLDGKEIKRLNVQWLRAHLGIVSQEPILFDCSIAENIAYGDNSRVVSQEEIVRAAKEANIHAFIESLPNKYSTKVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVFQNGRVKEHGTHQQLLAQKGIYFSMVSVQAGTKRQ,9.18045606445813 +Cc1ccc(cc1)-n1nc(cc1NC(=O)Nc1ccc(Oc2ccnc3[nH]c(=O)n(C)c23)c2ccccc12)C(C)(C)C,MSQERPTFYRQELNKTIWEVPERYQNLSPVGSGAYGSVCAAFDTKTGLRVAVKKLSRPFQSIIHAKRTYRELRLLKHMKHENVIGLLDVFTPARSLEEFNDVYLVTHLMGADLNNIVKCQKLTDDHVQFLIYQILRGLKYIHSADIIHRDLKPSNLAVNEDCELKILDFGLARHTDDEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLTGRTLFPGTDHIDQLKLILRLVGTPGAELLKKISSESARNYIQSLTQMPKMNFANVFIGANPLAVDLLEKMLVLDSDKRITAAQALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES,9.0 +Clc1ccc(CNc2nc3nc[nH]c3c(=O)[nH]2)cc1Cl,MSEPRFVHLRVHSDYSMIDGLAKTAPLVKKAAALGMPALAITDFTNLCGLVKFYGAGHGAGIKPIVGADFNVQCDLLGDELTHLTVLAANNTGYQNLTLLISKAYQRGYGAAGPIIDRDWLIELNEGLILLSGGRMGDVGRSLLRGNSALVDECVAFYEEHFPDRYFLELIRTGRPDEESYLHAAVELAEARGLPVVATNDVRFIDSSDFDAHEIRVAIHDGFTLDDPKRPRNYSPQQYMRSEEEMCELFADIPEALANTVEIAKRCNVTVRLGEYFLPQFPTGDMSTEDYLVKRAKEGLEERLAFLFPDEEERLKRRPEYDERLETELQVINQMGFPGYFLIVMEFIQWSKDNGVPVGPGRGSGAGSLVAYALKITDLDPLEFDLLFERFLNPERVSMPDFDVDFCMEKRDQVIEHVADMYGRDAVSQIITFGTMAAKAVIRDVGRVLGHPYGFVDRISKLIPPDPGMTLAKAFEAEPQLPEIYEADEEVKALIDMARKLEGVTRNAGKHAGGVVIAPTKITDFAPLYCDEEGKHPVTQFDKSDVEYAGLVKFDFLGLRTLTIINWALEMINKRRAKNGEPPLDIAAIPLDDKKSFDMLQRSETTAVFQLESRGMKDLIKRLQPDCFEDMIALVALFRPGPLQSGMVDNFIDRKHGREEISYPDVQWQHESLKPVLEPTYGIILYQEQVMQIAQVLSGYTLGGADMLRRAMGKKKPEEMAKQRSVFAEGAEKNGINAELAMKIFDLVEKFAGYGFNKSHSAAYALVSYQTLWLKAHYPAEFMAAVMTADMDNTEKVVGLVDECWRMGLKILPPDINSGLYHFHVNDDGEIVYGIGAIKGVGEGPIEAIIEARNKGGYFRELFDLCARTDTKKLNRRVLEKLIMSGAFDRLGPHRAALMNSLGDALKAADQHAKAEAIGQADMFGVLAEEPEQIEQSYASCQPWPEQVVLDGERETLGLYLTGHPINQYLKEIERYVGGVRLKDMHPTERGKVITAAGLVVAARVMVTKRGNRIGICTLDDRSGRLEVMLFTDALDKYQQLLEKDRILIVSGQVSFDDFSGGLKMTAREVMDIDEAREKYARGLAISLTDRQIDDQLLNRLRQSLEPHRSGTIPVHLYYQRADARARLRFGATWRVSPSDRLLNDLRGLIGSEQVELEFD,4.022276394711152 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+CC(C)c1c(F)cccc1-c1ncc2[nH]c(=O)n(Cc3ccc(cc3)-n3ccnn3)c2n1,MPGVIPSESNGLSRGSPSKKNRLSLKFFQKKETKRALDFTDSQENEEKASEYRASEIDQVVPAAQSSPINCEKRENLLPFVGLNNLGNTCYLNSILQVLYFCPGFKSGVKHLFNIISRKKEALKDEANQKDKGNCKEDSLASYELICSLQSLIISVEQLQASFLLNPEKYTDELATQPRRLLNTLRELNPMYEGYLQHDAQEVLQCILGNIQETCQLLKKEEVKNVAELPTKVEEIPHPKEEMNGINSIEMDSMRHSEDFKEKLPKGNGKRKSDTEFGNMKKKVKLSKEHQSLEENQRQTRSKRKATSDTLESPPKIIPKYISENESPRPSQKKSRVKINWLKSATKQPSILSKFCSLGKITTNQGVKGQSKENECDPEEDLGKCESDNTTNGCGLESPGNTVTPVNVNEVKPINKGEEQIGFELVEKLFQGQLVLRTRCLECESLTERREDFQDISVPVQEDELSKVEESSEISPEPKTEMKTLRWAISQFASVERIVGEDKYFCENCHHYTEAERSLLFDKMPEVITIHLKCFAASGLEFDCYGGGLSKINTPLLTPLKLSLEEWSTKPTNDSYGLFAVVMHSGITISSGHYTASVKVTDLNSLELDKGNFVVDQMCEIGKPEPLNEEEARGVVENYNDEEVSIRVGGNTQPSKVLNKKNVEAIGLLGGQKSKADYELYNKASNPDKVASTAFAENRNSETSDTTGTHESDRNKESSDQTGINISGFENKISYVVQSLKEYEGKWLLFDDSEVKVTEEKDFLNSLSPSTSPTSTPYLLFYKKL,6.903089986991944 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+OC(CCCN1CCN(CC1)c1ncccn1)c1ccc(F)cc1,MPWAVGRRWAWITLFLTIVAVLIQAVWLWLGTQSFVFQREEIAQLARQYAGLDHELAFSRLIVELRRLHPGHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSHGHSGRYWAEISDTIISGTFHQWREGTTKSEVYYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLAFALSDTIFSTQDFLTLFYTLRAYARGLRLELTTYLFGQDP,6.886056647693163 +COc1ccc2c(NCCNc3ccnc4cc(OC)ccc34)ccnc2c1,MDVLSPGQGNNTTSPPAPFETGGNTTGISDVTVSYQVITSLLLGTLIFCAVLGNACVVAAIALERSLQNVANYLIGSLAVTDLMVSVLVLPMAALYQVLNKWTLGQVTCDLFIALDVLCCTSSILHLCAIALDRYWAITDPIDYVNKRTPRRAAALISLTWLIGFLISIPPMLGWRTPEDRSDPDACTISKDHGYTIYSTFGAFYIPLLLMLVLYGRIFRAARFRIRKTVKKVEKTGADTRHGASPAPQPKKSVNGESGSRNWRLGVESKAGGALCANGAVRQGDDGAALEVIEVHRVGNSKEHLPLPSEAGPTPCAPASFERKNERNAEAKRKMALARERKTVKTLGIIMGTFILCWLPFFIVALVLPFCESSCHMPTLLGAIINWLGYSNSLLNPVIYAYFNKDFQNAFKKIIKCKFCRQ,6.050122295963125 +CN(Cc1ccc(cc1)B(O)O)c1ccc(cn1)C(=O)Nc1ccc(F)cc1,MEDFNMESDSFEDFWKGEDLSNYSYSSTLPPFLLDAAPCEPESLEINKYFVVIIYALVFLLSLLGNSLVMLVILYSRVGRSVTDVYLLNLALADLLFALTLPIWAASKVNGWIFGTFLCKVVSLLKEVNFYSGILLLACISVDRYLAIVHATRTLTQKRYLVKFICLSIWGLSLLLALPVLLFRRTVYSSNVSPACYEDMGNNTANWRMLLRILPQSFGFIVPLLIMLFCYGFTLRTLFKAHMGQKHRAMRVIFAVVLIFLLCWLPYNLVLLADTLMRTQVIQETCERRNHIDRALDATEILGILHSCLNPLIYAFIGQKFRHGLLKILAIHGLISKDSLPKDSRPSFVGSSSGHTSTTL,5.958607314841775 +COc1cc2c(cc1OCCCN1CCCC1)nc(-c1ccc(C)o1)c1ccc(CC3CCN(C)CC3)nc21,MAAAAGAAAAAAAEGEAPAEMGALLLEKETRGATERVHGSLGDTPRSEETLPKATPDSLEPAGPSSPASVTVTVGDEGADTPVGATPLIGDESENLEGDGDLRGGRILLGHATKSFPSSPSKGGSCPSRAKMSMTGAGKSPPSVQSLAMRLLSMPGAQGAAAAGSEPPPATTSPEGQPKVHRARKTMSKPGNGQPPVPEKRPPEIQHFRMSDDVHSLGKVTSDLAKRRKLNSGGGLSEELGSARRSGEVTLTKGDPGSLEEWETVVGDDFSLYYDSYSVDERVDSDSKSEVEALTEQLSEEEEEEEEEEEEEEEEEEEEEEEEDEESGNQSDRSGSSGRRKAKKKWRKDSPWVKPSRKRRKREPPRAKEPRGVNGVGSSGPSEYMEVPLGSLELPSEGTLSPNHAGVSNDTSSLETERGFEELPLCSCRMEAPKIDRISERAGHKCMATESVDGELSGCNAAILKRETMRPSSRVALMVLCETHRARMVKHHCCPGCGYFCTAGTFLECHPDFRVAHRFHKACVSQLNGMVFCPHCGEDASEAQEVTIPRGDGVTPPAGTAAPAPPPLSQDVPGRADTSQPSARMRGHGEPRRPPCDPLADTIDSSGPSLTLPNGGCLSAVGLPLGPGREALEKALVIQESERRKKLRFHPRQLYLSVKQGELQKVILMLLDNLDPNFQSDQQSKRTPLHAAAQKGSVEICHVLLQAGANINAVDKQQRTPLMEAVVNNHLEVARYMVQRGGCVYSKEEDGSTCLHHAAKIGNLEMVSLLLSTGQVDVNAQDSGGWTPIIWAAEHKHIEVIRMLLTRGADVTLTDNEENICLHWASFTGSAAIAEVLLNARCDLHAVNYHGDTPLHIAARESYHDCVLLFLSRGANPELRNKEGDTAWDLTPERSDVWFALQLNRKLRLGVGNRAIRTEKIICRDVARGYENVPIPCVNGVDGEPCPEDYKYISENCETSTMNIDRNITHLQHCTCVDDCSSSNCLCGQLSIRCWYDKDGRLLQEFNKIEPPLIFECNQACSCWRNCKNRVVQSGIKVRLQLYRTAKMGWGVRALQTIPQGTFICEYVGELISDAEADVREDDSYLFDLDNKDGEVYCIDARYYGNISRFINHLCDPNIIPVRVFMLHQDLRFPRIAFFSSRDIRTGEELGFDYGDRFWDIKSKYFTCQCGSEKCKHSAEAIALEQSRLARLDPHPELLPELGSLPPVNT,7.0 +CC(C)[C@@H]1SCC[C@@H]1OC(=O)N[C@@H](Cc1ccccc1)[C@H](O)CN1C[C@H]2CCS[C@H]2C[C@H]1C(=O)NC(C)(C)C,PQVTLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKMIGGIGGFIKVRQYDQILIEICGHKAIGTVLVGPTPVNIIGRNLLTQIGCTLNF,8.585026652029182 +CC(C)C[C@H](NC(=O)[C@H](Cc1c[nH]cn1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H]1CCCN1C(=O)[C@H](Cc1c[nH]cn1)NC(=O)[C@@H]1CCCN1)[C@@H](O)CC(=O)N[C@@H](C(C)C)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCCN)C(O)=O,MDGWRRMPRWGLLLLLWGSCTFGLPTDTTTFKRIFLKRMPSIRESLKERGVDMARLGPEWSQPMKRLTLGNTTSSVILTNYMDTQYYGEIGIGTPPQTFKVVFDTGSSNVWVPSSKCSRLYTACVYHKLFDASDSSSYKHNGTELTLRYSTGTVSGFLSQDIITVGGITVTQMFGEVTEMPALPFMLAEFDGVVGMGFIEQAIGRVTPIFDNIISQGVLKEDVFSFYYNRDSENSQSLGGQIVLGGSDPQHYEGNFHYINLIKTGVWQIQMKGVSVGSSTLLCEDGCLALVDTGASYISGSTSSIEKLMEALGAKKRLFDYVVKCNEGPTLPDISFHLGGKEYTLTSADYVFQESYSSKKLCTLAIHAMDIPPPTGPTWALGATFIRKFYTEFDRRNNRIGFALAR,7.045757490560675 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+N[C@@H](C[C@@H](C\C=C\c1ccc2ccccc2c1)C(O)=O)C(O)=O,MKIIFPILSNPVFRRTVKLLLCLLWIGYSQGTTHVLRFGGIFEYVESGPMGAEELAFRFAVNTINRNRTLLPNTTLTYDTQKINLYDSFEASKKACDQLSLGVAAIFGPSHSSSANAVQSICNALGVPHIQTRWKHQVSDNKDSFYVSLYPDFSSLSRAILDLVQFFKWKTVTVVYDDSTGLIRLQELIKAPSRYNLRLKIRQLPADTKDAKPLLKEMKRGKEFHVIFDCSHEMAAGILKQALAMGMMTEYYHYIFTTLDLFALDVEPYRYSGVNMTGFRILNTENTQVSSIIEKWSMERLQAPPKPDSGLLDGFMTTDAALMYDAVHVVSVAVQQFPQMTVSSLQCNRHKPWRFGTRFMSLIKEAHWEGLTGRITFNKTNGLRTDFDLDVISLKEEGLEKIGTWDPASGLNMTESQKGKPANITDSLSNRSLIVTTILEEPYVLFKKSDKPLYGNDRFEGYCIDLLRELSTILGFTYEIRLVEDGKYGAQDDANGQWNGMVRELIDHKADLAVAPLAITYVREKVIDFSKPFMTLGISILYRKPNGTNPGVFSFLNPLSPDIWMYILLAYLGVSCVLFVIARFSPYEWYNPHPCNPDSDVVENNFTLLNSFWFGVGALMQQGSELMPKALSTRIVGGIWWFFTLIIISSYTANLAAFLTVERMESPIDSADDLAKQTKIEYGAVEDGATMTFFKKSKISTYDKMWAFMSSRRQSVLVKSNEEGIQRVLTSDYAFLMESTTIEFVTQRNCNLTQIGGLIDSKGYGVGTPMGSPYRDKITIAILQLQEEGKLHMMKEKWWRGNGCPEEESKEASALGVQNIGGIFIVLAAGLVLSVFVAVGEFLYKSKKNAQLEKRSFCSAMVEELRMSLKCQRRLKHKPQAPVIVKTEEVINMHTFNDRRLPGKETMA,4.812310106474816 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+FC(F)(F)CNC(=O)Nc1cccc(c1)-c1cnc2cc(cnn12)-c1cnn(c1)C(CC#N)c1ccccc1,MGAPACALALCVAVAIVAGASSESLGTEQRVVGRAAEVPGPEPGQQEQLVFGSGDAVELSCPPPGGGPMGPTVWVKDGTGLVPSERVLVGPQRLQVLNASHEDSGAYSCRQRLTQRVLCHFSVRVTDAPSSGDDEDGEDEAEDTGVDTGAPYWTRPERMDKKLLAVPAANTVRFRCPAAGNPTPSISWLKNGREFRGEHRIGGIKLRHQQWSLVMESVVPSDRGNYTCVVENKFGSIRQTYTLDVLERSPHRPILQAGLPANQTAVLGSDVEFHCKVYSDAQPHIQWLKHVEVNGSKVGPDGTPYVTVLKTAGANTTDKELEVLSLHNVTFEDAGEYTCLAGNSIGFSHHSAWLVVLPAEEELVEADEAGSVYAGILSYGVGFFLFILVVAAVTLCRLRSPPKKGLGSPTVHKISRFPLKRQVSLESNASMSSNTPLVRIARLSSGEGPTLANVSELELPADPKWELSRARLTLGKPLGEGCFGQVVMAEAIGIDKDRAAKPVTVAVKMLKDDATDKDLSDLVSEMEMMKMIGKHKNIINLLGACTQGGPLYVLVEYAAKGNLREFLRARRPPGLDYSFDTCKPPEEQLTFKDLVSCAYQVARGMEYLASQKCIHRDLAARNVLVTEDNVMKIADFGLARDVHNLDYYKKTTNGRLPVKWMAPEALFDRVYTHQSDVWSFGVLLWEIFTLGGSPYPGIPVEELFKLLKEGHRMDKPANCTHDLYMIMRECWHAAPSQRPTFKQLVEDLDRVLTVTSTDEYLDLSAPFEQYSPGGQDTPSSSSSGDDSVFAHDLLPPAPPSSGGSRT,8.0 +Cn1cc(cn1)-c1cc(-c2ccc(nc2)N2CCC(C)(N)CC2)c2c(cnn2c1)C#N,HCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYGSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,7.379863945026242 +CCCCCCCCCCCCCC(=O)OCCCOP(O)(=O)OC[C@H](N)C(O)=O,MANLDKYTETFKMGSNSTSTAEIYCNVTNVKFQYSLYATTYILIFIPGLLANSAALWVLCRFISKKNKAIIFMINLSVADLAHVLSLPLRIYYYISHHWPFQRALCLLCFYLKYLNMYASICFLTCISLQRCFFLLKPFRARDWKRRYDVGISAAIWIVVGTACLPFPILRSTDLNNNKSCFADLGYKQMNAVALVGMITVAELAGFVIPVIIIAWCTWKTTISLRQPPMAFQGISERQKALRMVFMCAAVFFICFTPYHINFIFYTMVKETIISSCPVVRIALYFHPFCLCLASLCCLLDPILYYFMASEFRDQLSRHGSSVTRSRLMSKESGSSMIG,7.346787486224656 +COc1cc(cc(c1)C(F)(F)F)C(=O)Nc1cc(Nc2ncccc2-c2ncnc3[nH]cnc23)ccc1F,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,5.958607314841775 +Cl.Cl.C[C@H](Nc1nccc(n1)-c1cc(nnc1-c1cccc(c1)C(F)(F)F)C1CCNCC1)c1ccccc1,MSGPRAGFYRQELNKTVWEVPQRLQGLRPVGSGAYGSVCSAYDARLRQKVAVKKLSRPFQSLIHARRTYRELRLLKHLKHENVIGLLDVFTPATSIEDFSEVYLVTTLMGADLNNIVKCQALSDEHVQFLVYQLLRGLKYIHSAGIIHRDLKPSNVAVNEDCELRILDFGLARQADEEMTGYVATRWYRAPEIMLNWMHYNQTVDIWSVGCIMAELLQGKALFPGSDYIDQLKRIMEVVGTPSPEVLAKISSEHARTYIQSLPPMPQKDLSSIFRGANPLAIDLLGRMLVLDSDQRVSAAEALAHAYFSQYHDPEDEPEAEPYDESVEAKERTLEEWKELTYQEVLSFKPPEPPKPPGSLEIEQ,9.823908740944319 +COCCOc1cc(NC(=O)N2CCCc3ccc(C=O)nc23)ncc1C#N,GLYRGQALHGRHPRPPATVQKLSRFPLARQFSLESGSSGKSSSSLVRGVRLSSSGPALLAGLVSLDLPLDPLWEFPRDRLVLGKPLGEGCFGQVVRAEAFGMDPARPDQASTVAVKMLKDNASDKDLADLVSEMEVMKLIGRHKNIINLLGVCTQEGPLYVIVECAAKGNLREFLRARRPPGPDLSPDGPRSSEGPLSFPVLVSCAYQVARGMQYLESRKCIHRDLAARNVLVTEDNVMKIADFGLARGVHHIDYYKKTSNGRLPVKWMAPEALFDRVYTHQSDVWSFGILLWEIFTLGGSPYPGIPVEELFSLLREGHRMDRPPHCPPELYGLMRECWHAAPSQRPTFKQLVEALDKVLLAVSEEYLDLRLTFGPYSPSGGDASSTCSSSDSVFSHDPLPLGSSSFPFGSGVQT,8.886056647693163 +C[S+]([O-])c1ccc(\C=C2\C(C)=C(CC(=O)OCCOc3cc4ncnc(Nc5cccc(c5)C#C)c4cc3OCCOC(=O)CC3=C(C)\C(=C\c4ccc(cc4)[S+](C)[O-])c4ccc(F)cc34)c3cc(F)ccc23)cc1,MSRQSISLRFPLLLLLLSPSPVFSADPGAPAPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPEIWTWLRTTLRPSPSFIHFLLTHGRWLWDFVNATFIRDTLMRLVLTVRSNLIPSPPTYNIAHDYISWESFSNVSYYTRILPSVPRDCPTPMDTKGKKQLPDAEFLSRRFLLRRKFIPDPQSTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQMLNGEVYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATIWLREHNRVCDLLKAEHPTWGDEQLFQTARLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGAQFQYRNRIAMEFNQLYHWHPLMPDSFRVGPQDYSYEQFLFNTSMLVDYGVEALVDAFSRQPAGRIGGGRNIDHHILHVAVDVIKESRVLRLQPFNEYRKRFGMKPYTSFQELTGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEMGAPFSLKGLLGNPICSPEYWKASTFGGEVGFNLVKTATLKKLVCLNTKTCPYVSFHVPDPRQEDRPGVERPPTEL,5.0 +CCOC(=O)c1c(CC)c([nH]c1C=O)C(=O)NC(C)(C)C,MATGGRRGAAAAPLLVAVAALLLGAAGHLYPGEVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNNELCYLATIDWSRILDSVEDNYIVLNKDDNEECGDICPGTAKGKTNCPATVINGQFVERCWTHSHCQKVCPTICKSHGCTAEGLCCHSECLGNCSQPDDPTKCVACRNFYLDGRCVETCPPPYYHFQDWRCVNFSFCQDLHHKCKNSRRQGCHQYVIHNNKCIPECPSGYTMNSSNLLCTPCLGPCPKVCHLLEGEKTIDSVTSAQELRGCTVINGSLIINIRGGNNLAAELEANLGLIEEISGYLKIRRSYALVSLSFFRKLRLIRGETLEIGNYSFYALDNQNLRQLWDWSKHNLTITQGKLFFHYNPKLCLSEIHKMEEVSGTKGRQERNDIALKTNGDQASCENELLKFSYIRTSFDKILLRWEPYWPPDFRDLLGFMLFYKEAPYQNVTEFDGQDACGSNSWTVVDIDPPLRSNDPKSQNHPGWLMRGLKPWTQYAIFVKTLVTFSDERRTYGAKSDIIYVQTDATNPSVPLDPISVSNSSSQIILKWKPPSDPNGNITHYLVFWERQAEDSELFELDYCLKGLKLPSRTWSPPFESEDSQKHNQSEYEDSAGECCSCPKTDSQILKELEESSFRKTFEDYLHNVVFVPRKTSSGTGAEDPRPSRKRRSLGDVGNVTVAVPTVAAFPNTSSTSVPTSPEEHRPFEKVVNKESLVISGLRHFTGYRIELQACNQDTPEERCSVAAYVSARTMPEAKADDIVGPVTHEIFENNVVHLMWQEPKEPNGLIVLYEVSYRRYGDEELHLCVSRKHFALERGCRLRGLSPGNYSVRIRATSLAGNGSWTEPTYFYVTDYLDVPSNIAKIIIGPLIFVFLFSVVIGSIYLFLRKRQPDGPLGPLYASSNPEYLSASDVFPCSVYVPDEWEVSREKITLLRELGQGSFGMVYEGNARDIIKGEAETRVAVKTVNESASLRERIEFLNEASVMKGFTCHHVVRLLGVVSKGQPTLVVMELMAHGDLKSYLRSLRPEAENNPGRPPPTLQEMIQMAAEIADGMAYLNAKKFVHRDLAARNCMVAHDFTVKIGDFGMTRDIYETDYYRKGGKGLLPVRWMAPESLKDGVFTTSSDMWSFGVVLWEITSLAEQPYQGLSNEQVLKFVMDGGYLDQPDNCPERVTDLMRMCWQFNPKMRPTFLEIVNLLKDDLHPSFPEVSFFHSEENKAPESEELEMEFEDMENVPLDRSSHCQREEAGGRDGGSSLGFKRSYEEHIPYTHMNGGKKNGRILTLPRSNPS,4.769551078621726 +CCCOC(=O)c1c(N)n(CC=C)c2nc3ccccc3nc12,MSTNENANTPAARLHRFKNKGKDSTEMRRRRIEVNVELRKAKKDDQMLKRRNVSSFPDDATSPLQENRNNQGTVNWSVDDIVKGINSSNVENQLQATQAARKLLSREKQPPIDNIIRAGLIPKFVSFLGRTDCSPIQFESAWALTNIASGTSEQTKAVVDGGAIPAFISLLASPHAHISEQAVWALGNIAGDGSVFRDLVIKYGAVDPLLALLAVPDMSSLACGYLRNLTWTLSNLCRNKNPAPPIDAVEQILPTLVRLLHHDDPEVLADTCWAISYLTDGPNERIGMVVKTGVVPQLVKLLGASELPIVTPALRAIGNIVTGTDEQTQVVIDAGALAVFPSLLTNPKTNIQKEATWTMSNITAGRQDQIQQVVNHGLVPFLVSVLSKADFKTQKEAVWAVTNYTSGGTVEQIVYLVHCGIIEPLMNLLTAKDTKIILVILDAISNIFQAAEKLGETEKLSIMIEECGGLDKIEALQNHENESVYKASLSLIEKYFSVEEEEDQNVVPETTSEGYTFQVQDGAPGTFNF,3.3010299956639813 +CC1(C)OCC(COc2cc(F)cc(c2)[C@H]2CCCN2c2ccn3ncc(C(=O)NC4CC4)c3n2)O1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,6.0 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+COc1cccc(c1)-c1c(nn2c(ccnc12)-c1ccc(cc1)N1C[C@@H]2C[C@H]1CN2)-c1ccncc1,MAALSGGGGGGAEPGQALFNGDMEPEAGAGAGAAASSAADPAIPEEVWNIKQMIKLTQEHIEALLDKFGGEHNPPSIYLEAYEEYTSKLDALQQREQQLLESLGNGTDFSVSSSASMDTVTSSSSSSLSVLPSSLSVFQNPTDVARSNPKSPQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQDGEKKPIGWDTDISWLTGEELHVEVLENVPLTTHNFVRKTFFTLAFCDFCRKLLFQGFRCQTCGYKFHQRCSTEVPLMCVNYDQLDLLFVSKFFEHHPIPQEEASLAETALTSGSSPSAPASDSIGPQILTSPSPSKSIPIPQPFRPADEDHRNQFGQRDRSSSAPNVHINTIEPVNIDDLIRDQGFRGDGGSTTGLSATPPASLPGSLTNVKALQKSPGPQRERKSSSSSEDRNRMKTLGRRDSSDDWEIPDGQITVGQRIGSGSFGTVYKGKWHGDVAVKMLNVTAPTPQQLQAFKNEVGVLRKTRHVNILLFMGYSTKPQLAIVTQWCEGSSLYHHLHIIETKFEMIKLIDIARQTAQGMDYLHAKSIIHRDLKSNNIFLHEDLTVKIGDFGLATVKSRWSGSHQFEQLSGSILWMAPEVIRMQDKNPYSFQSDVYAFGIVLYELMTGQLPYSNINNRDQIIFMVGRGYLSPDLSKVRSNCPKAMKRLMAECLKKKRDERPLFPQILASIELLARSLPKIHRSASEPSLNRAGFQTEDFSLYACASPKTPIQAGGYGAFPVH,7.920818753952375 +CCC(=O)N[C@@H]1CCCc2c1cncc2-c1ccc2N(C)C(=O)CCc2c1,MALRAKAEVCVAAPWLSLQRARALGTRAARAPRTVLPFEAMPQHPGNRWLRLLQIWREQGYEHLHLEMHQTFQELGPIFRYNLGGPRMVCVMLPEDVEKLQQVDSLHPCRMILEPWVAYRQHRGHKCGVFLLNGPEWRFNRLRLNPDVLSPKAVQRFLPMVDAVARDFSQALKKKVLQNARGSLTLDVQPSIFHYTIEASNLALFGERLGLVGHSPSSASLNFLHALEVMFKSTVQLMFMPRSLSRWISPKVWKEHFEAWDCIFQYGDNCIQKIYQELAFNRPQHYTGIVAELLLKAELSLEAIKANSMELTAGSVDTTAFPLLMTLFELARNPDVQQILRQESLAAAASISEHPQKATTELPLLRAALKETLRLYPVGLFLERVVSSDLVLQNYHIPAGTLVQVFLYSLGRNAALFPRPERYNPQRWLDIRGSGRNFHHVPFGFGMRQCLGRRLAEAEMLLLLHHVLKHFLVETLTQEDIKMVYSFILRPGTSPLLTFRAIN,7.853871964321762 +NC(=O)c1ccc(Oc2cccc(c2)C(=O)N2CCC(CC2)c2cccc(F)c2)cc1,MAVPGSFPLLVEGSWGPDPPKNLNTKLQMYFQSPKRSGGGECEVRQDPRSPSRFLVFFYPEDVRQKVLERKNHELVWQGKGTFKLTVQLPATPDEIDHVFEEELLTKESKTKEDVKEPDVSEELDTKLPLDGGLDKMEDIPEECENISSLVAFENLKANVTDIMLILLVENISGLSNDDFQVEIIRDFDVAVVTFQKHIDTIRFVDDCTKHHSIKQLQLSPRLLEVTNTIRVENLPPGADDYSLKLFFENPYNGGGRVANVEYFPEESSALIEFFDRKVLDTIMATKLDFNKMPLSVFPYYASLGTALYGKEKPLIKLPAPFEESLDLPLWKFLQKKNHLIEEINDEMRRCHCELTWSQLSGKVTIRPAATLVNEGRPRIKTWQADTSTTLSSIRSKYKVNPIKVDPTMWDTIKNDVKDDRILIEFDTLKEMVILAGKSEDVQSIEVQVRELIESTTQKIKREEQSLKEKMIISPGRYFLLCHSSLLDHLLTECPEIEICYDRVTQHLCLKGPSADVYKAKCEIQEKVYTMAQKNIQVSPEIFQFLQQVNWKEFSKCLFIAQKILALYELEGTTVLLTSCSSEALLEAEKQMLSALNYKRIEVENKEVLHGKKWKGLTHNLLKKQNSSPNTVIINELTSETTAEVIITGCVKEVNETYKLLFNFVEQNMKIERLVEVKPSLVIDYLKTEKKLFWPKIKKVNVQVSFNPENKQKGILLTGSKTEVLKAVDIVKQVWDSVCVKSVHTDKPGAKQFFQDKARFYQSEIKRLFGCYIELQENEVMKEGGSPAGQKCFSRTVLAPGVVLIVQQGDLARLPVDVVVNASNEDLKHYGGLAAALSKAAGPELQADCDQIVKREGRLLPGNATISKAGKLPYHHVIHAVGPRWSGYEAPRCVYLLRRAVQLSLCLAEKYKYRSIAIPAISSGVFGFPLGRCVETIVSAIKENFQFKKDGHCLKEIYLVDVSEKTVEAFAEAVKTVFKATLPDTAAPPGLPPAAAGPGKTSWEKGSLVSPGGLQMLLVKEGVQNAKTDVVVNSVPLDLVLSRGPLSKSLLEKAGPELQEELDTVGQGVAVSMGTVLKTSSWNLDCRYVLHVVAPEWRNGSTSSLKIMEDIIRECMEITESLSLKSIAFPAIGTGNLGFPKNIFAELIISEVFKFSSKNQLKTLQEVHFLLHPSDHENIQAFSDEFARRANGNLVSDKIPKAKDTQGFYGTVSSPDSGVYEMKIGSIIFQVASGDITKEEADVIVNSTSNSFNLKAGVSKAILECAGQNVERECSQQAQQRKNDYIITGGGFLRCKNIIHVIGGNDVKSSVSSVLQECEKKNYSSICLPAIGTGNAKQHPDKVAEAIIDAIEDFVQKGSAQSVKKVKVVIFLPQVLDVFYANMKKREGTQLSSQQSVMSKLASFLGFSKQSPQKKNHLVLEKKTESATFRVCGENVTCVEYAISWLQDLIEKEQCPYTSEDECIKDFDEKEYQELNELQKKLNINISLDHKRPLIKVLGISRDVMQARDEIEAMIKRVRLAKEQESRADCISEFIEWQYNDNNTSHCFNKMTNLKLEDARREKKKTVDVKINHRHYTVNLNTYTATDTKGHSLSVQRLTKSKVDIPAHWSDMKQQNFCVVELLPSDPEYNTVASKFNQTCSHFRIEKIERIQNPDLWNSYQAKKKTMDAKNGQTMNEKQLFHGTDAGSVPHVNRNGFNRSYAGKNAVAYGKGTYFAVNANYSANDTYSRPDANGRKHVYYVRVLTGIYTHGNHSLIVPPSKNPQNPTDLYDTVTDNVHHPSLFVAFYDYQAYPEYLITFRK,5.840132152907433 +CC[C@@H](C)S(=O)(=O)Nc1cc(nc(Oc2c(F)cccc2Cl)n1)-c1ccc(=O)n(C)c1,MAENLLDGPPNPKRAKLSSPGFSANDSTDFGSLFDLENDLPDELIPNGGELGLLNSGNLVPDAASKHKQLSELLRGGSGSSINPGIGNVSASSPVQQGLGGQAQGQPNSANMASLSAMGKSPLSQGDSSAPSLPKQAASTSGPTPAASQALNPQAQKQVGLATSSPATSQTGPGICMNANFNQTHPGLLNSNSGHSLINQASQGQAQVMNGSLGAAGRGRGAGMPYPTPAMQGASSSVLAETLTQVSPQMTGHAGLNTAQAGGMAKMGITGNTSPFGQPFSQAGGQPMGATGVNPQLASKQSMVNSLPTFPTDIKNTSVTNVPNMSQMQTSVGIVPTQAIATGPTADPEKRKLIQQQLVLLLHAHKCQRREQANGEVRACSLPHCRTMKNVLNHMTHCQAGKACQVAHCASSRQIISHWKNCTRHDCPVCLPLKNASDKRNQQTILGSPASGIQNTIGSVGTGQQNATSLSNPNPIDPSSMQRAYAALGLPYMNQPQTQLQPQVPGQQPAQPQTHQQMRTLNPLGNNPMNIPAGGITTDQQPPNLISESALPTSLGATNPLMNDGSNSGNIGTLSTIPTAAPPSSTGVRKGWHEHVTQDLRSHLVHKLVQAIFPTPDPAALKDRRMENLVAYAKKVEGDMYESANSRDEYYHLLAEKIYKIQKELEEKRRSRLHKQGILGNQPALPAPGAQPPVIPQAQPVRPPNGPLSLPVNRMQVSQGMNSFNPMSLGNVQLPQAPMGPRAASPMNHSVQMNSMGSVPGMAISPSRMPQPPNMMGAHTNNMMAQAPAQSQFLPQNQFPSSSGAMSVGMGQPPAQTGVSQGQVPGAALPNPLNMLGPQASQLPCPPVTQSPLHPTPPPASTAAGMPSLQHTTPPGMTPPQPAAPTQPSTPVSSSGQTPTPTPGSVPSATQTQSTPTVQAAAQAQVTPQPQTPVQPPSVATPQSSQQQPTPVHAQPPGTPLSQAAASIDNRVPTPSSVASAETNSQQPGPDVPVLEMKTETQAEDTEPDPGESKGEPRSEMMEEDLQGASQVKEETDIAEQKSEPMEVDEKKPEVKVEVKEEEESSSNGTASQSTSPSQPRKKIFKPEELRQALMPTLEALYRQDPESLPFRQPVDPQLLGIPDYFDIVKNPMDLSTIKRKLDTGQYQEPWQYVDDVWLMFNNAWLYNRKTSRVYKFCSKLAEVFEQEIDPVMQSLGYCCGRKYEFSPQTLCCYGKQLCTIPRDAAYYSYQNRYHFCEKCFTEIQGENVTLGDDPSQPQTTISKDQFEKKKNDTLDPEPFVDCKECGRKMHQICVLHYDIIWPSGFVCDNCLKKTGRPRKENKFSAKRLQTTRLGNHLEDRVNKFLRRQNHPEAGEVFVRVVASSDKTVEVKPGMKSRFVDSGEMSESFPYRTKALFAFEEIDGVDVCFFGMHVQEYGSDCPPPNTRRVYISYLDSIHFFRPRCLRTAVYHEILIGYLEYVKKLGYVTGHIWACPPSEGDDYIFHCHPPDQKIPKPKRLQEWYKKMLDKAFAERIIHDYKDIFKQATEDRLTSAKELPYFEGDFWPNVLEESIKELEQEEEERKKEESTAASETTEGSQGDSKNAKKKNNKKTNKNKSSISRANKKKPSMPNVSNDLSQKLYATMEKHKEVFFVIHLHAGPVINTLPPIVDPDPLLSCDLMDGRDAFLTLARDKHWEFSSLRRSKWSTLCMLVELHTQGQDRFVYTCNECKHHVETRWHCTVCEDYDLCINCYNTKSHAHKMVKWGLGLDDEGSSQGEPQSKSPQESRRLSIQRCIQSLVHACQCRNANCSLPSCQKMKRVVQHTKGCKRKTNGGCPVCKQLIALCCYHAKHCQENKCPVPFCLNIKHKLRQQQIQHRLQQAQLMRRRMATMNTRNVPQQSLPSPTSAPPGTPTQQPSTPQTPQPPAQPQPSPVSMSPAGFPSVARTQPPTTVSTGKPTSQVPAPPPPAQPPPAAVEAARQIEREAQQQQHLYRVNINNSMPPGRTGMGTPGSQMAPVSLNVPRPNQVSGPVMPSMPPGQWQQAPLPQQQPMPGLPRPVISMQAQAAVAGPRMPSVQPPRSISPSALQDLLRTLKSPSSPQQQQQVLNILKSNPQLMAAFIKQRTAKYVANQPGMQPQPGLQSQPGMQPQPGMHQQPSLQNLNAMQAGVPRPGVPPQQQAMGGLNPQGQALNIMNPGHNPNMASMNPQYREMLRRQLLQQQQQQQQQQQQQQQQQQGSAGMAGGMAGHGQFQQPQGPGGYPPAMQQQQRMQQHLPLQGSSMGQMAAQMGQLGQMGQPGLGADSTPNIQQALQQRILQQQQMKQQIGSPGQPNPMSPQQHMLSGQPQASHLPGQQIATSLSNQVRSPAPVQSPRPQSQPPHSSPSPRIQPQPSPHHVSPQTGSPHPGLAVTMASSIDQGHLGNPEQSAMLPQLNTPSRSALSSELSLVGDTTGDTLEKFVEGL,6.301029995663981 +CC(C)NCC(O)COc1ccc(NC(C)=O)cc1,MGAGVLVLGASEPGNLSSAAPLPDGAATAARLLVPASPPASLLPPASESPEPLSQQWTAGMGLLMALIVLLIVAGNVLVIVAIAKTPRLQTLTNLFIMSLASADLVMGLLVVPFGATIVVWGRWEYGSFFCELWTSVDVLCVTASIETLCVIALDRYLAITSPFRYQSLLTRARARGLVCTVWAISALVSFLPILMHWWRAESDEARRCYNDPKCCDFVTNRAYAIASSVVSFYVPLCIMAFVYLRVFREAQKQVKKIDSCERRFLGGPARPPSPSPSPVPAPAPPPGPPRPAAAAATAPLANGRAGKRRPSRLVALREQKALKTLGIIMGVFTLCWLPFFLANVVKAFHRELVPDRLFVFFNWLGYANSAFNPIIYCRSPDFRKAFQRLLCCARRAARRRHATHGDRPRASGCLARPGPPPSPGAASDDDDDDVVGATPPARLLEPWAGCNGGAAADSDSSLDEPCRPGFASESKV,6.140261433802853 +COc1cc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2cc1NC1CCN(CC1)C(=O)C=C,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLIMQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGRAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,7.43533393574791 +COc1c(O)ccc2O\C(=C/c3sccc3C(C)O)c3c(ccc4NC(C)(C)C=C(C)c34)-c12,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,8.864337397999927 +CC(C)(C)CC(=O)N1CCC(CNC(=O)c2cc(Cl)ccc2C2CCN(CCN3C(=O)COc4ccccc34)CC2)CC1,MALSLESTTSFHMLTVSGSTVTELPGDSNVSLNSSWSGPTDPSSLKDLVATGVIGAVLSAMGVVGMVGNVYTLVVMCRFLRASASMYVYVVNLALADLLYLLSIPFIIATYVTKDWHFGDVGCRVLFSLDFLTMHASIFTLTIMSSERYAAVLRPLDTVQRSKGYRKLLVLGTWLLALLLTLPMMLAIQLVRRGSKSLCLPAWGPRAHRTYLTLLFGTSIVGPGLVIGLLYVRLARAYWLSQQASFKQTRRLPNPRVLYLILGIVLLFWACFLPFWLWQLLAQYHEAMPLTPETARIVNYLTTCLTYGNSCINPFLYTLLTKNYREYLRGRQRSLGSSCHSPGSPGSFLPSRVHLQQDSGRSLSSSSQQATETLMLSPVPRNGALL,6.481486060122112 +CN1c2ccc(Cl)cc2C(=NCC1=O)c1ccco1,MWGLAGGRLFGIFSAPVLVAVVCCAQSVNDPGNMSFVKETVDKLLKGYDIRLRPDFGGPPVCVGMNIDIASIDMVSEVNMDYTLTMYFQQYWRDKRLAYSGIPLNLTLDNRVADQLWVPDTYFLNDKKSFVHGVTVKNRMIRLHPDGTVLYGLRITTTAACMMDLRRYPLDEQNCTLEIESYGYTTDDIEFYWRGGDKAVTGVERIELPQFSIVEHRLVSRNVVFATGAYPRLSLSFRLKRNIGYFILQTYMPSILITILSWVSFWINYDASAARVALGITTVLTMTTINTHLRETLPKIPYVKAIDMYLMGCFVFVFLALLEYAFVNYIFFGRGPQRQKKLAEKTAKAKNDRSKSESNRVDAHGNILLTSLEVHNEMNEVSGGIGDTRNSAISFDNSGIQYRKQSMPREGHGRFLGDRSLPHKKTHLRRRSSQLKIKIPDLTDVNAIDRWSRIVFPFTFSLFNLVYWLYYVN,9.638272163982407 +CC(N)C1(CCCCC1)c1ccc2ccccc2c1,METTPLNSQKQLSACEDGEDCQENGVLQKVVPTPGDKVESGQISNGYSAVPSPGAGDDTRHSIPATTTTLVAELHQGERETWGKKVDFLLSVIGYAVDLGNVWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIMAWALYYLISSFTDQLPWTSCKNSWNTGNCTNYFSEDNITWTLHSTSPAEEFYTRHVLQIHRSKGLQDLGGISWQLALCIMLIFTVIYFSIWKGVKTSGKVVWVTATFPYIILSVLLVRGATLPGAWRGVLFYLKPNWQKLLETGVWIDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHVWAKRRERFVLAVVITCFFGSLVTLTFGGAYVVKLLEEYATGPAVLTVALIEAVAVSWFYGITQFCRDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPYWSIILGYCIGTSSFICIPTYIAYRLIITPGTFKERIIKSITPETPTEIPCGDIRLNAV,6.721246399047171 +CC(C)(C)OC(=O)c1cc2c(c[nH]1)nc1ccccc21,MSSPNIWSTGSSVYSTPVFSQKMTVWILLLLSLYPGFTSQKSDDDYEDYASNKTWVLTPKVPEGDVTVILNNLLEGYDNKLRPDIGVKPTLIHTDMYVNSIGPVNAINMEYTIDIFFAQTWYDRRLKFNSTIKVLRLNSNMVGKIWIPDTFFRNSKKADAHWITTPNRMLRIWNDGRVLYTLRLTIDAECQLQLHNFPMDEHSCPLEFSSYGYPREEIVYQWKRSSVEVGDTRSWRLYQFSFVGLRNTTEVVKTTSGDYVVMSVYFDLSRRMGYFTIQTYIPCTLIVVLSWVSFWINKDAVPARTSLGITTVLTMTTLSTIARKSLPKVSYVTAMDLFVSVCFIFVFSALVEYGTLHYFVSNRKPSKDKDKKKKNPAPTIDIRPRSATIQMNNATHLQERDEEYGYECLDGKDCASFFCCFEDCRTGAWRHGRIHIRIAKMDSYARIFFPTAFCLFNLVYWVSYLYL,7.823908740944319 +Cn1nc(c(c1C1CCN(C[C@@H](O)C(F)(F)F)CC1)-c1ccc2nc(NC(=O)c3ccnc(F)c3)cn2n1)-c1ccc(F)cc1,MELRVGNRYRLGRKIGSGSFGDIYLGTDIAAGEEVAIKLECVKTKHPQLHIESKIYKMMQGGVGIPTIRWCGAEGDYNVMVMELLGPSLEDLFNFCSRKFSLKTVLLLADQMISRIEYIHSKNFIHRDVKPDNFLMGLGKKGNLVYIIDFGLAKKYRDARTHQHIPYRENKNLTGTARYASINTHLGIEQSRRDDLESLGYVLMYFNLGSLPWQGLKAATKRQKYERISEKKMSTPIEVLCKGYPSEFATYLNFCRSLRFDDKPDYSYLRQLFRNLFHRQGFSYDYVFDWNMLKFGASRAADDAERERRDREERLRHSRNPATRGLPSTASGRLRGTQEVAPPTPLTPTSHTANTSPRPVSGMERERKVSMRLHRGAPVNISSSDLTGRQDTSRMSTSQIPGRVASSGLQSVVHR,9.698970004336019 +C(CCn1cncn1)COc1ccccc1,MSSEVETSEGVDESENNSTAPEKENHTKMADLSELLKEGTKEAHDRAENTQFVKDFLKGNIKKELFKLATTALYFTYSALEEEMDRNKDHPAFAPLYFPTELHRKEALIKDMEYFFGENWEEQVKCSEAAQKYVDRIHYVGQNEPELLVAHAYTRYMGDLSGGQVLKKVAQRALKLPSTGEGTQFYLFEHVDNAQQFKQFYRARMNALDLSMKTKERIVEEANKAFEYNMQIFSELDQAGSMLTKETLEDGLPVHDGKGDVRKCPFYAAQPDKGTLGGSNCPFRTAMAVLRKPSLQLILAASVALVAGLLAWYYM,4.568636235841012 +Cn1cc(nn1)-c1ccc2n(cc(C3CCN(CCN4CCNC4=O)CC3)c2c1)-c1ccc(F)cc1,MTFRDILSVTFEGPRSSSSTGGSGAGGGAGTVGPEGGAVGGVPGATGGGAVVGTGSGEDNQSSTGEPGAAASGEVNGSAAVGGLVVSAQGVGVGVFLAAFILTAVAGNLLVILSVACNRHLQTVTNYFIVNLAVADLLLSAAVLPFSATMEVLGFWAFGRTFCDVWAAVDVLCCTASILSLCTISVDRYVGVRHSLKYPAIMTERKAAAILALLWAVALVVSVGPLLGWKEPVPPDERFCGITEEVGYAIFSSVCSFYLPMAVIVVMYCRVYVVARSTTRSLEAGIKREPGKASEVVLRIHCRGAATSAKGYPGTQSSKGHTLRSSLSVRLLKFSREKKAAKTLAIVVGVFVLCWFPFFFVLPLGSLFPQLKPSEGVFKVIFWLGYFNSCVNPLIYPCSSREFKRAFLRLLRCQCRRRRRRLWAVYGHHWRASTGDARSDCAPSPRIAPPGAPLALTAHPGAGSADTPETQDSVSSSRKPASALREWRLLGPLQRPTTQLRAKVSSLSHKIRSGARRAETACALRSEVEAVSLNVPQDGAEAVICQAYEPGDYSNLRETDI,8.065501548756432 +COc1ccc2n(C(=O)c3ccc(Cl)cc3)c(C)c(CC(=O)NCCCCO)c2c1,MSRQSISLRFPLLLLLLSPSPVFSADPGAPAPVNPCCYYPCQHQGICVRFGLDRYQCDCTRTGYSGPNCTIPEIWTWLRTTLRPSPSFIHFLLTHGRWLWDFVNATFIRDTLMRLVLTVRSNLIPSPPTYNIAHDYISWESFSNVSYYTRILPSVPRDCPTPMDTKGKKQLPDAEFLSRRFLLRRKFIPDPQSTNLMFAFFAQHFTHQFFKTSGKMGPGFTKALGHGVDLGHIYGDNLERQYQLRLFKDGKLKYQMLNGEVYPPSVEEAPVLMHYPRGIPPQSQMAVGQEVFGLLPGLMLYATIWLREHNRVCDLLKAEHPTWGDEQLFQTARLILIGETIKIVIEEYVQQLSGYFLQLKFDPELLFGAQFQYRNRIAMEFNQLYHWHPLMPDSFRVGPQDYSYEQFLFNTSMLVDYGVEALVDAFSRQPAGRIGGGRNIDHHILHVAVDVIKESRVLRLQPFNEYRKRFGMKPYTSFQELTGEKEMAAELEELYGDIDALEFYPGLLLEKCHPNSIFGESMIEMGAPFSLKGLLGNPICSPEYWKASTFGGEVGFNLVKTATLKKLVCLNTKTCPYVSFHVPDPRQEDRPGVERPPTEL,4.0655015487564325 +COC(=O)CCc1ccc(OCc2oc(nc2C)-c2cccc(OC)c2)cc1,MEAMAASTSLPDPGDFDRNVPRICGVCGDRATGFHFNAMTCEGCKGFFRRSMKRKALFTCPFNGDCRITKDNRRHCQACRLKRCVDIGMMKEFILTDEEVQRKREMILKRKEEEALKDSLRPKLSEEQQRIIAILLDAHHKTYDPTYSDFCQFRPPVRVNDGGGSHPSRPNSRHTPSFSGDSSSSCSDHCITSSDMMDSSSFSNLDLSEEDSDDPSVTLELSQLSMLPHLADLVSYSIQKVIGFAKMIPGFRDLTSEDQIVLLKSSAIEVIMLRSNESFTMDDMSWTCGNQDYKYRVSDVTKAGHSLELIEPLIKFQVGLKKLNLHEEEHVLLMAICIVSPDRPGVQDAALIEAIQDRLSNTLQTYIRCRHPPPGSHLLYAKMIQKLADLRSLNEEHSKQYRCLSFQPECSMKLTPLVLEVFGNEIS,5.540607512240769 +COc1ccc(cc1)C(c1ccc(OC)cc1)C(Cl)(Cl)Cl,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREAIQNPGPRHPEAASIAPPGACLQQRQETSPRRRRRQQHPEDGSPQAHIRGTTGYLALEEEQQPSQQQSASEGHPESGCLPEPGAATAPGKGLPQQPPAPPDQDDSAAPSTLSLLGPTFPGLSSCSADIKDILSEAGTMQLLQQQQQQQQQQQQQQQQQQQQQQEVISEGSSSVRAREATGAPSSSKDSYLGGNSTISDSAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYASLLGGPPAVRPTPCAPLAECKGLSLDEGPGKGTEETAEYSSFKGGYAKGLEGESLGCSGSSEAGSSGTLEIPSSLSLYKSGAVDEAAAYQNRDYYNFPLALSGPPHPPPPTHPHARIKLENPSDYGSAWAAAAAQCRYGDLASLHGGSVAGPSTGSPPATASSSWHTLFTAEEGQLYGPGGGGGSSSPSDAGPVAPYGYTRPPQGLASQEGDFSASEVWYPGGVVNRVPYPSPSCVKSEMGPWMENYSGPYGDMRLDSTRDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGENSSAGSPTEDPSQKMTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,4.549999989408299 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+CC(C)c1cccc(c1)-c1cnc(C)nc1OC[C@H]1C[C@@H]1c1ccc(C)cn1,MRIEERKSQHLTGLTDEKVKAYLSLHPQVLDEFVSESVSAETVEKWLKRKNNKSEDESAPKEVSRYQDTNMQGVVYELNSYIEQRLDTGGDNQLLLYELSSIIKIATKADGFALYFLGECNNSLCIFTPPGIKEGKPRLIPAGPITQGTTVSAYVAKSRKTLLVEDILGDERFPRGTGLESGTRIQSVLCLPIVTAIGDLIGILELYRHWGKEAFCLSHQEVATANLAWASVAIHQVQVCRGLAKQTELNDFLLDVSKTYFDNIVAIDSLLEHIMIYAKNLVNADRCALFQVDHKNKELYSDLFDIGEEKEGKPVFKKTKEIRFSIEKGIAGQVARTGEVLNIPDAYADPRFNREVDLYTGYTTRNILCMPIVSRGSVIGVVQMVNKISGSAFSKTDENNFKMFAVFCALALHCANMYHRIRHSECIYRVTMEKLSYHSICTSEEWQGLMQFTLPVRLCKEIELFHFDIGPFENMWPGIFVYMVHRSCGTSCFELEKLCRFIMSVKKNYRRVPYHNWKHAVTVAHCMYAILQNNHTLFTDLERKGLLIACLCHDLDHRGFSNSYLQKFDHPLAALYSTSTMEQHHFSQTVSILQLEGHNIFSTLSSSEYEQVLEIIRKAIIATDLALYFGNRKQLEEMYQTGSLNLNNQSHRDRVIGLMMTACDLCSVTKLWPVTKLTANDIYAEFWAEGDEMKKLGIQPIPMMDRDKKDEVPQGQLGFYNAVAIPCYTTLTQILPPTEPLLKACRDNLSQWEKVIRGEETATWISSPSVAQKAAASED,8.669586226650809 +C[C@]1(O)CCN(C1)c1nc(nc2n(Cc3ncccc3Cl)nnc12)N1CCOCC1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,5.0 +CCCC[C@@H](NC(C)=O)C(=O)N[C@H]1CC(=O)NCCCC[C@H](N(C)C(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CCCNC(N)=N)N(C)C(=O)[C@@H](Cc2ccc3ccccc3c2)N(C)C(=O)[C@H](Cc2cnc[nH]2)NC1=O)C(N)=O,MNASCCLPSVQPTLPNGSEHLQAPFFSNQSSSAFCEQVFIKPEVFLSLGIVSLLENILVILAVVRNGNLHSPMYFFLCSLAVADMLVSVSNALETIMIAIVHSDYLTFEDQFIQHMDNIFDSMICISLVASICNLLAIAVDRYVTIFYALRYHSIMTVRKALTLIVAIWVCCGVCGVVFIVYSESKMVIVCLITMFFAMMLLMGTLYVHMFLFARLHVKRIAALPPADGVAPQQHSCMKGAVTITILLGVFIFCWAPFFLHLVLIITCPTNPYCICYTAHFNTYLVLIMCNSVIDPLIYAFRSLELRNTFREILCGCNGMNLG,8.096910013008056 +COC(=O)[C@@H]1C[C@H](OC(C)=O)C(=O)[C@H]2[C@@]1(C)CC[C@H]1C(=O)O[C@@H](C[C@]21C)c1nc(co1)C(=O)OC,MEPAPSAGAELQPPLFANASDAYPSACPSAGANASGPPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKMKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTRPRDGAVVCMLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDIDRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRKPCGRPDPSSFSRAREATARERVTACTPSDGPGGGAAA,5.0 +CCCOc1ccc(cc1-c1nc(CC)c(C)c(=O)[nH]1)S(=O)(=O)N1CCN(C)CC1,MERAGPSFGQQRQQQQPQQQKQQQRDQDSVEAWLDDHWDFTFSYFVRKATREMVNAWFAERVHTIPVCKEGIRGHTESCSCPLQQSPRADNSAPGTPTRKISASEFDRPLRPIVVKDSEGTVSFLSDSEKKEQMPLTPPRFDHDEGDQCSRLLELVKDISSHLDVTALCHKIFLHIHGLISADRYSLFLVCEDSSNDKFLISRLFDVAEGSTLEEVSNNCIRLEWNKGIVGHVAALGEPLNIKDAYEDPRFNAEVDQITGYKTQSILCMPIKNHREEVVGVAQAINKKSGNGGTFTEKDEKDFAAYLAFCGIVLHNAQLYETSLLENKRNQVLLDLASLIFEEQQSLEVILKKIAATIISFMQVQKCTIFIVDEDCSDSFSSVFHMECEELEKSSDTLTREHDANKINYMYAQYVKNTMEPLNIPDVSKDKRFPWTTENTGNVNQQCIRSLLCTPIKNGKKNKVIGVCQLVNKMEENTGKVKPFNRNDEQFLEAFVIFCGLGIQNTQMYEAVERAMAKQMVTLEVLSYHASAAEEETRELQSLAAAVVPSAQTLKITDFSFSDFELSDLETALCTIRMFTDLNLVQNFQMKHEVLCRWILSVKKNYRKNVAYHNWRHAFNTAQCMFAALKAGKIQNKLTDLEILALLIAALSHDLDHRGVNNSYIQRSEHPLAQLYCHSIMEHHHFDQCLMILNSPGNQILSGLSIEEYKTTLKIIKQAILATDLALYIKRRGEFFELIRKNQFNLEDPHQKELFLAMLMTACDLSAITKPWPIQQRIAELVATEFFDQGDRERKELNIEPTDLMNREKKNKIPSMQVGFIDAICLQLYEALTHVSEDCFPLLDGCRKNRQKWQALAEQQEKMLINGESGQAKRN,7.886056647693163 +CC(C)(C)NS(=O)(=O)c1ccc(-c2sc(nc2CC2CCCCC2)C(=O)N[C@H]2C[C@@H](C2)C(O)=O)c(c1)C(F)(F)F,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,7.920818753952375 +OCC1O[C@@]2(NC(=O)NC2=O)C(O)[C@@H](O)[C@@H]1O,MAKPLTDSEKRKQISVRGLAGLGDVAEVRKSFNRHLHFTLVKDRNVATPRDYFFALAHTVRDHLVGRWIRTQQHYYERDPKRIYYLSLEFYMGRTLQNTMVNLGLQNACDEAIYQLGLDLEELEEIEEDAGLGNGGLGRLAACFLDSMATLGLAAYGYGIRYEFGIFNQKIVNGWQVEEADDWLRYGNPWEKARPEYMLPVHFYGRVEHTPDGVKWLDTQVVLAMPYDTPVPGYKNNTVNTMRLWSAKAPNDFKLQDFNVGDYIEAVLDRNLAENISRVLYPNDNFFEGKELRLKQEYFVVAATLQDIIRRFKSSKFGCRDPVRTCFETFPDKVAIQLNDTHPALSIPELMRILVDVEKVDWDKAWEITKKTCAYTNHTVLPEALERWPVSMFEKLLPRHLEIIYAINQRHLDHVAALFPGDVDRLRRMSVIEEGDCKRINMAHLCVIGSHAVNGVARIHSEIVKQSVFKDFYELEPEKFQNKTNGITPRRWLLLCNPGLADTIVEKIGEEFLTDLSQLKKLLPLVSDEVFIRDVAKVKQENKLKFSAFLEKEYKVKINPSSMFDVHVKRIHEYKRQLLNCLHVVTLYNRIKRDPAKAFVPRTVMIGGKAAPGYHMAKLIIKLVTSIGDVVNHDPVVGDRLKVIFLENYRVSLAEKVIPAADLSQQISTAGTEASGTGNMKFMLNGALTIGTMDGANVEMAEEAGAENLFIFGLRVEDVEALDRKGYNAREYYDHLPELKQAVDQISSGFFSPKEPDCFKDIVNMLMHHDRFKVFADYEAYMQCQAQVDQLYRNPKEWTKKVIRNIACSGKFSSDRTITEYAREIWGVEPSDLQIPPPNIPRD,5.376750709602099 +COc1cc(NC(=O)c2cccs2)c(OC)cc1NC(=O)CCn1nnc2ccccc12,MWCIVLFSLLAWVYAEPTMYGEILSPNYPQAYPSEVEKSWDIEVPEGYGIHLYFTHLDIELSENCAYDSVQIISGDTEEGRLCGQRSSNNPHSPIVEEFQVPYNKLQVIFKSDFSNEERFTGFAAYYVATDINECTDFVDVPCSHFCNNFIGGYFCSCPPEYFLHDDMKNCGVNCSGDVFTALIGEIASPNYPKPYPENSRCEYQIRLEKGFQVVVTLRREDFDVEAADSAGNCLDSLVFVAGDRQFGPYCGHGFPGPLNIETKSNALDIIFQTDLTGQKKGWKLRYHGDPMPCPKEDTPNSVWEPAKAKYVFRDVVQITCLDGFEVVEGRVGATSFYSTCQSNGKWSNSKLKCQPVDCGIPESIENGKVEDPESTLFGSVIRYTCEEPYYYMENGGGGEYHCAGNGSWVNEVLGPELPKCVPVCGVPREPFEEKQRIIGGSDADIKNFPWQVFFDNPWAGGALINEYWVLTAAHVVEGNREPTMYVGSTSVQTSRLAKSKMLTPEHVFIHPGWKLLEVPEGRTNFDNDIALVRLKDPVKMGPTVSPICLPGTSSDYNLMDGDLGLISGWGRTEKRDRAVRLKAARLPVAPLRKCKEVKVEKPTADAEAYVFTPNMICAGGEKGMDSCKGDSGGAFAVQDPNDKTKFYAAGLVSWGPQCGTYGLYTRVKNYVDWIMKTMQENSTPRED,4.301029995663981 +Cc1sc(N=NCCCSc2ccc(Cl)cc2)nc1O,MSGWARALLLAAVLVVMACLVPAATASLHAEETLTSQFAEFKQKHGRVYESAAEEAFRLSVFRENLFLARLHAAANPHATFGVTPFSDLTREEFRSRYHNGAAHFAAAQERARVPVKVEVVGAPAAVDWRARGAVTAVKDQGQCGSCWAFSAIGNVECQWFLAGHPLTNLSEQMLVSCDKTDSGCSGGLMNNAFEWIVQENNGAVYTEDSYPYASGEGISPPCTTSGHTVGATITGHVELPQDEAQIAAWLAVNGPVAVAVDASSWMTYTGGVMTSCVSEQLDHGVLLVGYNDSAAVPYWIIKNSWTTQWGEEGYIRIAKGSNQCLVKEEASSAVVGGPGPTPEPTTTTTTSAPGPSPSYFVQMSCTDAACIVGCENVTLPTGQCLLTTSGVSAIVTCGAETLTEEVFLTSTHCSGPSVRSSVPLNKCNRLLRGSVEFFCGSSSSGRLADVDRQRRHQPYHSRHRRL,6.698970004336019 +CC(C(NC(=O)N1CCC(CC1)n1c2ccccc2[nH]c1=O)C(=O)NCC1CCCC(CN)C1)c1c[nH]c2ccccc12,MFPNGTASSPSSSPSPSPGSCGEGGGSRGPGAGAADGMEEPGRNASQNGTLSEGQGSAILISFIYSVVCLVGLCGNSMVIYVILRYAKMKTATNIYILNLAIADELLMLSVPFLVTSTLLRHWPFGALLCRLVLSVDAVNMFTSIYCLTVLSVDRYVAVVHPIKAARYRRPTVAKVVNLGVWVLSLLVILPIVVFSRTAANSDGTVACNMLMPEPAQRWLVGFVLYTFLMGFLLPVGAICLCYVLIIAKMRMVALKAGWQQRKRSERKITLMVMMVVMVFVICWMPFYVVQLVNVFAEQDDATVSQLSVILGYANSCANPILYGFLSDNFKRSFQRILCLSWMDNAAEEPVDYYATALKSRAYSVEDFQPENLESGGVFRNGTCTSRITTL,5.559090917934782 +CC[C@H](C)[C@H](NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@@H](NC(=O)[C@@H](N)CCCCN)[C@@H](C)O)C(=O)N[C@@H](CO)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](C(C)C)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CC(C)C)[C@H](O)CC(=O)N[C@@H](CC(O)=O)C(=O)N[C@@H](C)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](Cc1ccccc1)C(O)=O,MAQALPWLLLWMGAGVLPAHGTQHGIRLPLRSGLGGAPLGLRLPRETDEEPEEPGRRGSFVEMVDNLRGKSGQGYYVEMTVGSPPQTLNILVDTGSSNFAVGAAPHPFLHRYYQRQLSSTYRDLRKGVYVPYTQGKWEGELGTDLVSIPHGPNVTVRANIAAITESDKFFINGSNWEGILGLAYAEIARPDDSLEPFFDSLVKQTHVPNLFSLQLCGAGFPLNQSEVLASVGGSMIIGGIDHSLYTGSLWYTPIRREWYYEVIIVRVEINGQDLKMDCKEYNYDKSIVDSGTTNLRLPKKVFEAAVKSIKAASSTEKFPDGFWLGEQLVCWQAGTTPWNIFPVISLYLMGEVTNQSFRITILPQQYLRPVEDVATSQDDCYKFAISQSSTGTVMGAVIMEGFYVVFDRARKRIGFAVSACHVHDEFRTAAVEGPFVTLDMEDCGYNIPQTDESTLMTIAYVMAAICALFMLPLCLMVCQWRCLRCLRQQHDDFADDISLLK,3.6989700043360187 +N#Cc1cnc(NCCCc2ccncc2)nc1-n1cnc2ccccc12,MVSSQKLEKPIEMGSSEPLPIADGDRRRKKKRRGRATDSLPGKFEDMYKLTSELLGEGAYAKVQGAVSLQNGKEYAVKIIEKQAGHSRSRVFREVETLYQCQGNKNILELIEFFEDDTRFYLVFEKLQGGSILAHIQKQKHFNEREASRVVRDVAAALDFLHTKDKVSLCHLGWSAMAPSGLTAAPTSLGSSDPPTSASQVAGTTGIAHRDLKPENILCESPEKVSPVKICDFDLGSGMKLNNSCTPITTPELTTPCGSAEYMAPEVVEVFTDQATFYDKRCDLWSLGVVLYIMLSGYPPFVGHCGADCGWDRGEVCRVCQNKLFESIQEGKYEFPDKDWAHISSEAKDLISKLLVRDAKQRLSAAQVLQHPWVQGQAPEKGLPTPQVLQRNSSTMDLTLFAAEAIALNRQLSQHEENELAEEPEALADGLCSMKLSPPCKSRLARRRALAQAGRGEDRSPPTAL,5.0 +COc1ccc(Nc2nccc(n2)-c2nc3ccccc3n2C)cc1,MQSKVLLAVALWLCVETRAASVGLPSVSLDLPRLSIQKDILTIKANTTLQITCRGQRDLDWLWPNNQSGSEQRVEVTECSDGLFCKTLTIPKVIGNDTGAYKCFYRETDLASVIYVYVQDYRSPFIASVSDQHGVVYITENKNKTVVIPCLGSISNLNVSLCARYPEKRFVPDGNRISWDSKKGFTIPSYMISYAGMVFCEAKINDESYQSIMYIVVVVGYRIYDVVLSPSHGIELSVGEKLVLNCTARTELNVGIDFNWEYPSSKHQHKKLVNRDLKTQSGSEMKKFLSTLTIDGVTRSDQGLYTCAASSGLMTKKNSTFVRVHEKPFVAFGSGMESLVEATVGERVRIPAKYLGYPPPEIKWYKNGIPLESNHTIKAGHVLTIMEVSERDTGNYTVILTNPISKEKQSHVVSLVVYVPPQIGEKSLISPVDSYQYGTTQTLTCTVYAIPPPHHIHWYWQLEEECANEPSQAVSVTNPYPCEEWRSVEDFQGGNKIEVNKNQFALIEGKNKTVSTLVIQAANVSALYKCEAVNKVGRGERVISFHVTRGPEITLQPDMQPTEQESVSLWCTADRSTFENLTWYKLGPQPLPIHVGELPTPVCKNLDTLWKLNATMFSNSTNDILIMELKNASLQDQGDYVCLAQDRKTKKRHCVVRQLTVLERVAPTITGNLENQTTSIGESIEVSCTASGNPPPQIMWFKDNETLVEDSGIVLKDGNRNLTIRRVRKEDEGLYTCQACSVLGCAKVEAFFIIEGAQEKTNLEIIILVGTAVIAMFFWLLLVIILRTVKRANGGELKTGYLSIVMDPDELPLDEHCERLPYDASKWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGATHSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNLSTYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSASSGFVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGMEFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDARLPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFCRRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQANAQQDGKDYIVLPISETLSMEEDSGLSLPTSPVSCMEEEEVCDPKFHYDNTAGISQYLQNSKRKSRPVSVKTFEDIPLEEPEVKVIPDDNQTDSGMVLASEELKTLEDRTKLSPSFGGMVPSKSRESVASEGSNQTSGYQSGYHSDDTDTTVYSSEEAELLKLIEIGVQTGSTAQILQPDSGTTLSSPPV,4.356547323513812 +CN1CCN(CC1)C(=S)C(=O)Nc1ccc(Br)cc1,MEYETSLKCLDEIRCVNNVKYMETEDLTDFNKKSAYYICKEIYEKQLSNENGYVVIGLSGGKTPIDVYKNMCAIKDIKIDKNKLIFFIIDERYKNDDHKFSNYNNIKFLFDELNINKETQLYKPDTKKDLVSCIRDYNEQIKSMIEKYKKIDIVILGMGSDFHIASLFPNVYYNIYMNNYQNNYIYEDNETIRSLNADNNVNLSLLNEQVYFTTTNNFDVRKRITVSLNLLSNSTSKIFLLNTADKLNLWKNMLLNFYVNPNYNLYPAFKMIDSSNTTVIACGHKNYSKMLEDLYVQKDEALSPISNNNVENKNELLTIVIFGCSGDLAKKKIYPALFKLFCNNLLPKNIIIIGFARTGQDFESFFNKIAIYLKISLNSYKNLSVFEKAERLNSFKSKCRYFIGNYLSPESFENFDVYITQEERIALGCCGQKGNEKHKQVNVTSQFPNNHTSINIINNIDNGCESPMLTDSPKRYPCSSSYSSTSGTAVCPYSSQHDVKPSNNGCPYLSSQANTSDSSGCPYISYHTNKSGHLGCPYTITRMLYLALPPHVFVSTLQNYKKYCLNKNRINKILLEKPFGKDLESFKILSKQILETFPEKNIYRIDHYLGKDMVSGLLKLKFTNIFLLSLMNRHFIKCIKITLKETKGVYGRGQYFDPYGIIRDVMQNHMLQLLALITMEHPTDLNDKSIQNEKIKILKSIASIKLEDTVIGQYVKSNNDDTNNNINSNISENASIDKSKINHSYHDDPHVDPNSITPTFCACVLYINSINWHGVPIILKAGKGLNNDICEIKIQFHNIMGSSDESMYNNEFVIILQPVEGIYLKLMIKKMGSEEMEEVQLNLSLNENNNKAYVPEAYETLLSECYKGYKRKFISDEELYESWRIFTPLLNELQEKHIKPLSYPFGSSGPQEAYDLVRKYYNYGKNYATTAKFCRKSSYYDDSLFDNMRE,4.168130225719498 +NC(=O)c1cc(sc1Nc1cccc(n1)C(F)(F)F)-c1ccccc1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,6.050122295963125 +Cc1cc(N2CCN(CC2)C(=O)c2ccco2)n2nc(cc2n1)-c1cccc(Cl)c1,MDREPVTVRSYANIAIIKYWGKKKEKEMVPATSSISLTLENMYTETTLSPLPANVTADEFYINGQLQNEVEHAKMSKIIDRYRPAGEGFVRIDTQNNMPTAAGLSSSSSGLSALVKACNAYFKLGLDRSQLAQEAKFASGSSSRSFYGPLGAWDKDSGEIYPVETDLKLAMIMLVLEDKKKPISSRDGMKLCVETSTTFDDWVRQSEKDYQDMLIYLKENDFAKIGELTEKNALAMHATTKTASPAFSYLTDASYEAMDFVRQLREKGEACYFTMDAGPNVKVFCQEKDLEHLSEIFGQRYRLIVSKTKDLSQDDCC,2.0000434316198072 +C[N+]1(CC2CC2)CC[C@@]23[C@H]4Oc5c2c(C[C@@H]1[C@]3(O)CCC4=O)ccc5O,MEPAPSAGAELQPPLFANASDAYPSACPSAGANASGPPGARSASSLALAIAITALYSAVCAVGLLGNVLVMFGIVRYTKMKTATNIYIFNLALADALATSTLPFQSAKYLMETWPFGELLCKAVLSIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPAKAKLINICIWVLASGVGVPIMVMAVTRPRDGAVVCMLQFPSPSWYWDTVTKICVFLFAFVVPILIITVCYGLMLLRLRSVRLLSGSKEKDRSLRRITRMVLVVVGAFVVCWAPIHIFVIVWTLVDIDRRDPLVVAALHLCIALGYANSSLNPVLYAFLDENFKRCFRQLCRKPCGRPDPSSFSRAREATARERVTACTPSDGPGGGAAA,6.300162274132754 +FC(F)(F)Oc1ccc(\C=C\C(=O)c2ccc[nH]2)cc1,MALSQSVPFSATELLLASAIFCLVFWVLKGLRPRVPKGLKSPPEPWGWPLLGHVLTLGKNPHLALSRMSQRYGDVLQIRIGSTPVLVLSRLDTIRQALVRQGDDFKGRPDLYTSTLITDGQSLTFSTDSGPVWAARRRLAQNALNTFSIASDPASSSSCYLEEHVSKEAKALISRLQELMAGPGHFDPYNQVVVSVANVIGAMCFGQHFPESSDEMLSLVKNTHEFVETASSGNPLDFFPILRYLPNPALQRFKAFNQRFLWFLQKTVQEHYQDFDKNSVRDITGALFKHSKKGPRASGNLIPQEKIVNLVNDIFGAGFDTVTTAISWSLMYLVTKPEIQRKIQKELDTVIGRERRPRLSDRPQLPYLEAFILETFRHSSFLPFTIPHSTTRDTTLNGFYIPKKCCVFVNQWQVNHDPELWEDPSEFRPERFLTADGTAINKPLSEKMMLFGMGKRRCIGEVLAKWEIFLFLAILLQQLEFSVPPGVKVDLTPIYGLTMKHARCEHVQARLRFSIN,4.698970004336019 +Cc1cc(no1)N1C(C(C(=O)c2ccco2)C(=O)C1=O)c1cccc(Oc2ccccc2)c1,APITAYAQQTRGLLGCIITGLTGRDKNQVEGEVQIVSTAAQTFLATCINGVCWTVYHGAGTRTIASSKGPVIQMYTNVDQDLVGWPAPQGARSLTPCTCGSSDLYLVTRHADVIPVRRRGDGRGSLLSPRPISYLKGSSGGPLLCPAGHAVGIFRAAVCTRGVAKAVDFIPVEGLETTMRSPVFSDNSSPPAVPQSYQVAHLHAPTGSGKSTKVPAAYAAQGYKVLVLNPSVAATLGFGAYMSKAHGIDPNIRTGVRTITTGSPITYSTYGKFLADGGCSGSAYDIIICDECHSTDATSILGIGTVLDQAETAGARLTVLATATPPGSVTVPHPNIEEVALSTTGEIPFYGKAIPLEAIKGGRHLIFCHSKKKCDELAAKLVALGVNAVAYYRGLDVSVIPASGDVVVVATDALMTGFTGDFDSVIDCNTCVTQTVDFSLDPTFTIETTTLPQDAVSRTQRRGRTGRGKPGIYRFVTPGERPSGMFDSSVLCECYDAGCAWYELTPAETTVRLRAYMNTPGLPVCQDHLEFWEGVFTGLTHIDAHFLSQTKQSGENLPYLVAYQATVCARAQAPPPSWDQMWKCLIRLKPTLHGPTPLLYRLGAVQNEITLTHPITKYIMTCMSADLEVVT,5.577738549186397 +COc1cccc(Oc2ccc(cc2)\N=c2/[nH]c(=O)n(C[C@H](C)C(O)=O)c(=O)n2Cc2ccc(C)cc2)n1,MNCISDFFTYETTKSVVVKSWTIGIINRVVQLLIISYFVGWVFLHEKAYQVRDTAIESSVVTKVKGSGLYANRVMDVSDYVTPPQGTSVFVIITKMIVTENQMQGFCPESEEKYRCVSDSQCGPERLPGGGILTGRCVNYSSVLRTCEIQGWCPTEVDTVETPIMMEAENFTIFIKNSIRFPLFNFEKGNLLPNLTARDMKTCRFHPDKDPFCPILRVGDVVKFAGQDFAKLARTGGVLGIKIGWVCDLDKAWDQCIPKYSFTRLDSVSEKSSVSPGYNFRFAKYYKMENGSEYRTLLKAFGIRFDVLVYGNAGKFNIIPTIISSVAAFTSVGVGTVLCDIILLNFLKGADQYKAKKFEEVNETTLKIAALTNPVYPSDQTTAEKQSTDSGAFSIGH,8.0 +CC[C@H]1N(C2CCCC2)c2nc(Nc3ccc(cc3O)C(=O)NC3CCCC3)ncc2N(C)C1=O,MSAAVTAGKLARAPADPGKAGVPGVAAPGAPAAAPPAKEIPEVLVDPRSRRRYVRGRFLGKGGFAKCFEISDADTKEVFAGKIVPKSLLLKPHQREKMSMEISIHRSLAHQHVVGFHGFFEDNDFVFVVLELCRRRSLLELHKRRKALTEPEARYYLRQIVLGCQYLHRNRVIHRDLKLGNLFLNEDLEVKIGDFGLATKVEYDGERKKTLCGTPNYIAPEVLSKKGHSFEVDVWSIGCIMYTLLVGKPPFETSCLKETYLRIKKNEYSIPKHINPVAASLIQKMLQTDPTARPTINELLNDEFFTSGYIPARLPITCLTIPPRFSIAPSSLDPSNRKPLTVLNKGLENPLPERPREKEEPVVRETGEVVDCHLSDMLQQLHSVNASKPSERGLVRQEEAEDPACIPIFWVSKWVDYSDKYGLGYQLCDNSVGVLFNDSTRLILYNDGDSLQYIERDGTESYLTVSSHPNSLMKKITLLKYFRNYMSEHLLKAGANITPREGDELARLPYLRTWFRTRSAIILHLSNGSVQINFFQDHTKLILCPLMAAVTYIDEKRDFRTYRLSLLEEYGCCKELASRLRYARTMVDKLLSSRSASNRLKAS,8.229147988357855 +CN1CCc2ccccc2Cc2c[nH]c3cccc(C1)c23,MRTLNTSAMDGTGLVVERDFSVRILTACFLSLLILSTLLGNTLVCAAVIRFRHLRSKVTNFFVISLAVSDLLVAVLVMPWKAVAEIAGFWPFGSFCNIWVAFDIMCSTASILNLCVISVDRYWAISSPFRYERKMTPKAAFILISVAWTLSVLISFIPVQLSWHKAKPTSPSDGNATSLAETIDNCDSSLSRTYAISSSVISFYIPVAIMIVTYTRIYRIAQKQIRRIAALERAAVHAKNCQTTTGNGKPVECSQPESSFKMSFKRETKVLKTLSVIMGVFVCCWLPFFILNCILPFCGSGETQPFCIDSNTFDVFVWFGWANSSLNPIIYAFNADFRKAFSTLLGCYRLCPATNNAIETVSINNNGAAMFSSHHEPRGSISKECNLVYLIPHAVGSSEDLKKEEAAGIARPLEKLSPALSVILDYDTDVSLEKIQPITQNGQHPT,5.0 +CC(=O)C1CCN(CC1)C(=O)[C@@H](COCc1ccccc1)NC(=O)Nc1cccc(C)c1,MELLKLNRSVQGTGPGPGASLCRPGAPLLNSSSVGNLSCEPPRIRGAGTRELELAIRITLYAVIFLMSVGGNMLIIVVLGLSRRLRTVTNAFLLSLAVSDLLLAVACMPFTLLPNLMGTFIFGTVICKAVSYLMGVSVSVSTLSLVAIALERYSAICRPLQARVWQTRSHAARVIVATWLLSGLLMVPYPVYTVVQPVGPRVLQCVHRWPSARVRQTWSVLLLLLLFFIPGVVMAVAYGLISRELYLGLRFDGDSDSDSQSRVRNQGGLPGAVHQNGRCRPETGAVGEDSDGCYVQLPRSRPALELTALTAPGPGSGSRPTQAKLLAKKRVVRMLLVIVVLFFLCWLPVYSANTWRAFDGPGAHRALSGAPISFIHLLSYASACVNPLVYCFMHRRFRQACLETCARCCPRPPRARPRALPDEDPPTPSIASLSRLSYTTISTLGPG,5.161150909262744 +CCN1c2nc(OC)ccc2N(C)C(=O)c2cccnc12,PISPIETVPVKLKPGMDGPKVKQWPLTEEKIKALVEICTEMEKEGKISKIGPENPYNTPVFAIKKKDSTKWRKLVDFRELNKRTQDFWEVQLGIPHPAGLKKKKSVTVLDVGDAYFSVPLDEDFRKYTAFTIPSINNETPGIRYQYNVLPQGWKGSPAIFQSSMTKILEPFKKQNPDIVIYQYMDDLYVGSDLEIGQHRTKIEELRQHLLRWGLTTPDKKHQKEPPFLWMGYELHPDKWTVQPIVLPEKDSWTVNDIQKLVGKLNWASQIYPGIKVRQLCKLLRGTKALTEVIPLTEEAELELAENREILKEPVHGVYYDPSKDLIAEIQKQGQGQWTYQIYQEPFKNLKTGKYARMRGAHTNDVKQLTEAVQKITTESIVIWGKTPKFKLPIQKETWETWWTEYWQATWIPEWEFVNTPPLVKLWYQLEKEPIVGAETFYVDGAANRETKLGKAGYVTNKGRQKVVPLTNTTNQKTELQAIYLALQDSGLEVNIVTDSQYALGIIQAQPDKSESELVNQIIEQLIKKEKVYLAWVPAHKGIGGNEQVDKLVSAGI,7.3979400086720375 +OC(=O)CC1CC1c1ccc(OCCc2ccc3CCCNc3n2)c(F)c1,MPRAPAPLYACLLGLCALLPRLAGLNICTSGSATSCEECLLIHPKCAWCSKEDFGSPRSITSRCDLRANLVKNGCGGEIESPASSFHVLRSLPLSSKGSGSAGWDVIQMTPQEIAVNLRPGDKTTFQLQVRQVEDYPVDLYYLMDLSLSMKDDLDNIRSLGTKLAEEMRKLTSNFRLGFGSFVDKDISPFSYTAPRYQTNPCIGYKLFPNCVPSFGFRHLLPLTDRVDSFNEEVRKQRVSRNRDAPEGGFDAVLQAAVCKEKIGWRKDALHLLVFTTDDVPHIALDGKLGGLVQPHDGQCHLNEANEYTASNQMDYPSLALLGEKLAENNINLIFAVTKNHYMLYKNFTALIPGTTVEILDGDSKNIIQLIINAYNSIRSKVELSVWDQPEDLNLFFTATCQDGVSYPGQRKCEGLKIGDTASFEVSLEARSCPSRHTEHVFALRPVGFRDSLEVGVTYNCTCGCSVGLEPNSARCNGSGTYVCGLCECSPGYLGTRCECQDGENQSVYQNLCREAEGKPLCSGRGDCSCNQCSCFESEFGKIYGPFCECDNFSCARNKGVLCSGHGECHCGECKCHAGYIGDNCNCSTDISTCRGRDGQICSERGHCLCGQCQCTEPGAFGEMCEKCPTCPDACSTKRDCVECLLLHSGKPDNQTCHSLCRDEVITWVDTIVKDDQEAVLCFYKTAKDCVMMFTYVELPSGKSNLTVLREPECGNTPNAMTILLAVVGSILLVGLALLAIWKLLVTIHDRREFAKFQSERSRARYEMASNPLYRKPISTHTVDFTFNKFNKSYNGTVD,8.522878745280337 +Cc1ccc(NC(=O)c2cccc(c2)-n2cc(NC(=O)Nc3cccc(F)c3)cn2)cn1,MSRSKRDNNFYSVEIGDSTFTVLKRYQNLKPIGSGAQGIVCAAYDAILERNVAIKKLSRPFQNQTHAKRAYRELVLMKCVNHKNIIGLLNVFTPQKSLEEFQDVYIVMELMDANLCQVIQMELDHERMSYLLYQMLCGIKHLHSAGIIHRDLKPSNIVVKSDCTLKILDFGLARTAGTSFMMTPYVVTRYYRAPEVILGMGYKENVDLWSVGCIMGEMVCHKILFPGRDYIDQWNKVIEQLGTPCPEFMKKLQPTVRTYVENRPKYAGYSFEKLFPDVLFPADSEHNKLKASQARDLLSKMLVIDASKRISVDEALQHPYINVWYDPSEAEAPPPKIPDKQLDEREHTIEEWKELIYKEVMDLEERTKNGVIRGQPSPLGAAVINGSQHPSSSSSVNDVSSMSTDPTLASDTDSSLEAAAGPLGCCR,6.185086818724926 +CC(=O)NCCCC[C@@H]1NC(=O)C[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](Cc2cccc3ccccc23)NC(=O)[C@H](CCCCCC(O)=O)NC1=O,MAQTQGTRRKVCYYYDGDVGNYYYGQGHPMKPHRIRMTHNLLLNYGLYRKMEIYRPHKANAEEMTKYHSDDYIKFLRSIRPDNMSEYSKQMQRFNVGEDCPVFDGLFEFCQLSTGGSVASAVKLNKQQTDIAVNWAGGLHHAKKSEASGFCYVNDIVLAILELLKYHQRVLYIDIDIHHGDGVEEAFYTTDRVMTVSFHKYGEYFPGTGDLRDIGAGKGKYYAVNYPLRDGIDDESYEAIFKPVMSKVMEMFQPSAVVLQCGSDSLSGDRLGCFNLTIKGHAKCVEFVKSFNLPMLMLGGGGYTIRNVARCWTYETAVALDTEIPNELPYNDYFEYFGPDFKLHISPSNMTNQNTNEYLEKIKQRLFENLRMLPHAPGVQMQAIPEDAIPEESGDEDEDDPDKRISICSSDKRIACEEEFSDSEEEGEGGRKNSSNFKKAKRVKTEDEKEKDPEEKKEVTEEEKTKEEKPEAKGVKEEVKLA,6.540607512240769 +CCN1CCC[C@H](C1)c1cccc(O)c1,MPWAVGRRWAWITLFLTIVAVLIQAVWLWLGTQSFVFQREEIAQLARQYAGLDHELAFSRLIVELRRLHPGHVLPDEELQWVFVNAGGWMGAMCLLHASLSEYVLLFGTALGSHGHSGRYWAEISDTIISGTFHQWREGTTKSEVYYPGETVVHGPGEATAVEWGPNTWMVEYGRGVIPSTLAFALSDTIFSTQDFLTLFYTLRAYARGLRLELTTYLFGQDP,5.987162775294828 +CCOc1cc(-c2ccc(nc2)N2CCC(CN3CCN(CC)CC3)(CC2)NC(=O)OC)c2c(cnn2c1)C#N,MAKATSGAAGLRLLLLLLLPLLGKVALGLYFSRDAYWEKLYVDQAAGTPLLYVHALRDAPEEVPSFRLGQHLYGTYRTRLHENNWICIQEDTGLLYLNRSLDHSSWEKLSVRNRGFPLLTVYLKVFLSPTSLREGECQWPGCARVYFSFFNTSFPACSSLKPRELCFPETRPSFRIRENRPPGTFHQFRLLPVQFLCPNISVAYRLLEGEGLPFRCAPDSLEVSTRWALDREQREKYELVAVCTVHAGAREEVVMVPFPVTVYDEDDSAPTFPAGVDTASAVVEFKRKEDTVVATLRVFDADVVPASGELVRRYTSTLLPGDTWAQQTFRVEHWPNETSVQANGSFVRATVHDYRLVLNRNLSISENRTMQLAVLVNDSDFQGPGAGVLLLHFNVSVLPVSLHLPSTYSLSVSRRARRFAQIGKVCVENCQAFSGINVQYKLHSSGANCSTLGVVTSAEDTSGILFVNDTKALRRPKCAELHYMVVATDQQTSRQAQAQLLVTVEGSYVAEEAGCPLSCAVSKRRLECEECGGLGSPTGRCEWRQGDGKGITRNFSTCSPSTKTCPDGHCDVVETQDINICPQDCLRGSIVGGHEPGEPRGIKAGYGTCNCFPEEEKCFCEPEDIQDPLCDELCRTVIAAAVLFSFIVSVLLSAFCIHCYHKFAHKPPISSAEMTFRRPAQAFPVSYSSSGARRPSLDSMENQVSVDAFKILEDPKWEFPRKNLVLGKTLGEGEFGKVVKATAFHLKGRAGYTTVAVKMLKENASPSELRDLLSEFNVLKQVNHPHVIKLYGACSQDGPLLLIVEYAKYRSLRGFLRESRKVGPGYLGSGGSRNSSSLDHPDERALTMGDLISFAWQISQGMQYLAEMKLVHRDLAARNILVAEGRKMKISDFGLSRDVYEEDSYVKRSQGRIPVKWMAIESLFDHIYTTQSDVWSFGVLLWEIVTLGGNPYPGIPPERLFNLLKTGHRMERPDNCSEEMYRLMLQCWKQEPDKRPVFADISKDLEKMMVKRRDYLDLAASTPSDSLIYDDGLSEEETPLVDCNNAPLPRALPSTWIENKLYGMSDPNWPGESPVPLTRADGTNTGFPRYPNDSVYANWMLSPSAAKLMDTFDS,6.33913452199613 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+COc1ccccc1N1CCN(CCCCNC(=O)c2cc3ccccc3s2)CC1,MASLSQLSSHLNYTCGAENSTGASQARPHAYYALSYCALILAIVFGNGLVCMAVLKERALQTTTNYLVVSLAVADLLVATLVMPWVVYLEVTGGVWNFSRICCDVFVTLDVMMCTASILNLCAISIDRYTAVVMPVHYQHGTGQSSCRRVALMITAVWVLAFAVSCPLLFGFNTTGDPTVCSISNPDFVIYSSVVSFYLPFGVTVLVYARIYVVLKQRRRKRILTRQNSQCNSVRPGFPQQTLSPDPAHLELKRYYSICQDTALGGPGFQERGGELKREEKTRNSLSPTIAPKLSLEVRKLSNGRLSTSLKLGPLQPRGVPLREKKATQMVAIVLGAFIVCWLPFFLTHVLNTHCQTCHVSPELYSATTWLGYVNSALNPVIYTTFNIEFRKAFLKILSC,9.657577319177793 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+C[C@]12O[C@H](C[C@]1(O)CO)n1c3ccccc3c3c4C(=O)NCc4c4c5ccccc5n2c4c13,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,7.795880017344075 +CCCCCCCC(=O)OC[C@@H](COP(O)(O)=S)OC(=O)CCCCCCC,MARRSSFQSCQIISLFTFAVGVNICLGFTAHRIKRAEGWEEGPPTVLSDSPWTNISGSCKGRCFELQEAGPPDCRCDNLCKSYTSCCHDFDELCLKTARGWECTKDRCGEVRNEENACHCSEDCLARGDCCTNYQVVCKGESHWVDDDCEEIKAAECPAGFVRPPLIIFSVDGFRASYMKKGSKVMPNIEKLRSCGTHSPYMRPVYPTKTFPNLYTLATGLYPESHGIVGNSMYDPVFDATFHLRGREKFNHRWWGGQPLWITATKQGVKAGTFFWSVVIPHERRILTILQWLTLPDHERPSVYAFYSEQPDFSGHKYGPFGPEMTNPLREIDKIVGQLMDGLKQLKLHRCVNVIFVGDHGMEDVTCDRTEFLSNYLTNVDDITLVPGTLGRIRSKFSNNAKYDPKAIIANLTCKKPDQHFKPYLKQHLPKRLHYANNRRIEDIHLLVERRWHVARKPLDVYKKPSGKCFFQGDHGFDNKVNSMQTVFVGYGSTFKYKTKVPPFENIELYNVMCDLLGLKPAPNNGTHGSLNHLLRTNTFRPTMPEEVTRPNYPGIMYLQSDFDLGCTCDDKVEPKNKLDELNKRLHTKGSTEERHLLYGRPAVLYRTRYDILYHTDFESGYSEIFLMPLWTSYTVSKQAEVSSVPDHLTSCVRPDVRVSPSFSQNCLAYKNDKQMSYGFLFPPYLSSSPEAKYDAFLVTNMVPMYPAFKRVWNYFQRVLVKKYASERNGVNVISGPIFDYDYDGLHDTEDKIKQYVEGSSIPVPTHYYSIITSCLDFTQPADKCDGPLSVSSFILPHRPDNEESCNSSEDESKWVEELMKMHTARVRDIEHLTSLDFFRKTSRSYPEILTLKTYLHTYESEI,6.138465589140962 +Cc1cccc(Nc2nc(cs2)-c2cccs2)n1,MGTNGGVIAEQSMEIETNENPDKVEEPVVRRKRVTRRRHRRIHSKNNCLTPPNSDDDPQMSTPDDPVIHSPPSIGAAPGMNGYHGSGVKLEESSGACGSPDDGLLDSSEESRRRQKTCRVCGDHATGYNFNVITCESCKAFFRRNALRPKEFKCPYSEDCEINSVSRRFCQKCRLRKCFTVGMKKEWILNEEQLRRRKNSRLNNTGTCNKRSQPGNQQSPQGPNQQPHLSPHHPGVAIYPPQPQRPLTINPMDNQMMHHMQANRPNAMPQLISPPGAQPYPLTSPVGSSASDSPPNRSLTMMHNGEKSPDGYDPNIMAHRAPPPSFNNRPKMDSGQVVLSTEEYKQLLSRIPGAQVPGLMNEEEPINKRAAYNCNGHPMPAETTPPYSAPMSDMSLSRHNSTSSGTEKNHMTHSTVSAIPGNSAQNHFDIASFGMGIVTATGGGDAAEEMYKRMNMFYENCIQSALDSPENQEPKPQEAMIPKEEYMTPTHGFQYQSDPYQVPPAERNINYQLNAAELKALDAVREAFYGMDDPMEQGRQMQSFLKANKTPADIMNIMDVTMRRFVKVAKGVPAFREVSQEGKFSLLKGGMIEMLTVRGVTRYDASTNSFKTPTIKGQNVSVNVDDMFAKLNANAQAQKAKCLEFFGFFDEEIKKNELAVYLVMLAVLFSVRSDPPMNENDVRIVTERHNHFMSLLNRYLESLFGEQARRIFERIPKALGLLNEIARNAGMLFMGTVRSGEAEELPGEFFKIK,4.170503250279817 +COc1cc2CC(CC3CCN(CCCNc4c5CCCCc5nc5cc(Cl)ccc45)CC3)Cc2cc1OC,MRPPQCLLHTPSLASPLLLLLLWLLGGGVGAEGREDAELLVTVRGGRLRGIRLKTPGGPVSAFLGIPFAEPPMGPRRFLPPEPKQPWSGVVDATTFQSVCYQYVDTLYPGFEGTEMWNPNRELSEDCLYLNVWTPYPRPTSPTPVLVWIYGGGFYSGASSLDVYDGRFLVQAERTVLVSMNYRVGAFGFLALPGSREAPGNVGLLDQRLALQWVQENVAAFGGDPTSVTLFGESAGAASVGMHLLSPPSRGLFHRAVLQSGAPNGPWATVGMGEARRRATQLAHLVGCPPGGTGGNDTELVACLRTRPAQVLVNHEWHVLPQESVFRFSFVPVVDGDFLSDTPEALINAGDFHGLQVLVGVVKDEGSYFLVYGAPGFSKDNESLISRAEFLAGVRVGVPQVSDLAAEAVVLHYTDWLHPEDPARLREALSDVVGDHNVVCPVAQLAGRLAAQGARVYAYVFEHRASTLSWPLWMGVPHGYEIEFIFGIPLDPSRNYTAEEKIFAQRLMRYWANFARTGDPNEPRDPKAPQWPPYTAGAQQYVSLDLRPLEVRRGLRAQACAFWNRFLPKLLSATDTLDEAERQWKAEFHRWSSYMVHWKNQFDHYSKQDRCSDL,8.97469413473523 +Oc1c(ccc2C[C@H]3N(CC4CC4)CC[C@@]4(CC(=O)CC[C@@]34O)c12)C(=O)NCCc1ccc(cc1)-c1cccnc1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,8.537602002101044 +COc1cccc(COC(=O)c2nn(nc2N)-c2ccccc2)c1,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,7.721246399047171 +CN1CCN(CC1)c1ccc(NC=C2C(=O)NC(=O)c3ccc(I)cc23)cc1,MATSRYEPVAEIGVGAYGTVYKARDPHSGHFVALKSVRVPNGGGGGGGLPISTVREVALLRRLEAFEHPNVVRLMDVCATSRTDREIKVTLVFEHVDQDLRTYLDKAPPPGLPAETIKDLMRQFLRGLDFLHANCIVHRDLKPENILVTSGGTVKLADFGLARIYSYQMALTPVVVTLWYRAPEVLLQSTYATPVDMWSVGCIFAEMFRRKPLFCGNSEADQLGKIFDLIGLPPEDDWPRDVSLPRGAFPPRGPRPVQSVVPEMEESGAQLLLEMLTFNPHKRISAFRALQHSYLHKDEGNPE,6.318758762624412 +CC(C)C[C@@H]1[C@H](CCCOC(=O)N(C)CCCC[C@H](NC1=O)C(=O)NCC(=O)N1CCCC1)C(=O)NO,MRQSLLFLTSVVPFVLAPRPPDDPGFGPHQRLEKLDSLLSDYDILSLSNIQQHSVRKRDLQTSTHVETLLTFSALKRHFKLYLTSSTERFSQNFKVVVVDGKNESEYTVKWQDFFTGHVVGEPDSRVLAHIRDDDVIIRINTDGAEYNIEPLWRFVNDTKDKRMLVYKSEDIKNVSRLQSPKVCGYLKVDNEELLPKGLVDREPPEELVHRVKRRADPDPMKNTCKLLVVADHRFYRYMGRGEESTTTNYLIELIDRVDDIYRNTSWDNAGFKGYGIQIEQIRILKSPQEVKPGEKHYNMAKSYPNEEKDAWDVKMLLEQFSFDIAEEASKVCLAHLFTYQDFDMGTLGLAYVGSPRANSHGGVCPKAYYSPVGKKNIYLNSGLTSTKNYGKTILTKEADLVTTHELGHNFGAEHDPDGLAECAPNEDQGGKYVMYPIAVSGDHENNKMFSNCSKQSIYKTIESKAQECFQERSNKVCGNSRVDEGEECDPGIMYLNNDTCCNSDCTLKEGVQCSDRNSPCCKNCQFETAQKKCQEAINATCKGVSYCTGNSSECPPPGNAEDDTVCLDLGKCKDGKCIPFCEREQQLESCACNETDNSCKVCCRDLSGRCVPYVDAEQKNLFLRKGKPCTVGFCDMNGKCEKRVQDVIERFWDFIDQLSINTFGKFLADNIVGSVLVFSLIFWIPFSILVHCVDKKLDKQYESLSLFHPSNVEMLSSMDSASVRIIKPFPAPQTPGRLQPAPVIPSAPAAPKLDHQRMDTIQEDPSTDSHMDEDGFEKDPFPNSSTAAKSFEDLTDHPVTRSEKAASFKLQRQNRVDSKETEC,6.3979400086720375 +OC(=O)\C=C\C(O)=O.CN(C)C1CN(C1)c1ccnc(N)n1,MERAPPDGPLNASGALAGEAAAAGGARGFSAAWTAVLAALMALLIVATVLGNALVMLAFVADSSLRTQNNFFLLNLAISDFLVGAFCIPLYVPYVLTGRWTFGRGLCKLWLVVDYLLCTSSAFNIVLISYDRFLSVTRAVSYRAQQGDTRRAVRKMLLVWVLAFLLYGPAILSWEYLSGGSSIPEGHCYAEFFYNWYFLITASTLEFFTPFLSVTFFNLSIYLNIQRRTRLRLDGAREAAGPEPPPEAQPSPPPPPGCWGCWQKGHGEAMPLHRYGVGEAAVGAEAGEATLGGGGGGGSVASPTSSSGSSSRGTERPRSLKRGSKPSASSASLEKRMKMVSQSFTQRFRLSRDRKVAKSLAVIVSIFGLCWAPYTLLMIIRAACHGHCVPDYWYETSFWLLWANSAVNPVLYPLCHHSFRRAFTKLLCPQKLKIQPHSSLEHCWK,7.301029995663981 +CC(C)CC1=C(C(=O)N(C(CO)C(O)=O)C1=O)c1ccc(OCC=C(C)C)cc1,MSTNPKPQRKTKRNTNRRPQDVKFPGGGQIVGGVYLLPRRGPRLGVRATRKTSERSQPRGRRQPIPKARRPEGRTWAQPGYPWPLYGNEGCGWAGWLLSPRGSRPSWGPTDPRRRSRNLGKVIDTLTCGFADLMGYIPLVGAPLGGAARALAHGVRVLEDGVNYATGNLPGCSFSIFLLALLSCLTVPASAYQVRNSSGLYHVTNDCPNSSVVYEAADAILHTPGCVPCVREGNASRCWVAVTPTVATRDGKLPTTQLRRHIDLLVGSATLCSALYVGDLCGSVFLVGQLFTFSPRHHWTTQDCNCSIYPGHITGHRMAWNMMMNWSPTAALVVAQLLRIPQAIMDMIAGAHWGVLAGIKYFSMVGNWAKVLVVLLLFAGVDAETHVTGGNAGRTTAGLVGLLTPGAKQNIQLINTNGSWHINSTALNCNESLNTGWLAGLFYQHKFNSSGCPERLASCRRLTDFAQGWGPISYANGSGLDERPYCWHYPPRPCGIVPAKSVCGPVYCFTPSPVVVGTTDRSGAPTYSWGANDTDVFVLNNTRPPLGNWFGCTWMNSTGFTKVCGAPPCVIGGVGNNTLLCPTDCFRKYPEATYSRCGSGPRITPRCMVDYPYRLWHYPCTINYTIFKVRMYVGGVEHRLEAACNWTRGERCDLEDRDRSELSPLLLSTTQWQVLPCSFTTLPALSTGLIHLHQNIVDVQYLYGVGSSIASWAIKWEYVVLLFLLLADARVCSCLWMMLLISQAEAALENLVILNAASLAGTHGLVSFLVFFCFAWYLKGRWVPGAVYALYGMWPLLLLLLALPQRAYALDTEVAASCGGVVLVGLMALTLSPYYKRYISWCMWWLQYFLTRVEAQLHVWVPPLNVRGGRDAVILLTCVVHPALVFDITKLLLAIFGPLWILQASLLKVPYFVRVQGLLRICALARKIAGGHYVQMAIIKLGALTGTCVYNHLAPLRDWAHNGLRDLAVAVEPVVFSRMETKLITWGADTAACGDIINGLPVSARRGQEILLGPADGMVSKGWRLLAPITAYAQQTRGLLGCIITSLTGRDKNQVEGEVQIVSTATQTFLATCINGVCWTVYHGAGTRTIASPKGPVIQTYTNVDQDLVGWPAPQGSRSLTPCTCGSSDLYLVTRHADVIPVRRRGDSRGSLLSPRPISYLKGSSGGPLLCPTGHAVGLFRAAVCTRGVAKAVDFIPVENLETTMRSPVFTDNSSPPAVPQSFQVAHLHAPTGSGKSTKVPAAYAAKGYKVLVLNPSVAATLGFGAYMSKAHGVDPNIRTGVRTITTGSPITYSTYGKFLADAGCSGGAYDIIICDECHSTDATSISGIGTVLDQAETAGARLVVLATATPPGSVTVSHPNIEEVALSTTGEIPFYGKAIPLEVIKGGRHLIFCHSKKKCDELAAKLVALGINAVAYYRGLDVSVIPTSGDVVVVSTDALMTGFTGDFDSVIDCNTCVTQTVDFSLDPTFTIETTTLPQDAVSRTQRRGRTGRGKPGIYRFVAPGERPSGMFDSSVLCECYDAGCAWYELTPAETTVRLRAYMNTPGLPVCQDHLGFWEGVFTGLTHIDAHFLSQTKQSGENFPYLVAYQATVCARAQAPPPSWDQMRKCLIRLKPTLHGPTPLLYRLGAVQNEVTLTHPITKYIMTCMSADLEVVTSTWVLVGGVLAALAAYCLSTGCVVIVGRIVLSGKPAIIPDREVLYQEFDEMEECSQHLPYIEQGMMLAEQFKQKALGLLQTASRHAEVITPAVQTNWQKLEVFWAKHMWNFISGIQYLAGLSTLPGNPAIASLMAFTAAVTSPLTTGQTLLFNILGGWVAAQLAAPGAATAFVGAGLAGAALDSVGLGKVLVDILAGYGAGVAGALVAFKIMSGEVPSTEDLVNLLPAILSPGALAVGVVFASILRRRVGPGEGAVQWMNRLIAFASRGNHVSPTHYVPESDAAARVTAILSSLTVTQLLRRLHQWISSECTTPCSGSWLRDIWDWICEVLSDFKTWLKAKLMPQLPGIPFVSCQRGYRGVWRGDGIMHTRCHCGAEITGHVKNGTMRIVGPRTCKNMWSGTFFINAYTTGPCTPLPAPNYKFALWRVSAEEYVEIRRVGDFHYVSGMTTDNLKCPCQIPSPEFFTELDGVRLHRFAPPCKPLLREEVSFRVGLHEYPVGSQLPCEPEPDVAVLTSMLTDPSHITAEAAGRRLARGSPPSMASSSASQLSAPSLKATCTANHDSPDAELIEANLLWRQEMGGNITRVESENKVVILDSFDPLVAEEDEREVSVPAEILRKSRRFAPALPVWARPDYNPLLVETWKKPDYEPPVVHGCPLPPPRSPPVPPPRKKRTVVLTESTLPTALAELATKSFGSSSTSGITGDNTTTSSEPAPSGCPPDSDVESYSSMPPLEGEPGDPDLSDGSWSTVSSGADTEDVVCCSMSYSWTGALVTPCAAEEQKLPINALSNSLLRHHNLVYSTTSRSACQRKKKVTFDRLQVLDSHYQDVLKEVKAAASKVKANLLSVEEACSLAPPHSAKSKFGYGAKDVRCHARKAVAHINSVWKDLLEDSVTPIDTTIMAKNEVFCVQPEKGGRKPARLIVFPDLGVRVCEKMALYDVVSKLPLAVMGSSYGFQYSPGQRVEFLVQAWKSKKTPMGLSYDTRCFDSTVTESDIRTEEAIYQCCDLDPQARVAIKSLTERLYVGGPLTNSRGENCGYRRCRASRVLTTSCGNTLTRYIKARAACRAAGLQDCTMLVCGDDLVVICESAGVQEDAASLRAFTEAMTRYSAPPGDPPQPEYDLELITSCSSNVSVAHDGAGKRVYYLTRDPTTPLARAAWETARHTPVNSWLGNIIMFAPTLWARMILMTHFFSVLIARDQLEQALNCEIYGACYSIEPLDLPPIIQRLHGLSAFSLHSYSPGEINRVAACLRKLGVPPLRAWRHRAWSVRARLLARGGKAAICGKYLFNWAVRTKLKLTPITAAGRLDLSGWFTAGYSGGDIYHSVSHARPRWFWFCLLLLAAGVGIYLLPNR,4.568636235841012 +[I-].COc1cc2C3CCC[N+]3(C)CCc2cc1Oc1ccccc1,MGVVLLPPPLSMLMLVLMLLPAASASEAEHRLFQYLFEDYNEIIRPVANVSHPVIIQFEVSMSQLVKVDEVNQIMETNLWLKQIWNDYKLKWKPSDYQGVEFMRVPAEKIWKPDIVLYNNADGDFQVDDKTKALLKYTGEVTWIPPAIFKSSCKIDVTYFPFDYQNCTMKFGSWSYDKAKIDLVLIGSSMNLKDYWESGEWAIIKAPGYKHEIKYNCCEEIYQDITYSLYIRRLPLFYTINLIIPCLLISFLTVLVFYLPSDCGEKVTLCISVLLSLTVFLLVITETIPSTSLVIPLIGEYLLFTMIFVTLSIVITVFVLNVHYRTPTTHTMPTWVKAVFLNLLPRVMFMTRPTSGEGDTPKTRTFYGAELSNLNCFSRADSKSCKEGYPCQDGTCGYCHHRRVKISNFSANLTRSSSSESVNAVLSLSALSPEIKEAIQSVKYIAENMKAQNVAKEIQDDWKYVAMVIDRIFLWVFILVCILGTAGLFLQPLMARDDT,3.5228787452803374 +COc1ccccc1N1CCN(CCCCNC(=O)c2ccc3ccccc3c2)CC1,MDPLNLSWYDDDLERQNWSRPFNGSDGKADRPHYNYYATLLTLLIAVIVFGNVLVCMAVSREKALQTTTNYLIVSLAVADLLVATLVMPWVVYLEVVGEWKFSRIHCDIFVTLDVMMCTASILNLCAISIDRYTAVAMPMLYNTRYSSKRRVTVMISIVWVLSFTISCPLLFGLNNADQNECIIANPAFVVYSSIVSFYVPFIVTLLVYIKIYIVLRRRRKRVNTKRSSRAFRAHLRAPLKGNCTHPEDMKLCTVIMKSNGSFPVNRRRVEAARRAQELEMEMLSSTSPPERTRYSPIPPSHHQLTLPDPSHHGLHSTPDSPAKPEKNGHAKDHPKIAKIFEIQTMPNGKTRTSLKTMSRRKLSQQKEKKATQMLAIVLGVFIICWLPFFITHILNIHCDCNIPPVLYSAFTWLGYVNSAVNPIIYTTFNIEFRKAFLKILHC,6.6777807052660805 +Oc1ccc(cc1)-c1cc(C#N)c2c(Cl)c(O)ccc2c1,MDIKNSPSSLNSPSSYNCSQSILPLEHGSIYIPSSYVDSHHEYPAMTFYSPAVMNYSIPSNVTNLEGGPGRQTTSPNVLWPTPGHLSPLVVHRQLSHLYAEPQKSPWCEARSLEHTLPVNRETLKRKVSGNRCASPVTGPGSKRDAHFCAVCSDYASGYHYGVWSCEGCKAFFKRSIQGHNDYICPATNQCTIDKNRRKSCQACRLRKCYEVGMVKCGSRRERCGYRLVRRQRSADEQLHCAGKAKRSGGHAPRVRELLLDALSPEQLVLTLLEAEPPHVLISRPSAPFTEASMMMSLTKLADKELVHMISWAKKIPGFVELSLFDQVRLLESCWMEVLMMGLMWRSIDHPGKLIFAPDLVLDRDEGKCVEGILEIFDMLLATTSRFRELKLQHKEYLCVKAMILLNSSMYPLVTATQDADSSRKLAHLLNAVTDALVWVIAKSGISSQQQSMRLANLLMLLSHVRHASNKGMEHLLNMKCKNVVPVYDLLLEMLNAHVLRGCKSSITGSECSPAEDSKSKEGSQNPQSQ,8.221848749616356 +CCOc1ncccc1-c1cc(NCc2cnn(C)c2)c2n(CC)ncc2n1,MGSSATEIEELENTTFKYLTGEQTEKMWQRLKGILRCLVKQLERGDVNVVDLKKNIEYAASVLEAVYIDETRRLLDTEDELSDIQTDSVPSEVRDWLASTFTRKMGMTKKKPEEKPKFRSIVHAVQAGIFVERMYRKTYHMVGLAYPAAVIVTLKDVDKWSFDVFALNEASGEHSLKFMIYELFTRYDLINRFKIPVSCLITFAEALEVGYSKYKNPYHNLIHAADVTQTVHYIMLHTGIMHWLTELEILAMVFAAAIHDYEHTGTTNNFHIQTRSDVAILYNDRSVLENHHVSAAYRLMQEEEMNILINLSKDDWRDLRNLVIEMVLSTDMSGHFQQIKNIRNSLQQPEGIDRAKTMSLILHAADISHPAKSWKLHYRWTMALMEEFFLQGDKEAELGLPFSPLCDRKSTMVAQSQIGFIDFIVEPTFSLLTDSTEKIVIPLIEEASKAETSSYVASSSTTIVGLHIADALRRSNTKGSMSDGSYSPDYSLAAVDLKSFKNNLVDIIQQNKERWKELAAQEARTSSQKCEFIHQ,6.853871964321762 +Oc1cccc(c1)-c1nc(N2CCOCC2)c2oc3ncccc3c2n1,MRELVNIPLVHILTLVAFSGTEKLPKAPVITTPLETVDALVEEVATFMCAVESYPQPEISWTRNKILIKLFDTRYSIRENGQLLTILSVEDSDDGIYCCTANNGVGGAVESCGALQVKMKPKITRPPINVKIIEGLKAVLPCTTMGNPKPSVSWIKGDSPLRENSRIAVLESGSLRIHNVQKEDAGQYRCVAKNSLGTAYSKVVKLEVEVFARILRAPESHNVTFGSFVTLHCTATGIPVPTITWIENGNAVSSGSIQESVKDRVIDSRLQLFITKPGLYTCIATNKHGEKFSTAKAAATISIAEWSKPQKDNKGYCAQYRGEVCNAVLAKDALVFLNTSYADPEEAQELLVHTAWNELKVVSPVCRPAAEALLCNHIFQECSPGVVPTPIPICREYCLAVKELFCAKEWLVMEEKTHRGLYRSEMHLLSVPECSKLPSMHWDPTACARLPHLDYNKENLKTFPPMTSSKPSVDIPNLPSSSSSSFSVSPTYSMTVIISIMSSFAIFVLLTITTLYCCRRRKQWKNKKRESAAVTLTTLPSELLLDRLHPNPMYQRMPLLLNPKLLSLEYPRNNIEYVRDIGEGAFGRVFQARAPGLLPYEPFTMVAVKMLKEEASADMQADFQREAALMAEFDNPNIVKLLGVCAVGKPMCLLFEYMAYGDLNEFLRSMSPHTVCSLSHSDLSMRAQVSSPGPPPLSCAEQLCIARQVAAGMAYLSERKFVHRDLATRNCLVGENMVVKIADFGLSRNIYSADYYKANENDAIPIRWMPPESIFYNRYTTESDVWAYGVVLWEIFSYGLQPYYGMAHEEVIYYVRDGNILSCPENCPVELYNLMRLCWSKLPADRPSFTSIHRILERMCERAEGTVSV,5.0 +Fc1ccc(cc1)-c1nn2ncccc2c1-c1ccnc(Nc2ccccc2)n1,MENFQKVEKIGEGTYGVVYKARNKLTGEVVALKKIRLDTETEGVPSTAIREISLLKELNHPNIVKLLDVIHTENKLYLVFEFLHQDLKKFMDASALTGIPLPLIKSYLFQLLQGLAFCHSHRVLHRDLKPQNLLINTEGAIKLADFGLARAFGVPVRTYTHEVVTLWYRAPEILLGCKYYSTAVDIWSLGCIFAEMVTRRALFPGDSEIDQLFRIFRTLGTPDEVVWPGVTSMPDYKPSFPKWARQDFSKVVPPLDEDGRSLLSQMLHYDPNKRISAKAALAHPFFQDVTKPVPHLRL,4.700057099977233 +Cc1cccc(c1)-c1cc2nc(C)c(CN)c(-c3ccc(Cl)cc3Cl)n2n1,MWKRSEQMKIKSGKCNMAAAMETEQLGVEIFETADCEENIESQDRPKLEPFYVERYSWSQLKKLLADTRKYHGYMMAKAPHDFMFVKRNDPDGPHSDRIYYLAMSGENRENTLFYSEIPKTINRAAVLMLSWKPLLDLFQATLDYGMYSREEELLRERKRIGTVGIASYDYHQGSGTFLFQAGSGIYHVKDGGPQGFTQQPLRPNLVETSCPNIRMDPKLCPADPDWIAFIHSNDIWISNIVTREERRLTYVHNELANMEEDARSAGVATFVLQEEFDRYSGYWWCPKAETTPSGGKILRILYEENDESEVEIIHVTSPMLETRRADSFRYPKTGTANPKVTFKMSEIMIDAEGRIIDVIDKELIQPFEILFEGVEYIARAGWTPEGKYAWSILLDRSQTRLQIVLISPELFIPVEDDVMERQRLIESVPDSVTPLIIYEETTDIWINIHDIFHVFPQSHEEEIEFIFASECKTGFRHLYKITSILKESKYKRSSGGLPAPSDFKCPIKEEIAITSGEWEVLGRHGSNIQVDEVRRLVYFEGTKDSPLEHHLYVVSYVNPGEVTRLTDRGYSHSCCISQHCDFFISKYSNQKNPHCVSLYKLSSPEDDPTCKTKEFWATILDSAGPLPDYTPPEIFSFESTTGFTLYGMLYKPHDLQPGKKYPTVLFIYGGPQVQLVNNRFKGVKYFRLNTLASLGYVVVVIDNRGSCHRGLKFEGAFKYKMGQIEIDDQVEGLQYLASRYDFIDLDRVGIHGWSYGGYLSLMALMQRSDIFRVAIAGAPVTLWIFYDTGYTERYMGHPDQNEQGYYLGSVAMQAEKFPSEPNRLLLLHGFLDENVHFAHTSILLSFLVRAGKPYDLQIYPQERHSIRVPESGEHYELHLLHYLQENLGSRIAALKVI,4.913640169325252 +CC1CSCCN=C1N,MGNLKSVAQEPGPPCGLGLGLGLGLCGKQGPATPAPEPSRAPASLLPPAPEHSPPSSPLTQPPEGPKFPRVKNWEVGSITYDTLSAQAQQDGPCTPRRCLGSLVFPRKLQGRPSPGPPAPEQLLSQARDFINQYYSSIKRSGSQAHEQRLQEVEAEVAATGTYQLRESELVFGAKQAWRNAPRCVGRIQWGKLQVFDARDCRSAQEMFTYICNHIKYATNRGNLRSAITVFPQRCPGRGDFRIWNSQLVRYAGYRQQDGSVRGDPANVEITELCIQHGWTPGNGRFDVLPLLLQAPDEPPELFLLPPELVLEVPLEHPTLEWFAALGLRWYALPAVSNMLLEIGGLEFPAAPFSGWYMSTEIGTRNLCDPHRYNILEDVAVCMDLDTRTTSSLWKDKAAVEINVAVLHSYQLAKVTIVDHHAATASFMKHLENEQKARGGCPADWAWIVPPISGSLTPVFHQEMVNYFLSPAFRYQPDPWKGSAAKGTGITRKKTFKEVANAVKISASLMGTVMAKRVKATILYGSETGRAQSYAQQLGRLFRKAFDPRVLCMDEYDVVSLEHETLVLVVTSTFGNGDPPENGESFAAALMEMSGPYNSSPRPEQHKSYKIRFNSISCSDPLVSSWRRKRKESSNTDSAGALGTLRFCVFGLGSRAYPHFCAFARAVDTRLEELGGERLLQLGQGDELCGQEEAFRGWAQAAFQAACETFCVGEDAKAAARDIFSPKRSWKRQRYRLSAQAEGLQLLPGLIHVHRRKMFQATIRSVENLQSSKSTRATILVRLDTGGQEGLQYQPGDHIGVCPPNRPGLVEALLSRVEDPPAPTEPVAVEQLEKGSPGGPPPGWVRDPRLPPCTLRQALTFFLDITSPPSPQLLRLLSTLAEEPREQQELEALSQDPRRYEEWKWFRCPTLLEVLEQFPSVALPAPLLLTQLPLLQPRYYSVSSAPSTHPGEIHLTVAVLAYRTQDGLGPLHYGVCSTWLSQLKPGDPVPCFIRGAPSFRLPPDPSLPCILVGPGTGIAPFRGFWQERLHDIESKGLQPTPMTLVFGCRCSQLDHLYRDEVQNAQQRGVFGRVLTAFSREPDNPKTYVQDILRTELAAEVHRVLCLERGHMFVCGDVTMATNVLQTVQRILATEGDMELDEAGDVIGVLRDQQRYHEDIFGLTLRTQEVTSRIRTQSFSLQERQLRGAVPWAFDPPGSDTNSP,4.301029995663981 +COC(=O)\C=C\CNC(=O)CN1c2ccccc2C(=N[C@H](COC(=O)Nc2cccc3ccccc23)C1=O)c1ccccc1,MPRTEMVRFVRLPVVLLAMAACLASVALGSLHVEESLEMRFAAFKKKYGKVYKDAKEEAFRFRAFEENMEQAKIQAAANPYATFGVTPFSDMTREEFRARYRNGASYFAAAQKRLRKTVNVTTGRAPAAVDWREKGAVTPVKDQGQCGSCWAFSTIGNIEGQWQVAGNPLVSLSEQMLVSCDTIDFGCGGGLMDNAFNWIVNSNGGNVFTEASYPYVSGNGEQPQCQMNGHEIGAAITDHVDLPQDEDAIAAYLAENGPLAIAVDATSFMDYNGGILTSCTSEQLDHGVLLVGYNDSSNPPYWIIKNSWSNMWGEDGYIRIEKGTNQCLMNQAVSSAVVGGPTPPPPPPPPPSATFTQDFCEGKGCTKGCSHATFPTGECVQTTGVGSVIATCGASNLTQIIYPLSRSCSGLSVPITVPLDKCIPILIGSVEYHCSTNPPTKAARLVPHQ,6.031517051446065 +OP(O)(=O)C(CNc1cccc(c1)-c1ccccc1)P(O)(O)=O,MSARLNNLLQHIAVKDKDSDTMRHLKQRMALASLANQFTVGKDHLKQLMLYMVHQMIEGLEGRESTLRMLPSYVYKTDPSKATGVFYALDLGGTNFRVLRVTCKEGRVADRVDAKFVIPQQALQGTAEDLFGFIAQSVKKMMEQKAPEDLNRTVPLGFTFSFPTEQKGVDHGFLIKWTKGFSTRGVEGKDVVELLQKALKRMEVKVKVVALCNDTVGTLITNYFFDPDTQVGVIIGTGSNACYFEDAYAVTKEPSVAARGTTQTPINMECGNFDSKYKFVLPVTAYDEAMDAVTPNRNFQTQEKMVSGMYLGEISRRMIAHLAELHCLPSALASKMAKPWSFETKFMGMISADRMPGLQFTRQVFQELFQVDVTDVADLHVIRDVCCLVRGRAAQISAMFCSAPLVKTRKEGRATVAIDGSVFEKTPSFRRLLQQNMNAILGPGCDVTTALARDGSGIGAAFISALVVNDK,5.459670525209126 +COc1c(C)c2c(Nc3ccc(F)cc3O[C@@H]3CO[C@@H]4[C@H](O)CO[C@H]34)ncnc2cc1N=S1(=O)CCC1,MVSSQKLEKPIEMGSSEPLPIADGDRRRKKKRRGRATDSLPGKFEDMYKLTSELLGEGAYAKVQGAVSLQNGKEYAVKIIEKQAGHSRSRVFREVETLYQCQGNKNILELIEFFEDDTRFYLVFEKLQGGSILAHIQKQKHFNEREASRVVRDVAAALDFLHTKDKVSLCHLGWSAMAPSGLTAAPTSLGSSDPPTSASQVAGTTGIAHRDLKPENILCESPEKVSPVKICDFDLGSGMKLNNSCTPITTPELTTPCGSAEYMAPEVVEVFTDQATFYDKRCDLWSLGVVLYIMLSGYPPFVGHCGADCGWDRGEVCRVCQNKLFESIQEGKYEFPDKDWAHISSEAKDLISKLLVRDAKQRLSAAQVLQHPWVQGQAPEKGLPTPQVLQRNSSTMDLTLFAAEAIALNRQLSQHEENELAEEPEALADGLCSMKLSPPCKSRLARRRALAQAGRGEDRSPPTAL,7.7447274948966935 +CC(C)C[C@H](O)[C@H](O)[C@H](CC1CCCCC1)NC(=O)C(Cc1cnc[nH]1)NC(=O)[C@H](Cc1ccccc1)NS(=O)(=O)N1CCOCC1,MDGWRRMPRWGLLLLLWGSCTFGLPTDTTTFKRIFLKRMPSIRESLKERGVDMARLGPEWSQPMKRLTLGNTTSSVILTNYMDTQYYGEIGIGTPPQTFKVVFDTGSSNVWVPSSKCSRLYTACVYHKLFDASDSSSYKHNGTELTLRYSTGTVSGFLSQDIITVGGITVTQMFGEVTEMPALPFMLAEFDGVVGMGFIEQAIGRVTPIFDNIISQGVLKEDVFSFYYNRDSENSQSLGGQIVLGGSDPQHYEGNFHYINLIKTGVWQIQMKGVSVGSSTLLCEDGCLALVDTGASYISGSTSSIEKLMEALGAKKRLFDYVVKCNEGPTLPDISFHLGGKEYTLTSADYVFQESYSSKKLCTLAIHAMDIPPPTGPTWALGATFIRKFYTEFDRRNNRIGFALAR,9.638272163982407 +CN(C[C@@H](CCN1CCC2(CS(=O)c3ccccc23)CC1)c1ccc(F)cc1)S(=O)(=O)c1ccccc1,MDYQVSSPIYDINYYTSEPCQKINVKQIAARLLPPLYSLVFIFGFVGNMLVILILINCKRLKSMTDIYLLNLAISDLFFLLTVPFWAHYAAAQWDFGNTMCQLLTGLYFIGFFSGIFFIILLTIDRYLAVVHAVFALKARTVTFGVVTSVITWVVAVFASLPGIIFTRSQKEGLHYTCSSHFPYSQYQFWKNFQTLKIVILGLVLPLLVMVICYSGILKTLLRCRNEKKRHRAVRLIFTIMIVYFLFWAPYNIVLLLNTFQEFFGLNNCSSSNRLDQAMQVTETLGMTHCCINPIIYAFVGEKFRNYLLVFFQKHIAKRFCKCCSIFQQEAPERASSVYTRSTGEQEISVGL,6.2441251443275085 +Brc1ccc(CNc2ccc(cc2)[C@H]2CNCCO2)nc1,MATDDDRFPWDQDSILSRDLLSASSMQLCYEKLNRSCVRSPYSPGPRLILYAVFGFGAVLAVCGNLLVMTSILHFRQLHSPANFLVASLACADFLVGLTVMPFSMVRSVEGCWYFGDIYCKFHSSFDGSFCYSSIFHLCFISADRYIAVSDPLIYPTRFTASVSGKCITFSWLLSIIYSFSLFYTGVNEAGLEDLVSALTCVGGCQIAVNQSWVFINFLLFLVPALVMMTVYSKIFLIAKQQAQNIEKMGKQTARASESYKDRVAKRERKAAKTLGIAVAAFLLSWLPYFIDSIIDAFLGFVTPTYVYEILVWIGYYNSAMNPLIYAFFYPWFRKAIKLIVTGKILRENSSATNLFPE,6.092427421201449 +Cc1nn(Cc2nc(no2)-c2ccc(C)cc2)c2ncc(C(=O)Nc3ccc(cc3)C(F)(F)F)c(Cl)c12,MDSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVASQSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISLSSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKGQTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGEDDSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVIKQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFNVIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTATTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTLVSLLEVIEPEVLYAGYDSSVPDSTWRIMTTLNMLGGRQVIAAVKWAKAIPGFRNLHLDDQMTLLQYSWMFLMAFALGWRSYRQSSANLLCFAPDLIINEQRMTLPCMYDQCKHMLYVSSELHRLQVSYEEYLCMKTLLLLSSVPKDGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHEVVENLLNYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK,6.560667306169737 +COc1cccc(CCc2ccccc2OCCCN2CCc3cc(OC)c(OC)cc3C2)c1,MDLEGDRNGGAKKKNFFKLNNKSEKDKKEKKPTVSVFSMFRYSNWLDKLYMVVGTLAAIIHGAGLPLMMLVFGEMTDIFANAGNLEDLMSNITNRSDINDTGFFMNLEEDMTRYAYYYSGIGAGVLVAAYIQVSFWCLAAGRQIHKIRKQFFHAIMRQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQSMATFFTGFIVGFTRGWKLTLVILAISPVLGLSAAVWAKILSSFTDKELLAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNKNLEEAKRIGIKKAITANISIGAAFLLIYASYALAFWYGTTLVLSGEYSIGQVLTVFFSVLIGAFSVGQASPSIEAFANARGAAYEIFKIIDNKPSIDSYSKSGHKPDNIKGNLEFRNVHFSYPSRKEVKILKGLNLKVQSGQTVALVGNSGCGKSTTVQLMQRLYDPTEGMVSVDGQDIRTINVRFLREIIGVVSQEPVLFATTIAENIRYGRENVTMDEIEKAVKEANAYDFIMKLPHKFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQVALDKARKGRTTIVIAHRLSTVRNADVIAGFDDGVIVEKGNHDELMKEKGIYFKLVTMQTAGNEVELENAADESKSEIDALEMSSNDSRSSLIRKRSTRRSVRGSQAQDRKLSTKEALDESIPPVSFWRIMKLNLTEWPYFVVGVFCAIINGGLQPAFAIIFSKIIGVFTRIDDPETKRQNSNLFSLLFLALGIISFITFFLQGFTFGKAGEILTKRLRYMVFRSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGAIGSRLAVITQNIANLGTGIIISFIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENFRTVVSLTQEQKFEHMYAQSLQVPYRNSLRKAHIFGITFSFTQAMMYFSYAGCFRFGAYLVAHKLMSFEDVLLVFSAVVFGAMAVGQVSSFAPDYAKAKISAAHIIMIIEKTPLIDSYSTEGLMPNTLEGNVTFGEVVFNYPTRPDIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPLAGKVLLDGKEIKRLNVQWLRAHLGIVSQEPILFDCSIAENIAYGDNSRVVSQEEIVRAAKEANIHAFIESLPNKYSTKVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVFQNGRVKEHGTHQQLLAQKGIYFSMVSVQAGTKRQ,7.045757490560675 +CCn1c(=O)sn(-c2cccc3ccccc23)c1=O,MKKWTNRLMTIAGVVLILVAAYLFAKPHIDNYLHDKDKDEKIEQYDKNVKEQASKDKKQQAKPQIPKDKSKVAGYIEIPDADIKEPVYPGPATPEQLNRGVSFAEENESLDDQNISIAGHTFIDRPNYQFTNLKAAKKGSMVYFKVGNETRKYKMTSIRDVKPTDVGVLDEQKGKDKQLTLITCDDYNEKTGVWEKRKIFVATEVK,5.086186147616283 +CCn1c(CCc2c[nH]c3ccc(OC)cc23)n[nH]c1=S,MQGNGSALPNASQPVLRGDGARPSWLASALACVLIFTIVVDILGNLLVILSVYRNKKLRNAGNIFVVSLAVADLVVAIYPYPLVLMSIFNNGWNLGYLHCQVSGFLMGLSVIGSIFNITGIAINRYCYICHSLKYDKLYSSKNSLCYVLLIWLLTLAAVLPNLRAGTLQYDPRIYSCTFAQSVSSAYTIAVVVFHFLVPMIIVIFCYLRIWILVLQVRQRVKPDRKPKLKPQDFRNFVTMFVVFVLFAICWAPLNFIGLAVASDPASMVPRIPEWLFVASYYMAYFNSCLNAIIYGLLNQNFRKEYRRIIVSLCTARVFFVDSSNDVADRVKWKPSPLMTNNNVVKVDSV,6.0 +OC(c1ccc(cc1)N(CC(F)(F)F)S(=O)(=O)c1cccc(c1)C#N)(C(F)(F)F)C(F)(F)F,MDRAPQRQHRASRELLAAKKTHTSQIEVIPCKICGDKSSGIHYGVITCEGCKGFFRRSQRCNAAYSCTRQQNCPIDRTSRNRCQHCRLQKCLALGMSRDAVKFGRMSKKQRDSLHAEVQKQLQQRQQQQQEPVVKTPPAGAQGADTLTYTLGLPDGQLPLGSSPDLPEASACPPGLLKASGSGPSYSNNLAKAGLNGASCHLEYSPERGKAEGRESFYSTGSQLTPDRCGLRFEEHRHPGLGELGQGPDSYGSPSFRSTPEAPYASLTEIEHLVQSVCKSYRETCQLRLEDLLRQRSNIFSREEVTGYQRKSMWEMWERCAHHLTEAIQYVVEFAKRLSGFMELCQNDQIVLLKAGAMEVVLVRMCRAYNADNRTVFFEGKYGGMELFRALGCSELISSIFDFSHSLSALHFSEDEIALYTALVLINAHRPGLQEKRKVEQLQYNLELAFHHHLCKTHRQSILAKLPPKGKLRSLCSQHVERLQIFQHLHPIVVQAAFPPLYKELFSTETESPVGLSK,7.0 +O=C(NCc1cccnc1)Nc1cccc(c1)S(=O)(=O)N1CCCCC1,MNPAAEAEFNILLATDSYKVTHYKQYPPNTSKVYSYFECREKKTENSKLRKVKYEETVFYGLQYILNKYLKGKVVTKEKIQEAKDVYKEHFQDDVFNEKGWNYILEKYDGHLPIEIKAVPEGFVIPRGNVLFTVENTDPECYWLTNWIETILVQSWYPITVATNSREQKKILAKYLLETSGNLDGLEYKLHDFGYRGVSSQETAGIGASAHLVNFKGTDTVAGLALIKKYYGTKDPVPGYSVPAAEHSTITAWGKDHEKDAFEHIVTQFSSVPVSVVSDSYDIYNACEKIWGEDLRHLIVSRSTQAPLIIRPDSGNPLDTVLKVLEILGKKFPVTENSKGYKLLPPYLRVIQGDGVDINTLQEIVEGMKQKMWSIENIAFGSGGGLLQKLTRDLLNCSFKCSYVVTNGLGINVFKDPVADPNKRSKKGRLSLHRTPAGNFVTLEEGKGDLEEYGQDLLHTVFKNGKVTKSYSFDEIRKNAQLNIELEAAHH,5.0 +CN(C)C(=O)Oc1ccc2c(C)c(Cc3cccc(c3)N(C)S(=O)(=O)CCCNCCCCCC(=O)N3CCN(CC3)c3nc(nc(n3)-n3c(nc4ccccc34)C(F)F)N3CCOCC3)c(=O)oc2c1,MPKKKPTPIQLNPAPDGSAVNGTSSAETNLEALQKKLEELELDEQQRKRLEAFLTQKQKVGELKDDDFEKISELGAGNGGVVFKVSHKPSGLVMARKLIHLEIKPAIRNQIIRELQVLHECNSPYIVGFYGAFYSDGEISICMEHMDGGSLDQVLKKAGRIPEQILGKVSIAVIKGLTYLREKHKIMHRDVKPSNILVNSRGEIKLCDFGVSGQLIDSMANSFVGTRSYMSPERLQGTHYSVQSDIWSMGLSLVEMAVGRYPIPPPDAKELELMFGCQVEGDAAETPPRPRTPGRPLSSYGMDSRPPMAIFELLDYIVNEPPPKLPSGVFSLEFQDFVNKCLIKNPAERADLKQLMVHAFIKRSDAEEVDFAGWLCSTIGLNQPSTPTHAAGV,6.325138859262188 +NCc1ccc(s1)-c1cccnc1,MDPFVVLVLCLSCLLLLSIWRQSSGRGKLPPGPTPLPVIGNILQIDIKDVSKSLTNLSKIYGPVFTLYFGLERMVVLHGYEVVKEALIDLGEEFSGRGHFPLAERANRGFGIVFSNGKRWKEIRRFSLMTLRNFGMGKRSIEDRVQEEARCLVEELRKTKASPCDPTFILGCAPCNVICSIIFQKRFDYKDQQFLNLMEKLNENIRIVSTPWIQICNNFPTIIDYFPGTHNKLLKNLAFMESDILEKVKEHQESMDINNPRDFIDCFLIKMEKEKQNQQSEFTIENLVITAADLLGAGTETTSTTLRYALLLLLKHPEVTAKVQEEIERVVGRNRSPCMQDRGHMPYTDAVVHEVQRYIDLIPTSLPHAVTCDVKFRNYLIPKGTTILTSLTSVLHDNKEFPNPEMFDPRHFLDEGGNFKKSNYFMPFSAGKRICVGEGLARMELFLFLTFILQNFNLKSLIDPKDLDTTPVVNGFASVPPFYQLCFIPV,5.698970004336019 +C[N+](C)(CCCC[C@H](N)C(=O)NCCCCCNC(=O)[C@H](CC(N)=O)NC(=O)Cc1c[nH]c2cccc(O)c12)CCCNC(=O)[C@@H](N)CCCNC(N)=N,MSTMHLLTFALLFSCSFARAACDPKIVNIGAVLSTRKHEQMFREAVNQANKRHGSWKIQLNATSVTHKPNAIQMALSVCEDLISSQVYAILVSHPPTPNDHFTPTPVSYTAGFYRIPVLGLTTRMSIYSDKSIHLSFLRTVPPYSHQSSVWFEMMRVYNWNHIILLVSDDHEGRAAQKRLETLLEERESKAEKVLQFDPGTKNVTALLMEARELEARVIILSASEDDAATVYRAAAMLNMTGSGYVWLVGEREISGNALRYAPDGIIGLQLINGKNESAHISDAVGVVAQAVHELLEKENITDPPRGCVGNTNIWKTGPLFKRVLMSSKYADGVTGRVEFNEDGDRKFANYSIMNLQNRKLVQVGIYNGTHVIPNDRKIIWPGGETEKPRGYQMSTRLKIVTIHQEPFVYVKPTMSDGTCKEEFTVNGDPVKKVICTGPNDTSPGSPRHTVPQCCYGFCIDLLIKLARTMNFTYEVHLVADGKFGTQERVNNSNKKEWNGMMGELLSGQADMIVAPLTINNERAQYIEFSKPFKYQGLTILVKKEIPRSTLDSFMQPFQSTLWLLVGLSVHVVAVMLYLLDRFSPFGRFKVNSEEEEEDALTLSSAMWFSWGVLLNSGIGEGAPRSFSARILGMVWAGFAMIIVASYTANLAAFLVLDRPEERITGINDPRLRNPSDKFIYATVKQSSVDIYFRRQVELSTMYRHMEKHNYESAAEAIQAVRDNKLHAFIWDSAVLEFEASQKCDLVTTGELFFRSGFGIGMRKDSPWKQNVSLSILKSHENGFMEDLDKTWVRYQECDSRSNAPATLTFENMAGVFMLVAGGIVAGIFLIFIEIAYKRHKDARRKQMQLAFAAVNVWRKNLQDRKSGRAEPDPKKKATFRAITSTLASSFKRRRSSKDTSTGGGRGALQNQKDTVLPRRAIEREEGQLQLCSRHRES,5.414313721547503 +COc1c(OCCF)cccc1C(=O)C1CCN(CCc2ccc(C)cc2)CC1,MMDVNSSGRPDLYGHLRSFLLPEVGRGLPDLSPDGGADPVAGSWAPHLLSEVTASPAPTWDAPPDNASGCGEQINYGRVEKVVIGSILTLITLLTIAGNCLVVISVCFVKKLRQPSNYLIVSLALADLSVAVAVMPFVSVTDLIGGKWIFGHFFCNVFIAMDVMCCTASIMTLCVISIDRYLGITRPLTYPVRQNGKCMAKMILSVWLLSASITLPPLFGWAQNVNDDKVCLISQDFGYTIYSTAVAFYIPMSVMLFMYYQIYKAARKSAAKHKFPGFPRVEPDSVIALNGIVKLQKEVEECANLSRLLKHERKNISIFKREQKAATTLGIIVGAFTVCWLPFFLLSTARPFICGTSCSCIPLWVERTFLWLGYANSLINPFIYAFFNRDLRTTYRSLLQCQYRNINRKLSAAGMHEALKLAERPERPEFVLRACTRRVLLRPEKRPPVSVWVLQSPDHHNWLADKMLTTVEKKVMIHD,6.13608262304214 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+COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,5.0 +COc1ccc(Nc2ncc3ncc(=O)n(-c4ccc(NC(=O)\C=C\CN(C)C)cc4)c3n2)cc1,MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNCEVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYALAVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMSMDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCCHNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFGATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGEFKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLIQAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNKNLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCVSCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQCAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCPTNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGEAPNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACIDRNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVYHNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISLDNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA,7.508638306165727 +C[C@H]([C@H](CS)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(O)=O)c1ccccc1,MRGVWPPPVSALLSALGMSTYKRATLDEEDLVDSLSEGDAYPNGLQVNFHSPRSGQRCWAARTQVEKRLVVLVVLLAAGLVACLAALGIQYQTRSPSVCLSEACVSVTSSILSSMDPTVDPCHDFFSYACGGWIKANPVPDGHSRWGTFSNLWEHNQAIIKHLLENSTASVSEAERKAQVYYRACMNETRIEELRAKPLMELIERLGGWNITGPWAKDNFQDTLQVVTAHYRTSPFFSVYVSADSKNSNSNVIQVDQSGLGLPSRDYYLNKTENEKVLTGYLNYMVQLGKLLGGGDEEAIRPQMQQILDFETALANITIPQEKRRDEELIYHKVTAAELQTLAPAINWLPFLNTIFYPVEINESEPIVVYDKEYLEQISTLINTTDRCLLNNYMIWNLVRKTSSFLDQRFQDADEKFMEVMYGTKKTCLPRWKFCVSDTENNLGFALGPMFVKATFAEDSKSIATEIILEIKKAFEESLSTLKWMDEETRKSAKEKADAIYNMIGYPNFIMDPKELDKVFNDYTAVPDLYFENAMRFFNFSWRVTADQLRKAPNRDQWSMTPPMVNAYYSPTKNEIVFPAGILQAPFYTRSSPKALNFGGIGVVVGHELTHAFDDQGREYDKDGNLRPWWKNSSVEAFKRQTECMVEQYSNYSVNGEPVNGRHTLGENIADNGGLKAAYRAYQNWVKKNGAEHSLPTLGLTNNQLFFLGFAQVWCSVRTPESSHEGLITDPHSPSRFRVIGSLSNSKEFSEHFRCPPGSPMNPPHKCEVW,6.107905397309519 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+O[C@H](CNCCNC(=O)N1CCOCC1)COc1ccc(O)cc1,MGAGVLVLGASEPGNLSSAAPLPDGAATAARLLVPASPPASLLPPASESPEPLSQQWTAGMGLLMALIVLLIVAGNVLVIVAIAKTPRLQTLTNLFIMSLASADLVMGLLVVPFGATIVVWGRWEYGSFFCELWTSVDVLCVTASIETLCVIALDRYLAITSPFRYQSLLTRARARGLVCTVWAISALVSFLPILMHWWRAESDEARRCYNDPKCCDFVTNRAYAIASSVVSFYVPLCIMAFVYLRVFREAQKQVKKIDSCERRFLGGPARPPSPSPSPVPAPAPPPGPPRPAAAAATAPLANGRAGKRRPSRLVALREQKALKTLGIIMGVFTLCWLPFFLANVVKAFHRELVPDRLFVFFNWLGYANSAFNPIIYCRSPDFRKAFQRLLCCARRAARRRHATHGDRPRASGCLARPGPPPSPGAASDDDDDDVVGATPPARLLEPWAGCNGGAAADSDSSLDEPCRPGFASESKV,7.7447274948966935 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+CC1(C)C2CC[C@@]1(CS(=O)(=O)N1CCC3(CC1)C=Cc1c3cccc1Cl)C(=O)C2,MNSEPSWTATPSPGGTLPVPNATTPWLGRDEELAKVEIGILATVLVLATGGNLAVLLTLGRHGHKRSRMHLFVLHLALTDLGVALFQVLPQLLWDITYRFQGSDLLCRAVKYLQVLSMFASTYMLLAMTLDRYLAVCHPLRSLRQPSQSTYPLIAAPWLLAAILSLPQVFIFSLREVIQGSGVLDCWADFYFSWGPRAYITWTTMAIFVLPVAVLSACYGLICHEIYKNLKVKTQAGREERRGWRTWDKSSSSAVATAATRGLPSRVSSISTISRAKIRTVKMTFVIVLAYIACWAPFFSVQMWSVWDENAPNEDSTNVAFTISMLLGNLSSCCNPWIYMGFNSRLLPRSLSHHACCTGSKPQVHRQLSTSSLTSRRTTLLTHACGSPTLRLSLNLSLRAKPRPAGSLKDLEQVDGEATMETSIF,5.0 +OC(=O)c1cc(ccc1F)-c1cccc(c1)-c1cnc(s1)-c1ccccc1,MESLLGFLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEECGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHSDAPTAVTGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAATQRLNASFTWVASDGWGALESVVAGSERAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEERFHCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTHLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTDDEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSFIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFVFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVAAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAPRASANLGQGSGSQFVPTVCNGREVVDSTTSSL,5.0 +Cn1c2CCNCc2nc1C(=O)Nc1cccc(c1Cl)-c1cccc(NC(=O)c2nc3CN(CCC45CCC(CC4)(C5)C(O)=O)CCc3n2C)c1Cl,LDSPDRPWNPPTFSPALLVVTEGDNATFTCSFSNTSESFVLNWYRMSPSNQTDKLAAFPEDRSQPGQDCRFRVTQLPNGRDFHMSVVRARRNDSGTYLCGAISLAPKAQIKESLRAELRVTERRAEVPTAHPSPSPRPAGQFQ,8.301029995663981 +COc1cccc(CNC(=O)c2nc3ccc(F)c(OCCc4ccc(cc4)C(O)=O)c3c(=O)[nH]2)c1,MKSLPILLLLCVAVCSAYPLDGAARGEDTSMNLVQKYLENYYDLKKDVKQFVRRKDSGPVVKKIREMQKFLGLEVTGKLDSDTLEVMRKPRCGVPDVGHFRTFPGIPKWRKTHLTYRIVNYTPDLPKDAVDSAVEKALKVWEEVTPLTFSRLYEGEADIMISFAVREHGDFYPFDGPGNVLAHAYAPGPGINGDAHFDDDEQWTKDTTGTNLFLVAAHEIGHSLGLFHSANTEALMYPLYHSLTDLTRFRLSQDDINGIQSLYGPPPDSPETPLVPTEPVPPEPGTPANCDPALSFDAVSTLRGEILIFKDRHFWRKSLRKLEPELHLISSFWPSLPSGVDAAYEVTSKDLVFIFKGNQFWAIRGNEVRAGYPRGIHTLGFPPTVRKIDAAISDKEKNKTYFFVEDKYWRFDEKRNSMEPGFPKQIAEDFPGIDSKIDAVFEEFGFFYFFTGSSQLEFDPNAKKVTHTLKSNSWLNC,5.3979400086720375 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+CC(C)c1cc(Cc2c(C)cc(OCC(O)=O)cc2C)cc(C#Cc2ccccc2)c1O,MTPNSMTENGLTAWDKPKHCPDREHDWKLVGMSEACLHRKSHSERRSTLKNEQSSPHLIQTTWTSSIFHLDHDDVNDQSVSSAQTFQTEEKKCKGYIPSYLDKDELCVVCGDKATGYHYRCITCEGCKGFFRRTIQKNLHPSYSCKYEGKCVIDKVTRNQCQECRFKKCIYVGMATDLVLDDSKRLAKRKLIEENREKRRREELQKSIGHKPEPTDEEWELIKTVTEAHVATNAQGSHWKQKRKFLPEDIGQAPIVNAPEGGKVDLEAFSHFTKIITPAITRVVDFAKKLPMFCELPCEDQIILLKGCCMEIMSLRAAVRYDPESETLTLNGEMAVTRGQLKNGGLGVVSDAIFDLGMSLSSFNLDDTEVALLQAVLLMSSDRPGLACVERIEKYQDSFLLAFEHYINYRKHHVTHFWPKLLMKVTDLRMIGACHASRFLHMKVECPTELFPPLFLEVFED,6.301029995663981 +CCC1NC(=O)C(C(O)C(C)C\C=C\C)N(C)C(=O)C(C(C)C)N(C)C(=O)C(CC(C)C)N(C)C(=O)C(CC(C)C)N(C)C(=O)C(C)NC(=O)C(C)NC(=O)C(CC(C)C)N(C)C(=O)C(NC(=O)C(CC(C)C)N(C)C(=O)CN(C)C1=O)C(C)C,MDLEGDRNGGAKKKNFFKLNNKSEKDKKEKKPTVSVFSMFRYSNWLDKLYMVVGTLAAIIHGAGLPLMMLVFGEMTDIFANAGNLEDLMSNITNRSDINDTGFFMNLEEDMTRYAYYYSGIGAGVLVAAYIQVSFWCLAAGRQIHKIRKQFFHAIMRQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQSMATFFTGFIVGFTRGWKLTLVILAISPVLGLSAAVWAKILSSFTDKELLAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNKNLEEAKRIGIKKAITANISIGAAFLLIYASYALAFWYGTTLVLSGEYSIGQVLTVFFSVLIGAFSVGQASPSIEAFANARGAAYEIFKIIDNKPSIDSYSKSGHKPDNIKGNLEFRNVHFSYPSRKEVKILKGLNLKVQSGQTVALVGNSGCGKSTTVQLMQRLYDPTEGMVSVDGQDIRTINVRFLREIIGVVSQEPVLFATTIAENIRYGRENVTMDEIEKAVKEANAYDFIMKLPHKFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQVALDKARKGRTTIVIAHRLSTVRNADVIAGFDDGVIVEKGNHDELMKEKGIYFKLVTMQTAGNEVELENAADESKSEIDALEMSSNDSRSSLIRKRSTRRSVRGSQAQDRKLSTKEALDESIPPVSFWRIMKLNLTEWPYFVVGVFCAIINGGLQPAFAIIFSKIIGVFTRIDDPETKRQNSNLFSLLFLALGIISFITFFLQGFTFGKAGEILTKRLRYMVFRSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGAIGSRLAVITQNIANLGTGIIISFIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENFRTVVSLTQEQKFEHMYAQSLQVPYRNSLRKAHIFGITFSFTQAMMYFSYAGCFRFGAYLVAHKLMSFEDVLLVFSAVVFGAMAVGQVSSFAPDYAKAKISAAHIIMIIEKTPLIDSYSTEGLMPNTLEGNVTFGEVVFNYPTRPDIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPLAGKVLLDGKEIKRLNVQWLRAHLGIVSQEPILFDCSIAENIAYGDNSRVVSQEEIVRAAKEANIHAFIESLPNKYSTKVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVFQNGRVKEHGTHQQLLAQKGIYFSMVSVQAGTKRQ,6.136677139879544 +C(NC1CC1)[C@H]1CC[C@H](CC1)c1nnn2cnc3[nH]ccc3c12,MPLRHWGMARGSKPVGDGAQPMAAMGGLKVLLHWAGPGGGEPWVTFSESSLTAEEVCIHIAHKVGITPPCFNLFALFDAQAQVWLPPNHILEIPRDASLMLYFRIRFYFRNWHGMNPREPAVYRCGPPGTEASSDQTAQGMQLLDPASFEYLFEQGKHEFVNDVASLWELSTEEEIHHFKNESLGMAFLHLCHLALRHGIPLEEVAKKTSFKDCIPRSFRRHIRQHSALTRLRLRNVFRRFLRDFQPGRLSQQMVMVKYLATLERLAPRFGTERVPVCHLRLLAQAEGEPCYIRDSGVAPTDPGPESAAGPPTHEVLVTGTGGIQWWPVEEEVNKEEGSSGSSGRNPQASLFGKKAKAHKAVGQPADRPREPLWAYFCDFRDITHVVLKEHCVSIHRQDNKCLELSLPSRAAALSFVSLVDGYFRLTADSSHYLCHEVAPPRLVMSIRDGIHGPLLEPFVQAKLRPEDGLYLIHWSTSHPYRLILTVAQRSQAPDGMQSLRLRKFPIEQQDGAFVLEGWGRSFPSVRELGAALQGCLLRAGDDCFSLRRCCLPQPGETSNLIIMRGARASPRTLNLSQLSFHRVDQKEITQLSHLGQGTRTNVYEGRLRVEGSGDPEEGKMDDEDPLVPGRDRGQELRVVLKVLDPSHHDIALAFYETASLMSQVSHTHLAFVHGVCVRGPENIMVTEYVEHGPLDVWLRRERGHVPMAWKMVVAQQLASALSYLENKNLVHGNVCGRNILLARLGLAEGTSPFIKLSDPGVGLGALSREERVERIPWLAPECLPGGANSLSTAMDKWGFGATLLEICFDGEAPLQSRSPSEKEHFYQRQHRLPEPSCPQLATLTSQCLTYEPTQRPSFRTILRDLTRLQPHNLADVLTVNPDSPASDPTVFHKRYLKKIRDLGEGHFGKVSLYCYDPTNDGTGEMVAVKALKADCGPQHRSGWKQEIDILRTLYHEHIIKYKGCCEDQGEKSLQLVMEYVPLGSLRDYLPRHSIGLAQLLLFAQQICEGMAYLHAQHYIHRDLAARNVLLDNDRLVKIGDFGLAKAVPEGHEYYRVREDGDSPVFWYAPECLKEYKFYYASDVWSFGVTLYELLTHCDSSQSPPTKFLELIGIAQGQMTVLRLTELLERGERLPRPDKCPCEVYHLMKNCWETEASFRPTFENLIPILKTVHEKYQGQAPSVFSVC,6.026872146400302 +COc1ccc(-c2ccccc2)c(c1)C(=O)N1CCC[C@H]1c1nc(no1)-c1cccc(Cl)c1C,MEPSATPGAQMGVPPGSREPSPVPPDYEDEFLRYLWRDYLYPKQYEWVLIAAYVAVFVVALVGNTLVCLAVWRNHHMRTVTNYFIVNLSLADVLVTAICLPASLLVDITESWLFGHALCKVIPYLQAVSVSVAVLTLSFIALDRWYAICHPLLFKSTARRARGSILGIWAVSLAIMVPQAAVMECSSVLPELANRTRLFSVCDERWADDLYPKIYHSCFFIVTYLAPLGLMAMAYFQIFRKLWGRQIPGTTSALVRNWKRPSDQLGDLEQGLSGEPQPRARAFLAEVKQMRARRKTAKMLMVVLLVFALCYLPISVLNVLKRVFGMFRQASDREAVYACFTFSHWLVYANSAANPIIYNFLSGKFREQFKAAFSCCLPGLGPCGSLKAPSPRSSASHKSLSLQSRCSISKISEHVVLTSVTTVLP,8.045757490560675 +COC(=O)[C@@H]1CCCC[C@@H]1c1ccccc1,METTPLNSQKQLSACEDGEDCQENGVLQKVVPTPGDKVESGQISNGYSAVPSPGAGDDTRHSIPATTTTLVAELHQGERETWGKKVDFLLSVIGYAVDLGNVWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIMAWALYYLISSFTDQLPWTSCKNSWNTGNCTNYFSEDNITWTLHSTSPAEEFYTRHVLQIHRSKGLQDLGGISWQLALCIMLIFTVIYFSIWKGVKTSGKVVWVTATFPYIILSVLLVRGATLPGAWRGVLFYLKPNWQKLLETGVWIDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHVWAKRRERFVLAVVITCFFGSLVTLTFGGAYVVKLLEEYATGPAVLTVALIEAVAVSWFYGITQFCRDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPYWSIILGYCIGTSSFICIPTYIAYRLIITPGTFKERIIKSITPETPTEIPCGDIRLNAV,2.8210230527068303 +O=C1C[C@@H](N2CCOCC2)C(=O)NC[C@@H](Cc2ccccc2)NC(=O)[C@H](Cc2ccccc2)NC(=O)[C@H](Cc2c[nH]c3ccccc23)N1,MGTCDIVTEANISSGPESNTTGITAFSMPSWQLALWATAYLALVLVAVTGNAIVIWIILAHRRMRTVTNYFIVNLALADLCMAAFNAAFNFVYASHNIWYFGRAFCYFQNLFPITAMFVSIYSMTAIAADRYMAIVHPFQPRLSAPSTKAVIAGIWLVALALASPQCFYSTVTMDQGATKCVVAWPEDSGGKTLLLYHLVVIALIYFLPLAVMFVAYSVIGLTLWRRAVPGHQAHGANLRHLQAMKKFVKTMVLVVLTFAICWLPYHLYFILGSFQEDIYCHKFIQQVYLALFWLAMSSTMYNPIIYCCLNHRFRSGFRLAFRCCPWVTPTKEDKLELTPTTSLSTRVNRCHTKETLFMAGDTAPSEATSGEAGRPQDGSGLWFGYGLLAPTKTHVEI,9.800000874803203 +OC(=O)C(F)(F)F.OC(=O)C(F)(F)F.NC(=N)c1ccc(CNC(=O)[C@@H]2Cc3ccc(NC(=O)CN4CCN(CC4)CC(=O)Nc4ccc(C[C@@H](NC(=O)CCc5ccccc5)C(=O)N2)cc4)cc3)cc1,FPTDDDDKIVGGYTCAANSIPYQVSLNSGSHFCGGSLINSQWVVSAAHCYKSRIQVRLGEHNIDVLEGNEQFINAAKIITHPNFNGNTLDNDIMLIKLSSPATLNSRVATVSLPRSCAAAGTECLISGWGNTKSSGSSYPSLLQCLKAPVLSDSSCKSSYPGQITGNMICVGFLEGGKDSCQGDSGGPVVCNGQLQGIVSWGYGCAQKNKPGVYTKVCNYVNWIQQTIAAN,5.8449677712090296 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+Nc1scc2c(nn(-c3ccccc3)c(=O)c12)C(=O)N\N=C\c1ccc(Cl)cc1,MENTENSVDSKSIKNLEPKIIHGSESMDSGISLDNSYKMDYPEMGLCIIINNKNFHKSTGMTSRSGTDVDAANLRETFRNLKYEVRNKNDLTREEIVELMRDVSKEDHSKRSSFVCVLLSHGEEGIIFGTNGPVDLKKITNFFRGDRCRSLTGKPKLFIIQACRGTELDCGIETDSGVDDDMACHKIPVEADFLYAYSTAPGYYSWRNSKDGSWFIQSLCAMLKQYADKLEFMHILTRVNRKVATEFESFSFDATFHAKKQIPCIVSMLTKELYFYH,5.349692476868063 +COc1ccccc1C(O)CNCCOc1ccc(cc1)-n1ccnc1,MAPWPHENSSLAPWPDLPTLAPNTANTSGLPGVPWEAALAGALLALAVLATVGGNLLVIVAIAWTPRLQTMTNVFVTSLAAADLVMGLLVVPPAATLALTGHWPLGATGCELWTSVDVLCVTASIETLCALAVDRYLAVTNPLRYGALVTKRCARTAVVLVWVVSAAVSFAPIMSQWWRVGADAEAQRCHSNPRCCAFASNMPYVLLSSSVSFYLPLLVMLFVYARVFVVATRQLRLLRGELGRFPPEESPPAPSRSLAPAPVGTCAPPEGVPACGRRPARLLPLREHRALCTLGLIMGTFTLCWLPFFLANVLRALGGPSLVPGPAFLALNWLGYANSAFNPLIYCRSPDFRSAFRRLLCRCGRRLPPEPCAAARPALFPSGVPAARSSPAQPRLCQRLDGASWGVS,5.431798275933005 +Clc1cccc(c1)N1CCN(CCN2C(=O)CC3(CCCC3)CC2=O)CC1,MTFRDILSVTFEGPRSSSSTGGSGAGGGAGTVGPEGGAVGGVPGATGGGAVVGTGSGEDNQSSTGEPGAAASGEVNGSAAVGGLVVSAQGVGVGVFLAAFILTAVAGNLLVILSVACNRHLQTVTNYFIVNLAVADLLLSAAVLPFSATMEVLGFWAFGRTFCDVWAAVDVLCCTASILSLCTISVDRYVGVRHSLKYPAIMTERKAAAILALLWAVALVVSVGPLLGWKEPVPPDERFCGITEEVGYAIFSSVCSFYLPMAVIVVMYCRVYVVARSTTRSLEAGIKREPGKASEVVLRIHCRGAATSAKGYPGTQSSKGHTLRSSLSVRLLKFSREKKAAKTLAIVVGVFVLCWFPFFFVLPLGSLFPQLKPSEGVFKVIFWLGYFNSCVNPLIYPCSSREFKRAFLRLLRCQCRRRRRRLWAVYGHHWRASTGDARSDCAPSPRIAPPGAPLALTAHPGAGSADTPETQDSVSSSRKPASALREWRLLGPLQRPTTQLRAKVSSLSHKIRSGARRAETACALRSEVEAVSLNVPQDGAEAVICQAYEPGDYSNLRETDI,8.694648630553376 +C(N=Nc1nc2ccccc2[nH]1)c1c[nH]c2ccccc12,MALKLLSEKANSQALKVLLCSYYVKRPVEVSLSGAYATPILHHPAFKQPIIAPNEMARVILFYSVEPTSNNGGAADSSNGDGTASPVAGLTNLTLEHETWLEWEATTFTRAVHPLYTQRRQTAESLAVFSYLDKKISENDDRCVYSPAVEGKGAADPTDAVSTFFIDCIVWCAVLPALCESGVLRDSEKQQLPHLVKWFNTFQKEQKTLIDNAFENLSVQEAADFLRCPRVYKVSAKVEKVFFVTSPIYYVNAAPHIGHVYSTLITDVIGRYHRVKGERVFALTGTDEHGQKVAEAAKQKQVSPYDFTAAVAGEFKKCFEQMDYSIDYFIRTTNEQHKAVVKELWTKLEQKGDIYLGRYEGWYSISDESFLTPQNITDGVDKDGNPCKVSLESGHVVTWVSEENYMFRLSAFRERLLEWYHANPGCIVPEFRRREVIRAVEKGLPDLSVSRKKETLHNWAIPVPGNPDHCVYVWLDALTNYLTGSRLRVDESGKEVSLADDFSELERFPADVHVIGKDILKFHAIYWPAFLLSAGLPLPKKIVAHGWWTKDRKKISKSLGNVFDPVEKAEEFGYDALKYFLLRESGFSDDGDYSDKNMIARLNGELADTLGNLVMRCTSAKINVNGEWPSPAAYTEEDESLIQLIKDLPGTADHYYLIPDIQKAIIAVFDVLRAINAYVTDMAPWKLVKTDPERLRTVLYITLEGVRVTTLLLSPILPRKSVVIFDMLGVPEVHRKGIENFEFGAVPPGTRLGPAVEGEVLFSKRSTENTKST,4.492778499484339 +Cc1c(NC(=O)c2ccc(cc2)-c2ccc(F)cc2)ccc2cc(CN3CCCC3)cnc12,QATCTGCMDLQTSLLSTGPNASNISDGQDNLTLPGSPPRTGSVSYINIIMPSVFGTICLLGIVGNSTVIFAVVKKSKLHWCSNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMTIDRYLATVHPISSTKFRKPSMATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVKILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRTVSNAQTADEERTESKGT,9.0 +Clc1cccc(CN([C@H]2CCNC2)C2CCOCC2)c1Cl,MGLEALVPLAVIVAIFLLLVDLMHRRQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQLRRRFGDVFSLQLAWTPVVVLNGLAAVREALVTHGEDTADRPPVPITQILGFGPRSQGVFLARYGPAWREQRRFSVSTLRNLGLGKKSLEQWVTEEAACLCAAFANHSGRPFRPNGLLDKAVSNVIASLTCGRRFEYDDPRFLRLLDLAQEGLKEESGFLREVLNAVPVLLHIPALAGKVLRFQKAFLTQLDELLTEHRMTWDPAQPPRDLTEAFLAEMEKAKGNPESSFNDENLRIVVADLFSAGMVTTSTTLAWGLLLMILHPDVQRRVQQEIDDVIGQVRRPEMGDQAHMPYTTAVIHEVQRFGDIVPLGVTHMTSRDIEVQGFRIPKGTTLITNLSSVLKDEAVWEKPFRFHPEHFLDAQGHFVKPEAFLPFSAGRRACLGEPLARMELFLFFTSLLQHFSFSVPTGQPRPSHHGVFAFLVSPSPYELCAVPR,5.318758762624412 +COc1ccccc1-c1cccc(c1)-c1csc(n1)-c1ccccc1,MESLLGFLALLLLWGAVAEGPAKKVLTLEGDLVLGGLFPVHQKGGPAEECGPVNEHRGIQRLEAMLFALDRINRDPHLLPGVRLGAHILDSCSKDTHALEQALDFVRASLSRGADGSRHICPDGSYATHSDAPTAVTGVIGGSYSDVSIQVANLLRLFQIPQISYASTSAKLSDKSRYDYFARTVPPDFFQAKAMAEILRFFNWTYVSTVASEGDYGETGIEAFELEARARNICVATSEKVGRAMSRAAFEGVVRALLQKPSARVAVLFTRSEDARELLAATQRLNASFTWVASDGWGALESVVAGSERAAEGAITIELASYPISDFASYFQSLDPWNNSRNPWFREFWEERFHCSFRQRDCAAHSLRAVPFEQESKIMFVVNAVYAMAHALHNMHRALCPNTTHLCDAMRPVNGRRLYKDFVLNVKFDAPFRPADTDDEVRFDRFGDGIGRYNIFTYLRAGSGRYRYQKVGYWAEGLTLDTSFIPWASPSAGPLPASRCSEPCLQNEVKSVQPGEVCCWLCIPCQPYEYRLDEFTCADCGLGYWPNASLTGCFELPQEYIRWGDAWAVGPVTIACLGALATLFVLGVFVRHNATPVVKASGRELCYILLGGVFLCYCMTFVFIAKPSTAVCTLRRLGLGTAFSVCYSALLTKTNRIARIFGGAREGAQRPRFISPASQVAICLALISGQLLIVAAWLVVEAPGTGKETAPERREVVTLRCNHRDASMLGSLAYNVLLIALCTLYAFKTRKCPENFNEAKFIGFTMYTTCIIWLAFLPIFYVTSSDYRVQTTTMCVSVSLSGSVVLGCLFAPKLHIILFQPQKNVVSHRAPTSRFGSAAPRASANLGQGSGSQFVPTVCNGREVVDSTTSSL,5.7423214251308154 +Fc1cccc(Oc2c(Cl)cccc2Cl)c1OC1CNC1,MLLARMNPQVQPENNGADTGPEQPLRARKTAELLVVKERNGVQCLLAPRDGDAQPRETWGKKIDFLLSVVGFAVDLANVWRFPYLCYKNGGGAFLIPYTLFLIIAGMPLFYMELALGQYNREGAATVWKICPFFKGVGYAVILIALYVGFYYNVIIAWSLYYLFSSFTLNLPWTDCGHTWNSPNCTDPKLLNGSVLGNHTKYSKYKFTPAAEFYERGVLHLHESSGIHDIGLPQWQLLLCLMVVVIVLYFSLWKGVKTSGKVVWITATLPYFVLFVLLVHGVTLPGASNGINAYLHIDFYRLKEATVWIDAATQIFFSLGAGFGVLIAFASYNKFDNNCYRDALLTSSINCITSFVSGFAIFSILGYMAHEHKVNIEDVATEGAGLVFILYPEAISTLSGSTFWAVVFFVMLLALGLDSSMGGMEAVITGLADDFQVLKRHRKLFTFGVTFSTFLLALFCITKGGIYVLTLLDTFAAGTSILFAVLMEAIGVSWFYGVDRFSNDIQQMMGFRPGLYWRLCWKFVSPAFLLFVVVVSIINFKPLTYDDYIFPPWANWVGWGIALSSMVLVPIYVIYKFLSTQGSLWERLAYGITPENEHHLVAQRDIRQFQLQHWLAI,6.785156151952302 +COc1cc(NC(=O)c2ccc(Oc3ccccc3)cc2)ccc1C(=O)NCCCN(C)C,MSVGAMKKGVGRAVGLGGGSGCQATEEDPLPNCGACAPGQGGRRWRLPQPAWVEGSSARLWEQATGTGWMDLEASLLPTGPNASNTSDGPDNLTSAGSPPRTGSISYINIIMPSVFGTICLLGIIGNSTVIFAVVKKSKLHWCNNVPDIFIINLSVVDLLFLLGMPFMIHQLMGNGVWHFGETMCTLITAMDANSQFTSTYILTAMAIDRYLATVHPISSTKFRKPSVATLVICLLWALSFISITPVWLYARLIPFPGGAVGCGIRLPNPDTDLYWFTLYQFFLAFALPFVVITAAYVRILQRMTSSVAPASQRSIRLRTKRVTRTAIAICLVFFVCWAPYYVLQLTQLSISRPTLTFVYLYNAAISLGYANSCLNPFVYIVLCETFRKRLVLSVKPAAQGQLRAVSNAQTADEERTESKGT,5.71669877129645 +C[C@H]([C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H]1Cc2ccccc2CN1C(=O)[C@@H](N)Cc1ccc(O)cc1)C(N)=O)c1ccccc1,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,7.327902142064282 +CCc1c(C#N)c(c(C(O)=O)n1C)-c1ccc(cc1)-c1ccccc1SC,MQKIMHISVLLSPVLWGLIFGVSSNSIQIGGLFPRGADQEYSAFRVGMVQFSTSEFRLTPHIDNLEVANSFAVTNAFCSQFSRGVYAIFGFYDKKSVNTITSFCGTLHVSFITPSFPTDGTHPFVIQMRPDLKGALLSLIEYYQWDKFAYLYDSDRGLSTLQAVLDSAAEKKWQVTAINVGNINNDKKDEMYRSLFQDLELKKERRVILDCERDKVNDIVDQVITIGKHVKGYHYIIANLGFTDGDLLKIQFGGANVSGFQIVDYDDSLVSKFIERWSTLEEKEYPGAHTTTIKYTSALTYDAVQVMTEAFRNLRKQRIEISRRGNAGDCLANPAVPWGQGVEIERALKQVQVEGLSGNIKFDQNGKRINYTINIMELKTNGPRKIGYWSEVDKMVVTLTELPSGNDTSGLENKTVVVTTILESPYVMMKKNHEMLEGNERYEGYCVDLAAEIAKHCGFKYKLTIVGDGKYGARDADTKIWNGMVGELVYGKADIAIAPLTITLVREEVIDFSKPFMSLGISIMIKKPQKSKPGVFSFLDPLAYEIWMCIVFAYIGVSVVLFLVSRFSPYEWHTEEFEDGRETQSSESTNEFGIFNSLWFSLGAFMQQGCDISPRSLSGRIVGGVWWFFTLIIISSYTANLAAFLTVERMVSPIESAEDLSKQTEIAYGTLDSGSTKEFFRRSKIAVFDKMWTYMRSAEPSVFVRTTAEGVARVRKSKGKYAYLLESTMNEYIEQRKPCDTMKVGGNLDSKGYGIATPKGSSLRNAVNLAVLKLNEQGLLDKLKNKWWYDKGECGSGGGDSKEKTSALSLSNVAGVFYILVGGLGLAMLVALIEFCYKSRAEAKRMKVAKNAQNINPSSSQNSQNFATYKEGYNVYGIESVKI,7.494850021680094 +Cc1cc(COc2ccc(cc2)S(=O)(=O)CC(C=C2CCSCC2)N(O)C=O)c2ccccc2n1,MHPGVLAAFLFLSWTHCRALPLPSGGDEDDLSEEDLQFAERYLRSYYHPTNLAGILKENAASSMTERLREMQSFFGLEVTGKLDDNTLDVMKKPRCGVPDVGEYNVFPRTLKWSKMNLTYRIVNYTPDMTHSEVEKAFKKAFKVWSDVTPLNFTRLHDGIADIMISFGIKEHGDFYPFDGPSGLLAHAFPPGPNYGGDAHFDDDETWTSSSKGYNLFLVAAHEFGHSLGLDHSKDPGALMFPIYTYTGKSHFMLPDDDVQGIQSLYGPGDEDPNPKHPKTPDKCDPSLSLDAITSLRGETMIFKDRFFWRLHPQQVDAELFLTKSFWPELPNRIDAAYEHPSHDLIFIFRGRKFWALNGYDILEGYPKKISELGLPKEVKKISAAVHFEDTGKTLLFSGNQVWRYDDTNHIMDKDYPRLIEEDFPGIGDKVDAVYEKNGYIYFFNGPIQFEYSIWSNRIVRVMPANSILWC,4.6020599913279625 +C[C@@H]1C[C@H]2OC(=O)C(=C)[C@H]2[C@H](OC(=O)CC(=O)O[C@H]2[C@H]3[C@@H](C[C@@H](C)[C@@H]4C=CC(=O)[C@@]24C)OC(=O)C3=C)[C@@]2(C)[C@H]1C=CC2=O,MGFCRSALHPLSLLVQAIMLAMTLALGTLPAFLPCELQPHGLVNCNWLFLKSVPHFSMAAPRGNVTSLSLSSNRIHHLHDSDFAHLPSLRHLNLKWNCPPVGLSPMHFPCHMTIEPSTFLAVPTLEELNLSYNNIMTVPALPKSLISLSLSHTNILMLDSASLAGLHALRFLFMDGNCYYKNPCRQALEVAPGALLGLGNLTHLSLKYNNLTVVPRNLPSSLEYLLLSYNRIVKLAPEDLANLTALRVLDVGGNCRRCDHAPNPCMECPRHFPQLHPDTFSHLSRLEGLVLKDSSLSWLNASWFRGLGNLRVLDLSENFLYKCITKTKAFQGLTQLRKLNLSFNYQKRVSFAHLSLAPSFGSLVALKELDMHGIFFRSLDETTLRPLARLPMLQTLRLQMNFINQAQLGIFRAFPGLRYVDLSDNRISGASELTATMGEADGGEKVWLQPGDLAPAPVDTPSSEDFRPNCSTLNFTLDLSRNNLVTVQPEMFAQLSHLQCLRLSHNCISQAVNGSQFLPLTGLQVLDLSHNKLDLYHEHSFTELPRLEALDLSYNSQPFGMQGVGHNFSFVAHLRTLRHLSLAHNNIHSQVSQQLCSTSLRALDFSGNALGHMWAEGDLYLHFFQGLSGLIWLDLSQNRLHTLLPQTLRNLPKSLQVLRLRDNYLAFFKWWSLHFLPKLEVLDLAGNQLKALTNGSLPAGTRLRRLDVSCNSISFVAPGFFSKAKELRELNLSANALKTVDHSWFGPLASALQILDVSANPLHCACGAAFMDFLLEVQAAVPGLPSRVKCGSPGQLQGLSIFAQDLRLCLDEALSWDCFALSLLAVALGLGVPMLHHLCGWDLWYCFHLCLAWLPWRGRQSGRDEDALPYDAFVVFDKTQSAVADWVYNELRGQLEECRGRWALRLCLEERDWLPGKTLFENLWASVYGSRKTLFVLAHTDRVSGLLRASFLLAQQRLLEDRKDVVVLVILSPDGRRSRYVRLRQRLCRQSVLLWPHQPSGQRSFWAQLGMALTRDNHHFYNRNFCQGPTAE,5.136617651559212 +NCCCOc1cc2ncccc2cc1NC(=O)c1csc2cncnc12,MASSGMADSANHLPFFFGNITREEAEDYLVQGGMSDGLYLLRQSRNYLGGFALSVAHGRKAHHYTIERELNGTYAIAGGRTHASPADLCHYHSQESDGLVCLLKKPFNRPQGVQPKTGPFEDLKENLIREYVKQTWNLQGQALEQAIISQKPQLEKLIATTAHEKMPWFHGKISREESEQIVLIGSKTNGKFLIRARDNNGSYALCLLHEGKVLHYRIDKDKTGKLSIPEGKKFDTLWQLVEHYSYKADGLLRVLTVPCQKIGTQGNVNFGGRPQLPGSHPATWSAGGIISRIKSYSFPKPGHRKSSPAQGNRQESTVSFNPYEPELAPWAADKGPQREALPMDTEVYESPYADPEEIRPKEVYLDRKLLTLEDKELGSGNFGTVKKGYYQMKKVVKTVAVKILKNEANDPALKDELLAEANVMQQLDNPYIVRMIGICEAESWMLVMEMAELGPLNKYLQQNRHVKDKNIIELVHQVSMGMKYLEESNFVHRDLAARNVLLVTQHYAKISDFGLSKALRADENYYKAQTHGKWPVKWYAPECINYYKFSSKSDVWSFGVLMWEAFSYGQKPYRGMKGSEVTAMLEKGERMGCPAGCPREMYDLMNLCWTYDVENRPGFAAVELRLRNYYYDVVN,6.424812155072339 +CN(C1CCOCC1)C(=O)c1ccc(Nc2nn([C@@H](CC#N)C3CC3)c3cc[nH]c(=O)c23)cc1C,MQYLNIKEDCNAMAFCAKMRSSKKTEVNLEAPEPGVEVIFYLSDREPLRLGSGEYTAEELCIRAAQACRISPLCHNLFALYDENTKLWYAPNRTITVDDKMSLRLHYRMRFYFTNWHGTNDNEQSVWRHSPKKQKNGYEKKKIPDATPLLDASSLEYLFAQGQYDLVKCLAPIRDPKTEQDGHDIENECLGMAVLAISHYAMMKKMQLPELPKDISYKRYIPETLNKSIRQRNLLTRMRINNVFKDFLKEFNNKTICDSSVSTHDLKVKYLATLETLTKHYGAEIFETSMLLISSENEMNWFHSNDGGNVLYYEVMVTGNLGIQWRHKPNVVSVEKEKNKLKRKKLENKHKKDEEKNKIREEWNNFSYFPEITHIVIKESVVSINKQDNKKMELKLSSHEEALSFVSLVDGYFRLTADAHHYLCTDVAPPLIVHNIQNGCHGPICTEYAINKLRQEGSEEGMYVLRWSCTDFDNILMTVTCFEKSEQVQGAQKQFKNFQIEVQKGRYSLHGSDRSFPSLGDLMSHLKKQILRTDNISFMLKRCCQPKPREISNLLVATKKAQEWQPVYPMSQLSFDRILKKDLVQGEHLGRGTRTHIYSGTLMDYKDDEGTSEEKKIKVILKVLDPSHRDISLAFFEAASMMRQVSHKHIVYLYGVCVRDVENIMVEEFVEGGPLDLFMHRKSDVLTTPWKFKVAKQLASALSYLEDKDLVHGNVCTKNLLLAREGIDSECGPFIKLSDPGIPITVLSRQECIERIPWIAPECVEDSKNLSVAADKWSFGTTLWEICYNGEIPLKDKTLIEKERFYESRCRPVTPSCKELADLMTRCMNYDPNQRPFFRAIMRDINKLEEQNPDIVSEKKPATEVDPTHFEKRFLKRIRDLGEGHFGKVELCRYDPEGDNTGEQVAVKSLKPESGGNHIADLKKEIEILRNLYHENIVKYKGICTEDGGNGIKLIMEFLPSGSLKEYLPKNKNKINLKQQLKYAVQICKGMDYLGSRQYVHRDLAARNVLVESEHQVKIGDFGLTKAIETDKEYYTVKDDRDSPVFWYAPECLMQSKFYIASDVWSFGVTLHELLTYCDSDSSPMALFLKMIGPTHGQMTVTRLVNTLKEGKRLPCPPNCPDEVYQLMRKCWEFQPSNRTSFQNLIEGFEALLK,6.1938200260161125 +CCOc1c(cc(Cl)c(C#N)c1C1CN(CC2CCOC2)C1)C(C)n1nc(C)c2c(N)ncnc12,MPPGVDCPMEFWTKEENQSVVVDFLLPTGVYLNFPVSRNANLSTIKQLLWHRAQYEPLFHMLSGPEAYVFTCINQTAEQQELEDEQRRLCDVQPFLPVLRLVAREGDRVKKLINSQISLLIGKGLHEFDSLCDPEVNDFRAKMCQFCEEAAARRQQLGWEAWLQYSFPLQLEPSAQTWGPGTLRLPNRALLVNVKFEGSEESFTFQVSTKDVPLALMACALRKKATVFRQPLVEQPEDYTLQVNGRHEYLYGSYPLCQFQYICSCLHSGLTPHLTMVHSSSILAMRDEQSNPAPQVQKPRAKPPPIPAKKPSSVSLWSLEQPFRIELIQGSKVNADERMKLVVQAGLFHGNEMLCKTVSSSEVSVCSEPVWKQRLEFDINICDLPRMARLCFALYAVIEKAKKARSTKKKSKKADCPIAWANLMLFDYKDQLKTGERCLYMWPSVPDEKGELLNPTGTVRSNPNTDSAAALLICLPEVAPHPVYYPALEKILELGRHSECVHVTEEEQLQLREILERRGSGELYEHEKDLVWKLRHEVQEHFPEALARLLLVTKWNKHEDVAQMLYLLCSWPELPVLSALELLDFSFPDCHVGSFAIKSLRKLTDDELFQYLLQLVQVLKYESYLDCELTKFLLDRALANRKIGHFLFWHLRSEMHVPSVALRFGLILEAYCRGSTHHMKVLMKQGEALSKLKALNDFVKLSSQKTPKPQTKELMHLCMRQEAYLEALSHLQSPLDPSTLLAEVCVEQCTFMDSKMKPLWIMYSNEEAGSGGSVGIIFKNGDDLRQDMLTLQMIQLMDVLWKQEGLDLRMTPYGCLPTGDRTGLIEVVLRSDTIANIQLNKSNMAATAAFNKDALLNWLKSKNPGEALDRAIEEFTLSCAGYCVATYVLGIGDRHSDNIMIRESGQLFHIDFGHFLGNFKTKFGINRERVPFILTYDFVHVIQQGKTNNSEKFERFRGYCERAYTILRRHGLLFLHLFALMRAAGLPELSCSKDIQYLKDSLALGKTEEEALKHFRVKFNEALRESWKTKVNWLAHNVSKDNRQ,8.0 +O=C(N[C@H]1[C@@H]([C@@H]1c1ccccc1)c1ccccc1)N1CCCCC1,MTLRAAVFDLDGVLALPAVFGVLGRTEEALALPRGLLNDAFQKGGPEGATTRLMKGEITLSQWIPLMEENCRKCSETAKVCLPKNFSIKEIFDKAISARKINRPMLQAALMLRKKGFTTAILTNTWLDDRAERDGLAQLMCELKMHFDFLIESCQVGMVKPEPQIYKFLLDTLKASPSEVVFLDDIGANLKPARDLGMVTILVQDTDTALKELEKVTGIQLLNTPAPLPTSCNPSDMSHGYVTVKPRVRLHFVELGSGPAVCLCHGFPESWYSWRYQIPALAQAGYRVLAMDMKGYGESSAPPEIEEYCMEVLCKEMVTFLDKLGLSQAVFIGHDWGGMLVWYMALFYPERVRAVASLNTPFIPANPNMSPLESIKANPVFDYQLYFQEPGVAEAELEQNLSRTFKSLFRASDESVLSMHKVCEAGGLFVNSPEEPSLSRMVTEEEIQFYVQQFKKSGFRGPLNWYRNMERNWKWACKSLGRKILIPALMVTAEKDFVLVPQMSQHMEDWIPHLKRGHIEDCGHWTQMDKPTEVNQILIKWLDSDARNPPVVSKM,8.744727494896694 +CC(C)[N+]1([O-])C(=O)[C@]2(C)O[C@@](C)(c3c(O)n(c(O)c23)-c2ccc(C#N)c(c2)C(F)(F)F)C1=O,MEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAPPGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLVLDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGPTFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGTSTISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAECKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYKSGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYGDLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGGGGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMDSYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAEGKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASSTTSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELGERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDLVFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFDELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVSVDFPEMMAEIISVQVPKILSGKVKPIYFHTQ,5.443697499232712 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+CC(C)(C)Nc1nc(N2CCC(F)(F)C2)c2nnn(Cc3ccccc3Cl)c2n1,MKSILDGLADTTFRTITTDLLYVGSNDIQYEDIKGDMASKLGYFPQKFPLTSFRGSPFQEKMTAGDNPQLVPADQVNITEFYNKSLSSFKENEENIQCGENFMDIECFMVLNPSQQLAIAVLSLTLGTFTVLENLLVLCVILHSRSLRCRPSYHFIGSLAVADLLGSVIFVYSFIDFHVFHRKDSRNVFLFKLGGVTASFTASVGSLFLTAIDRYISIHRPLAYKRIVTRPKAVVAFCLMWTIAIVIAVLPLLGWNCEKLQSVCSDIFPHIDETYLMFWIGVTSVLLLFIVYAYMYILWKAHSHAVRMIQRGTQKSIIIHTSEDGKVQVTRPDQARMDIRLAKTLVLILVVLIICWGPLLAIMVYDVFGKMNKLIKTVFAFCSMLCLLNSTVNPIIYALRSKDLRHAFRSMFPSCEGTAQPLDNSMGDSDCLHKHANNAASVHRAAESCIKSTVKIAKVTMSVSTDTSAEAL,6.437707135543525 +C[C@@H]1COCCN1c1cc(N=S(C)(C)=O)nc(n1)-n1c(C)nc2ccccc12,MGEHGLELASMIPALRELGSATPEEYNTVVQKPRQILCQFIDRILTDVNVVAVELVKKTDSQPTSVMLLDFIQHIMKSSPLMFVNVSGSHEAKGSCIEFSNWIITRLLRIAATPSCHLLHKKICEVICSLLFLFKSKSPAIFGVLTKELLQLFEDLVYLHRRNVMGHAVEWPVVMSRFLSQLDEHMGYLQSAPLQLMSMQNLEFIEVTLLMVLTRIIAIVFFRRQELLLWQIGCVLLEYGSPKIKSLAISFLTELFQLGGLPAQPASTFFSSFLELLKHLVEMDTDQLKLYEEPLSKLIKTLFPFEAEAYRNIEPVYLNMLLEKLCVMFEDGVLMRLKSDLLKAALCHLLQYFLKFVPAGYESALQVRKVYVRNICKALLDVLGIEVDAEYLLGPLYAALKMESMEIIEEIQCQTQQENLSSNSDGISPKRRRLSSSLNPSKRAPKQTEEIKHVDMNQKSILWSALKQKAESLQISLEYSGLKNPVIEMLEGIAVVLQLTALCTVHCSHQNMNCRTFKDCQHKSKKKPSVVITWMSLDFYTKVLKSCRSLLESVQKLDLEATIDKVVKIYDALIYMQVNSSFEDHILEDLCGMLSLPWIYSHSDDGCLKLTTFAANLLTLSCRISDSYSPQAQSRCVFLLTLFPRRIFLEWRTAVYNWALQSSHEVIRASCVSGFFILLQQQNSCNRVPKILIDKVKDDSDIVKKEFASILGQLVCTLHGMFYLTSSLTEPFSEHGHVDLFCRNLKATSQHECSSSQLKASVCKPFLFLLKKKIPSPVKLAFIDNLHHLCKHLDFREDETDVKAVLGTLLNLMEDPDKDVRVAFSGNIKHILESLDSEDGFIKELFVLRMKEAYTHAQISRNNELKDTLILTTGDIGRAAKGDLVPFALLHLLHCLLSKSASVSGAAYTEIRALVAAKSVKLQSFFSQYKKPICQFLVESLHSSQMTALPNTPCQNADVRKQDVAHQREMALNTLSEIANVFDFPDLNRFLTRTLQVLLPDLAAKASPAASALIRTLGKQLNVNRREILINNFKYIFSHLVCSCSKDELERALHYLKNETEIELGSLLRQDFQGLHNELLLRIGEHYQQVFNGLSILASFASSDDPYQGPRDIISPELMADYLQPKLLGILAFFNMQLLSSSVGIEDKKMALNSLMSLMKLMGPKHVSSVRVKMMTTLRTGLRFKDDFPELCCRAWDCFVRCLDHACLGSLLSHVIVALLPLIHIQPKETAAIFHYLIIENRDAVQDFLHEIYFLPDHPELKKIKAVLQEYRKETSESTDLQTTLQLSMKAIQHENVDVRIHALTSLKETLYKNQEKLIKYATDSETVEPIISQLVTVLLKGCQDANSQARLLCGECLGELGAIDPGRLDFSTTETQGKDFTFVTGVEDSSFAYGLLMELTRAYLAYADNSRAQDSAAYAIQELLSIYDCREMETNGPGHQLWRRFPEHVREILEPHLNTRYKSSQKSTDWSGVKKPIYLSKLGSNFAEWSASWAGYLITKVRHDLASKIFTCCSIMMKHDFKVTIYLLPHILVYVLLGCNQEDQQEVYAEIMAVLKHDDQHTINTQDIASDLCQLSTQTVFSMLDHLTQWARHKFQALKAEKCPHSKSNRNKVDSMVSTVDYEDYQSVTRFLDLIPQDTLAVASFRSKAYTRAVMHFESFITEKKQNIQEHLGFLQKLYAAMHEPDGVAGVSAIRKAEPSLKEQILEHESLGLLRDATACYDRAIQLEPDQIIHYHGVVKSMLGLGQLSTVITQVNGVHANRSEWTDELNTYRVEAAWKLSQWDLVENYLAADGKSTTWSVRLGQLLLSAKKRDITAFYDSLKLVRAEQIVPLSAASFERGSYQRGYEYIVRLHMLCELEHSIKPLFQHSPGDSSQEDSLNWVARLEMTQNSYRAKEPILALRRALLSLNKRPDYNEMVGECWLQSARVARKAGHHQTAYNALLNAGESRLAELYVERAKWLWSKGDVHQALIVLQKGVELCFPENETPPEGKNMLIHGRAMLLVGRFMEETANFESNAIMKKYKDVTACLPEWEDGHFYLAKYYDKLMPMVTDNKMEKQGDLIRYIVLHFGRSLQYGNQFIYQSMPRMLTLWLDYGTKAYEWEKAGRSDRVQMRNDLGKINKVITEHTNYLAPYQFLTAFSQLISRICHSHDEVFVVLMEIIAKVFLAYPQQAMWMMTAVSKSSYPMRVNRCKEILNKAIHMKKSLEKFVGDATRLTDKLLELCNKPVDGSSSTLSMSTHFKMLKKLVEEATFSEILIPLQSVMIPTLPSILGTHANHASHEPFPGHWAYIAGFDDMVEILASLQKPKKISLKGSDGKFYIMMCKPKDDLRKDCRLMEFNSLINKCLRKDAESRRRELHIRTYAVIPLNDECGIIEWVNNTAGLRPILTKLYKEKGVYMTGKELRQCMLPKSAALSEKLKVFREFLLPRHPPIFHEWFLRTFPDPTSWYSSRSAYCRSTAVMSMVGYILGLGDRHGENILFDSLTGECVHVDFNCLFNKGETFEVPEIVPFRLTHNMVNGMGPMGTEGLFRRACEVTMRLMRDQREPLMSVLKTFLHDPLVEWSKPVKGHSKAPLNETGEVVNEKAKTHVLDIEQRLQGVIKTRNRVTGLPLSIEGHVHYLIQEATDENLLCQMYLGWTPYM,8.522878745280337 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+Clc1cccc(c1)-c1cccc(n1)C(=O)NC1CCCCC1,MEECWVTEIANGSKDGLDSNPMKDYMILSGPQKTAVAVLCTLLGLLSALENVAVLYLILSSHQLRRKPSYLFIGSLAGADFLASVVFACSFVNFHVFHGVDSKAVFLLKIGSVTMTFTASVGSLLLTAIDRYLCLRYPPSYKALLTRGRALVTLGIMWVLSALVSYLPLMGWTCCPRPCSELFPLIPNDYLLSWLLFIAFLFSGIIYTYGHVLWKAHQHVASLSGHQDRQVPGMARMRLDVRLAKTLGLVLAVLLICWFPVLALMAHSLATTLSDQVKKAFAFCSMLCLINSMVNPVIYALRSGEIRSSAHHCLAHWKKCVRGLGSEAKEEAPRSSVTETEADGKITPWPDSRDLDLSDC,7.013228265733755 +COC(=O)c1cc(I)cnc1N1CCC(NC2CCCCC2)C(O)C1,MDSPIQIFRGEPGPTCAPSACLPPNSSAWFPGWAEPDSNGSAGSEDAQLEPAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSTVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLSSSVGISAIVLGGTKVREDVDVIECSLQFPDDDYSWWDLFMKICVFIFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITRLVLVVVAVFVVCWTPIHIFILVEALGSTSHSTAALSSYYFCIALGYTNSSLNPILYAFLDENFKRCFRDFCFPLKMRMERQSTSRVRNTVQDPAYLRDIDGMNKPV,6.950781977329818 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+CCCCNNC(=O)c1ccc(OC(F)(F)F)cc1,IPPMLYDADQQRIKFINMNGLMADPMKVYKDRQVMNMWSEQEKETFREKFMQHPKNFGLIASFLERKTVAECVLYYYLTKKNENYKSLVRRSYRRRGKSQQQQQ,5.041436116778033 +CN1CCN(CC1)c1ccc(Nc2ncc3ccn(-c4cccnc4)c3n2)cc1,mehqllccevetirraypdanllndrvlramlkaeetcapsvsyfkcvqkevlpsmrkivatwmlevceeqkceeevfplamnyldrflslepvkksrlqllgatcmfvaskmketipltaeklciytdgsirpeellqmelllvnklkwnlaamtphdfiehflskmpeaeenkqiirkhaqtfvascatdvkfisnppsmvaagsvvaavqglnlrspnnflsyyrltrflsrvikcdpdclracqeqieallesslrqaqqnmdpkaaeeeeeeeeevdlactptdvrdvdi,5.853871964321762 +CC(C)(CO)S(=O)(=O)c1c(Cl)ccc(NC(=O)N[C@@H]2CCC=C2Cl)c1O,MEDFNMESDSFEDFWKGEDLSNYSYSSTLPPFLLDAAPCEPESLEINKYFVVIIYALVFLLSLLGNSLVMLVILYSRVGRSVTDVYLLNLALADLLFALTLPIWAASKVNGWIFGTFLCKVVSLLKEVNFYSGILLLACISVDRYLAIVHATRTLTQKRYLVKFICLSIWGLSLLLALPVLLFRRTVYSSNVSPACYEDMGNNTANWRMLLRILPQSFGFIVPLLIMLFCYGFTLRTLFKAHMGQKHRAMRVIFAVVLIFLLCWLPYNLVLLADTLMRTQVIQETCERRNHIDRALDATEILGILHSCLNPLIYAFIGQKFRHGLLKILAIHGLISKDSLPKDSRPSFVGSSSGHTSTTL,8.397940008672037 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+Clc1cccc-2c1C(=O)c1nc3ccccc3c(=O)n-21,MLHFHYYDTSNKIMEPHRPNVKTAVPLSLESYHISEEYGFLLPDSLKELPDHYRPWMEIANKLPQLIDAHQLQAHVDKMPLLSCQFLKGHREQRLAHLVLSFLTMGYVWQEGEAQPAEVLPRNLALPFVEVSRNLGLPPILVHSDLVLTNWTKKDPDGFLEIGNLETIISFPGGESLHGFILVTALVEKEAVPGIKALVQATNAILQPNQEALLQALQRLRLSIQDITKTLGQMHDYVDPDIFYAGIRIFLSGWKDNPAMPAGLMYEGVSQEPLKYSGGSAAQSTVLHAFDEFLGIRHSKESGDFLYRMRDYMPPSHKAFIEDIHSAPSLRDYILSSGQDHLLTAYNQCVQALAELRSYHITMVTKYLITAAAKAKHGKPNHLPGPPQALKDRGTGGTAVMSFLKSVRDKTLESILHPRG,4.362510270487489 +CC[C@H]1[C@@H](O)[C@H]2[C@@H]3CC[C@H]([C@H](C)CCOC(=O)N4CCC(Cc5ccccc5)CC4)[C@@]3(C)CC[C@@H]2[C@@]2(C)CC[C@@H](O)C[C@@H]12,MVMQFQGLENPIQISPHCSCTPSGFFMEMMSMKPAKGVLTEQVAGPLGQNLEVEPYSQYSNVQFPQVQPQISSSSYYSNLGFYPQQPEEWYSPGIYELRRMPAETLYQGETEVAEMPVTKKPRMGASAGRIKGDELCVVCGDRASGYHYNALTCEGCKGFFRRSITKNAVYKCKNGGNCVMDMYMRRKCQECRLRKCKEMGMLAECMYTGLLTEIQCKSKRLRKNVKQHADQTVNEDSEGRDLRQVTSTTKSCREKTELTPDQQTLLHFIMDSYNKQRMPQEITNKILKEEFSAEENFLILTEMATNHVQVLVEFTKKLPGFQTLDHEDQIALLKGSAVEAMFLRSAEIFNKKLPSGHSDLLEERIRNSGISDEYITPMFSFYKSIGELKMTQEEYALLTAIVILSPDRQYIKDREAVEKLQEPLLDVLQKLCKIHQPENPQHFACLLGRLTELRTFNHHHAEMLMSWRVNDHKFTPLLCEIWDVQ,7.259637310505756 +CC(N1CCN(CC1)C(=O)OC(C)(C)C)c1ccnc(Nc2nc3ccc(cc3[nH]2)-c2cnn(CC3CC3C)c2)c1,MQSTSNHLWLLSDILGQGATANVFRGRHKKTGDLFAIKVFNNISFLRPVDVQMREFEVLKKLNHKNIVKLFAIEEETTTRHKVLIMEFCPCGSLYTVLEEPSNAYGLPESEFLIVLRDVVGGMNHLRENGIVHRDIKPGNIMRVIGEDGQSVYKLTDFGAARELEDDEQFVSLYGTEEYLHPDMYERAVLRKDHQKKYGATVDLWSIGVTFYHAATGSLPFRPFEGPRRNKEVMYKIITGKPSGAISGVQKAENGPIDWSGDMPVSCSLSRGLQVLLTPVLANILEADQEKCWGFDQFFAETSDILHRMVIHVFSLQQMTAHKIYIHSYNTATIFHELVYKQTKIISSNQELIYEGRRLVLEPGRLAQHFPKTTEENPIFVVSREPLNTIGLIYEKISLPKVHPRYDLDGDASMAKAITGVVCYACRIASTLLLYQELMRKGIRWLIELIKDDYNETVHKKTEVVITLDFCIRNIEKTVKVYEKLMKINLEAAELGEISDIHTKLLRLSSSQGTIETSLQDIDSRLSPGGSLADAWAHQEGTHPKDRNVEKLQVLLNCMTEIYYQFKKDKAERRLAYNEEQIHKFDKQKLYYHATKAMTHFTDECVKKYEAFLNKSEEWIRKMLHLRKQLLSLTNQCFDIEEEVSKYQEYTNELQETLPQKMFTASSGIKHTMTPIYPSSNTLVEMTLGMKKLKEEMEGVVKELAENNHILERFGSLTMDGGLRNVDCL,7.782516055786093 +COc1nc(N)ncc1-c1nc2C(=O)N([C@H](c2n1C(C)C)c1ccc(Cl)cc1)c1cccc(Cl)c1F,MCNTNMSVPTDGAVTTSQIPASEQETLVRPKPLLLKLLKSVGAQKDTYTMKEVLFYLGQYIMTKRLYDEKQQHIVYCSNDLLGDLFGVPSFSVKEHRKIYTMIYRNLVVVNQQESSDSGTSVSENRCHLEGGSDQKDLVQELQEEKPSSSHLVSRPSTSSRRRAISETEENSDELSGERQRKRHKSDSISLSFDESLALCVIREICCERSSSSESTGTPSNPDLDAGVSEHSGDWLDQDSVSDQFSVEFEVESLDSEDYSLSEEGQELSDEDDEVYQVTVYQAGESDTDSFEEDPEISLADYWKCTSCNEMNPPLPSHCNRCWALRENWLPEDKGKDKGEISEKAKLENSTQAEEGFDVPDCKKTIVNDSRESCVEENDDKITQASQSQESEDYSQPSTSSSIIYSSQEDVKEFEREETQDKEESVESSLPLNAIEPCVICQGRPKNGCIVHGKTGHLMACFTCAKKLKKRNKPCPVCRQPIQMIVLTYFP,9.744727494896694 +COc1ncccc1NC(=O)N1CCC(CC1)N1CC(CC#N)(C1)n1ccc(c1)-c1ncnc2[nH]ccc12,FFRAIMRDINKLEEQNPDIVSEKKPATEVDPTHFEKRFLKRIRDLGEGHFGKVELCRYDPEGDNTGEQVAVKSLKPESGGNHIADLKKEIEILRNLYHENIVKYKGICTEDGGNGIKLIMEFLPSGSLKEYLPKNKNKINLKQQLKYAVQICKGMDYLGSRQYVHRDLAARNVLVESEHQVKIGDFGLTKAIETDKEYYTVKDDRDSPVFWYAPECLMQSKFYIASDVWSFGVTLHELLTYCDSDSSPMALFLKMIGPTHGQMTVTRLVNTLKEGKRLPCPPNCPDEVYQLMRKCWEFQPSNRTSF,8.0 +Cc1ccc(cc1)C1C2CSCCC2=C(C#N)C(=N)C1(C#N)C#N,MADAKVETHEFTAEISQLMSLIINTVYSNKEIFLRELISNASDALDKIRYQALSDPSQLESEPELFIRIIPQKDQKVLEIRDSGIGMTKADLVNNLGTIAKSGTKSFMEALSAGADVSMIGQFGVGFYSLFLVADHVQVISKHNDDEQYVWESNAGGKFTVTLDETNERLGRGTMLRLFLKEDQLEYLEEKRIKEVVKKHSEFVAYPIQLVVTKEVEKEVPETEEEDKAAEEDDKKPKLEEVKDEEDEKKEKKTKTVKEEVTETEELNKTKPLWTRNPSDITQDEYNAFYKSISNDWEDPLAVKHFSVEGQLEFRAILFVPKRAPFDAFESKKKKNNIKLYVRRVFITDDAEELIPEWLSFIKGVVDSEDLPLNLSREMLQQNKILKVIRKNIVKKMIETFNEISEDQEQFNQFYTAFSKNIKLGIHEDAQNRQSLAKLLRFYSTKSSEEMTSLSDYVTRMPEHQKNIYYITGESIKAVEKSPFLDALKAKNFEVLFMVDPIDEYAMTQLKEFEDKKLVDITKDFELEESDEEKAAREKEIKEYEPLTKALKDILGDQVEKVVVSYKLVDAPAAIRTGQFGWSANMERIMKAQALRDTTMSSYMSSKKTFEISPSSPIIKELKKKVETDGAEDKTVKDLTTLLFDTALLTSGFTLDEPSNFAHRINRLIALGLNIDDDSEETAVEPEATTTASTDEPAGESAMEEVD,4.7891199096931345 +COc1ccc(Cn2cnc(N)c3nc(nc23)C(C)(C)OCc2ccc(Cl)c(Cl)c2)cc1OC1CCCC1,MEPPTVPSERSLSLSLPGPREGQATLKPPPQHLWRQPRTPIRIQQRGYSDSAERAERERQPHRPIERADAMDTSDRPGLRTTRMSWPSSFHGTGTGSGGAGGGSSRRFEAENGPTPSPGRSPLDSQASPGLVLHAGAATSQRRESFLYRSDSDYDMSPKTMSRNSSVTSEAHAEDLIVTPFAQVLASLRSVRSNFSLLTNVPVPSNKRSPLGGPTPVCKATLSEETCQQLARETLEELDWCLEQLETMQTYRSVSEMASHKFKRMLNRELTHLSEMSRSGNQVSEYISTTFLDKQNEVEIPSPTMKEREKQQAPRPRPSQPPPPPVPHLQPMSQITGLKKLMHSNSLNNSNIPRFGVKTDQEELLAQELENLNKWGLNIFCVSDYAGGRSLTCIMYMIFQERDLLKKFRIPVDTMVTYMLTLEDHYHADVAYHNSLHAADVLQSTHVLLATPALDAVFTDLEILAALFAAAIHDVDHPGVSNQFLINTNSELALMYNDESVLENHHLAVGFKLLQEDNCDIFQNLSKRQRQSLRKMVIDMVLATDMSKHMTLLADLKTMVETKKVTSSGVLLLDNYSDRIQVLRNMVHCADLSNPTKPLELYRQWTDRIMAEFFQQGDRERERGMEISPMCDKHTASVEKSQVGFIDYIVHPLWETWADLVHPDAQEILDTLEDNRDWYYSAIRQSPSPPPEEESRGPGHPPLPDKFQFELTLEEEEEEEISMAQIPCTAQEALTAQGLSGVEEALDATIAWEASPAQESLEVMAQEASLEAELEAVYLTQQAQSTGSAPVAPDEFSSREEFVVAVSHSSPSALALQSPLLPAWRTLSVSEHAPGLPGLPSTAAEVEAQREHQAAKRACSACAGTFGEDTSALPAPGGGGSGGDPT,6.779891911959945 +Cc1csc2nc([nH]c(=O)c12)C(=O)NCc1cccc(OCCOc2nc[nH]n2)c1,MFSLKTLPFLLLLHVQISKAFPVSSKEKNTKTVQDYLEKFYQLPSNQYQSTRKNGTNVIVEKLKEMQRFFGLNVTGKPNEETLDMMKKPRCGVPDSGGFMLTPGNPKWERTNLTYRIRNYTPQLSEAEVERAIKDAFELWSVASPLIFTRISQGEADINIAFYQRDHGDNSPFDGPNGILAHAFQPGQGIGGDAHFDAEETWTNTSANYNLFLVAAHEFGHSLGLAHSSDPGALMYPNYAFRETSNYSLPQDDIDGIQAIYGLSSNPIQPTGPSTPKPCDPSLTFDAITTLRGEILFFKDRYFWRRHPQLQRVEMNFISLFWPSLPTGIQAAYEDFDRDLIFLFKGNQYWALSGYDILQGYPKDISNYGFPSSVQAIDAAVFYRSKTYFFVNDQFWRYDNQRQFMEPGYPKSISGAFPGIESKVDAVFQQEHFFHVFSGPRYYAFDLIAQRVTRVARGNKWLNCRYG,7.958607314841775 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+C[C@@H]1CCCN1CCc1ccc2nc(ccc2c1)-c1csc(n1)-c1ccc(OCC(F)(F)F)nc1,MERAPPDGLMNASGTLAGEAAAAGGARGFSAAWTAVLAALMALLIVATVLGNALVMLAFVADSSLRTQNNFFLLNLAISDFLVGAFCIPLYVPYVLTGRWTFGRGLCKLWLVVDYLLCASSVFNIVLISYDRFLSVTRAVSYRAQQGDTRRAVRKMALVWVLAFLLYGPAILSWEYLSGGSSIPEGHCYAEFFYNWYFLITASTLEFFTPFLSVTFFNLSIYLNIQRRTRLRLDGGREAGPEPPPDAQPSPPPAPPSCWGCWPKGHGEAMPLHRYGVGEAGPGVEAGEAALGGGSGGGAAASPTSSSGSSSRGTERPRSLKRGSKPSASSASLEKRMKMVSQSITQRFRLSRDKKVAKSLAIIVSIFGLCWAPYTLLMIIRAACHGRCIPDYWYETSFWLLWANSAVNPVLYPLCHYSFRRAFTKLLCPQKLKVQPHGSLEQCWK,7.236572006437062 +O=c1ccc(cn1-c1ccccc1)C1CCCC1,MDYLLMIFSLLFVACQGAPETAVLGAELSAVGENGGEKPTPSPPWRLRRSKRCSCSSLMDKECVYFCHLDIIWVNTPEHVVPYGLGSPRSKRALENLLPTKATDRENRCQCASQKDKKCWNFCQAGKELRAEDIMEKDWNNHKKGKDCSKLGKKCIYQQLVRGRKIRRSSEEHLRQTRSETMRNSVKSSFHDPKLKGKPSRERYVTHNRAHW,3.9030899869919433 +COc1ccc(CN2C[C@]3(CC[C@@](CC3)(N(C)C)c3ccccc3)N(CC3CCOC3)C2=O)cc1,MDSSAAPTNASNCTDALAYSSCSPAPSPGSWVNLSHLDGNLSDPCGPNRTDLGGRDSLCPPTGSPSMITAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIINVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALVTIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSNIEQQNSTRIRQNTRDHPSTANTVDRTNHQLENLEAETAPLP,7.721246399047171 +CCNC(=O)[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1cnc2c(N)ncnc12,MPIMGSSVYITVELAIAVLAILGNVLVCWAVWLNSNLQNVTNYFVVSLAAADIAVGVLAIPFAITISTGFCAACHGCLFIACFVLVLTQSSIFSLLAIAIDRYIAIRIPLRYNGLVTGTRAKGIIAICWVLSFAIGLTPMLGWNNCGQPKEGKNHSQGCGEGQVACLFEDVVPMNYMVYFNFFACVLVPLLLMLGVYLRIFLAARRQLKQMESQPLPGERARSTLQKEVHAAKSLAIIVGLFALCWLPLHIINCFTFFCPDCSHAPLWLMYLAIVLSHTNSVVNPFIYAYRIREFRQTFRKIIRSHVLRQQEPFKAAGTSARVLAAHGSDGEQVSLRLNGHPPGVWANGSAPHPERRPNGYALGLVSGGSAQESQGNTGLPDVELLSHELKGVCPEPPGLDDPLAQDGAGVS,7.669586226650809 +COc1cc2OC[C@H]3[C@H](CN4CCN(C\C=C\c5ccc(Cl)cc5)CC4)ON=C3c2cc1OC,METTPLNSQKQLSACEDGEDCQENGVLQKVVPTPGDKVESGQISNGYSAVPSPGAGDDTRHSIPATTTTLVAELHQGERETWGKKVDFLLSVIGYAVDLGNVWRFPYICYQNGGGAFLLPYTIMAIFGGIPLFYMELALGQYHRNGCISIWRKICPIFKGIGYAICIIAFYIASYYNTIMAWALYYLISSFTDQLPWTSCKNSWNTGNCTNYFSEDNITWTLHSTSPAEEFYTRHVLQIHRSKGLQDLGGISWQLALCIMLIFTVIYFSIWKGVKTSGKVVWVTATFPYIILSVLLVRGATLPGAWRGVLFYLKPNWQKLLETGVWIDAAAQIFFSLGPGFGVLLAFASYNKFNNNCYQDALVTSVVNCMTSFVSGFVIFTVLGYMAEMRNEDVSEVAKDAGPSLLFITYAEAIANMPASTFFAIIFFLMLITLGLDSTFAGLEGVITAVLDEFPHVWAKRRERFVLAVVITCFFGSLVTLTFGGAYVVKLLEEYATGPAVLTVALIEAVAVSWFYGITQFCRDVKEMLGFSPGWFWRICWVAISPLFLLFIICSFLMSPPQLRLFQYNYPYWSIILGYCIGTSSFICIPTYIAYRLIITPGTFKERIIKSITPETPTEIPCGDIRLNAV,8.886056647693163 +NC(N)=Nc1ccc(cc1)C(=O)NCCC(=O)N1CCC(CC(O)=O)CC1,MARALCPLQALWLLEWVLLLLGPCAAPPAWALNLDPVQLTFYAGPNGSQFGFSLDFHKDSHGRVAIVVGAPRTLGPSQEETGGVFLCPWRAEGGQCPSLLFDLRDETRNVGSQTLQTFKARQGLGASVVSWSDVIVACAPWQHWNVLEKTEEAEKTPVGSCFLAQPESGRRAEYSPCRGNTLSRIYVENDFSWDKRYCEAGFSSVVTQAGELVLGAPGGYYFLGLLAQAPVADIFSSYRPGILLWHVSSQSLSFDSSNPEYFDGYWGYSVAVGEFDGDLNTTEYVVGAPTWSWTLGAVEILDSYYQRLHRLRGEQMASYFGHSVAVTDVNGDGRHDLLVGAPLYMESRADRKLAEVGRVYLFLQPRGPHALGAPSLLLTGTQLYGRFGSAIAPLGDLDRDGYNDIAVAAPYGGPSGRGQVLVFLGQSEGLRSRPSQVLDSPFPTGSAFGFSLRGAVDIDDNGYPDLIVGAYGANQVAVYRAQPVVKASVQLLVQDSLNPAVKSCVLPQTKTPVSCFNIQMCVGATGHNIPQKLSLNAELQLDRQKPRQGRRVLLLGSQQAGTTLNLDLGGKHSPICHTTMAFLRDEADFRDKLSPIVLSLNVSLPPTEAGMAPAVVLHGDTHVQEQTRIVLDCGEDDVCVPQLQLTASVTGSPLLVGADNVLELQMDAANEGEGAYEAELAVHLPQGAHYMRALSNVEGFERLICNQKKENETRVVLCELGNPMKKNAQIGIAMLVSVGNLEEAGESVSFQLQIRSKNSQNPNSKIVLLDVPVRAEAQVELRGNSFPASLVVAAEEGEREQNSLDSWGPKVEHTYELHNNGPGTVNGLHLSIHLPGQSQPSDLLYILDIQPQGGLQCFPQPPVNPLKVDWGLPIPSPSPIHPAHHKRDRRQIFLPEPEQPSRLQDPVLVSCDSAPCTVVQCDLQEMARGQRAMVTVLAFLWLPSLYQRPLDQFVLQSHAWFNVSSLPYAVPPLSLPRGEAQVWTQLLRALEERAIPIWWVLVGVLGGLLLLTILVLAMWKVGFFKRNRPPLEEDDEEGE,3.7000005038830164 +CN1CCCC1CCOC(=O)Nc1ccc(F)cc1-c1cccc(N)c1,MTLHNNSTTSPLFPNISSSWIHSPSDAGLPPGTVTHFGSYNVSRAAGNFSSPDGTTDDPLGGHTVWQVVFIAFLTGILALVTIIGNILVIVSFKVNKQLKTVNNYFLLSLACADLIIGVISMNLFTTYIIMNRWALGNLACDLWLAIDYVASNASVMNLLVISFDRYFSITRPLTYRAKRTTKRAGVMIGLAWVISFVLWAPAILFWQYFVGKRTVPPGECFIQFLSEPTITFGTAIAAFYMPVTIMTILYWRIYKETEKRTKELAGLQASGTEAETENFVHPTGSSRSCSSYELQQQSMKRSNRRKYGRCHFWFTTKSWKPSSEQMDQDHSSSDSWNNNDAAASLENSASSDEEDIGSETRAIYSIVLKLPGHSTILNSTKLPSSDNLQVPEEELGMVDLERKADKLQAQKSVDDGGSFPKSFSKLPIQLESAVDTAKTSDVNSSVGKSTATLPLSFKEATLAKRFALKTRSQITKRKRMSLVKEKKAAQTLSAILLAFIITWTPYNIMVLVNTFCDSCIPKTFWNLGYWLCYINSTVNPVCYALCNKTFRTTFKMLLLCQCDKKKRRKQQYQQRQSVIFHKRAPEQAL,7.425968732272281 +C[C@@H](Oc1cc(F)ccc1Nc1ncnc2cc(cc(Cl)c12)N=S1(=O)CCCC1)c1cc(C)no1,MVQKKPAELQGFHRSFKGQNPFELAFSLDQPDHGDSDFGLQCSARPDMPASQPIDIPDAKKRGKKKKRGRATDSFSGRFEDVYQLQEDVLGEGAHARVQTCINLITSQEYAVKIIEKQPGHIRSRVFREVEMLYQCQGHRNVLELIEFFEEEDRFYLVFEKMRGGSILSHIHKRRHFNELEASVVVQDVASALDFLHNKGIAHRDLKPENILCEHPNQVSPVKICDFDLGSGIKLNGDCSPISTPELLTPCGSAEYMAPEVVEAFSEEASIYDKRCDLWSLGVILYILLSGYPPFVGRCGSDCGWDRGEACPACQNMLFESIQEGKYEFPDKDWAHISCAAKDLISKLLVRDAKQRLSAAQVLQHPWVQGCAPENTLPTPMVLQRNSCAKDLTSFAAEAIAMNRQLAQHDEDLAEEEAAGQGQPVLVRATSRCLQLSPPSQSKLAQRRQRASLSSAPVVLVGDHA,8.698970004336019 +COc1ccc2[nH]cc(CCN)c2c1,MEILCEDNISLSSIPNSLMQLGDGPRLYHNDFNSRDANTSEASNWTIDAENRTNLSCEGYLPPTCLSILHLQEKNWSALLTTVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAIWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVAFFIPLTIMVITYFLTIKSLQKEATLCVSDLSTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYAGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNENVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENRKPLQLILVNTIPALAYKSSQLQVGQKKNSQEDAEQTVDDCSMVTLGKQQSEENCTDNIETVNEKVSCV,6.161150909262744 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+CCn1c(I)nc(C[C@H](NC(=O)c2cnccn2)C(=O)N2CCC[C@H]2C(N)=O)c1I,MENDTVSEMNQTELQPQAAVALEYQVVTILLVVIICGLGIVGNIMVVLVVMRTKHMRTPTNCYLVSLAVADLMVLVAAGLPNITDSIYGSWVYGYVGCLCITYLQYLGINASSCSITAFTIERYIAICHPIKAQFLCTFSRAKKIIIFVWAFTSIYCMLWFFLLDLNISTYKNAVVVSCGYKISRNYYSPIYLMDFGVFYVVPMILATVLYGFIARILFLNPIPSDPKENSKMWKNDSIHQNKNLNLNATNRCFNSTVSSRKQVTKMLAVVVILFALLWMPYRTLVVVNSFLSSPFQENWFLLFCRICIYLNSAINPVIYNLMSQKFRAAFRKLCNCKQKPTEKAANYSVALNYSVIKESDRFSTELEDITVTDTYVSTTKVSFDDTCLASEN,4.301029995663981 +COc1cc(C[C@H]2NCCc3cc(O)c(O)cc23)cc(OC)c1OC,MGQPGNGSAFLLAPNGSHAPDHDVTQERDEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGAAHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYANETCCDFFTNQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLQKIDKSEGRFHVQNLSQVEQDGRTGHGLRRSSKFCLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQDNLIRKEVYILLNWIGYVNSGFNPLIYCRSPDFRIAFQELLCLRRSSLKAYGNGYSSNGNTGEQSGYHVEQEKENKLLCEDLPGTEDFVGHQGTVPSDNIDSQGRNCSTNDSLL,5.0 +OC(=O)[C@H](CCN(CCCCc1ccc2CCCNc2n1)CCC(F)F)Nc1ccnc(n1)C(F)(F)F,MGIELLCLFFLFLGRNDHVQGGCALGGAETCEDCLLIGPQCAWCAQENFTHPSGVGERCDTPANLLAKGCQLNFIENPVSQVEILKNKPLSVGRQKNSSDIVQIAPQSLILKLRPGGAQTLQVHVRQTEDYPVDLYYLMDLSASMDDDLNTIKELGSRLSKEMSKLTSNFRLGFGSFVEKPVSPFVKTTPEEIANPCSSIPYFCLPTFGFKHILPLTNDAERFNEIVKNQKISANIDTPEGGFDAIMQAAVCKEKIGWRNDSLHLLVFVSDADSHFGMDSKLAGIVIPNDGLCHLDSKNEYSMSTVLEYPTIGQLIDKLVQNNVLLIFAVTQEQVHLYENYAKLIPGATVGLLQKDSGNILQLIISAYEELRSEVELEVLGDTEGLNLSFTAICNNGTLFQHQKKCSHMKVGDTASFSVTVNIPHCERRSRHIIIKPVGLGDALELLVSPECNCDCQKEVEVNSSKCHHGNGSFQCGVCACHPGHMGPRCECGEDMLSTDSCKEAPDHPSCSGRGDCYCGQCICHLSPYGNIYGPYCQCDNFSCVRHKGLLCGGNGDCDCGECVCRSGWTGEYCNCTTSTDSCVSEDGVLCSGRGDCVCGKCVCTNPGASGPTCERCPTCGDPCNSKRSCIECHLSAAGQAREECVDKCKLAGATISEEEDFSKDGSVSCSLQGENECLITFLITTDNEGKTIIHSINEKDCPKPPNIPMIMLGVSLAILLIGVVLLCIWKLLVSFHDRKEVAKFEAERSKAKWQTGTNPLYRGSTSTFKNVTYKHREKQKVDLSTDC,6.823908740944319 +Cn1nc2CCc3cnc(Nc4ccn(CCN5CCCC5)n4)nc3-c2c1-c1ccccc1,MKSGSGGGSPTSLWGLLFLSAALSLWPTSGEICGPGIDIRNDYQQLKRLENCTVIEGYLHILLISKAEDYRSYRFPKLTVITEYLLLFRVAGLESLGDLFPNLTVIRGWKLFYNYALVIFEMTNLKDIGLYNLRNITRGAIRIEKNADLCYLSTVDWSLILDAVSNNYIVGNKPPKECGDLCPGTMEEKPMCEKTTINNEYNYRCWTTNRCQKMCPSTCGKRACTENNECCHPECLGSCSAPDNDTACVACRHYYYAGVCVPACPPNTYRFEGWRCVDRDFCANILSAESSDSEGFVIHDGECMQECPSGFIRNGSQSMYCIPCEGPCPKVCEEEKKTKTIDSVTSAQMLQGCTIFKGNLLINIRRGNNIASELENFMGLIEVVTGYVKIRHSHALVSLSFLKNLRLILGEEQLEGNYSFYVLDNQNLQQLWDWDHRNLTIKAGKMYFAFNPKLCVSEIYRMEEVTGTKGRQSKGDINTRNNGERASCESDVLHFTSTTTSKNRIIITWHRYRPPDYRDLISFTVYYKEAPFKNVTEYDGQDACGSNSWNMVDVDLPPNKDVEPGILLHGLKPWTQYAVYVKAVTLTMVENDHIRGAKSEILYIRTNASVPSIPLDVLSASNSSSQLIVKWNPPSLPNGNLSYYIVRWQRQPQDGYLYRHNYCSKDKIPIRKYADGTIDIEEVTENPKTEVCGGEKGPCCACPKTEAEKQAEKEEAEYRKVFENFLHNSIFVPRPERKRRDVMQVANTTMSSRSRNTTAADTYNITDPEELETEYPFFESRVDNKERTVISNLRPFTLYRIDIHSCNHEAEKLGCSASNFVFARTMPAEGADDIPGPVTWEPRPENSIFLKWPEPENPNGLILMYEIKYGSQVEDQRECVSRQEYRKYGGAKLNRLNPGNYTARIQATSLSGNGSWTDPVFFYVQAKTGYENFIHLIIALPVAVLLIVGGLVIMLYVFHRKRNNSRLGNGVLYASVNPEYFSAADVYVPDEWEVAREKITMSRELGQGSFGMVYEGVAKGVVKDEPETRVAIKTVNEAASMRERIEFLNEASVMKEFNCHHVVRLLGVVSQGQPTLVIMELMTRGDLKSYLRSLRPEMENNPVLAPPSLSKMIQMAGEIADGMAYLNANKFVHRDLAARNCMVAEDFTVKIGDFGMTRDIYETDYYRKGGKGLLPVRWMSPESLKDGVFTTYSDVWSFGVVLWEIATLAEQPYQGLSNEQVLRFVMEGGLLDKPDNCPDMLFELMRMCWQYNPKMRPSFLEIISSIKEEMEPGFREVSFYYSEENKLPEPEELDLEPENMESVPLDPSASSSSLPLPDRHSGHKAENGPGPGVLVLRASFDERQPYAHMNGGRKNERALPLPQSSTC,8.522878745280337 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+N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H]1CCCC[C@@H]1C(=O)N[C@@H](Cc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)C(N)=O,MDSSTGPGNTSDCSDPLAQASCSPAPGSWLNLSHVDGNQSDPCGLNRTGLGGNDSLCPQTGSPSMVTAITIMALYSIVCVVGLFGNFLVMYVIVRYTKMKTATNIYIFNLALADALATSTLPFQSVNYLMGTWPFGTILCKIVISIDYYNMFTSIFTLCTMSVDRYIAVCHPVKALDFRTPRNAKIVNVCNWILSSAIGLPVMFMATTKYRQGSIDCTLTFSHPTWYWENLLKICVFIFAFIMPVLIITVCYGLMILRLKSVRMLSGSKEKDRNLRRITRMVLVVVAVFIVCWTPIHIYVIIKALITIPETTFQTVSWHFCIALGYTNSCLNPVLYAFLDENFKRCFREFCIPTSSTIEQQNSTRVRQNTREHPSTANTVDRTNHQLENLEAETAPLP,6.244887733604929 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+Oc1c(F)c(F)cc(C(=O)c2ccc(s2)-c2cc(NS(=O)(=O)c3ccc(cc3)C#N)c(F)cc2F)c1F,MSPFASESAWLCLAAAAVLGGTLLCGCRSGRQLRSQAVCLAGLWGGACLLSLSLLCTLFLLSVACFLLLYMSSSDQDLLPVDQKAVLVTGADSGFGHGLAKHLDKLGFTVFAGVLDKEGPGAEELRKHCSERLSVLQMDVTKPEQIKDAHSKVTEKIQDKGLWAVVNNAGVFHLPIDGELIPMSIYRKCMAVNFFGTVEVTKAFLPLLRKSKGRLVNVSSMGGTVPLQMTSAYAATKAALTMFSTIIRQELDKWGVKVVTIKPGGFKTNITGSQDIWDKMEKEILDHFSKDIQENYGQDYVHTQKLIIPTLKERSNPDITPVLRDIQHAISARNPSSFYYPGRMAYLWVCLAAYCPTSLLDYVIKKGFYPQPTPRALRTVH,7.301029995663981 +CC(C)(C)OC(=O)NC1CCN(CC1)C(=O)Nc1cnc2ccc(nn12)N1CCC[C@@H]1c1cc(F)ccc1F,MLRGGRRGQLGWHSWAAGPGSLLAWLILASAGAAPCPDACCPHGSSGLRCTRDGALDSLHHLPGAENLTELYIENQQHLQHLELRDLRGLGELRNLTIVKSGLRFVAPDAFHFTPRLSRLNLSFNALESLSWKTVQGLSLQELVLSGNPLHCSCALRWLQRWEEEGLGGVPEQKLQCHGQGPLAHMPNASCGVPTLKVQVPNASVDVGDDVLLRCQVEGRGLEQAGWILTELEQSATVMKSGGLPSLGLTLANVTSDLNRKNVTCWAENDVGRAEVSVQVNVSFPASVQLHTAVEMHHWCIPFSVDGQPAPSLRWLFNGSVLNETSFIFTEFLEPAANETVRHGCLRLNQPTHVNNGNYTLLAANPFGQASASIMAAFMDNPFEFNPEDPIPVSFSPVDTNSTSGDPVEKKDETPFGVSVAVGLAVFACLFLSTLLLVLNKCGRRNKFGINRPAVLAPEDGLAMSLHFMTLGGSSLSPTEGKGSGLQGHIIENPQYFSDACVHHIKRRDIVLKWELGEGAFGKVFLAECHNLLPEQDKMLVAVKALKEASESARQDFQREAELLTMLQHQHIVRFFGVCTEGRPLLMVFEYMRHGDLNRFLRSHGPDAKLLAGGEDVAPGPLGLGQLLAVASQVAAGMVYLAGLHFVHRDLATRNCLVGQGLVVKIGDFGMSRDIYSTDYYRVGGRTMLPIRWMPPESILYRKFTTESDVWSFGVVLWEIFTYGKQPWYQLSNTEAIDCITQGRELERPRACPPEVYAIMRGCWQREPQQRHSIKDVHARLQALAQAPPVYLDVLG,7.764471553092451 +N[C@H]1CC[C@@H](CC1)Nc1nccc(n1)-c1cccnc1Oc1ccc(Nc2nc3ccccc3[nH]2)c2ccccc12,MSLHFLYYCSEPTLDVKIAFCQGFDKQVDVSYIAKHYNMSKSKVDNQFYSVEVGDSTFTVLKRYQNLKPIGSGAQGIVCAAYDAVLDRNVAIKKLSRPFQNQTHAKRAYRELVLMKCVNHKNIISLLNVFTPQKTLEEFQDVYLVMELMDANLCQVIQMELDHERMSYLLYQMLCGIKHLHSAGIIHRDLKPSNIVVKSDCTLKILDFGLARTAGTSFMMTPYVVTRYYRAPEVILGMGYKENVDIWSVGCIMGEMVRHKILFPGRDYIDQWNKVIEQLGTPCPEFMKKLQPTVRNYVENRPKYAGLTFPKLFPDSLFPADSEHNKLKASQARDLLSKMLVIDPAKRISVDDALQHPYINVWYDPAEVEAPPPQIYDKQLDEREHTIEEWKELIYKEVMNSEEKTKNGVVKGQPSPSGAAVNSSESLPPSSSVNDISSMSTDQTLASDTDSSLEASAGPLGCCR,8.721246399047171 +COc1ccccc1CNC(=O)NC[C@H](NC(=O)C1CCCN1S(=O)(=O)c1ccccc1)C(O)=O,MGPERTGAAPLPLLLVLALSQGILNCCLAYNVGLPEAKIFSGPSSEQFGYAVQQFINPKGNWLLVGSPWSGFPENRMGDVYKCPVDLSTATCEKLNLQTSTSIPNVTEMKTNMSLGLILTRNMGTGGFLTCGPLWAQQCGNQYYTTGVCSDISPDFQLSASFSPATQPCPSLIDVVVVCDESNSIYPWDAVKNFLEKFVQGLDIGPTKTQVGLIQYANNPRVVFNLNTYKTKEEMIVATSQTSQYGGDLTNTFGAIQYARKYAYSAASGGRRSATKVMVVVTDGESHDGSMLKAVIDQCNHDNILRFGIAVLGYLNRNALDTKNLIKEIKAIASIPTERYFFNVSDEAALLEKAGTLGEQIFSIEGTVQGGDNFQMEMSQVGFSADYSSQNDILMLGAVGAFGWSGTIVQKTSHGHLIFPKQAFDQILQDRNHSSYLGYSVAAISTGESTHFVAGAPRANYTGQIVLYSVNENGNITVIQAHRGDQIGSYFGSVLCSVDVDKDTITDVLLVGAPMYMSDLKKEEGRVYLFTIKKGILGQHQFLEGPEGIENTRFGSAIAALSDINMDGFNDVIVGSPLENQNSGAVYIYNGHQGTIRTKYSQKILGSDGAFRSHLQYFGRSLDGYGDLNGDSITDVSIGAFGQVVQLWSQSIADVAIEASFTPEKITLVNKNAQIILKLCFSAKFRPTKQNNQVAIVYNITLDADGFSSRVTSRGLFKENNERCLQKNMVVNQAQSCPEHIIYIQEPSDVVNSLDLRVDISLENPGTSPALEAYSETAKVFSIPFHKDCGEDGLCISDLVLDVRQIPAAQEQPFIVSNQNKRLTFSVTLKNKRESAYNTGIVVDFSENLFFASFSLPVDGTEVTCQVAASQKSVACDVGYPALKREQQVTFTINFDFNLQNLQNQASLSFQALSESQEENKADNLVNLKIPLLYDAEIHLTRSTNINFYEISSDGNVPSIVHSFEDVGPKFIFSLKVTTGSVPVSMATVIIHIPQYTKEKNPLMYLTGVQTDKAGDISCNADINPLKIGQTSSSVSFKSENFRHTKELNCRTASCSNVTCWLKDVHMKGEYFVNVTTRIWNGTFASSTFQTVQLTAAAEINTYNPEIYVIEDNTVTIPLMIMKPDEKAEVPTGVIIGSIIAGILLLLALVAILWKLGFFKRKYEKMTKNPDEIDETTELSS,6.330683119433888 +Cc1cccc(c1)C(CC(O)=O)NC(=O)CCCCc1ccc2CCCNc2n1,MAFPPRRRLRLGPRGLPLLLSGLLLPLCRAFNLDVDSPAEYSGPEGSYFGFAVDFFVPSASSRMFLLVGAPKANTTQPGIVEGGQVLKCDWSSTRRCQPIEFDATGNRDYAKDDPLEFKSHQWFGASVRSKQDKILACAPLYHWRTEMKQEREPVGTCFLQDGTKTVEYAPCRSQDIDADGQGFCQGGFSIDFTKADRVLLGGPGSFYWQGQLISDQVAEIVSKYDPNVYSIKYNNQLATRTAQAIFDDSYLGYSVAVGDFNGDGIDDFVSGVPRAARTLGMVYIYDGKNMSSLYNFTGEQMAAYFGFSVAATDINGDDYADVFIGAPLFMDRGSDGKLQEVGQVSVSLQRASGDFQTTKLNGFEVFARFGSAIAPLGDLDQDGFNDIAIAAPYGGEDKKGIVYIFNGRSTGLNAVPSQILEGQWAARSMPPSFGYSMKGATDIDKNGYPDLIVGAFGVDRAILYRARPVITVNAGLEVYPSILNQDNKTCSLPGTALKVSCFNVRFCLKADGKGVLPRKLNFQVELLLDKLKQKGAIRRALFLYSRSPSHSKNMTISRGGLMQCEELIAYLRDESEFRDKLTPITIFMEYRLDYRTAADTTGLQPILNQFTPANISRQAHILLDCGEDNVCKPKLEVSVDSDQKKIYIGDDNPLTLIVKAQNQGEGAYEAELIVSIPLQADFIGVVRNNEALARLSCAFKTENQTRQVVCDLGNPMKAGTQLLAGLRFSVHQQSEMDTSVKFDLQIQSSNLFDKVSPVVSHKVDLAVLAAVEIRGVSSPDHVFLPIPNWEHKENPETEEDVGPVVQHIYELRNNGPSSFSKAMLHLQWPYKYNNNTLLYILHYDIDGPMNCTSDMEINPLRIKISSLQTTEKNDTVAGQGERDHLITKRDLALSEGDIHTLGCGVAQCLKIVCQVGRLDRGKSAILYVKSLLWTETFMNKENQNHSYSLKSSASFNVIEFPYKNLPIEDITNSTLVTTNVTWGIQPAPMPVPVWVIILAVLAGLLLLAVLVFVMYRMGFFKRVRPPQEEQEREQLQPHENGEGNSET,6.801342913045577 +CC(C)CNC1CCN(CC1)c1ncc(C)cc1-c1cc(C)no1,MDSPIQIFRGEPGPTCAPSACLPPNSSAWFPGWAEPDSNGSAGSEDAQLEPAHISPAIPVIITAVYSVVFVVGLVGNSLVMFVIIRYTKMKTATNIYIFNLALADALVTTTMPFQSTVYLMNSWPFGDVLCKIVISIDYYNMFTSIFTLTMMSVDRYIAVCHPVKALDFRTPLKAKIINICIWLLSSSVGISAIVLGGTKVREDVDVIECSLQFPDDDYSWWDLFMKICVFIFAFVIPVLIIIVCYTLMILRLKSVRLLSGSREKDRNLRRITRLVLVVVAVFVVCWTPIHIFILVEALGSTSHSTAALSSYYFCIALGYTNSSLNPILYAFLDENFKRCFRDFCFPLKMRMERQSTSRVRNTVQDPAYLRDIDGMNKPV,6.0655015487564325 +CC(C)C(=O)Nc1cc(NC(=O)c2c(Cl)cccc2Cl)ccn1,MGMACLTMTEMEGTSTSSIYQNGDISGNANSMKQIDPVLQVYLYHSLGKSEADYLTFPSGEYVAEEICIAASKACGITPVYHNMFALMSETERIWYPPNHVFHIDESTRHNVLYRIRFYFPRWYCSGSNRAYRHGISRGAEAPLLDDFVMSYLFAQWRHDFVHGWIKVPVTHETQEECLGMAVLDMMRIAKENDQTPLAIYNSISYKTFLPKCIRAKIQDYHILTRKRIRYRFRRFIQQFSQCKATARNLKLKYLINLETLQSAFYTEKFEVKEPGSGPSGEEIFATIIITGNGGIQWSRGKHKESETLTEQDLQLYCDFPNIIDVSIKQANQEGSNESRVVTIHKQDGKNLEIELSSLREALSFVSLIDGYYRLTADAHHYLCKEVAPPAVLENIQSNCHGPISMDFAISKLKKAGNQTGLYVLRCSPKDFNKYFLTFAVERENVIEYKHCLITKNENEEYNLSGTKKNFSSLKDLLNCYQMETVRSDNIIFQFTKCCPPKPKDKSNLLVFRTNGVSDVPTSPTLQRPTHMNQMVFHKIRNEDLIFNESLGQGTFTKIFKGVRREVGDYGQLHETEVLLKVLDKAHRNYSESFFEAASMMSKLSHKHLVLNYGVCVCGDENILVQEFVKFGSLDTYLKKNKNCINILWKLEVAKQLAWAMHFLEENTLIHGNVCAKNILLIREEDRKTGNPPFIKLSDPGISITVLPKDILQERIPWVPPECIENPKNLNLATDKWSFGTTLWEICSGGDKPLSALDSQRKLQFYEDRHQLPAPKWAELANLINNCMDYEPDFRPSFRAIIRDLNSLFTPDYELLTENDMLPNMRIGALGFSGAFEDRDPTQFEERHLKFLQQLGKGNFGSVEMCRYDPLQDNTGEVVAVKKLQHSTEEHLRDFEREIEILKSLQHDNIVKYKGVCYSAGRRNLKLIMEYLPYGSLRDYLQKHKERIDHIKLLQYTSQICKGMEYLGTKRYIHRDLATRNILVENENRVKIGDFGLTKVLPQDKEYYKVKEPGESPIFWYAPESLTESKFSVASDVWSFGVVLYELFTYIEKSKSPPAEFMRMIGNDKQGQMIVFHLIELLKNNGRLPRPDGCPDEIYMIMTECWNNNVNQRPSFRDLALRVDQIRDNMAG,5.455931955649724 +CCCCc1nc2cc(N)ccc2n1Cc1ccc(cc1)-c1ccccc1C(O)=O,MALNSSAEDGIKRIQDDCPKAGRHSYIFVMIPTLYSIIFVVGIFGNSLVVIVIYFYMKLKTVASVFLLNLALADLCFLLTLPLWAVYTAMEYRWPFGNHLCKIASASVSFNLYASVFLLTCLSIDRYLAIVHPMKSRLRRTMLVAKVTCIIIWLMAGLASLPAVIHRNVYFIENTNITVCAFHYESRNSTLPIGLGLTKNILGFLFPFLIILTSYTLIWKALKKAYEIQKNKPRNDDIFRIIMAIVLFFFFSWVPHQIFTFLDVLIQLGVIHDCKISDIVDTAMPITICIAYFNNCLNPLFYGFLGKKFKKYFLQLLKYIPPKAKSHSSLSTKMSTLSYRPSDNMSSSAKKPASCFEVE,7.79997073344623 +FC(F)(C(=O)NCc1ccccc1)C(=O)C(Cc1ccccc1)NC(=O)OCc1ccccc1,PQVTLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKMIGGIGGFIKVRQYDQILIEICGHKAIGTVLVGPTPVNIIGRNLLTQIGCTLNF,9.221848749616356 +CCO[C@H](Cc1ccc(CCC(OC(=S)NCc2ccccc2)c2ccccc2)cc1)C(O)=O,MGETLGDSPIDPESDSFTDTLSANISQEMTMVDTEMPFWPTNFGISSVDLSVMEDHSHSFDIKPFTTVDFSSISTPHYEDIPFTRTDPVVADYKYDLKLQEYQSAIKVEPASPPYYSEKTQLYNKPHEEPSNSLMAIECRVCGDKASGFHYGVHACEGCKGFFRRTIRLKLIYDRCDLNCRIHKKSRNKCQYCRFQKCLAVGMSHNAIRFGRMPQAEKEKLLAEISSDIDQLNPESADLRALAKHLYDSYIKSFPLTKAKARAILTGKTTDKSPFVIYDMNSLMMGEDKIKFKHITPLQEQSKEVAIRIFQGCQFRSVEAVQEITEYAKSIPGFVNLDLNDQVTLLKYGVHEIIYTMLASLMNKDGVLISEGQGFMTREFLKSLRKPFGDFMEPKFEFAVKFNALELDDSDLAIFIAVIILSGDRPGLLNVKPIEDIQDNLLQALELQLKLNHPESSQLFAKLLQKMTDLRQIVTEHVQLLQVIKKTETDMSLHPLLQEIYKDLY,6.455931955649724 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+639,COc1cccc(NC(=S)Nc2cccc(Cl)c2)c1,7.611543547299734 +640,Cc1cc(Nc2ccc(S(F)(F)(F)(F)F)cc2)n2nc(C(C)(F)F)nc2n1,8.67778070526608 +641,O=C(CCCNC(=O)c1cc2c(cn1)[nH]c1ccccc12)NO,8.806875401645538 +642,O=C(O)COC(=O)Cc1ccccc1Nc1c(Cl)cccc1Cl,8.227165072760982 +643,CCNC(=O)c1cccnc1N1CCN(C)CC1,7.657577319177793 +644,Nc1ccc2oc(N3CCN(c4ccc(Cl)cc4)CC3)nc2c1,8.707965564005264 +645,CC(=O)Nc1ccc(-c2c[nH]c(=O)c(O)c2)cc1,7.8696662315049934 +646,N#Cc1ccc(Oc2cc(Cl)c([N+](=O)[O-])cc2[N+](=O)[O-])cc1,8.619788758288394 +647,C#CCOc1cc(-n2nnc3nn(CC=C)cc3c2=O)c(F)cc1Cl,7.509999358109048 +648,Cn1ncc2ccc(C(=O)Nc3nnc(C4CC4)s3)cc21,8.774949303861952 +649,C=CC(=O)N1CCC[C@@H](Nc2ncnc3[nH]ccc23)C1,8.853871964321762 +650,CN(C)C1CC(c2ccc(Br)cc2)c2ccccc21,8.045757490560675 +651,CCCNC(=O)O[C@H]1CO[C@@H]2[C@H](O[N+](=O)[O-])CO[C@H]12,5.818156412055227 +652,Cc1c(C(=O)O)cc(C(F)(F)F)n1-c1ccccc1,7.657577319177793 +653,C=Cn1cnc2c(Nc3ccc(P(C)(C)=O)cc3)ncnc21,9.0 +654,COc1ccccc1Nc1nccc(-c2ccc(C(=O)O)cc2)n1,8.40000018605658 +655,O=C(NC(=S)Nc1cc(Cl)ccc1Cl)c1cccc(Cl)c1,8.012333735073724 +656,COc1ccc(C2=C(c3c[nH]c4ccccc34)C(=O)NC2)cc1,7.886056647693163 +657,N[C@H](Cc1cc(F)ccc1F)c1ccc(-c2ccncc2)cc1,7.1938200260161125 +658,CN1CCCCC1CC(=O)c1cccs1,7.982966660701219 +659,COc1ccc(Nc2nc(-c3ccccc3F)no2)cc1,8.958607314841775 +660,C#CCN(C)Cc1ccc(Cl)cc1Cl,8.036212172654444 +661,Cc1ccc(S(=O)(=O)Nc2cccc3cccnc23)cc1,8.661543506395395 +662,CN1CCC/C1=N\C(=O)Nc1cccc(Cl)c1,8.698970004336019 +663,O=C(O)CC[C@@H](O)C(=O)O,7.619788758288394 +664,CCC(=O)c1c(C)nc2c(c1N)c1ccccc1n2C,8.795880017344075 +665,O=S1(=O)N=C(Nc2ccccc2Cl)Nc2c(O)cccc21,8.2839966563652 +666,O=C(O)C1=C(c2ccccc2)c2ccccc2C1=O,7.6020599913279625 +667,O=C(Nc1ccc(Sc2nc3ccccc3s2)c(Cl)c1)c1cc(Br)ccc1O,7.619788758288394 +668,N#Cc1cccc2[nH]nc(N)c12,6.522878745280337 +669,CC(=O)C1=C(O)C=C2Oc3c(C(N)=O)c(O)cc(O)c3[C@]2(C)C1=O,8.995678626217357 +670,O=S(=O)(NCc1cccc(C(F)(F)F)c1)c1ccc2sc(CO)nc2c1,8.541966807503494 +671,O=C(O)/C=C\C(=O)N[C@@H](CCC(=O)O)C(=O)O,7.080921907623926 +672,CNc1nc(/C=C2\C=Nc3c(Br)cccc32)c(O)n1C,8.96657624451305 +673,O=C(O)c1cc([N+](=O)[O-])cc([N+](=O)[O-])c1,5.949999401714238 +674,COc1cccc(C(=O)c2cnc(Nc3ccccc3)s2)c1,8.910094888560602 +675,COc1cc(Sc2c[nH]c3ccccc23)cc(OC)c1OC,8.585026652029182 +676,CN(C)CCc1c[nH]c2cc3c(cc12)OCO3,7.39040559077478 +677,CN1CCC[C@H]1COC(=O)c1cccc(N)c1,6.318758762624412 +678,Cc1ccc([N+](=O)[O-])c(NCCCCN)c1,7.698970004336019 +679,Cc1nn(CCCC(=O)O)c(=O)c2noc(C)c12,7.186752699102395 +680,CNc1nc(Nc2ccc(F)cc2)c2cn[nH]c2n1,8.108629825303852 +681,O=c1cc(-c2ccc(Cl)cc2)nc2c(-c3ccc(Cl)cc3)c(C(F)(F)F)[nH]n12,8.853871964321762 +682,Nc1nc(NCCCOc2ccc([N+](=O)[O-])cc2)c(N=O)c(=O)[nH]1,9.0 +683,C#Cc1[nH]nc2c1Cc1cc(OC)c(OC)cc1-2,8.289036881004725 +684,COc1ccc(Nc2c(-c3ccc(Cl)cc3)nc3cnccn23)cc1,7.337242168318426 +685,CCCCCN1C[C@H](O)[C@@H](O)[C@H](O)[C@H]1CO,6.301029995663981 +686,FC(CNCc1ccc2c(c1)OCO2)=C1CCCCC1,7.889410289700751 +687,c1ccc(-c2cnc[nH]2)c(OCCC2CCCC2)c1,8.142667503568731 +688,COc1cc(/C=C2\S/C(=N\c3nccs3)NC2=O)cc(OC)c1O,6.912928794093465 +689,CCc1cc2c(Nc3nnc(C)s3)ncnc2s1,7.036212172654444 +690,O=c1c2ccc(O)c(O)c2oc2cc(O)cc(O)c12,7.221848749616356 +691,N#C/C(=C\c1ccc(C(=O)O)cc1)C(N)=S,7.920818753952375 +692,CN(Cc1ccccc1)Cc1ccc(C(=O)C(F)(F)F)s1,8.985059650207063 +693,Cc1noc(Cn2ccc3ncc(-c4ccc(F)c(C)c4)cc32)n1,8.920818753952375 +694,Nc1nc2ccccc2[nH]1,6.698970004336019 +695,Cc1nsc(-c2nnc3n2CCN(C(=O)c2ccc(Cl)cc2)[C@@H]3C)n1,7.00436480540245 +696,CN1c2ccccc2C(n2cnc([N+](=O)[O-])n2)c2ccccc21,8.931814138253838 +697,CC(N)=NCc1cccc(CN)c1,8.10790539730952 +698,Nc1ccc(-c2nnc3n2-c2cccnc2Nc2ccccc2-3)cn1,8.67778070526608 +699,Brc1ccc(-c2noc(Cc3c[nH]c4ccccc34)n2)s1,7.852014679316195 +700,c1cncc(-c2n[nH]c3ccccc23)c1,8.909741947068683 +701,Cn1cnc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,8.602059991327963 +702,CNC(Cc1ccccc1N)c1ccc(C)s1,8.2839966563652 +703,Cc1cc2c(cc1Cl)NC(=O)CN=C2c1ccccc1F,4.146000198199519 +704,CCC(C)N1CCc2ccc3[nH]c(=O)c(=O)[nH]c3c2C1,7.6777807052660805 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+1070,O=C(O)C1=Cc2ccccc2CC1=O,7.820000358220839 +1071,O=C(O)Cc1ccccc1Nc1ccc(Cl)c(Cl)c1,5.149999867728904 +1072,Nc1nc(N)c2nc(CCc3cccc4ccccc34)cnc2n1,7.221848749616356 +1073,O=C(/C=C/c1cccc(C(F)(F)F)c1)c1ccc[nH]1,6.573488738635425 +1074,C=CCc1cccc(/C=N/n2c(-c3ccccc3)n[nH]c2=S)c1O,7.698970004336019 +1075,NC(=O)c1ccsc1NC(=O)Cc1csc2ccccc12,8.1249387366083 +1076,CCN1C(=O)/C(=C/c2ccnc3ccccc23)SC1=S,6.721246399047171 +1077,Nc1n[nH]c(N)c1N=Nc1ccncc1,8.876148359032914 +1078,O=c1[nH]c2ccc(Cl)cc2cc1CNc1ccc(-n2ccnc2)cc1,8.767003889607846 +1079,O=C(NCCS)C(=O)Nc1ccccc1,8.55284196865778 +1080,Cc1cc(-c2n[nH]c(CNc3ccc(Cl)cc3)n2)ccn1,8.148741651280925 +1081,COC(=O)c1ccc(Cl)nc1N(C)c1ccc(OC)cc1,8.853871964321762 +1082,O=C1NC(=O)C2C3c4ccccc4C(c4cccc(Cl)c43)C12,7.958607314841775 +1083,O=C1C=C(c2ccc3[nH]ccc3c2)CCC1,7.251811972993799 +1084,Clc1ccc2sc(SCc3cn(Cc4ccccc4Cl)nn3)nc2c1,7.698970004336019 +1085,CC1=CC(=NC(C)C)c2ccccc2C1=O,8.200659450546418 +1086,CSc1nc2ccc([N+](=O)[O-])cc2c(=O)n1Cc1ccccc1,7.522878745280337 +1087,COc1cc(/C=N/Nc2ccc(F)cc2)ccc1O,8.920818753952375 +1088,CC1=NC(SCc2ccc(Cl)cc2Cl)=NC(=O)C1,6.66354026615147 +1089,C[C@H]1C[C@H]2CSC(N)=NC2(c2cc(C#N)ccc2Cl)CO1,8.63264407897398 +1090,CCc1[nH]c(=O)nc2ccc(OC)c(OC)c12,7.7447274948966935 +1091,NC(=S)NCC(=O)O,7.7447274948966935 +1092,COc1cc(-c2cc3c(nn2)-c2ccccc2C3=O)ccc1O,8.0 +1093,CC(=O)c1cccs1,6.823908740944319 +1094,CCC1CCCCNC1=O,5.494850021680094 +1095,COc1ccc2c(c1)[nH]c1c(C)nccc12,7.7447274948966935 +1096,COc1c(O)cc2oc(-c3ccc(O)c(O)c3)cc(=O)c2c1O,7.175874166083451 +1097,CC(C)CSc1cccc(OS(C)(=O)=O)n1,5.698970004336019 +1098,COc1ccc2c(c1)NC(=O)Cc1c-2[nH]c2ccc([N+](=O)[O-])cc12,9.0 +1099,Nc1ccc(-n2cnc3ccccc32)cc1,8.698970004336019 +1100,O=C(O)CNC(=O)c1cc(NC(=O)c2cc(Cl)c(Cl)[nH]2)c[nH]1,8.2839966563652 +1101,O=C(Nc1ccccc1)c1nc(-c2cccs2)[nH]c(=O)c1O,9.0 +1102,N[C@H](C(=O)O)[C@H](OCc1ccsc1)C(=O)O,8.910461368774685 +1103,Clc1ccc(C(c2ccc(Cl)cc2)C(Cl)Cl)cc1,7.809999051930338 +1104,N=C(N)c1ccc2nc(-c3ncnc(-c4ccccc4)c3O)[nH]c2c1,8.958607314841775 +1105,CC(=O)N(CC(=O)O)c1ccc(C)cc1,7.823908740944319 +1106,CCOC(=O)c1c(-c2ccc(C)cc2)nc2ccc(C)cn12,8.939302159646388 +1107,O=C(NO)[C@@H]1[C@H](c2ccccc2)[C@H]1c1ccc(-c2cnco2)cc1,7.920818753952375 +1108,O=C(/C=C/c1ccc(CONC(=O)c2ccccc2)cc1)NO,8.978810700930062 +1109,O=C(NC[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O)c1ccc(F)cc1,6.333669255698031 +1110,COc1ccc(N=Cc2ccc(S(N)(=O)=O)cc2)cc1OC,7.504872118757067 +1111,O=C(O)/C=C/c1cc(Br)c(Br)c(Br)c1Br,8.154901959985743 +1112,O=c1cc(-c2nc(-c3ccc(O)cc3)[nH]c2-c2ccc(F)cc2)cc[nH]1,7.841637507904751 +1113,O=[N+]([O-])c1c(O)c(F)c(OCc2ccc(-c3ccccc3)cc2)c(F)c1F,6.698970004336019 +1114,COC(=O)Nc1nc2ccc(C(=O)c3cc(CN)cs3)cc2[nH]1,6.920818753952375 +1115,CCOC(=O)c1cc(-c2ccc(NC(C)=O)cc2)n[nH]1,4.638272163982407 +1116,CC(C)CC(N)P(=O)(O)Oc1ccccc1,8.031517051446064 +1117,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)Nc1ccccc1,7.045757490560675 +1118,COc1ccc(NCC(=O)N/N=C/c2ccncc2)cc1,8.431798275933005 +1119,COc1ccc2c(c1)OCC(C(=O)c1cc(O)ccc1O)=C2,8.400116927926312 +1120,COc1cc(O)c(/C=C\C(=O)O)cc1[C@@H](O)CC(C)C,7.313363730737707 +1121,O=C(/C=C(\O)c1cc(O)ccc1O)/C=C/c1cc(O)ccc1O,7.707743928643524 +1122,O=C(Cc1ccccc1)Nc1nc(-c2cc(Cl)ccc2Cl)cs1,8.0 +1123,NNC(N)=O,8.173925197299173 +1124,NC1=NC(c2ccccc2)Cc2cccc(Cl)c21,8.221848749616356 +1125,COc1ccc(CNC(=S)SC[C@H](NC(C)=O)C(=O)O)cc1,5.531652669587842 +1126,COc1ccc(-c2cc3cc(Cl)ccc3oc2=O)cc1,8.317854923626168 +1127,CCOC(=O)[C@@H](C)NC(=O)C(=O)c1c[nH]c2ccc(Br)cc12,7.2839966563652006 +1128,C[C@](O)(C(=O)Nc1ccc(S(=O)(=O)c2ccncc2)cc1)C(F)(F)F,8.795880017344075 +1129,O=Cc1cccc(C(=O)Sc2cccc(Cl)c2)n1,7.102372908709558 +1130,O=c1[nH]c2cc(Br)c3c(c2[nH]c1=O)CCCN3,8.045757490560675 +1131,COc1cc2nc(C)nc(-c3cc(O)cc(O)c3)c2cc1OC,7.628932137728263 +1132,CC1(C)CC12CCOC2=O,8.943095148663527 +1133,O=C1Nc2ccc(NCC(O)CCl)c3cccc1c23,6.552841968657781 +1134,O=C(Nc1ccc(Oc2cc(Br)cc(C(F)(F)F)c2)cc1)c1c(F)cccc1Cl,8.6345120151091 +1135,CN(C)c1cccc(C(=O)NO)c1,8.802443786846464 +1136,Cc1sc2nc(-c3ccc(C(=O)O)cc3)[nH]c(=O)c2c1C,8.795880017344075 +1137,Nc1n[nH]c(N)c1N=Nc1cccc(O)c1,7.251811972993799 +1138,CNc1c(C(=O)OC)c(C)nc2c1c1ccccc1n2C,7.767003889607846 +1139,CCn1cnc2ccc3nc(C(=N)OC(C)C)sc3c2c1=O,8.366531544420413 +1140,CCCC(=O)Nc1n[nH]c2cc(-c3cc(F)cc(F)c3)ccc12,7.860120913598763 +1141,Cc1cccc(C23SCCN2C(=O)c2ccccc23)n1,8.387216143280265 +1142,O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1ccccc1[N+](=O)[O-],8.065501548756432 +1143,O=C(O)c1cc2cccc(O)c2oc1=O,7.224680878170522 +1144,NC(CCCC(=O)O)C(=O)O,7.886056647693163 +1145,NC(=S)Nc1ccccc1,8.744727494896694 +1146,CCc1ccc(Br)c(S(=O)(=O)Nc2onc(C)c2C)c1,7.568636235841013 +1147,Nc1nc(N)c2c(COc3ccc(F)cc3F)cccc2n1,8.698970004336019 +1148,Cc1cc(=O)c(O)cn1-c1ccc(-n2cncn2)cc1,8.61871430487212 +1149,Cn1c(N)nc2c1c(=O)n(CC1CC1)c(=O)n2CC1CC1,7.769551078621726 +1150,Cn1ccc2cc[nH]c2c1=O,7.368556230986828 +1151,Cc1cn([C@H]2C[C@H](O)[C@@H](CO)O2)c(=O)[nH]c1=O,8.387216143280265 +1152,O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1nnc(Cl)cc1C(F)(F)F,8.0 +1153,Cc1o[nH]c(=O)c1[C@@H](N)C(=O)O,8.431798275933005 +1154,NCCNC1=C(c2cc3ccccc3[nH]2)C(=O)NC1=O,7.045757490560675 +1155,O=C(NO)c1cc2cccc(Cl)c2s1,8.536107011014092 +1156,CCOC(=O)N/N=C/c1ccc(O)cc1,7.366531544420414 +1157,Cc1nc(-c2ccc(P(=O)(O)O)o2)c(CC(C)C)o1,8.221848749616356 +1158,O=C(O)Cc1ccccc1Nc1c(Cl)cc(O)cc1Cl,5.149999867728904 +1159,N[C@@H](Cc1o[nH]c(=O)c1-c1cccc(O)c1)C(=O)O,7.2076083105017466 +1160,CCOP(=S)(OCC)SCc1ccncc1,7.620694482249418 +1161,O=C1N=c2ccccc2=C1c1sc(Nc2ccc(O)cc2)nc1O,7.853871964321762 +1162,CC(=O)OCc1cccc(-n2sc3cc(F)ccc3c2=O)c1,8.638272163982407 +1163,COc1cc(-c2cc(=O)c3cc(O)ccc3o2)cc(OC)c1OC,7.585026652029182 +1164,CN[C@H]1CCc2ccccc2[C@H]1c1ccc(Cl)c(Cl)c1,8.138943755423126 +1165,O=C(O)C1CCCNC1,8.221848749616356 +1166,CS(=O)(=O)c1ccc(S(=O)(=O)n2cc(CC(=O)O)c3ccsc32)cc1,8.397940008672037 +1167,Cc1[nH]nc2c1N=C(c1ccc([N+](=O)[O-])cc1)CNC2=O,7.515700160653214 +1168,CCc1nccc2c1[nH]c1ccccc12,6.602019459067794 +1169,Cc1ccc(C)c(OCCCC(C)(C)C(=O)O)c1,8.149999867728903 +1170,NC(=O)c1cccc2c(NCc3cc(F)c(F)c(F)c3)ncnc12,8.795880017344075 +1171,c1ccc(-c2cnc(NCc3ccco3)c3cncn23)cc1,8.661543506395395 +1172,O=C1NC(=O)c2c1c1c3ccccc3[nH]c1c1[nH]c3ccccc3c21,7.221848749616356 +1173,CC(=O)OCC(=O)O,5.958607314841775 +1174,O=c1cc(N2CCOCC2)oc2c(-c3cccs3)csc12,8.2839966563652 +1175,O=C(O)c1cccc(NS(=O)(=O)c2ccc(-c3ccon3)s2)c1,8.199970640755867 +1176,COc1cccc(N2C(=O)C=CC2=O)c1,8.18045606445813 +1177,O=c1c(O)c(-c2cc(O)c(O)c(O)c2)oc2cc(O)cc(O)c12,8.10790539730952 +1178,O=c1[nH]c2cc([N+](=O)[O-])c([N+](=O)[O-])cc2cc1-c1nn[nH]n1,7.698970004336019 +1179,CN(CCC[C@H](N)C(=O)O)/C(=N/O)NO,6.910094888560602 +1180,O=C(NCc1ccncc1)Nc1nc(-c2ccncc2)cs1,8.684029654543082 +1181,O=c1cc(-c2ccc(O)cc2)oc2cc(O)ccc12,7.865504144165326 +1182,O=C(O)CNC(=O)C(=O)O,7.322764089573579 +1183,Cc1ncc(COP(=O)(O)O)c(C2NC(C(=O)O)CS2)c1O,7.136825896339948 +1184,CC(C)Cc1ccc(C(C)C(=O)O)cc1,6.540578526732223 +1185,O=C(CCCCCONC(=O)c1cc(Br)cc(Br)c1)NO,8.763210900590707 +1186,CN1CCCc2[nH]c3ccccc3c2C1,8.148741651280925 +1187,Oc1ccc2c(c1)C(O)(C(F)(F)F)c1ccccc1-2,7.920023276367402 +1188,COc1ccc2oc(C(CN)CC(=O)O)cc2c1,8.2518119729938 +1189,O=C1NCCc2c1cc(-c1ccncc1)n2CCO,8.481486060122112 +1190,CSc1nn(-c2ccc(Cl)cc2C)c2nc(C)[nH]c(=O)c12,7.130768280269024 +1191,O=c1c2cccnc2sn1Cc1ccc(Cl)cc1,8.709965388637482 +1192,O=C(O)COc1ccc(N=Nc2ccc3cc(Br)ccc3c2O)cc1,7.096910013008056 +1193,COc1ccc(-c2[nH]c3nccnc3c2CCCCl)cc1,8.522878745280337 +1194,C=CCN1C(=O)c2cccn2S(=O)(=O)c2ccccc21,8.397940008672037 +1195,Cc1ncn(-c2ccc(Cl)cc2)c1-c1c(F)ccc(Cl)c1F,7.91721462968355 +1196,COC(=N)c1cccc(C(=N)OC)n1,6.698970004336019 +1197,C(#Cc1[nH]nc2ncccc12)c1cccnc1,8.045757490560675 +1198,N=C(N)N1CCC(C(CS)C(=O)O)CC1,8.508638306165727 +1199,COc1ccc2cc([C@H](C)NC(=O)NO)ccc2c1,8.148741651280925 +1200,NS(=O)(=O)c1ccc(-c2ccc(/C=C3\SC(=O)NC3=O)o2)cc1,7.568636235841013 +1201,C[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccn1,8.68214551066853 +1202,O=C(NO)c1cc(OCc2ccc(-c3ccccc3)cc2)no1,8.60467360693065 +1203,C[C@]1(Cn2ccnn2)[C@H](C(=O)O)N2C(=O)C[C@H]2S1(=O)=O,8.318758762624412 +1204,O=c1cc(-c2ccc(O)cc2)oc2cc(O)c(O)c(O)c12,8.01592296609717 +1205,C=C1C(=O)O[C@H]2[C@H]1CCC(C)=CCC[C@@]1(C)O[C@@H]21,7.555955204081924 +1206,C=CCC1(O)C(=O)Nc2ccc(-c3c(C)noc3C)cc21,8.602059991327963 +1207,C[C@@H]1Cc2ccc(-c3ncnc4[nH]ccc34)cc2[C@@H]1NC#N,8.7281583934635 +1208,N#Cc1ccc(-c2cc(C(F)F)nn2-c2ccc(S(N)(=O)=O)cc2)cc1,7.527243550682788 +1209,O=C(O)c1cccc(-n2sc3ccccc3c2=O)c1,8.958607314841775 +1210,O=C1/C(=C/c2ccc(Cl)cc2)SC(=S)N1CN1CCCCC1,7.42021640338319 +1211,CCOC(=O)c1sc(SC(C)=O)cc1O,7.6020599913279625 +1212,O=C(NS(=O)(=O)c1ccccc1)c1cccnc1,7.801342913045577 +1213,NC(N)=N/N=C/c1cc(Br)ccc1OCc1cccc(C(=O)O)c1,7.408467386694032 +1214,CC(=O)CCCCn1c(=O)c2c(ncn2C)n(C)c1=O,6.774690718274137 +1215,CC1CC(=O)NN=C1c1c(C(C)C)nn2ccccc12,7.356547323513812 +1216,Cn1c(=O)c2c(nc3n2CCN(c2ccccc2)C3)n(C)c1=O,8.0 +1217,CCCNC1CCCc2nc3ccccc3c(N)c21,7.903089986991944 +1218,COc1nc2c(N(C)C)ncnc2n1Cc1ccccc1,8.268801388729079 +1219,CC(=O)c1cc(-c2ccccc2CO)c2cc(C(N)=O)ccn12,8.721246399047171 +1220,NC(=S)Nc1ccccc1,7.366531544420414 +1221,O=C(c1c(F)cccc1F)N1CCN(c2nc(Cl)ncc2Br)CC1,8.576754126063193 +1222,COc1ccccc1C(O)CC(=O)N(C)O,7.075720713938118 +1223,O=C(CNS(=O)(=O)c1ccc(Oc2ccccc2)nc1)NO,8.455931955649724 +1224,C/C(O)=C(\C#N)C(=O)Nc1ccc(-c2c(Cl)cccc2Cl)cc1Cl,7.782516055786093 +1225,c1ccc(CSCCn2ccnc2)cc1,8.397940008672037 +1226,c1cc(-c2cn(CCC3CC3)c3cnccc23)ccn1,8.943095148663527 +1227,O=C1c2cc(O)c(O)cc2OCC1c1ccc(O)cc1,8.42021640338319 +1228,O=C1Nc2cc(Cl)ccc2C(=O)C1C(=O)c1ccccc1,8.500312917381596 +1229,O=C1c2c(ccc(O)c2O)CN1Cc1cc(F)ccc1F,7.568636235841013 +1230,CN(C)C(=O)c1cccc2[nH]c(-c3ccncc3)nc12,7.246723429815582 +1231,CNCc1ccc2c(-c3cccc(C(N)=S)c3)c[nH]c2c1,7.698970004336019 +1232,FC(F)(F)c1ccc(Nc2cc(C(F)(F)F)nc3ncnn23)cc1,8.769551078621726 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+1605,O=c1[nH]c2c(O)cccc2n1-c1nc2ccccc2[nH]1,7.6777807052660805 +1606,O=C1NC(=S)N/C1=C\c1cccc(OCc2ccc(Cl)cc2)c1,7.489454989793388 +1607,O=S(=O)(c1ccccc1)n1c2cc(O)c(O)cc2c2ccc(O)c(O)c21,6.6020599913279625 +1608,Cc1[nH]ncc1-c1cc2nc(CN3CC[C@H](F)C3)[nH]c(=O)c2s1,8.346787486224656 +1609,Cn1cc(NC(=O)c2cccc(-c3ccnc(N)c3)n2)c(C(N)=O)n1,7.6020599913279625 +1610,N#CC1=Cc2ccccc2CC=C1,8.238824186844269 +1611,O[C@H]1CCOc2ccccc21,6.285670240254767 +1612,CN(c1ccccc1)c1nc(Cl)nc2ccccc12,8.397940008672037 +1613,O=C(O)c1cc2ccc([N+](=O)[O-])cc2[nH]c1=O,8.886056647693163 +1614,COc1cccc2[nH]nc(-c3cccc(S(N)(=O)=O)c3)c12,8.638272163982407 +1615,CC(c1cccc(O)c1)n1cnc2c(=O)[nH]cnc21,8.657577319177793 +1616,COc1cc2ccc(=O)oc2cc1O,6.773142429711276 +1617,CCCCc1sc(-c2ccccc2)nc1O,7.7447274948966935 +1618,N#Cc1ccccc1-c1ccc(CNc2ccc(O)cc2)cc1,7.461175011062096 +1619,CCCNC(=O)Cn1c(-c2ccc(Cl)cc2)nc2cccnc21,8.899629454882437 +1620,Nc1nc(N)c2cc(COC(=O)c3ccc(C(=O)O)cc3)ccc2n1,9.0 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+1637,COC[C@H]1[C@H](C(=O)O)[C@@H]1[C@H](N)C(=O)O,8.397940008672037 +1638,CC(=O)N1CCc2c(c(=O)[nH]c3onc(C)c23)C1,8.85078088734462 +1639,O=C(/C=C/c1cccs1)c1cc(O)c(O)c([N+](=O)[O-])c1,7.201349354554731 +1640,Cc1cc2ccnc(NCCCN(C)C)c2[nH]c1=O,7.200000237109354 +1641,Cn1c(=O)[nH]c2ccc(OCc3ccc(Cl)cc3)cc21,7.248720896016658 +1642,Nc1ncnc2c1nc(-c1ccccc1)n2-c1ccccc1,7.785156151952302 +1643,COc1ccnc(CCc2nc3nc(OC)ccc3[nH]2)c1,7.0 +1644,Cc1ccc2nc(/C=C/c3ccccc3)[nH]c(=O)c2c1,8.698970004336019 +1645,NC(=O)c1cc2c(Sc3ccccn3)cncc2s1,7.187086643357144 +1646,CCOC(=O)COc1cc(C(=O)O)c(O)c2ccccc12,7.031517051446065 +1647,Cc1nnc(C(CC(=O)O)c2cccc(-c3ccncc3)c2)o1,7.6595558851598815 +1648,Cc1ccncc1-c1ncc(Cl)cc1-c1ccc(S(C)(=O)=O)cc1,8.753255290276158 +1649,O=C(O)c1cnn(-c2ccc(COCc3cccc(Cl)c3)cn2)c1,8.769551078621726 +1650,CC(NC(C)(C)C)C(=O)c1cccc(Br)c1,8.21824462534753 +1651,CC(C)[C@H](N)C(=O)NCC(=O)O,5.95999928552668 +1652,CC(NC(=O)C(=O)c1c[nH]c2ccc(Br)cc12)C(=O)O,7.397831448621003 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+1669,OCc1cc2c(cn1)[nH]c1ccccc12,8.832682665251824 +1670,O=c1c2cc(O)c(O)cc2oc2cc(O)cc(O)c12,7.9446216686249995 +1671,Nc1nc(OCCc2ccccc2)c2[nH]cnc2n1,7.187086643357144 +1672,Oc1c(Cc2ccccc2)cccc1Cc1ccccc1,7.2839966563652006 +1673,CC(C)c1ccc(/C=N/NC(=O)c2ccc(O)cc2)cc1,8.698970004336019 +1674,O=Cc1cccc(OCc2ccccc2)c1,8.707743928643524 +1675,COc1ccc(F)c(-c2nc(C)c3nnc4ccc(OC)nc4n23)c1,8.31695296176115 +1676,CNc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,8.207608310501746 +1677,CC(CCn1cnc2ccc(Cl)cc2c1=O)n1ccnc1,8.096910013008056 +1678,O=c1c(O)c(-c2ccc(O)c(O)c2)oc2cc(O)cc(O)c12,6.795880017344075 +1679,CC(C(=O)N(C)O)c1ccc2c(c1)C(=O)c1ccccc1CO2,8.886056647693163 +1680,O=[N+]([O-])c1ccc(S(=O)(=O)Nc2ccc(O)c(Sc3ncn[nH]3)c2)cc1,8.823908740944319 +1681,Cc1cc(N2CCCCC2)nc2ccccc12,8.749579997691106 +1682,O=C(OCCCCOc1ccccc1)c1cccc(=S)[nH]1,7.107905397309519 +1683,Nc1nccc(-n2ccc3ccc(F)cc32)n1,7.468521082957745 +1684,COc1ccc2ncc(-c3ccc(C(F)(F)F)cc3)n2n1,8.55284196865778 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+CC1=NC(CC#N)CO1,30.926 +OC1CC2CC(=O)C2C1,31.056 +OC1COCC2COC12,30.369 +CC1CC(C)(CC=O)O1,36.356 +CCC12C(C)C1CC2C,39.06 +CC1(CO)CCC=C1,32.219 +CC1(COC=NC1)C#N,30.708 +CN1CC1CC=O,27.013 +CC1CC(C1)C(=O)CO,35.559 +CCOC1(C)C2COC12,35.059 +c1c2n(cn1)CC=C2,22.074 +CCC1NC1C(O)C#N,35.435 diff --git a/data/data_handling.py b/data/data_handling.py new file mode 100644 index 0000000000000000000000000000000000000000..ebed5ed2af72620bf0079884652de4433da977ef --- /dev/null +++ b/data/data_handling.py @@ -0,0 +1,152 @@ +import os +import torch +from torch_geometric.loader import DataLoader +from pathlib import Path +import numpy as np +import multiprocessing +from joblib import Parallel, delayed + +# --- Assume these are imported from your project --- +from data.loaders import load_dataset +from data.featurize import ( + smiles_to_graph, + selfies_to_graph, + ecfp_to_graph, + smiles_for_gp, + selfies_for_gp, + ecfp_for_gp, +) +from data.polyatomic_featurize import compressed_topsignal_graph_from_smiles +from models.gnn import GCN, GIN, GAT, GraphSAGE +from models.polyatomic import PolyatomicNet + +# --- Configuration Dictionaries --- +# Representation functions for GNN +REPRESENTATIONS = { + "smiles": smiles_to_graph, + "selfies": selfies_to_graph, + "ecfp": ecfp_to_graph, + "polyatomic": compressed_topsignal_graph_from_smiles, +} + +# Feature functions for GP (numeric vectors) +GP_FEATURIZERS = { + "smiles": smiles_for_gp, + "selfies": selfies_for_gp, + "ecfp": ecfp_for_gp, +} + +GNN_MODELS = { + "gcn": GCN, + "gin": GIN, + "gat": GAT, + "sage": GraphSAGE, + "polyatomic": PolyatomicNet, # Custom GNN for polyatomic complexes +} + +try: + multiprocessing.set_start_method("fork") +except RuntimeError: + pass + + +def featurize_dataset_parallel(X, y, featurizer, n_jobs=None): + """Your provided parallel featurization function.""" + if n_jobs is None: + n_jobs = max(1, multiprocessing.cpu_count() - 2) + + if featurizer.__name__ == "compressed_topsignal_graph_from_smiles": + results = Parallel(n_jobs=n_jobs, backend="loky", verbose=10)( + delayed(featurizer)(xi, yi) for xi, yi in zip(X, y) + ) + else: + results = Parallel(n_jobs=n_jobs, backend="loky", verbose=10)( + delayed(featurizer)(xi) for xi in X + ) + + # Filter out None results and attach the original y-value + data_list = [] + # This robustly handles cases where some featurizations might fail + for i, res in enumerate(results): + if res is not None: + res.y = torch.tensor([y[i]], dtype=torch.float) + data_list.append(res) + + return data_list + + +def prepare_and_load_data(args): + """ + Performs the expensive featurization ONCE and caches the result. + Subsequent runs will load the cached file instantly. + """ + root_dir = Path(__file__).parent.parent.resolve().__str__() + datasets_dir = root_dir + "/" + "datasets" + cache_dir = Path(datasets_dir) + if not os.path.exists(cache_dir): + cache_dir.mkdir(exist_ok=False) + train_cache_file = Path(f"{cache_dir}" + "/" + f"{args.rep}_data_{args.dataset}.pt") + test_cache_file = Path( + f"{cache_dir}" + "/" + f"{args.rep}_test_data_{args.dataset}.pt" + ) + + print(f"train cache file is: {train_cache_file}") + print(f"test cache file is: {test_cache_file}") + + if train_cache_file.exists() and test_cache_file.exists(): + print( + f"INFO: Loading pre-featurized data from cache for dataset '{args.dataset}'..." + ) + train_graphs = torch.load(train_cache_file, weights_only=False) + test_graphs = torch.load(test_cache_file, weights_only=False) + return train_graphs, test_graphs + + print("INFO: No cached data found. Starting one-time featurization process...") + X_train, X_test, y_train, y_test = load_dataset(args.dataset) + featurizer = REPRESENTATIONS[args.rep] + + print("Featurizing training set (this may take a while)...") + train_graphs = featurize_dataset_parallel(X_train, y_train, featurizer) + torch.save(train_graphs, train_cache_file) + print(f"Saved featurized training data to {train_cache_file}") + + print("Featurizing test set...") + test_graphs = featurize_dataset_parallel(X_test, y_test, featurizer) + torch.save(test_graphs, test_cache_file) + print(f"Saved featurized test data to {test_cache_file}") + + return train_graphs, test_graphs + + +def get_model_instance(args, params, train_graphs): + """Instantiates a model, handling the special case for polyatomic.""" + model_class = GNN_MODELS[args.model] + sample_graph = train_graphs[0] + + if args.model == "polyatomic": + from torch_geometric.utils import degree + + print("INFO: Calculating degree vector for polyatomic model...") + loader = DataLoader(train_graphs, batch_size=params.get("batch_size", 128)) + deg = torch.zeros(32, dtype=torch.long) + for data in loader: + d = degree(data.edge_index[1], num_nodes=data.num_nodes, dtype=torch.long) + bc = torch.bincount(d, minlength=deg.size(0)) + if bc.size(0) > deg.size(0): + new_deg = torch.zeros(bc.size(0), dtype=torch.long) + new_deg[: deg.size(0)] = deg + deg = new_deg + deg += bc + return model_class( + node_feat_dim=sample_graph.x.shape[1], + edge_feat_dim=sample_graph.edge_attr.shape[1], + graph_feat_dim=sample_graph.graph_feats.shape[0], + hidden_dim=params["hidden_dim"], + deg=deg, + ) + else: + return model_class( + in_channels=sample_graph.num_node_features, + hidden_channels=params["hidden_dim"], + out_channels=1, + ) diff --git a/data/featurize.py b/data/featurize.py new file mode 100644 index 0000000000000000000000000000000000000000..aa8f950a649af36f5a666e7dfeb4103bb573d5c8 --- /dev/null +++ b/data/featurize.py @@ -0,0 +1,121 @@ +import numpy as np +import torch +from rdkit import Chem +from rdkit.Chem.rdFingerprintGenerator import GetMorganGenerator +import selfies as sf +from torch_geometric.data import Data +from torch_geometric.loader import DataLoader + +mfpgen = GetMorganGenerator( + radius=2, + countSimulation=False, + includeChirality=False, + useBondTypes=True, + onlyNonzeroInvariants=False, + includeRingMembership=True, + countBounds=None, + fpSize=2048, + atomInvariantsGenerator=None, + bondInvariantsGenerator=None, + includeRedundantEnvironments=False, +) + + +def smiles_to_graph(smiles): + mol = Chem.MolFromSmiles(smiles) # type: ignore + if mol is None: + return None + return mol_to_graph(mol) + + +def selfies_to_graph(smiles_string): + try: + selfies_string = sf.encoder(smiles_string) + smiles = sf.decoder(selfies_string) + mol = Chem.MolFromSmiles(smiles) # type: ignore + if mol is None: + raise ValueError("Decoded SELFIES is invalid") + return mol_to_graph(mol) + except Exception: + fallback = smiles_to_graph(smiles_string) + if fallback is None: + return None + return fallback + + +def ecfp_to_graph(smiles_str: str, max_bits: int = 2048, k: int = 2) -> Data | None: + mol = Chem.MolFromSmiles(smiles_str) # type: ignore + if mol is None: + return None + fp = mfpgen.GetFingerprintAsNumPy(mol) + active_bits = np.nonzero(fp)[0] + n = len(active_bits) + if n == 0: + return None + edge_index = [] + for i in range(n): + for j in range(i + 1, min(i + 1 + k, n)): + edge_index.append([i, j]) + edge_index.append([j, i]) + edge_index = torch.tensor(edge_index, dtype=torch.long).t().contiguous() + x = torch.zeros((n, max_bits), dtype=torch.float) + for i, bit_idx in enumerate(active_bits): + x[i, bit_idx] = 1.0 + return Data(x=x, edge_index=edge_index) + + +def mol_to_graph(mol): + atom_feats = [] + for atom in mol.GetAtoms(): + atom_feats.append( + [ + atom.GetAtomicNum(), + atom.GetDegree(), + atom.GetFormalCharge(), + atom.GetIdx(), + ] + ) + x = torch.tensor(atom_feats, dtype=torch.float) + + edge_index = [] + edge_attr = [] + for bond in mol.GetBonds(): + i = bond.GetBeginAtomIdx() + j = bond.GetEndAtomIdx() + edge_index.append((i, j)) + edge_index.append((j, i)) + btype = bond.GetBondTypeAsDouble() + edge_attr.append([btype]) + edge_attr.append([btype]) + + edge_index = torch.tensor(edge_index, dtype=torch.long).t().contiguous() + edge_attr = torch.tensor(edge_attr, dtype=torch.float) + return Data(x=x, edge_index=edge_index, edge_attr=edge_attr) + + +def smiles_for_gp(smiles: str) -> np.ndarray: + mol = Chem.MolFromSmiles(smiles) # type: ignore + if mol is None: + return np.zeros(mfpgen.GetNumBits(), dtype=np.float32) + arr = mfpgen.GetFingerprintAsNumPy(mol) + return arr.astype(np.float32) + + +def selfies_for_gp(selfies_str, radius=2, n_bits=2048): + try: + smiles = sf.decoder(selfies_str) + assert isinstance(smiles, str) + return smiles_for_gp(smiles) + except: + return np.zeros(n_bits) + + +def ecfp_for_gp(smiles_str: str) -> np.ndarray: + mol = Chem.MolFromSmiles(smiles_str) # type: ignore + if mol is None: + return np.zeros(mfpgen.GetNumBits(), dtype=np.float32) + return mfpgen.GetFingerprintAsNumPy(mol).astype(np.float32) + + +def graph_native_loader(graph_list, batch_size=32, shuffle=True): + return DataLoader(graph_list, batch_size=batch_size, shuffle=shuffle) diff --git a/data/loaders.py b/data/loaders.py new file mode 100644 index 0000000000000000000000000000000000000000..d54aa18f810efc26812d338fd96146712e46e7ec --- /dev/null +++ b/data/loaders.py @@ -0,0 +1,64 @@ +import pandas as pd +from sklearn.model_selection import train_test_split +import importlib.resources as pkg_resources +import polyatomic_complexes +import numpy as np +from typing import Tuple +from pathlib import Path + + +def load_dataset(name) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + if name.lower() == "esol": + data_path = ( + pkg_resources.files("polyatomic_complexes.dataset.esol") / "ESOL.csv" + ) + df = pd.read_csv(str(data_path)) + target_col = "measured log solubility in mols per litre" + elif name.lower() == "freesolv": + data_path = ( + pkg_resources.files("polyatomic_complexes.dataset.free_solv") + / "FreeSolv.csv" + ) + df = pd.read_csv(str(data_path)) + target_col = "expt" + elif name.lower() == "lipophil": + data_path = ( + pkg_resources.files("polyatomic_complexes.dataset.lipophilicity") + / "Lipophilicity.csv" + ) + df = pd.read_csv(str(data_path)) + target_col = "exp" + elif name.lower() == "boilingpoint": + data_path = ( + Path(__file__).parent.parent / "benchmark_csv/boiling_point.csv".__str__() + ) + df = pd.read_csv(data_path) + target_col = "boiling_point_K" + elif name.lower() == "qm9": + data_path = ( + Path(__file__).parent.parent / "benchmark_csv/qm9_subset.csv".__str__() + ) + df = pd.read_csv(data_path) + target_col = "cv" + elif name.lower() == "ic50": + data_path = ( + Path(__file__).parent.parent / "benchmark_csv/ic_50_subset.csv".__str__() + ) + df = pd.read_csv(data_path) + target_col = "pIC50" + elif name.lower() == "bindingdb": + data_path = ( + Path(__file__).parent.parent / "benchmark_csv/bindingdb.csv".__str__() + ) + df = pd.read_csv(data_path) + target_col = "pIC50" + else: + raise ValueError(f"Unknown dataset: {name}") + + df.dropna(subset=["smiles", target_col], inplace=True) + smiles = df["smiles"] + targets = df[target_col] + X_train, X_test, y_train, y_test = train_test_split( + smiles, targets, test_size=0.2, random_state=42 + ) + return X_train.to_numpy(), X_test.to_numpy(), y_train.to_numpy(), y_test.to_numpy() diff --git a/data/polyatomic_featurize.py b/data/polyatomic_featurize.py new file mode 100644 index 0000000000000000000000000000000000000000..bb83557c4ce1be5bdf6df8c4d0a73f4799aae79d --- /dev/null +++ b/data/polyatomic_featurize.py @@ -0,0 +1,160 @@ +import torch +import numpy as np +from rdkit import Chem +import networkx as nx +from collections import defaultdict +from torch_geometric.data import Data +from polyatomic_complexes.src.complexes.abstract_complex import AbstractComplex +from polyatomic_complexes.src.complexes import PolyatomicGeometrySMILE + + +def compressed_topsignal_graph_from_smiles( + smile: str, y_val: int, topk_lap: int = 5 +) -> Data | None: + try: + # 1) Abstract complex + pg = PolyatomicGeometrySMILE(smile=smile, mode="abstract") + ac = pg.smiles_to_geom_complex() + assert isinstance(ac, AbstractComplex) + + # 2) RDKit molecule + mol = Chem.MolFromSmiles(smile) # type: ignore + if mol is None: + return None + + # 3) Node features: chain0 value + RDKit descriptors + chains = ac.get_raw_k_chains() + chain0 = chains.get("chain_0", []) + atom_types = [6, 7, 8, 15, 16, 17] + hyb_types = [ + Chem.rdchem.HybridizationType.SP, + Chem.rdchem.HybridizationType.SP2, + Chem.rdchem.HybridizationType.SP3, + ] + node_feats = [] + for atom in mol.GetAtoms(): + idx = atom.GetIdx() + # fallback if chain0 shorter than atom count + c0 = float(chain0[idx]) if idx < len(chain0) else 0.0 + feats = [c0] + feats += one_hot(atom.GetAtomicNum(), atom_types) + feats += one_hot(atom.GetHybridization(), hyb_types) + feats += [ + float(atom.GetDegree()), + float(atom.GetIsAromatic()), + float(atom.GetFormalCharge()), + ] + node_feats.append(feats) + x = torch.tensor(node_feats, dtype=torch.float32) + n = x.size(0) # use number of atoms for all subsequent node counts + + # 4) Edges: abstract bonds + RDKit fallback + sk = ac.get_skeleta().get("molecule_skeleta", [[]])[0] + zero = next((lst for dim, lst in sk if dim == "0"), []) + node_ids = [next(iter(fz))[0] for fz in zero] + atom_map = defaultdict(list) + for i, nid in enumerate(node_ids): + symbol = nid.split("_")[0] + atom_map[symbol].append(i) + + edge_index_list, edge_attr_list = [], [] + bond_types = [ + Chem.rdchem.BondType.SINGLE, + Chem.rdchem.BondType.DOUBLE, + Chem.rdchem.BondType.TRIPLE, + Chem.rdchem.BondType.AROMATIC, + ] + for a1, a2, (btype, order) in ac.get_bonds(): + bt_val = getattr(Chem.rdchem.BondType, btype, None) + for i in atom_map.get(a1, []): + for j in atom_map.get(a2, []): + if i < n and j < n: + edge_index_list += [[i, j], [j, i]] + attr = one_hot(bt_val, bond_types) + [float(order), 0.0] + edge_attr_list += [attr, attr] + if not edge_index_list: + for bond in mol.GetBonds(): + i, j = bond.GetBeginAtomIdx(), bond.GetEndAtomIdx() + edge_index_list += [[i, j], [j, i]] + attr = one_hot(bond.GetBondType(), bond_types) + attr += [float(bond.GetIsConjugated()), float(bond.IsInRing())] + edge_attr_list += [attr, attr] + + edge_index = torch.tensor(edge_index_list, dtype=torch.long).t().contiguous() + edge_attr = torch.tensor(edge_attr_list, dtype=torch.float32) + + # 5) Topology features: centrality + SPD + G = nx.Graph() + G.add_nodes_from(range(n)) + G.add_edges_from(edge_index_list) + cent = nx.closeness_centrality(G) + spd = dict(nx.all_pairs_shortest_path_length(G)) + cent_vec = [cent.get(i, 0.0) for i in range(n)] + spd_vec = [ + sum(d.values()) / max(len(d), 1) for d in (spd.get(i, {}) for i in range(n)) + ] + cent_t = torch.tensor(cent_vec, dtype=torch.float32).view(n, 1) + spd_t = torch.tensor(spd_vec, dtype=torch.float32).view(n, 1) + x = torch.cat([x, cent_t, spd_t], dim=1) + + # print("MANAGED TO CONCAT?") + + # 6) Graph-level features: chain stats + laplacians + g_stats, lap_feats = [], [] + for k, arr in chains.items(): + if k == "chain_0": + continue + a = np.array(arr, dtype=np.float32) + g_stats += [a.mean(), a.std()] + + # print("COMPUTED GRAP STATS") + + for grp in ac.get_laplacians().get("molecule_laplacians", []): + recs = grp if isinstance(grp, list) else [grp] + for _, mat in recs: + # use dense eigen solver to avoid ARPACK issues + M = np.array(mat, dtype=np.float32) + # compute eigenvalues of symmetric Laplacian + try: + eigs = np.linalg.eigvalsh(M) + except Exception: + eigs = np.zeros(M.shape[0], dtype=np.float32) + # take smallest non-zero eigenvalues (skip the first zero) + nonzero = eigs[eigs > 1e-6] + vals = nonzero[:topk_lap] if len(nonzero) >= topk_lap else nonzero + # pad to exactly topk_lap + if len(vals) < topk_lap: + vals = np.pad(vals, (0, topk_lap - len(vals))) + lap_feats += list(vals) + + # --- 7) Spectral k-chains stats --- + spectral = ac.get_spectral_k_chains() + spec_feats = [] + for arr in spectral.values(): + a = np.array(arr, dtype=np.float32) + spec_feats += [a.mean(), a.std()] + + # --- 8) Betti numbers (components & cycles) --- + b0 = nx.number_connected_components(G) + b1 = sum( + len(nx.cycle_basis(G.subgraph(comp))) for comp in nx.connected_components(G) + ) + + # --- 9) Assemble graph_feats --- + all_feats = g_stats + lap_feats + spec_feats + [float(b0), float(b1)] + graph_feats = torch.tensor(all_feats, dtype=torch.float32) + + # print("managed to feat?") + + data = Data(x=x, edge_index=edge_index, edge_attr=edge_attr) + data.graph_feats = graph_feats + data.y = torch.tensor([y_val], dtype=torch.float) + # print(f"SUCCESS for : {smile}") + return data + except Exception as e: + # print(f"Failed {smile}: {e}") + return None + + +def one_hot(val, choices): + return [1.0 if val == c else 0.0 for c in choices] diff --git a/datasets/ecfp_data_bindingdb.pt b/datasets/ecfp_data_bindingdb.pt new file mode 100644 index 0000000000000000000000000000000000000000..5f8ad355c55353fc4ef7a4a0df76650c1048b749 --- /dev/null +++ b/datasets/ecfp_data_bindingdb.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:20ce607c4a5508c65c6dba97656dd7f6c677459ece54f4e0f811ee276d6ffab4 +size 134 diff --git a/datasets/ecfp_data_boilingpoint.pt b/datasets/ecfp_data_boilingpoint.pt new file mode 100644 index 0000000000000000000000000000000000000000..6d14411add83660535dc56bf292c5bf18a74b232 --- /dev/null +++ b/datasets/ecfp_data_boilingpoint.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:183b9f30b2fd6ddc6781f1aa6d0ea8967623cb68042580c97593b5f134b5d17f +size 134 diff --git a/datasets/ecfp_data_esol.pt b/datasets/ecfp_data_esol.pt new file mode 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new file mode 100644 index 0000000000000000000000000000000000000000..701a69018addf694a8eb3c4e0f812b54d6dc305b --- /dev/null +++ b/datasets/smiles_test_data_bindingdb.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6946ccda19e1ec9015002059fb8dd096851805dfdf8b329e64ee0a3a0137b0aa +size 132 diff --git a/datasets/smiles_test_data_boilingpoint.pt b/datasets/smiles_test_data_boilingpoint.pt new file mode 100644 index 0000000000000000000000000000000000000000..8b294910f33a8864e12eb34104a0813d6dc95bf8 --- /dev/null +++ b/datasets/smiles_test_data_boilingpoint.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:95f60ad6b699250a63d9aba8b73575ca87fec99a3d519556e5c18cf775b62cc5 +size 131 diff --git a/datasets/smiles_test_data_esol.pt b/datasets/smiles_test_data_esol.pt new file mode 100644 index 0000000000000000000000000000000000000000..db546ed9508d9d4c165d04d5b36b4e92e5fca620 --- /dev/null +++ b/datasets/smiles_test_data_esol.pt @@ -0,0 +1,3 @@ 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b/datasets/smiles_test_data_lipophil.pt new file mode 100644 index 0000000000000000000000000000000000000000..fc95c353fd97e915f754d0f0f90fe9c7074347fc --- /dev/null +++ b/datasets/smiles_test_data_lipophil.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:89b5da21def4bcb85878f609b05d19507f0101d57c54b76d42147b096c657b06 +size 132 diff --git a/datasets/smiles_test_data_qm9.pt b/datasets/smiles_test_data_qm9.pt new file mode 100644 index 0000000000000000000000000000000000000000..9b6f0eaa564f833ffde3f76edd00b0c70a5cf532 --- /dev/null +++ b/datasets/smiles_test_data_qm9.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:aac243d877916e7d6c37bc04d5c02e2345ecde62b99d9df6ef9307f65a04703f +size 131 diff --git a/logs/bindingdb-bench/gat/gat_ecfp_bindingdb_20250729_221953.txt b/logs/bindingdb-bench/gat/gat_ecfp_bindingdb_20250729_221953.txt new file mode 100644 index 0000000000000000000000000000000000000000..3b22c65182ae344e24a00ef139ca4fd7a26580cb --- /dev/null +++ b/logs/bindingdb-bench/gat/gat_ecfp_bindingdb_20250729_221953.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.0448 +RMSE: 2.2158, MAE: 1.6808, R2: -0.9182 + +FOLD 2/5 +GNN Train Loss: 0.0256 +RMSE: 2.2666, MAE: 1.8282, R2: -1.2520 + +FOLD 3/5 +GNN Train Loss: 0.0417 +RMSE: 2.2055, MAE: 1.7431, R2: -1.2155 + +FOLD 4/5 +GNN Train Loss: 0.0312 +RMSE: 2.3380, MAE: 1.8459, R2: -1.2036 + +FOLD 5/5 +GNN Train Loss: 0.0400 +RMSE: 2.6496, MAE: 1.8400, R2: -2.0842 + +====== K-FOLD SUMMARY ====== +RMSE: 2.3384 [2.2218, 2.4985] +MAE: 1.7883 [1.7250, 1.8400] +R2: -1.3438 [-1.7416, -1.0420] + +★ Using fold 3 model for test inference +RMSE: 2.6823, MAE: 1.9119, R2: -1.1935 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.682283261974216, 'mae': 1.911918044090271, 'r2': -1.193528652191162} +Test RMSE: 2.6672 (95 % CI: 2.2364–3.1913) + +Test MAE : 1.9156 (95 % CI: 1.7338–2.1126) + +Test R² : -1.2170 (95 % CI: -2.1555–-0.6869) + diff --git a/logs/bindingdb-bench/gat/gat_selfies_bindingdb_20250729_222144.txt b/logs/bindingdb-bench/gat/gat_selfies_bindingdb_20250729_222144.txt new file mode 100644 index 0000000000000000000000000000000000000000..1d75aee1d820065c6089cdec1ec63c01636d0a53 --- /dev/null +++ b/logs/bindingdb-bench/gat/gat_selfies_bindingdb_20250729_222144.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on bindingdb + +FOLD 1/5 +GNN Train Loss: 1.0133 +RMSE: 1.5494, MAE: 1.2730, R2: 0.0621 + +FOLD 2/5 +GNN Train Loss: 0.9337 +RMSE: 1.4945, MAE: 1.2274, R2: 0.0210 + +FOLD 3/5 +GNN Train Loss: 0.9459 +RMSE: 1.4927, MAE: 1.2433, R2: -0.0148 + +FOLD 4/5 +GNN Train Loss: 0.9468 +RMSE: 1.5140, MAE: 1.2402, R2: 0.0760 + +FOLD 5/5 +GNN Train Loss: 0.9547 +RMSE: 1.5082, MAE: 1.2453, R2: 0.0007 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5119 [1.4965, 1.5313] +MAE: 1.2456 [1.2338, 1.2609] +R2: 0.0292 [0.0016, 0.0581] + +★ Using fold 3 model for test inference +RMSE: 1.8185, MAE: 1.3746, R2: -0.0082 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.8185145458387524, 'mae': 1.3745886087417603, 'r2': -0.008248567581176758} +Test RMSE: 1.8164 (95 % CI: 1.5619–2.0952) + +Test MAE : 1.3696 (95 % CI: 1.2537–1.4855) + +Test R² : -0.0126 (95 % CI: -0.1590–0.0830) + diff --git a/logs/bindingdb-bench/gat/gat_smiles_bindingdb_20250729_222250.txt b/logs/bindingdb-bench/gat/gat_smiles_bindingdb_20250729_222250.txt new file mode 100644 index 0000000000000000000000000000000000000000..c04cb7e4c99ae2a34727b2d9b625795d1334b715 --- /dev/null +++ b/logs/bindingdb-bench/gat/gat_smiles_bindingdb_20250729_222250.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9514 +RMSE: 1.5340, MAE: 1.2692, R2: 0.0806 + +FOLD 2/5 +GNN Train Loss: 0.9419 +RMSE: 1.4995, MAE: 1.2323, R2: 0.0143 + +FOLD 3/5 +GNN Train Loss: 0.9412 +RMSE: 1.4703, MAE: 1.2275, R2: 0.0155 + +FOLD 4/5 +GNN Train Loss: 0.9436 +RMSE: 1.5220, MAE: 1.2454, R2: 0.0662 + +FOLD 5/5 +GNN Train Loss: 0.9476 +RMSE: 1.4768, MAE: 1.2251, R2: 0.0418 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5002 [1.4787, 1.5223] +MAE: 1.2401 [1.2275, 1.2561] +R2: 0.0438 [0.0205, 0.0671] + +★ Using fold 3 model for test inference +RMSE: 1.8019, MAE: 1.3712, R2: 0.0101 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.8018726674096883, 'mae': 1.3711559772491455, 'r2': 0.010120749473571777} +Test RMSE: 1.7932 (95 % CI: 1.5775–2.0451) + +Test MAE : 1.3722 (95 % CI: 1.2613–1.4966) + +Test R² : 0.0054 (95 % CI: -0.1048–0.0787) + diff --git a/logs/bindingdb-bench/gcn/gcn_ecfp_bindingdb_20250729_222216.txt b/logs/bindingdb-bench/gcn/gcn_ecfp_bindingdb_20250729_222216.txt new file mode 100644 index 0000000000000000000000000000000000000000..6224cd29c6e7581ca22cdbafed8f9ee2517fc2d5 --- /dev/null +++ b/logs/bindingdb-bench/gcn/gcn_ecfp_bindingdb_20250729_222216.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.0852 +RMSE: 1.9536, MAE: 1.5108, R2: -0.4911 + +FOLD 2/5 +GNN Train Loss: 0.0616 +RMSE: 1.9378, MAE: 1.5399, R2: -0.6460 + +FOLD 3/5 +GNN Train Loss: 0.0782 +RMSE: 1.8320, MAE: 1.4621, R2: -0.5285 + +FOLD 4/5 +GNN Train Loss: 0.0556 +RMSE: 2.0135, MAE: 1.6022, R2: -0.6343 + +FOLD 5/5 +GNN Train Loss: 0.0695 +RMSE: 2.3323, MAE: 1.6195, R2: -1.3897 + +====== K-FOLD SUMMARY ====== +RMSE: 2.0102 [1.8894, 2.1776] +MAE: 1.5475 [1.4971, 1.5967] +R2: -0.7360 [-1.0664, -0.5296] + +★ Using fold 3 model for test inference +RMSE: 2.1806, MAE: 1.5863, R2: -0.4497 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1805873093719375, 'mae': 1.5863122940063477, 'r2': -0.44970953464508057} +Test RMSE: 2.1744 (95 % CI: 1.8807–2.5071) + +Test MAE : 1.5856 (95 % CI: 1.4413–1.7316) + +Test R² : -0.4582 (95 % CI: -0.6690–-0.2806) + diff --git a/logs/bindingdb-bench/gcn/gcn_selfies_bindingdb_20250729_221912.txt b/logs/bindingdb-bench/gcn/gcn_selfies_bindingdb_20250729_221912.txt new file mode 100644 index 0000000000000000000000000000000000000000..56391aa638fda66776bc5590d64254d8f61a4504 --- /dev/null +++ b/logs/bindingdb-bench/gcn/gcn_selfies_bindingdb_20250729_221912.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9571 +RMSE: 1.5357, MAE: 1.2671, R2: 0.0786 + +FOLD 2/5 +GNN Train Loss: 0.9392 +RMSE: 1.4943, MAE: 1.2213, R2: 0.0211 + +FOLD 3/5 +GNN Train Loss: 0.9423 +RMSE: 1.4756, MAE: 1.2283, R2: 0.0083 + +FOLD 4/5 +GNN Train Loss: 0.9547 +RMSE: 1.5292, MAE: 1.2510, R2: 0.0573 + +FOLD 5/5 +GNN Train Loss: 0.9533 +RMSE: 1.4685, MAE: 1.2210, R2: 0.0526 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5004 [1.4779, 1.5261] +MAE: 1.2381 [1.2239, 1.2547] +R2: 0.0435 [0.0197, 0.0649] + +★ Using fold 5 model for test inference +RMSE: 1.7701, MAE: 1.3618, R2: 0.0448 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.7700657995030333, 'mae': 1.3618320226669312, 'r2': 0.04475921392440796} +Test RMSE: 1.7671 (95 % CI: 1.5530–2.0194) + +Test MAE : 1.3612 (95 % CI: 1.2540–1.4652) + +Test R² : 0.0405 (95 % CI: -0.0058–0.0818) + diff --git a/logs/bindingdb-bench/gcn/gcn_smiles_bindingdb_20250729_221840.txt b/logs/bindingdb-bench/gcn/gcn_smiles_bindingdb_20250729_221840.txt new file mode 100644 index 0000000000000000000000000000000000000000..fbaa5abd13c2e9549bd48b94aa935cc849b5fe25 --- /dev/null +++ b/logs/bindingdb-bench/gcn/gcn_smiles_bindingdb_20250729_221840.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9566 +RMSE: 1.5393, MAE: 1.2731, R2: 0.0743 + +FOLD 2/5 +GNN Train Loss: 0.9398 +RMSE: 1.5351, MAE: 1.2295, R2: -0.0330 + +FOLD 3/5 +GNN Train Loss: 0.9639 +RMSE: 1.4639, MAE: 1.2034, R2: 0.0240 + +FOLD 4/5 +GNN Train Loss: 0.9515 +RMSE: 1.5266, MAE: 1.2519, R2: 0.0606 + +FOLD 5/5 +GNN Train Loss: 0.9504 +RMSE: 1.4687, MAE: 1.2229, R2: 0.0524 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5059 [1.4783, 1.5350] +MAE: 1.2364 [1.2164, 1.2589] +R2: 0.0351 [-0.0029, 0.0644] + +★ Using fold 3 model for test inference +RMSE: 1.8375, MAE: 1.3801, R2: -0.0295 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.8375356009012365, 'mae': 1.3801325559616089, 'r2': -0.02945077419281006} +Test RMSE: 1.8313 (95 % CI: 1.5812–2.1121) + +Test MAE : 1.3773 (95 % CI: 1.2624–1.4966) + +Test R² : -0.0315 (95 % CI: -0.2108–0.0743) + diff --git a/logs/bindingdb-bench/gin/gin_ecfp_bindingdb_20250729_222416.txt b/logs/bindingdb-bench/gin/gin_ecfp_bindingdb_20250729_222416.txt new file mode 100644 index 0000000000000000000000000000000000000000..7255f8281e7e6945fb37c7e7f139a675a5b40ca2 --- /dev/null +++ b/logs/bindingdb-bench/gin/gin_ecfp_bindingdb_20250729_222416.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.0171 +RMSE: 1.7724, MAE: 1.3869, R2: -0.2273 + +FOLD 2/5 +GNN Train Loss: 0.0217 +RMSE: 1.7963, MAE: 1.4253, R2: -0.4145 + +FOLD 3/5 +GNN Train Loss: 0.0179 +RMSE: 1.7046, MAE: 1.3570, R2: -0.3235 + +FOLD 4/5 +GNN Train Loss: 0.0196 +RMSE: 1.8985, MAE: 1.5419, R2: -0.4530 + +FOLD 5/5 +GNN Train Loss: 0.0135 +RMSE: 1.7420, MAE: 1.4135, R2: -0.3332 + +====== K-FOLD SUMMARY ====== +RMSE: 1.7838 [1.7318, 1.8468] +MAE: 1.4238 [1.3796, 1.4852] +R2: -0.3489 [-0.4146, -0.2697] + +★ Using fold 3 model for test inference +RMSE: 2.0158, MAE: 1.4913, R2: -0.2389 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.0158109357372025, 'mae': 1.4913249015808105, 'r2': -0.23889243602752686} +Test RMSE: 2.0116 (95 % CI: 1.7335–2.3415) + +Test MAE : 1.4942 (95 % CI: 1.3729–1.6222) + +Test R² : -0.2441 (95 % CI: -0.3634–-0.1405) + diff --git a/logs/bindingdb-bench/gin/gin_selfies_bindingdb_20250729_222231.txt b/logs/bindingdb-bench/gin/gin_selfies_bindingdb_20250729_222231.txt new file mode 100644 index 0000000000000000000000000000000000000000..651c854e704e9d16bcaf5a2aab66b743a941b849 --- /dev/null +++ b/logs/bindingdb-bench/gin/gin_selfies_bindingdb_20250729_222231.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9757 +RMSE: 1.5584, MAE: 1.2829, R2: 0.0512 + +FOLD 2/5 +GNN Train Loss: 0.9506 +RMSE: 1.4919, MAE: 1.2230, R2: 0.0243 + +FOLD 3/5 +GNN Train Loss: 0.9521 +RMSE: 1.4578, MAE: 1.2127, R2: 0.0321 + +FOLD 4/5 +GNN Train Loss: 0.9585 +RMSE: 1.5511, MAE: 1.2722, R2: 0.0301 + +FOLD 5/5 +GNN Train Loss: 0.9451 +RMSE: 1.4885, MAE: 1.2289, R2: 0.0266 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5105 [1.4769, 1.5429] +MAE: 1.2441 [1.2201, 1.2699] +R2: 0.0331 [0.0263, 0.0428] + +★ Using fold 3 model for test inference +RMSE: 1.7509, MAE: 1.3484, R2: 0.0653 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.7508875094999254, 'mae': 1.348360538482666, 'r2': 0.06534677743911743} +Test RMSE: 1.7480 (95 % CI: 1.5285–2.0136) + +Test MAE : 1.3502 (95 % CI: 1.2410–1.4656) + +Test R² : 0.0639 (95 % CI: 0.0251–0.1043) + diff --git a/logs/bindingdb-bench/gin/gin_smiles_bindingdb_20250729_221940.txt b/logs/bindingdb-bench/gin/gin_smiles_bindingdb_20250729_221940.txt new file mode 100644 index 0000000000000000000000000000000000000000..dfc477287343b73a954dfc924d0fead5047a9083 --- /dev/null +++ b/logs/bindingdb-bench/gin/gin_smiles_bindingdb_20250729_221940.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9566 +RMSE: 1.5539, MAE: 1.2913, R2: 0.0566 + +FOLD 2/5 +GNN Train Loss: 0.9461 +RMSE: 1.5077, MAE: 1.2368, R2: 0.0036 + +FOLD 3/5 +GNN Train Loss: 0.9587 +RMSE: 1.4572, MAE: 1.2110, R2: 0.0330 + +FOLD 4/5 +GNN Train Loss: 0.9732 +RMSE: 1.5450, MAE: 1.2673, R2: 0.0377 + +FOLD 5/5 +GNN Train Loss: 0.9620 +RMSE: 1.4862, MAE: 1.2299, R2: 0.0296 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5106 [1.4789, 1.5393] +MAE: 1.2471 [1.2237, 1.2721] +R2: 0.0316 [0.0163, 0.0458] + +★ Using fold 3 model for test inference +RMSE: 1.7594, MAE: 1.3573, R2: 0.0563 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.7593861635440051, 'mae': 1.357285499572754, 'r2': 0.05625122785568237} +Test RMSE: 1.7566 (95 % CI: 1.5319–2.0345) + +Test MAE : 1.3585 (95 % CI: 1.2572–1.4668) + +Test R² : 0.0538 (95 % CI: 0.0184–0.0879) + diff --git a/logs/bindingdb-bench/gp+tanimoto/gp_ecfp_bindingdb_20250729_222309.txt b/logs/bindingdb-bench/gp+tanimoto/gp_ecfp_bindingdb_20250729_222309.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f2644d0fcefbac74e6f6c39332acefb1ccf44b3 --- /dev/null +++ b/logs/bindingdb-bench/gp+tanimoto/gp_ecfp_bindingdb_20250729_222309.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on bindingdb + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5326, MAE: 1.2571, R2: 0.0823 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.4593, MAE: 1.1720, R2: 0.0665 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.3997, MAE: 1.1361, R2: 0.1077 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5166, MAE: 1.2414, R2: 0.0728 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.4447, MAE: 1.2015, R2: 0.0831 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4713 [1.4267, 1.5118] +MAE: 1.2018 [1.1635, 1.2397] +R2: 0.0824 [0.0722, 0.0958] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 1.7011, MAE: 1.2663, R2: 0.1177 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.7011460718590876, 'mae': 1.2663183300531364, 'r2': 0.11769805958162904} +Test RMSE: 1.6921 (95 % CI: 1.4672–1.9761) + +Test MAE : 1.2645 (95 % CI: 1.1611–1.3713) + +Test R² : 0.1160 (95 % CI: 0.0714–0.1646) + diff --git a/logs/bindingdb-bench/gp+tanimoto/gp_selfies_bindingdb_20250729_222201.txt b/logs/bindingdb-bench/gp+tanimoto/gp_selfies_bindingdb_20250729_222201.txt new file mode 100644 index 0000000000000000000000000000000000000000..aad88fd578aa0bef2f9fe5420b01a237b6396123 --- /dev/null +++ b/logs/bindingdb-bench/gp+tanimoto/gp_selfies_bindingdb_20250729_222201.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on bindingdb + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.6027, MAE: 1.3185, R2: -0.0035 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5107, MAE: 1.2320, R2: -0.0004 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5007, MAE: 1.2661, R2: -0.0257 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5753, MAE: 1.2975, R2: -0.0004 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5153, MAE: 1.2604, R2: -0.0087 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5400 [1.5085, 1.5768] +MAE: 1.2753 [1.2501, 1.3017] +R2: -0.0077 [-0.0172, -0.0010] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 1.8114, MAE: 1.3790, R2: -0.0003 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.8113702712418467, 'mae': 1.3790373572231982, 'r2': -0.00034197488555598454} +Test RMSE: 1.8034 (95 % CI: 1.5761–2.0769) + +Test MAE : 1.3793 (95 % CI: 1.2702–1.4972) + +Test R² : -0.0028 (95 % CI: -0.0139–-0.0000) + diff --git a/logs/bindingdb-bench/gp+tanimoto/gp_smiles_bindingdb_20250729_222035.txt b/logs/bindingdb-bench/gp+tanimoto/gp_smiles_bindingdb_20250729_222035.txt new file mode 100644 index 0000000000000000000000000000000000000000..dfdca50108743998b8da6bac6e4ddee0a82c1afe --- /dev/null +++ b/logs/bindingdb-bench/gp+tanimoto/gp_smiles_bindingdb_20250729_222035.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on bindingdb + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5326, MAE: 1.2571, R2: 0.0823 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.4593, MAE: 1.1720, R2: 0.0665 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.3997, MAE: 1.1361, R2: 0.1077 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5166, MAE: 1.2414, R2: 0.0728 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.4447, MAE: 1.2015, R2: 0.0831 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4717 [1.4325, 1.5118] +MAE: 1.2009 [1.1635, 1.2370] +R2: 0.0824 [0.0722, 0.0945] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 1.7011, MAE: 1.2663, R2: 0.1177 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.7011460718590876, 'mae': 1.2663183300531364, 'r2': 0.11769805958162904} +Test RMSE: 1.6945 (95 % CI: 1.4576–1.9855) + +Test MAE : 1.2650 (95 % CI: 1.1628–1.3742) + +Test R² : 0.1167 (95 % CI: 0.0702–0.1678) + diff --git a/logs/bindingdb-bench/sage/sage_ecfp_bindingdb_20250729_222033.txt b/logs/bindingdb-bench/sage/sage_ecfp_bindingdb_20250729_222033.txt new file mode 100644 index 0000000000000000000000000000000000000000..4bca44b951e9cb41022936ab60a23828128e19b5 --- /dev/null +++ b/logs/bindingdb-bench/sage/sage_ecfp_bindingdb_20250729_222033.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.0328 +RMSE: 2.0164, MAE: 1.5621, R2: -0.5885 + +FOLD 2/5 +GNN Train Loss: 0.0291 +RMSE: 2.0527, MAE: 1.6329, R2: -0.8471 + +FOLD 3/5 +GNN Train Loss: 0.0314 +RMSE: 1.9125, MAE: 1.5087, R2: -0.6659 + +FOLD 4/5 +GNN Train Loss: 0.0254 +RMSE: 2.0702, MAE: 1.6654, R2: -0.7277 + +FOLD 5/5 +GNN Train Loss: 0.0349 +RMSE: 2.0278, MAE: 1.6167, R2: -0.8065 + +====== K-FOLD SUMMARY ====== +RMSE: 2.0157 [1.9613, 2.0563] +MAE: 1.5984 [1.5506, 1.6427] +R2: -0.7272 [-0.8028, -0.6442] + +★ Using fold 3 model for test inference +RMSE: 2.1999, MAE: 1.6335, R2: -0.4755 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1999243896669416, 'mae': 1.6334670782089233, 'r2': -0.47553515434265137} +Test RMSE: 2.1945 (95 % CI: 1.9240–2.5469) + +Test MAE : 1.6303 (95 % CI: 1.4934–1.7703) + +Test R² : -0.4847 (95 % CI: -0.6705–-0.3110) + diff --git a/logs/bindingdb-bench/sage/sage_selfies_bindingdb_20250729_222351.txt b/logs/bindingdb-bench/sage/sage_selfies_bindingdb_20250729_222351.txt new file mode 100644 index 0000000000000000000000000000000000000000..6641a5ef837f71c34ff3dc2bb14f608fd3aeaebc --- /dev/null +++ b/logs/bindingdb-bench/sage/sage_selfies_bindingdb_20250729_222351.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9560 +RMSE: 1.5570, MAE: 1.2700, R2: 0.0528 + +FOLD 2/5 +GNN Train Loss: 0.9405 +RMSE: 1.5295, MAE: 1.2208, R2: -0.0255 + +FOLD 3/5 +GNN Train Loss: 0.9346 +RMSE: 1.4611, MAE: 1.2000, R2: 0.0277 + +FOLD 4/5 +GNN Train Loss: 0.9611 +RMSE: 1.5587, MAE: 1.2779, R2: 0.0205 + +FOLD 5/5 +GNN Train Loss: 0.9435 +RMSE: 1.5036, MAE: 1.2408, R2: 0.0068 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5221 [1.4866, 1.5522] +MAE: 1.2423 [1.2167, 1.2673] +R2: 0.0164 [-0.0084, 0.0372] + +★ Using fold 3 model for test inference +RMSE: 1.9238, MAE: 1.3998, R2: -0.1283 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.9237669029757383, 'mae': 1.399815320968628, 'r2': -0.12833726406097412} +Test RMSE: 1.9251 (95 % CI: 1.6046–2.2936) + +Test MAE : 1.4001 (95 % CI: 1.2816–1.5341) + +Test R² : -0.1460 (95 % CI: -0.5350–0.0634) + diff --git a/logs/bindingdb-bench/sage/sage_smiles_bindingdb_20250729_222323.txt b/logs/bindingdb-bench/sage/sage_smiles_bindingdb_20250729_222323.txt new file mode 100644 index 0000000000000000000000000000000000000000..88bd0e051822001cb4f5b4cae7ec1395fb5a7e13 --- /dev/null +++ b/logs/bindingdb-bench/sage/sage_smiles_bindingdb_20250729_222323.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.9626 +RMSE: 1.5762, MAE: 1.2768, R2: 0.0294 + +FOLD 2/5 +GNN Train Loss: 0.9599 +RMSE: 1.4857, MAE: 1.2226, R2: 0.0324 + +FOLD 3/5 +GNN Train Loss: 0.9573 +RMSE: 1.5084, MAE: 1.2550, R2: -0.0363 + +FOLD 4/5 +GNN Train Loss: 0.9554 +RMSE: 1.5206, MAE: 1.2468, R2: 0.0679 + +FOLD 5/5 +GNN Train Loss: 0.9811 +RMSE: 1.4882, MAE: 1.2327, R2: 0.0270 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5162 [1.4912, 1.5474] +MAE: 1.2469 [1.2311, 1.2637] +R2: 0.0243 [-0.0094, 0.0526] + +★ Using fold 2 model for test inference +RMSE: 1.8698, MAE: 1.3790, R2: -0.0659 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.8697623531271643, 'mae': 1.378983497619629, 'r2': -0.06587648391723633} +Test RMSE: 1.8614 (95 % CI: 1.5443–2.2311) + +Test MAE : 1.3816 (95 % CI: 1.2602–1.5166) + +Test R² : -0.0690 (95 % CI: -0.3854–0.0891) + diff --git a/logs/boilingpoint-bench/gat/gat_ecfp_boilingpoint_20250729_203205.txt b/logs/boilingpoint-bench/gat/gat_ecfp_boilingpoint_20250729_203205.txt new file mode 100644 index 0000000000000000000000000000000000000000..ba8202fc76dc3b7052f461972fe0c55719e0fa24 --- /dev/null +++ b/logs/boilingpoint-bench/gat/gat_ecfp_boilingpoint_20250729_203205.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.0372 +RMSE: 78.0904, MAE: 59.8778, R2: 0.1586 + +FOLD 2/5 +GNN Train Loss: 0.0377 +RMSE: 73.4101, MAE: 55.4288, R2: 0.1515 + +FOLD 3/5 +GNN Train Loss: 0.0352 +RMSE: 81.4680, MAE: 61.1589, R2: -0.0629 + +FOLD 4/5 +GNN Train Loss: 0.0368 +RMSE: 78.6284, MAE: 60.3925, R2: 0.1403 + +FOLD 5/5 +GNN Train Loss: 0.0361 +RMSE: 76.6873, MAE: 57.9401, R2: 0.0824 + +====== K-FOLD SUMMARY ====== +RMSE: 77.6151 [75.1092, 79.8363] +MAE: 58.9168 [57.0736, 60.5961] +R2: 0.0932 [0.0206, 0.1535] + +★ Using fold 2 model for test inference +RMSE: 73.2012, MAE: 53.8653, R2: 0.1487 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 73.20124564022971, 'mae': 53.865325927734375, 'r2': 0.14870458841323853} +Test RMSE: 73.1437 (95 % CI: 66.4370–79.6764) + +Test MAE : 53.9304 (95 % CI: 49.2536–58.6133) + +Test R² : 0.1413 (95 % CI: -0.0589–0.3178) + diff --git a/logs/boilingpoint-bench/gat/gat_selfies_boilingpoint_20250729_203550.txt b/logs/boilingpoint-bench/gat/gat_selfies_boilingpoint_20250729_203550.txt new file mode 100644 index 0000000000000000000000000000000000000000..70c97372b6f987af64500fd7fe77ff0855243c87 --- /dev/null +++ b/logs/boilingpoint-bench/gat/gat_selfies_boilingpoint_20250729_203550.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.5480 +RMSE: 60.5901, MAE: 45.4457, R2: 0.4934 + +FOLD 2/5 +GNN Train Loss: 0.5361 +RMSE: 57.2543, MAE: 43.9552, R2: 0.4839 + +FOLD 3/5 +GNN Train Loss: 0.5523 +RMSE: 61.2499, MAE: 48.2317, R2: 0.3992 + +FOLD 4/5 +GNN Train Loss: 0.5518 +RMSE: 63.1904, MAE: 50.3941, R2: 0.4447 + +FOLD 5/5 +GNN Train Loss: 0.5393 +RMSE: 59.8413, MAE: 46.9372, R2: 0.4413 + +====== K-FOLD SUMMARY ====== +RMSE: 60.3947 [58.5886, 62.0261] +MAE: 46.9671 [45.1086, 48.8377] +R2: 0.4525 [0.4244, 0.4799] + +★ Using fold 2 model for test inference +RMSE: 60.1515, MAE: 44.2776, R2: 0.4252 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 60.15153796480394, 'mae': 44.277584075927734, 'r2': 0.42517346143722534} +Test RMSE: 60.0938 (95 % CI: 55.3119–65.2983) + +Test MAE : 44.2603 (95 % CI: 40.3585–48.2360) + +Test R² : 0.4214 (95 % CI: 0.3193–0.5124) + diff --git a/logs/boilingpoint-bench/gat/gat_smiles_boilingpoint_20250729_203403.txt b/logs/boilingpoint-bench/gat/gat_smiles_boilingpoint_20250729_203403.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c91c06dd4afff2ea5a037d44b5d9d3f4ed276c9 --- /dev/null +++ b/logs/boilingpoint-bench/gat/gat_smiles_boilingpoint_20250729_203403.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.5855 +RMSE: 64.2889, MAE: 49.0046, R2: 0.4297 + +FOLD 2/5 +GNN Train Loss: 0.5581 +RMSE: 57.9930, MAE: 45.2234, R2: 0.4705 + +FOLD 3/5 +GNN Train Loss: 0.5310 +RMSE: 60.6374, MAE: 46.3484, R2: 0.4111 + +FOLD 4/5 +GNN Train Loss: 0.5936 +RMSE: 64.7461, MAE: 50.0246, R2: 0.4171 + +FOLD 5/5 +GNN Train Loss: 0.5310 +RMSE: 59.6839, MAE: 46.2362, R2: 0.4442 + +====== K-FOLD SUMMARY ====== +RMSE: 61.4943 [59.1983, 63.7415] +MAE: 47.3780 [45.8535, 49.0629] +R2: 0.4344 [0.4172, 0.4545] + +★ Using fold 2 model for test inference +RMSE: 60.1759, MAE: 45.0453, R2: 0.4247 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 60.17590385110036, 'mae': 45.045310974121094, 'r2': 0.42470771074295044} +Test RMSE: 60.0681 (95 % CI: 55.2129–64.6316) + +Test MAE : 45.0223 (95 % CI: 41.2615–48.9794) + +Test R² : 0.4230 (95 % CI: 0.3270–0.5052) + diff --git a/logs/boilingpoint-bench/gcn/gcn_ecfp_boilingpoint_20250729_203043.txt b/logs/boilingpoint-bench/gcn/gcn_ecfp_boilingpoint_20250729_203043.txt new file mode 100644 index 0000000000000000000000000000000000000000..e03480cf5da08d0f3f1ced94e5ed1f9bbec7f648 --- /dev/null +++ b/logs/boilingpoint-bench/gcn/gcn_ecfp_boilingpoint_20250729_203043.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.0470 +RMSE: 69.8726, MAE: 53.8127, R2: 0.3264 + +FOLD 2/5 +GNN Train Loss: 0.0486 +RMSE: 67.2414, MAE: 51.5744, R2: 0.2881 + +FOLD 3/5 +GNN Train Loss: 0.0362 +RMSE: 70.1854, MAE: 52.7899, R2: 0.2111 + +FOLD 4/5 +GNN Train Loss: 0.0440 +RMSE: 67.9179, MAE: 51.5008, R2: 0.3585 + +FOLD 5/5 +GNN Train Loss: 0.0375 +RMSE: 69.9591, MAE: 52.5685, R2: 0.2363 + +====== K-FOLD SUMMARY ====== +RMSE: 69.0227 [67.9029, 70.0150] +MAE: 52.4433 [51.7438, 53.1549] +R2: 0.2834 [0.2342, 0.3328] + +★ Using fold 2 model for test inference +RMSE: 63.2932, MAE: 48.2241, R2: 0.3636 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 63.29316438765821, 'mae': 48.22407531738281, 'r2': 0.3635607361793518} +Test RMSE: 63.2157 (95 % CI: 58.1825–68.3604) + +Test MAE : 48.2488 (95 % CI: 44.3807–52.2295) + +Test R² : 0.3593 (95 % CI: 0.2320–0.4740) + diff --git a/logs/boilingpoint-bench/gcn/gcn_selfies_boilingpoint_20250729_203020.txt b/logs/boilingpoint-bench/gcn/gcn_selfies_boilingpoint_20250729_203020.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f675b2548ce792b172d64cbd392da4415003225 --- /dev/null +++ b/logs/boilingpoint-bench/gcn/gcn_selfies_boilingpoint_20250729_203020.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.6891 +RMSE: 70.8493, MAE: 55.3658, R2: 0.3074 + +FOLD 2/5 +GNN Train Loss: 0.6556 +RMSE: 62.1160, MAE: 48.2950, R2: 0.3925 + +FOLD 3/5 +GNN Train Loss: 0.6699 +RMSE: 68.5904, MAE: 53.2266, R2: 0.2466 + +FOLD 4/5 +GNN Train Loss: 0.6793 +RMSE: 69.4785, MAE: 54.0070, R2: 0.3287 + +FOLD 5/5 +GNN Train Loss: 0.6874 +RMSE: 65.0235, MAE: 52.3577, R2: 0.3403 + +====== K-FOLD SUMMARY ====== +RMSE: 67.2630 [63.9924, 69.9457] +MAE: 52.6087 [50.2672, 54.3969] +R2: 0.3234 [0.2817, 0.3650] + +★ Using fold 2 model for test inference +RMSE: 66.4703, MAE: 50.7398, R2: 0.2981 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 66.47025959146127, 'mae': 50.739803314208984, 'r2': 0.2980630397796631} +Test RMSE: 66.5821 (95 % CI: 61.4342–71.4562) + +Test MAE : 50.7737 (95 % CI: 46.6584–55.0369) + +Test R² : 0.2949 (95 % CI: 0.1982–0.3747) + diff --git a/logs/boilingpoint-bench/gcn/gcn_smiles_boilingpoint_20250729_202944.txt b/logs/boilingpoint-bench/gcn/gcn_smiles_boilingpoint_20250729_202944.txt new file mode 100644 index 0000000000000000000000000000000000000000..0a960b2c9127515825f0f93fb1b51babb4e5678d --- /dev/null +++ b/logs/boilingpoint-bench/gcn/gcn_smiles_boilingpoint_20250729_202944.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.7120 +RMSE: 71.0407, MAE: 55.0565, R2: 0.3036 + +FOLD 2/5 +GNN Train Loss: 0.6757 +RMSE: 62.9607, MAE: 48.5271, R2: 0.3759 + +FOLD 3/5 +GNN Train Loss: 0.6704 +RMSE: 69.8276, MAE: 51.9118, R2: 0.2191 + +FOLD 4/5 +GNN Train Loss: 0.6836 +RMSE: 69.9763, MAE: 54.3068, R2: 0.3191 + +FOLD 5/5 +GNN Train Loss: 0.7002 +RMSE: 65.4859, MAE: 51.0074, R2: 0.3309 + +====== K-FOLD SUMMARY ====== +RMSE: 67.9077 [65.0764, 70.3723] +MAE: 52.2176 [50.1791, 54.1277] +R2: 0.3104 [0.2615, 0.3524] + +★ Using fold 2 model for test inference +RMSE: 68.8002, MAE: 52.4742, R2: 0.2480 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 68.80023022990184, 'mae': 52.474151611328125, 'r2': 0.24799084663391113} +Test RMSE: 68.6942 (95 % CI: 63.6000–73.7829) + +Test MAE : 52.5543 (95 % CI: 48.4512–56.9878) + +Test R² : 0.2454 (95 % CI: 0.1304–0.3379) + diff --git a/logs/boilingpoint-bench/gin/gin_ecfp_boilingpoint_20250729_203257.txt b/logs/boilingpoint-bench/gin/gin_ecfp_boilingpoint_20250729_203257.txt new file mode 100644 index 0000000000000000000000000000000000000000..fe6c3133219982636c104763ddedf36180c5df23 --- /dev/null +++ b/logs/boilingpoint-bench/gin/gin_ecfp_boilingpoint_20250729_203257.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.0113 +RMSE: 61.3718, MAE: 47.1698, R2: 0.4803 + +FOLD 2/5 +GNN Train Loss: 0.0104 +RMSE: 61.6748, MAE: 47.0310, R2: 0.4011 + +FOLD 3/5 +GNN Train Loss: 0.0118 +RMSE: 66.8881, MAE: 49.5290, R2: 0.2835 + +FOLD 4/5 +GNN Train Loss: 0.0142 +RMSE: 62.8507, MAE: 46.8086, R2: 0.4507 + +FOLD 5/5 +GNN Train Loss: 0.0101 +RMSE: 62.9604, MAE: 47.0711, R2: 0.3815 + +====== K-FOLD SUMMARY ====== +RMSE: 63.1586 [61.7501, 65.0599] +MAE: 47.5227 [46.9333, 48.5458] +R2: 0.3993 [0.3365, 0.4546] + +★ Using fold 1 model for test inference +RMSE: 59.5519, MAE: 44.7449, R2: 0.4366 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 59.55186035940124, 'mae': 44.744850158691406, 'r2': 0.4365777373313904} +Test RMSE: 59.5471 (95 % CI: 54.6784–64.8380) + +Test MAE : 44.7224 (95 % CI: 40.9831–48.9338) + +Test R² : 0.4339 (95 % CI: 0.3280–0.5305) + diff --git a/logs/boilingpoint-bench/gin/gin_selfies_boilingpoint_20250729_203129.txt b/logs/boilingpoint-bench/gin/gin_selfies_boilingpoint_20250729_203129.txt new file mode 100644 index 0000000000000000000000000000000000000000..9fc3c9c043cc4336c67f9129449daef32d69b22c --- /dev/null +++ b/logs/boilingpoint-bench/gin/gin_selfies_boilingpoint_20250729_203129.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.7156 +RMSE: 72.8064, MAE: 56.4089, R2: 0.2686 + +FOLD 2/5 +GNN Train Loss: 0.7301 +RMSE: 64.2829, MAE: 49.2077, R2: 0.3494 + +FOLD 3/5 +GNN Train Loss: 0.7157 +RMSE: 71.0719, MAE: 56.1007, R2: 0.1911 + +FOLD 4/5 +GNN Train Loss: 0.7229 +RMSE: 73.4997, MAE: 57.8782, R2: 0.2488 + +FOLD 5/5 +GNN Train Loss: 0.6998 +RMSE: 65.7907, MAE: 52.6860, R2: 0.3246 + +====== K-FOLD SUMMARY ====== +RMSE: 69.4469 [66.2409, 72.5982] +MAE: 54.4603 [51.3436, 56.9349] +R2: 0.2750 [0.2293, 0.3233] + +★ Using fold 2 model for test inference +RMSE: 72.1316, MAE: 54.6580, R2: 0.1734 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 72.13157668780539, 'mae': 54.6579704284668, 'r2': 0.1734023094177246} +Test RMSE: 72.0029 (95 % CI: 66.4804–77.3895) + +Test MAE : 54.6066 (95 % CI: 50.2223–59.4431) + +Test R² : 0.1692 (95 % CI: 0.0452–0.2750) + diff --git a/logs/boilingpoint-bench/gin/gin_smiles_boilingpoint_20250729_203225.txt b/logs/boilingpoint-bench/gin/gin_smiles_boilingpoint_20250729_203225.txt new file mode 100644 index 0000000000000000000000000000000000000000..cbe4f13c252290560356b18dbb963c2c75fb6b3a --- /dev/null +++ b/logs/boilingpoint-bench/gin/gin_smiles_boilingpoint_20250729_203225.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.7016 +RMSE: 70.4793, MAE: 54.6593, R2: 0.3146 + +FOLD 2/5 +GNN Train Loss: 0.7170 +RMSE: 67.9560, MAE: 53.4831, R2: 0.2729 + +FOLD 3/5 +GNN Train Loss: 0.7029 +RMSE: 69.0791, MAE: 52.5093, R2: 0.2358 + +FOLD 4/5 +GNN Train Loss: 0.7063 +RMSE: 74.6538, MAE: 59.3849, R2: 0.2250 + +FOLD 5/5 +GNN Train Loss: 0.7017 +RMSE: 69.9189, MAE: 55.1017, R2: 0.2372 + +====== K-FOLD SUMMARY ====== +RMSE: 70.4272 [68.7411, 72.7039] +MAE: 55.0484 [53.3288, 57.3479] +R2: 0.2564 [0.2315, 0.2905] + +★ Using fold 2 model for test inference +RMSE: 70.1267, MAE: 55.1206, R2: 0.2187 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 70.12669199161971, 'mae': 55.12058639526367, 'r2': 0.21871399879455566} +Test RMSE: 70.0021 (95 % CI: 65.2385–75.2084) + +Test MAE : 55.1386 (95 % CI: 50.7973–59.3468) + +Test R² : 0.2164 (95 % CI: 0.1404–0.2809) + diff --git a/logs/boilingpoint-bench/gp/gp_ecfp_boilingpoint_20250729_203452.txt b/logs/boilingpoint-bench/gp/gp_ecfp_boilingpoint_20250729_203452.txt new file mode 100644 index 0000000000000000000000000000000000000000..476ef58f008e351586bfac12ab6387d489d368bc --- /dev/null +++ b/logs/boilingpoint-bench/gp/gp_ecfp_boilingpoint_20250729_203452.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on boilingpoint + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 51.2254, MAE: 39.2345, R2: 0.6379 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 52.2225, MAE: 39.3987, R2: 0.5706 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 54.2514, MAE: 39.7716, R2: 0.5286 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 54.9253, MAE: 39.6450, R2: 0.5805 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 54.3252, MAE: 40.4723, R2: 0.5395 + +====== K-FOLD SUMMARY ====== +RMSE: 53.3681 [52.0301, 54.5505] +MAE: 39.7083 [39.3821, 40.1414] +R2: 0.5712 [0.5412, 0.6068] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 51.6787, MAE: 37.8442, R2: 0.5757 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 51.678703654278934, 'mae': 37.844151638793946, 'r2': 0.575706353380506} +Test RMSE: 51.6225 (95 % CI: 46.8898–56.8055) + +Test MAE : 37.8647 (95 % CI: 34.5927–41.5900) + +Test R² : 0.5733 (95 % CI: 0.4894–0.6445) + diff --git a/logs/boilingpoint-bench/gp/gp_selfies_boilingpoint_20250729_203428.txt b/logs/boilingpoint-bench/gp/gp_selfies_boilingpoint_20250729_203428.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a0592fbd07487ffeaee2c863291def65ce61743 --- /dev/null +++ b/logs/boilingpoint-bench/gp/gp_selfies_boilingpoint_20250729_203428.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on boilingpoint + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 85.1317, MAE: 67.4568, R2: -0.0000 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 79.8633, MAE: 64.6445, R2: -0.0042 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 79.0686, MAE: 63.2376, R2: -0.0012 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 84.8178, MAE: 68.7179, R2: -0.0004 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 80.0615, MAE: 66.0971, R2: -0.0001 + +====== K-FOLD SUMMARY ====== +RMSE: 81.8288 [79.6247, 84.0549] +MAE: 66.0318 [64.3628, 67.6893] +R2: -0.0012 [-0.0028, -0.0001] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 79.4702, MAE: 63.4164, R2: -0.0033 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 79.47015506907266, 'mae': 63.416413952636724, 'r2': -0.003347626488782618} +Test RMSE: 79.3254 (95 % CI: 73.6080–85.3324) + +Test MAE : 63.3404 (95 % CI: 58.9658–68.1350) + +Test R² : -0.0060 (95 % CI: -0.0259–-0.0000) + diff --git a/logs/boilingpoint-bench/gp/gp_smiles_boilingpoint_20250729_203202.txt b/logs/boilingpoint-bench/gp/gp_smiles_boilingpoint_20250729_203202.txt new file mode 100644 index 0000000000000000000000000000000000000000..9c20406c1a2b2dec84ae43d4a4199c7b010d3198 --- /dev/null +++ b/logs/boilingpoint-bench/gp/gp_smiles_boilingpoint_20250729_203202.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on boilingpoint + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 51.2254, MAE: 39.2345, R2: 0.6379 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 52.2225, MAE: 39.3987, R2: 0.5706 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 54.2514, MAE: 39.7716, R2: 0.5286 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 54.9253, MAE: 39.6450, R2: 0.5805 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 54.3252, MAE: 40.4723, R2: 0.5395 + +====== K-FOLD SUMMARY ====== +RMSE: 53.3564 [52.1618, 54.5357] +MAE: 39.6968 [39.3658, 40.1174] +R2: 0.5718 [0.5392, 0.6110] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 51.6787, MAE: 37.8442, R2: 0.5757 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 51.678703654278934, 'mae': 37.844151638793946, 'r2': 0.575706353380506} +Test RMSE: 51.5120 (95 % CI: 46.3578–57.0047) + +Test MAE : 37.8171 (95 % CI: 34.4494–41.5315) + +Test R² : 0.5730 (95 % CI: 0.4979–0.6446) + diff --git a/logs/boilingpoint-bench/sage/sage_ecfp_boilingpoint_20250729_203407.txt b/logs/boilingpoint-bench/sage/sage_ecfp_boilingpoint_20250729_203407.txt new file mode 100644 index 0000000000000000000000000000000000000000..b1698395aa034b254ad73adbae13185aa1f2224b --- /dev/null +++ b/logs/boilingpoint-bench/sage/sage_ecfp_boilingpoint_20250729_203407.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.0283 +RMSE: 72.4983, MAE: 55.9575, R2: 0.2748 + +FOLD 2/5 +GNN Train Loss: 0.0258 +RMSE: 67.8160, MAE: 52.1426, R2: 0.2759 + +FOLD 3/5 +GNN Train Loss: 0.0259 +RMSE: 72.7572, MAE: 55.1328, R2: 0.1522 + +FOLD 4/5 +GNN Train Loss: 0.0384 +RMSE: 70.6124, MAE: 53.9133, R2: 0.3066 + +FOLD 5/5 +GNN Train Loss: 0.0332 +RMSE: 71.9125, MAE: 54.6514, R2: 0.1931 + +====== K-FOLD SUMMARY ====== +RMSE: 71.1310 [69.4938, 72.4847] +MAE: 54.3854 [53.2050, 55.3837] +R2: 0.2404 [0.1913, 0.2877] + +★ Using fold 2 model for test inference +RMSE: 64.4998, MAE: 47.8499, R2: 0.3391 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 64.49977289204203, 'mae': 47.84987258911133, 'r2': 0.33906352519989014} +Test RMSE: 64.4034 (95 % CI: 59.1904–69.9921) + +Test MAE : 47.8241 (95 % CI: 43.8330–52.1125) + +Test R² : 0.3353 (95 % CI: 0.1852–0.4637) + diff --git a/logs/boilingpoint-bench/sage/sage_selfies_boilingpoint_20250729_203625.txt b/logs/boilingpoint-bench/sage/sage_selfies_boilingpoint_20250729_203625.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca898b870b4d24d0b772fc66aba4aa804cf9fbb5 --- /dev/null +++ b/logs/boilingpoint-bench/sage/sage_selfies_boilingpoint_20250729_203625.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.5642 +RMSE: 65.4180, MAE: 48.0273, R2: 0.4095 + +FOLD 2/5 +GNN Train Loss: 0.5651 +RMSE: 57.4463, MAE: 44.4124, R2: 0.4804 + +FOLD 3/5 +GNN Train Loss: 0.5467 +RMSE: 62.3395, MAE: 46.2084, R2: 0.3776 + +FOLD 4/5 +GNN Train Loss: 0.5378 +RMSE: 61.8394, MAE: 47.2259, R2: 0.4682 + +FOLD 5/5 +GNN Train Loss: 0.5446 +RMSE: 61.3520, MAE: 47.5264, R2: 0.4127 + +====== K-FOLD SUMMARY ====== +RMSE: 61.7010 [59.2060, 63.9891] +MAE: 46.6665 [45.4900, 47.6666] +R2: 0.4303 [0.3974, 0.4620] + +★ Using fold 2 model for test inference +RMSE: 59.3171, MAE: 44.6586, R2: 0.4410 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 59.317103762979905, 'mae': 44.65864181518555, 'r2': 0.44101107120513916} +Test RMSE: 59.2558 (95 % CI: 54.7944–64.2917) + +Test MAE : 44.8262 (95 % CI: 40.8595–48.4985) + +Test R² : 0.4414 (95 % CI: 0.3598–0.5206) + diff --git a/logs/boilingpoint-bench/sage/sage_smiles_boilingpoint_20250729_203602.txt b/logs/boilingpoint-bench/sage/sage_smiles_boilingpoint_20250729_203602.txt new file mode 100644 index 0000000000000000000000000000000000000000..d3ae0bc6243f8606bb690d86881575daba349689 --- /dev/null +++ b/logs/boilingpoint-bench/sage/sage_smiles_boilingpoint_20250729_203602.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.5331 +RMSE: 63.2506, MAE: 48.2120, R2: 0.4480 + +FOLD 2/5 +GNN Train Loss: 0.5548 +RMSE: 58.4127, MAE: 44.2368, R2: 0.4628 + +FOLD 3/5 +GNN Train Loss: 0.5391 +RMSE: 61.6733, MAE: 47.9831, R2: 0.3909 + +FOLD 4/5 +GNN Train Loss: 0.5621 +RMSE: 62.9847, MAE: 49.5898, R2: 0.4483 + +FOLD 5/5 +GNN Train Loss: 0.5531 +RMSE: 61.2254, MAE: 49.3617, R2: 0.4151 + +====== K-FOLD SUMMARY ====== +RMSE: 61.4661 [59.8896, 62.8288] +MAE: 47.8889 [46.0567, 49.2230] +R2: 0.4332 [0.4101, 0.4541] + +★ Using fold 2 model for test inference +RMSE: 62.1058, MAE: 46.6291, R2: 0.3872 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 62.105754611463944, 'mae': 46.62908172607422, 'r2': 0.38721656799316406} +Test RMSE: 62.0991 (95 % CI: 57.4973–66.8543) + +Test MAE : 46.6419 (95 % CI: 42.6169–50.7307) + +Test R² : 0.3800 (95 % CI: 0.2681–0.4690) + diff --git a/logs/esol-bench/gat/gat_ecfp_esol_20250729_145423.txt b/logs/esol-bench/gat/gat_ecfp_esol_20250729_145423.txt new file mode 100644 index 0000000000000000000000000000000000000000..cc9585ec210101580eea254393253f0ec33c01de --- /dev/null +++ b/logs/esol-bench/gat/gat_ecfp_esol_20250729_145423.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on esol + +FOLD 1/5 +GNN Train Loss: 0.0286 +RMSE: 1.3150, MAE: 0.9893, R2: 0.5361 + +FOLD 2/5 +GNN Train Loss: 0.0248 +RMSE: 1.3747, MAE: 1.0435, R2: 0.6461 + +FOLD 3/5 +GNN Train Loss: 0.0356 +RMSE: 1.3700, MAE: 1.0226, R2: 0.5425 + +FOLD 4/5 +GNN Train Loss: 0.0262 +RMSE: 1.3732, MAE: 1.0522, R2: 0.5630 + +FOLD 5/5 +GNN Train Loss: 0.0375 +RMSE: 1.5337, MAE: 1.0635, R2: 0.4028 + +====== K-FOLD SUMMARY ====== +RMSE: 1.3935 [1.3386, 1.4688] +MAE: 1.0343 [1.0108, 1.0550] +R2: 0.5390 [0.4628, 0.6034] + +★ Using fold 1 model for test inference +RMSE: 1.2549, MAE: 0.9408, R2: 0.6669 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.2548568307287193, 'mae': 0.9407985806465149, 'r2': 0.6668645739555359} +Test RMSE: 1.2483 (95 % CI: 1.0970–1.4039) + +Test MAE : 0.9410 (95 % CI: 0.8366–1.0485) + +Test R² : 0.6609 (95 % CI: 0.5504–0.7524) + diff --git a/logs/esol-bench/gat/gat_selfies_esol_20250729_145312.txt b/logs/esol-bench/gat/gat_selfies_esol_20250729_145312.txt new file mode 100644 index 0000000000000000000000000000000000000000..e907e4eac397ba4809650b2b16048f3b2642b511 --- /dev/null +++ b/logs/esol-bench/gat/gat_selfies_esol_20250729_145312.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on esol + +FOLD 1/5 +GNN Train Loss: 0.4681 +RMSE: 1.4433, MAE: 1.0814, R2: 0.4411 + +FOLD 2/5 +GNN Train Loss: 0.4994 +RMSE: 1.5963, MAE: 1.2107, R2: 0.5228 + +FOLD 3/5 +GNN Train Loss: 0.4577 +RMSE: 1.3382, MAE: 1.0120, R2: 0.5635 + +FOLD 4/5 +GNN Train Loss: 0.4734 +RMSE: 1.5475, MAE: 1.1569, R2: 0.4450 + +FOLD 5/5 +GNN Train Loss: 0.4722 +RMSE: 1.3750, MAE: 1.0340, R2: 0.5200 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4588 [1.3803, 1.5447] +MAE: 1.0988 [1.0347, 1.1676] +R2: 0.4986 [0.4583, 0.5385] + +★ Using fold 3 model for test inference +RMSE: 1.5715, MAE: 1.1439, R2: 0.4776 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5714631680606348, 'mae': 1.1439266204833984, 'r2': 0.4775546193122864} +Test RMSE: 1.5646 (95 % CI: 1.3700–1.7417) + +Test MAE : 1.1441 (95 % CI: 1.0098–1.2837) + +Test R² : 0.4769 (95 % CI: 0.3827–0.5666) + diff --git a/logs/esol-bench/gat/gat_smiles_esol_20250729_145203.txt b/logs/esol-bench/gat/gat_smiles_esol_20250729_145203.txt new file mode 100644 index 0000000000000000000000000000000000000000..0d5ca5d86adeaff6d73ae2d09a8bb42d25257162 --- /dev/null +++ b/logs/esol-bench/gat/gat_smiles_esol_20250729_145203.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on esol + +FOLD 1/5 +GNN Train Loss: 0.4349 +RMSE: 1.3426, MAE: 1.0463, R2: 0.5164 + +FOLD 2/5 +GNN Train Loss: 0.4577 +RMSE: 1.5814, MAE: 1.2004, R2: 0.5317 + +FOLD 3/5 +GNN Train Loss: 0.5187 +RMSE: 1.3590, MAE: 1.0256, R2: 0.5498 + +FOLD 4/5 +GNN Train Loss: 0.4773 +RMSE: 1.4368, MAE: 1.1037, R2: 0.5216 + +FOLD 5/5 +GNN Train Loss: 0.5247 +RMSE: 1.3672, MAE: 1.0055, R2: 0.5254 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4159 [1.3541, 1.4957] +MAE: 1.0783 [1.0217, 1.1424] +R2: 0.5290 [0.5203, 0.5401] + +★ Using fold 1 model for test inference +RMSE: 1.5168, MAE: 1.1519, R2: 0.5133 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5167663838369498, 'mae': 1.1519267559051514, 'r2': 0.5132904648780823} +Test RMSE: 1.5192 (95 % CI: 1.3508–1.6987) + +Test MAE : 1.1516 (95 % CI: 1.0302–1.2876) + +Test R² : 0.5080 (95 % CI: 0.4151–0.5932) + diff --git a/logs/esol-bench/gcn/gcn_ecfp_esol_20250729_145352.txt b/logs/esol-bench/gcn/gcn_ecfp_esol_20250729_145352.txt new file mode 100644 index 0000000000000000000000000000000000000000..17b615357f2417d414504f26614beba826107da1 --- /dev/null +++ b/logs/esol-bench/gcn/gcn_ecfp_esol_20250729_145352.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on esol + +FOLD 1/5 +GNN Train Loss: 0.0288 +RMSE: 1.2406, MAE: 0.9308, R2: 0.5871 + +FOLD 2/5 +GNN Train Loss: 0.0282 +RMSE: 1.2970, MAE: 0.9768, R2: 0.6850 + +FOLD 3/5 +GNN Train Loss: 0.0390 +RMSE: 1.2943, MAE: 0.9921, R2: 0.5917 + +FOLD 4/5 +GNN Train Loss: 0.0277 +RMSE: 1.3241, MAE: 1.0180, R2: 0.5937 + +FOLD 5/5 +GNN Train Loss: 0.0347 +RMSE: 1.4515, MAE: 0.9953, R2: 0.4651 + +====== K-FOLD SUMMARY ====== +RMSE: 1.3202 [1.2686, 1.3891] +MAE: 0.9825 [0.9553, 1.0046] +R2: 0.5837 [0.5158, 0.6467] + +★ Using fold 1 model for test inference +RMSE: 1.1665, MAE: 0.8822, R2: 0.7121 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1664995630118757, 'mae': 0.8821554183959961, 'r2': 0.7121264934539795} +Test RMSE: 1.1634 (95 % CI: 1.0428–1.2933) + +Test MAE : 0.8822 (95 % CI: 0.7864–0.9841) + +Test R² : 0.7075 (95 % CI: 0.6227–0.7777) + diff --git a/logs/esol-bench/gcn/gcn_selfies_esol_20250729_145244.txt b/logs/esol-bench/gcn/gcn_selfies_esol_20250729_145244.txt new file mode 100644 index 0000000000000000000000000000000000000000..34cc4b5e237dcdabb189283e4c2ad2328ee1cd80 --- /dev/null +++ b/logs/esol-bench/gcn/gcn_selfies_esol_20250729_145244.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on esol + +FOLD 1/5 +GNN Train Loss: 0.5513 +RMSE: 1.5536, MAE: 1.2417, R2: 0.3525 + +FOLD 2/5 +GNN Train Loss: 0.5781 +RMSE: 1.7409, MAE: 1.3704, R2: 0.4324 + +FOLD 3/5 +GNN Train Loss: 0.6017 +RMSE: 1.5079, MAE: 1.1737, R2: 0.4458 + +FOLD 4/5 +GNN Train Loss: 0.5735 +RMSE: 1.5705, MAE: 1.1965, R2: 0.4284 + +FOLD 5/5 +GNN Train Loss: 0.5804 +RMSE: 1.4975, MAE: 1.1340, R2: 0.4307 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5748 [1.5129, 1.6581] +MAE: 1.2238 [1.1623, 1.3008] +R2: 0.4182 [0.3837, 0.4393] + +★ Using fold 5 model for test inference +RMSE: 1.6892, MAE: 1.3041, R2: 0.3964 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.6891670469946387, 'mae': 1.304105281829834, 'r2': 0.39636051654815674} +Test RMSE: 1.6861 (95 % CI: 1.4984–1.8634) + +Test MAE : 1.3087 (95 % CI: 1.1733–1.4496) + +Test R² : 0.3904 (95 % CI: 0.2908–0.4751) + diff --git a/logs/esol-bench/gcn/gcn_smiles_esol_20250729_145143.txt b/logs/esol-bench/gcn/gcn_smiles_esol_20250729_145143.txt new file mode 100644 index 0000000000000000000000000000000000000000..00870fc3bae1c32771ba2287c2cf61ddd4609584 --- /dev/null +++ b/logs/esol-bench/gcn/gcn_smiles_esol_20250729_145143.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on esol + +FOLD 1/5 +GNN Train Loss: 0.5948 +RMSE: 1.6331, MAE: 1.3225, R2: 0.2846 + +FOLD 2/5 +GNN Train Loss: 0.5538 +RMSE: 1.7125, MAE: 1.3444, R2: 0.4508 + +FOLD 3/5 +GNN Train Loss: 0.5904 +RMSE: 1.4784, MAE: 1.1700, R2: 0.4672 + +FOLD 4/5 +GNN Train Loss: 0.5632 +RMSE: 1.5437, MAE: 1.2003, R2: 0.4478 + +FOLD 5/5 +GNN Train Loss: 0.5981 +RMSE: 1.5661, MAE: 1.2264, R2: 0.3774 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5872 [1.5176, 1.6629] +MAE: 1.2518 [1.1934, 1.3120] +R2: 0.4077 [0.3502, 0.4562] + +★ Using fold 3 model for test inference +RMSE: 1.7204, MAE: 1.3145, R2: 0.3738 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.720409008787294, 'mae': 1.314476490020752, 'r2': 0.3738247752189636} +Test RMSE: 1.7133 (95 % CI: 1.5338–1.8989) + +Test MAE : 1.3146 (95 % CI: 1.1789–1.4578) + +Test R² : 0.3716 (95 % CI: 0.2770–0.4566) + diff --git a/logs/esol-bench/gin/gin_ecfp_esol_20250729_145407.txt b/logs/esol-bench/gin/gin_ecfp_esol_20250729_145407.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9204123790e0df9d7de5f378ff03e14fe01e90b --- /dev/null +++ b/logs/esol-bench/gin/gin_ecfp_esol_20250729_145407.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on esol + +FOLD 1/5 +GNN Train Loss: 0.0212 +RMSE: 1.1588, MAE: 0.8814, R2: 0.6397 + +FOLD 2/5 +GNN Train Loss: 0.0279 +RMSE: 1.2718, MAE: 0.9532, R2: 0.6971 + +FOLD 3/5 +GNN Train Loss: 0.0306 +RMSE: 1.1992, MAE: 0.9184, R2: 0.6494 + +FOLD 4/5 +GNN Train Loss: 0.0260 +RMSE: 1.2563, MAE: 0.9668, R2: 0.6343 + +FOLD 5/5 +GNN Train Loss: 0.0304 +RMSE: 1.2068, MAE: 0.9033, R2: 0.6303 + +====== K-FOLD SUMMARY ====== +RMSE: 1.2179 [1.1780, 1.2526] +MAE: 0.9248 [0.8975, 0.9517] +R2: 0.6509 [0.6346, 0.6742] + +★ Using fold 1 model for test inference +RMSE: 1.1527, MAE: 0.8547, R2: 0.7189 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1526609856962138, 'mae': 0.8547297120094299, 'r2': 0.7189162969589233} +Test RMSE: 1.1526 (95 % CI: 1.0244–1.2798) + +Test MAE : 0.8507 (95 % CI: 0.7494–0.9578) + +Test R² : 0.7176 (95 % CI: 0.6432–0.7810) + diff --git a/logs/esol-bench/gin/gin_selfies_esol_20250729_145259.txt b/logs/esol-bench/gin/gin_selfies_esol_20250729_145259.txt new file mode 100644 index 0000000000000000000000000000000000000000..5e45b8975067212f4d25ac322924d76d80bcd8d4 --- /dev/null +++ b/logs/esol-bench/gin/gin_selfies_esol_20250729_145259.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on esol + +FOLD 1/5 +GNN Train Loss: 0.5128 +RMSE: 1.4865, MAE: 1.1794, R2: 0.4072 + +FOLD 2/5 +GNN Train Loss: 0.6342 +RMSE: 1.7253, MAE: 1.3798, R2: 0.4426 + +FOLD 3/5 +GNN Train Loss: 0.5812 +RMSE: 1.4307, MAE: 1.1665, R2: 0.5010 + +FOLD 4/5 +GNN Train Loss: 0.5527 +RMSE: 1.5812, MAE: 1.2413, R2: 0.4206 + +FOLD 5/5 +GNN Train Loss: 0.5530 +RMSE: 1.4627, MAE: 1.0820, R2: 0.4568 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5374 [1.4547, 1.6440] +MAE: 1.2104 [1.1333, 1.3094] +R2: 0.4459 [0.4197, 0.4735] + +★ Using fold 3 model for test inference +RMSE: 1.6573, MAE: 1.2684, R2: 0.4190 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.6572543284080146, 'mae': 1.2683876752853394, 'r2': 0.41895365715026855} +Test RMSE: 1.6538 (95 % CI: 1.4624–1.8395) + +Test MAE : 1.2690 (95 % CI: 1.1350–1.4204) + +Test R² : 0.4174 (95 % CI: 0.3147–0.5086) + diff --git a/logs/esol-bench/gin/gin_smiles_esol_20250729_145147.txt b/logs/esol-bench/gin/gin_smiles_esol_20250729_145147.txt new file mode 100644 index 0000000000000000000000000000000000000000..adcc5e504058c7ade8d9d2a125b30467cd38e8fb --- /dev/null +++ b/logs/esol-bench/gin/gin_smiles_esol_20250729_145147.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on esol + +FOLD 1/5 +GNN Train Loss: 0.5372 +RMSE: 1.5610, MAE: 1.2440, R2: 0.3463 + +FOLD 2/5 +GNN Train Loss: 0.5639 +RMSE: 1.7676, MAE: 1.3645, R2: 0.4149 + +FOLD 3/5 +GNN Train Loss: 0.5717 +RMSE: 1.4853, MAE: 1.1897, R2: 0.4622 + +FOLD 4/5 +GNN Train Loss: 0.5912 +RMSE: 1.5848, MAE: 1.2340, R2: 0.4180 + +FOLD 5/5 +GNN Train Loss: 0.5727 +RMSE: 1.4795, MAE: 1.0873, R2: 0.4443 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5749 [1.4981, 1.6699] +MAE: 1.2221 [1.1459, 1.3034] +R2: 0.4181 [0.3796, 0.4492] + +★ Using fold 5 model for test inference +RMSE: 1.6440, MAE: 1.2449, R2: 0.4282 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.6440389807040656, 'mae': 1.2449389696121216, 'r2': 0.42818349599838257} +Test RMSE: 1.6409 (95 % CI: 1.4631–1.8062) + +Test MAE : 1.2461 (95 % CI: 1.1088–1.3926) + +Test R² : 0.4252 (95 % CI: 0.3407–0.5058) + diff --git a/logs/esol-bench/gp+tanimoto/gp_ecfp_esol_20250728_130845.txt b/logs/esol-bench/gp+tanimoto/gp_ecfp_esol_20250728_130845.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb2ecfb8c0d4a29df6ab829bf323580f84a646ee --- /dev/null +++ b/logs/esol-bench/gp+tanimoto/gp_ecfp_esol_20250728_130845.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on esol + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0363, MAE: 0.7947, R2: 0.7119 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.2251, MAE: 0.8642, R2: 0.7189 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.9953, MAE: 0.7663, R2: 0.7585 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0954, MAE: 0.8471, R2: 0.7219 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0513, MAE: 0.7919, R2: 0.7194 + +====== K-FOLD SUMMARY ====== +RMSE: 1.0797 [1.0229, 1.1532] +MAE: 0.8127 [0.7822, 0.8446] +R2: 0.7262 [0.7159, 0.7429] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 1.0497, MAE: 0.7789, R2: 0.7669 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.0497223731781768, 'mae': 0.778936529429613, 'r2': 0.7668790202085198} +Test RMSE: 1.0513 (95 % CI: 0.9318–1.1691) + +Test MAE : 0.7792 (95 % CI: 0.6939–0.8670) + +Test R² : 0.7658 (95 % CI: 0.7082–0.8132) + diff --git a/logs/esol-bench/gp+tanimoto/gp_selfies_esol_20250728_130617.txt b/logs/esol-bench/gp+tanimoto/gp_selfies_esol_20250728_130617.txt new file mode 100644 index 0000000000000000000000000000000000000000..3fe1dbd207859c4ea81cf02e53631eb808d808be --- /dev/null +++ b/logs/esol-bench/gp+tanimoto/gp_selfies_esol_20250728_130617.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on esol + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.9308, MAE: 1.5431, R2: -0.0001 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 2.3342, MAE: 1.8513, R2: -0.0204 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 2.0263, MAE: 1.6086, R2: -0.0008 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 2.0774, MAE: 1.6662, R2: -0.0001 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.9991, MAE: 1.5442, R2: -0.0146 + +====== K-FOLD SUMMARY ====== +RMSE: 2.0740 [1.9718, 2.2110] +MAE: 1.6436 [1.5569, 1.7526] +R2: -0.0070 [-0.0151, -0.0002] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 2.1742, MAE: 1.7323, R2: -0.0001 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1742307536415177, 'mae': 1.7322798912419684, 'r2': -0.00010067704218408302} +Test RMSE: 2.1744 (95 % CI: 1.9719–2.3680) + +Test MAE : 1.7338 (95 % CI: 1.5690–1.9121) + +Test R² : -0.0046 (95 % CI: -0.0233–-0.0000) + diff --git a/logs/esol-bench/gp+tanimoto/gp_smiles_esol_20250728_130432.txt b/logs/esol-bench/gp+tanimoto/gp_smiles_esol_20250728_130432.txt new file mode 100644 index 0000000000000000000000000000000000000000..6858ab2875c9fc712853803667c4835bda3b31ec --- /dev/null +++ b/logs/esol-bench/gp+tanimoto/gp_smiles_esol_20250728_130432.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on esol + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0363, MAE: 0.7947, R2: 0.7119 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.2251, MAE: 0.8642, R2: 0.7189 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.9953, MAE: 0.7663, R2: 0.7585 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0954, MAE: 0.8471, R2: 0.7219 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.0513, MAE: 0.7919, R2: 0.7194 + +====== K-FOLD SUMMARY ====== +RMSE: 1.0801 [1.0199, 1.1526] +MAE: 0.8119 [0.7822, 0.8463] +R2: 0.7265 [0.7154, 0.7429] + +★ Using fold 3 model for test inference +Evaluating GP model... +RMSE: 1.0497, MAE: 0.7789, R2: 0.7669 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.0497223731781768, 'mae': 0.778936529429613, 'r2': 0.7668790202085198} +Test RMSE: 1.0503 (95 % CI: 0.9288–1.1758) + +Test MAE : 0.7798 (95 % CI: 0.6794–0.8797) + +Test R² : 0.7646 (95 % CI: 0.7049–0.8163) + diff --git a/logs/esol-bench/sage/sage_ecfp_esol_20250729_145436.txt b/logs/esol-bench/sage/sage_ecfp_esol_20250729_145436.txt new file mode 100644 index 0000000000000000000000000000000000000000..813b84045d85ed3a8a2cd2fde0174446a6162c5b --- /dev/null +++ b/logs/esol-bench/sage/sage_ecfp_esol_20250729_145436.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on esol + +FOLD 1/5 +GNN Train Loss: 0.0255 +RMSE: 1.2065, MAE: 0.9007, R2: 0.6095 + +FOLD 2/5 +GNN Train Loss: 0.0272 +RMSE: 1.3326, MAE: 1.0061, R2: 0.6674 + +FOLD 3/5 +GNN Train Loss: 0.0330 +RMSE: 1.3335, MAE: 0.9863, R2: 0.5665 + +FOLD 4/5 +GNN Train Loss: 0.0258 +RMSE: 1.3108, MAE: 1.0032, R2: 0.6018 + +FOLD 5/5 +GNN Train Loss: 0.0330 +RMSE: 1.4817, MAE: 1.0496, R2: 0.4426 + +====== K-FOLD SUMMARY ====== +RMSE: 1.3322 [1.2528, 1.4179] +MAE: 0.9894 [0.9428, 1.0243] +R2: 0.5780 [0.5093, 0.6341] + +★ Using fold 1 model for test inference +RMSE: 1.1489, MAE: 0.8723, R2: 0.7207 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.14890627473613, 'mae': 0.8722635507583618, 'r2': 0.7207445502281189} +Test RMSE: 1.1407 (95 % CI: 1.0132–1.2773) + +Test MAE : 0.8713 (95 % CI: 0.7765–0.9731) + +Test R² : 0.7157 (95 % CI: 0.6354–0.7802) + diff --git a/logs/esol-bench/sage/sage_selfies_esol_20250729_145326.txt b/logs/esol-bench/sage/sage_selfies_esol_20250729_145326.txt new file mode 100644 index 0000000000000000000000000000000000000000..a2cc7cfb8daea45f23d3bc19df791e141fa3f21f --- /dev/null +++ b/logs/esol-bench/sage/sage_selfies_esol_20250729_145326.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on esol + +FOLD 1/5 +GNN Train Loss: 0.4482 +RMSE: 1.4139, MAE: 1.0729, R2: 0.4637 + +FOLD 2/5 +GNN Train Loss: 0.5096 +RMSE: 1.5713, MAE: 1.2157, R2: 0.5376 + +FOLD 3/5 +GNN Train Loss: 0.5272 +RMSE: 1.3690, MAE: 1.0761, R2: 0.5431 + +FOLD 4/5 +GNN Train Loss: 0.4939 +RMSE: 1.5876, MAE: 1.2563, R2: 0.4159 + +FOLD 5/5 +GNN Train Loss: 0.4801 +RMSE: 1.4336, MAE: 1.1198, R2: 0.4783 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4748 [1.3998, 1.5503] +MAE: 1.1478 [1.0842, 1.2128] +R2: 0.4880 [0.4475, 0.5280] + +★ Using fold 3 model for test inference +RMSE: 1.6123, MAE: 1.2330, R2: 0.4501 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.6122791789651947, 'mae': 1.2329822778701782, 'r2': 0.45006299018859863} +Test RMSE: 1.6127 (95 % CI: 1.4437–1.7857) + +Test MAE : 1.2302 (95 % CI: 1.1001–1.3625) + +Test R² : 0.4479 (95 % CI: 0.3523–0.5362) + diff --git a/logs/esol-bench/sage/sage_smiles_esol_20250729_145207.txt b/logs/esol-bench/sage/sage_smiles_esol_20250729_145207.txt new file mode 100644 index 0000000000000000000000000000000000000000..483dddc75eec950287c71f06d8a7e4861c5ddeab --- /dev/null +++ b/logs/esol-bench/sage/sage_smiles_esol_20250729_145207.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on esol + +FOLD 1/5 +GNN Train Loss: 0.4495 +RMSE: 1.4767, MAE: 1.1599, R2: 0.4150 + +FOLD 2/5 +GNN Train Loss: 0.4835 +RMSE: 1.5992, MAE: 1.2936, R2: 0.5211 + +FOLD 3/5 +GNN Train Loss: 0.4892 +RMSE: 1.3215, MAE: 1.0112, R2: 0.5743 + +FOLD 4/5 +GNN Train Loss: 0.4818 +RMSE: 1.5106, MAE: 1.1371, R2: 0.4712 + +FOLD 5/5 +GNN Train Loss: 0.4774 +RMSE: 1.4686, MAE: 1.1736, R2: 0.4525 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4766 [1.3904, 1.5486] +MAE: 1.1535 [1.0688, 1.2310] +R2: 0.4865 [0.4412, 0.5330] + +★ Using fold 3 model for test inference +RMSE: 1.5437, MAE: 1.1616, R2: 0.4959 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5436616910935124, 'mae': 1.1616016626358032, 'r2': 0.4958767890930176} +Test RMSE: 1.5419 (95 % CI: 1.3725–1.7113) + +Test MAE : 1.1597 (95 % CI: 1.0338–1.2990) + +Test R² : 0.4942 (95 % CI: 0.3928–0.5798) + diff --git a/logs/freesolv-bench/gat/gat_ecfp_freesolv_20250729_145709.txt b/logs/freesolv-bench/gat/gat_ecfp_freesolv_20250729_145709.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c444c1708c5030ef882907226a49ce67f6a323c --- /dev/null +++ b/logs/freesolv-bench/gat/gat_ecfp_freesolv_20250729_145709.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on freesolv + +FOLD 1/5 +GNN Train Loss: 0.0032 +RMSE: 2.5012, MAE: 1.7291, R2: 0.5067 + +FOLD 2/5 +GNN Train Loss: 0.0025 +RMSE: 2.1889, MAE: 1.3120, R2: 0.7080 + +FOLD 3/5 +GNN Train Loss: 0.0025 +RMSE: 2.0495, MAE: 1.3345, R2: 0.7276 + +FOLD 4/5 +GNN Train Loss: 0.0017 +RMSE: 1.7232, MAE: 1.2818, R2: 0.7437 + +FOLD 5/5 +GNN Train Loss: 0.0025 +RMSE: 2.0090, MAE: 1.3014, R2: 0.7217 + +====== K-FOLD SUMMARY ====== +RMSE: 2.0970 [1.9023, 2.3403] +MAE: 1.3945 [1.2963, 1.5646] +R2: 0.6825 [0.5927, 0.7349] + +★ Using fold 4 model for test inference +RMSE: 2.5791, MAE: 1.7366, R2: 0.5983 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.579116538140448, 'mae': 1.7365798950195312, 'r2': 0.5983405113220215} +Test RMSE: 2.5469 (95 % CI: 2.0199–3.2175) + +Test MAE : 1.7310 (95 % CI: 1.4362–2.0835) + +Test R² : 0.5951 (95 % CI: 0.4630–0.7188) + diff --git a/logs/freesolv-bench/gat/gat_selfies_freesolv_20250729_145939.txt b/logs/freesolv-bench/gat/gat_selfies_freesolv_20250729_145939.txt new file mode 100644 index 0000000000000000000000000000000000000000..bd1e9368d999521e8d17a2b762672abb56abab7e --- /dev/null +++ b/logs/freesolv-bench/gat/gat_selfies_freesolv_20250729_145939.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on freesolv + +FOLD 1/5 +GNN Train Loss: 0.7667 +RMSE: 3.3944, MAE: 2.5839, R2: 0.0915 + +FOLD 2/5 +GNN Train Loss: 0.8129 +RMSE: 3.7210, MAE: 2.4873, R2: 0.1562 + +FOLD 3/5 +GNN Train Loss: 0.8399 +RMSE: 3.6435, MAE: 2.5785, R2: 0.1391 + +FOLD 4/5 +GNN Train Loss: 0.8376 +RMSE: 3.2357, MAE: 2.4622, R2: 0.0964 + +FOLD 5/5 +GNN Train Loss: 0.9170 +RMSE: 3.3063, MAE: 2.4931, R2: 0.2462 + +====== K-FOLD SUMMARY ====== +RMSE: 3.4598 [3.2957, 3.6381] +MAE: 2.5205 [2.4784, 2.5635] +R2: 0.1471 [0.1030, 0.2034] + +★ Using fold 4 model for test inference +RMSE: 3.7898, MAE: 2.8510, R2: 0.1328 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.789755091340831, 'mae': 2.850984573364258, 'r2': 0.13276177644729614} +Test RMSE: 3.7543 (95 % CI: 3.1051–4.5488) + +Test MAE : 2.8503 (95 % CI: 2.4634–3.2559) + +Test R² : 0.1193 (95 % CI: -0.0645–0.2465) + diff --git a/logs/freesolv-bench/gat/gat_smiles_freesolv_20250729_145910.txt b/logs/freesolv-bench/gat/gat_smiles_freesolv_20250729_145910.txt new file mode 100644 index 0000000000000000000000000000000000000000..552f9e0dc035eed6163c13251dc396055f4a61e8 --- /dev/null +++ b/logs/freesolv-bench/gat/gat_smiles_freesolv_20250729_145910.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8179 +RMSE: 3.3786, MAE: 2.5776, R2: 0.1000 + +FOLD 2/5 +GNN Train Loss: 0.8385 +RMSE: 3.8134, MAE: 2.5189, R2: 0.1138 + +FOLD 3/5 +GNN Train Loss: 0.7912 +RMSE: 3.4725, MAE: 2.4274, R2: 0.2180 + +FOLD 4/5 +GNN Train Loss: 0.7695 +RMSE: 3.1172, MAE: 2.3403, R2: 0.1614 + +FOLD 5/5 +GNN Train Loss: 0.8353 +RMSE: 3.3668, MAE: 2.5870, R2: 0.2184 + +====== K-FOLD SUMMARY ====== +RMSE: 3.4271 [3.2382, 3.6348] +MAE: 2.4883 [2.4051, 2.5696] +R2: 0.1615 [0.1150, 0.2068] + +★ Using fold 4 model for test inference +RMSE: 3.6029, MAE: 2.6115, R2: 0.2162 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.6028548629881447, 'mae': 2.6115078926086426, 'r2': 0.2161921262741089} +Test RMSE: 3.5968 (95 % CI: 2.8876–4.3576) + +Test MAE : 2.6242 (95 % CI: 2.2097–3.0936) + +Test R² : 0.2033 (95 % CI: 0.0492–0.3298) + diff --git a/logs/freesolv-bench/gcn/gcn_ecfp_freesolv_20250729_145959.txt b/logs/freesolv-bench/gcn/gcn_ecfp_freesolv_20250729_145959.txt new file mode 100644 index 0000000000000000000000000000000000000000..68a47d12525dbbdc4965e8cd84274ef80c4c25d4 --- /dev/null +++ b/logs/freesolv-bench/gcn/gcn_ecfp_freesolv_20250729_145959.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on freesolv + +FOLD 1/5 +GNN Train Loss: 0.0120 +RMSE: 2.5209, MAE: 1.7016, R2: 0.4990 + +FOLD 2/5 +GNN Train Loss: 0.0103 +RMSE: 2.3136, MAE: 1.2769, R2: 0.6738 + +FOLD 3/5 +GNN Train Loss: 0.0163 +RMSE: 1.9982, MAE: 1.2653, R2: 0.7411 + +FOLD 4/5 +GNN Train Loss: 0.0147 +RMSE: 1.6721, MAE: 1.2505, R2: 0.7587 + +FOLD 5/5 +GNN Train Loss: 0.0135 +RMSE: 1.9441, MAE: 1.2546, R2: 0.7394 + +====== K-FOLD SUMMARY ====== +RMSE: 2.0833 [1.8461, 2.3334] +MAE: 1.3466 [1.2559, 1.5249] +R2: 0.6827 [0.5951, 0.7478] + +★ Using fold 4 model for test inference +RMSE: 2.5033, MAE: 1.6673, R2: 0.6216 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.5033262060024155, 'mae': 1.6673259735107422, 'r2': 0.6216001510620117} +Test RMSE: 2.5038 (95 % CI: 1.9165–3.2066) + +Test MAE : 1.6743 (95 % CI: 1.3694–2.0345) + +Test R² : 0.6170 (95 % CI: 0.4896–0.7392) + diff --git a/logs/freesolv-bench/gcn/gcn_selfies_freesolv_20250729_145753.txt b/logs/freesolv-bench/gcn/gcn_selfies_freesolv_20250729_145753.txt new file mode 100644 index 0000000000000000000000000000000000000000..f542032367be50eced74fbbc89bf23b34e6f8ee2 --- /dev/null +++ b/logs/freesolv-bench/gcn/gcn_selfies_freesolv_20250729_145753.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8784 +RMSE: 3.4350, MAE: 2.6553, R2: 0.0697 + +FOLD 2/5 +GNN Train Loss: 0.8729 +RMSE: 3.8787, MAE: 2.6063, R2: 0.0831 + +FOLD 3/5 +GNN Train Loss: 0.8664 +RMSE: 3.7232, MAE: 2.5616, R2: 0.1011 + +FOLD 4/5 +GNN Train Loss: 0.8758 +RMSE: 3.2411, MAE: 2.4326, R2: 0.0934 + +FOLD 5/5 +GNN Train Loss: 0.8929 +RMSE: 3.5052, MAE: 2.7558, R2: 0.1528 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5533 [3.3763, 3.7418] +MAE: 2.6009 [2.5029, 2.6955] +R2: 0.1007 [0.0798, 0.1290] + +★ Using fold 4 model for test inference +RMSE: 3.8312, MAE: 2.7679, R2: 0.1137 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.8312131298089525, 'mae': 2.767855405807495, 'r2': 0.11368370056152344} +Test RMSE: 3.8168 (95 % CI: 3.0612–4.6924) + +Test MAE : 2.7834 (95 % CI: 2.3575–3.2673) + +Test R² : 0.1054 (95 % CI: -0.0085–0.1973) + diff --git a/logs/freesolv-bench/gcn/gcn_smiles_freesolv_20250729_145637.txt b/logs/freesolv-bench/gcn/gcn_smiles_freesolv_20250729_145637.txt new file mode 100644 index 0000000000000000000000000000000000000000..c18438d6e10000fb4bbe2c35ad6f85ee5e6924bf --- /dev/null +++ b/logs/freesolv-bench/gcn/gcn_smiles_freesolv_20250729_145637.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8754 +RMSE: 3.3961, MAE: 2.6382, R2: 0.0906 + +FOLD 2/5 +GNN Train Loss: 0.8774 +RMSE: 3.8759, MAE: 2.6121, R2: 0.0845 + +FOLD 3/5 +GNN Train Loss: 0.8707 +RMSE: 3.7354, MAE: 2.5668, R2: 0.0952 + +FOLD 4/5 +GNN Train Loss: 0.8800 +RMSE: 3.2584, MAE: 2.4776, R2: 0.0837 + +FOLD 5/5 +GNN Train Loss: 0.8952 +RMSE: 3.5678, MAE: 2.8178, R2: 0.1223 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5607 [3.3754, 3.7581] +MAE: 2.6249 [2.5366, 2.7265] +R2: 0.0952 [0.0855, 0.1093] + +★ Using fold 4 model for test inference +RMSE: 3.8673, MAE: 2.8618, R2: 0.0969 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.8673295428459094, 'mae': 2.86177659034729, 'r2': 0.09689462184906006} +Test RMSE: 3.8458 (95 % CI: 3.0620–4.7722) + +Test MAE : 2.8537 (95 % CI: 2.4158–3.3218) + +Test R² : 0.0850 (95 % CI: -0.0425–0.1978) + diff --git a/logs/freesolv-bench/gin/gin_ecfp_freesolv_20250729_150234.txt b/logs/freesolv-bench/gin/gin_ecfp_freesolv_20250729_150234.txt new file mode 100644 index 0000000000000000000000000000000000000000..d2c0654c3e5acc93a1ef10ded8082305fae6ed17 --- /dev/null +++ b/logs/freesolv-bench/gin/gin_ecfp_freesolv_20250729_150234.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on freesolv + +FOLD 1/5 +GNN Train Loss: 0.0027 +RMSE: 1.9627, MAE: 1.4046, R2: 0.6963 + +FOLD 2/5 +GNN Train Loss: 0.0052 +RMSE: 1.7123, MAE: 1.0102, R2: 0.8213 + +FOLD 3/5 +GNN Train Loss: 0.0100 +RMSE: 1.7900, MAE: 1.1467, R2: 0.7922 + +FOLD 4/5 +GNN Train Loss: 0.0039 +RMSE: 1.6437, MAE: 1.2223, R2: 0.7668 + +FOLD 5/5 +GNN Train Loss: 0.0050 +RMSE: 1.7879, MAE: 1.2211, R2: 0.7796 + +====== K-FOLD SUMMARY ====== +RMSE: 1.7808 [1.6986, 1.8785] +MAE: 1.1995 [1.0921, 1.3163] +R2: 0.7719 [0.7321, 0.8046] + +★ Using fold 4 model for test inference +RMSE: 2.3560, MAE: 1.5695, R2: 0.6648 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.3560457297908033, 'mae': 1.5694881677627563, 'r2': 0.6648157835006714} +Test RMSE: 2.3410 (95 % CI: 1.8118–2.9798) + +Test MAE : 1.5615 (95 % CI: 1.2744–1.8932) + +Test R² : 0.6625 (95 % CI: 0.5395–0.7721) + diff --git a/logs/freesolv-bench/gin/gin_selfies_freesolv_20250729_145809.txt b/logs/freesolv-bench/gin/gin_selfies_freesolv_20250729_145809.txt new file mode 100644 index 0000000000000000000000000000000000000000..023039a335db80cf7d4e9fa43885b5b28929070a --- /dev/null +++ b/logs/freesolv-bench/gin/gin_selfies_freesolv_20250729_145809.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8838 +RMSE: 3.3086, MAE: 2.5899, R2: 0.1369 + +FOLD 2/5 +GNN Train Loss: 0.8686 +RMSE: 3.8456, MAE: 2.5741, R2: 0.0987 + +FOLD 3/5 +GNN Train Loss: 0.8574 +RMSE: 3.6883, MAE: 2.5495, R2: 0.1179 + +FOLD 4/5 +GNN Train Loss: 0.8654 +RMSE: 3.2185, MAE: 2.3957, R2: 0.1060 + +FOLD 5/5 +GNN Train Loss: 0.8751 +RMSE: 3.5316, MAE: 2.7929, R2: 0.1400 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5198 [3.3172, 3.7200] +MAE: 2.5815 [2.4671, 2.7004] +R2: 0.1200 [0.1055, 0.1343] + +★ Using fold 4 model for test inference +RMSE: 3.7895, MAE: 2.7287, R2: 0.1329 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.7894967685660017, 'mae': 2.7287309169769287, 'r2': 0.1328800916671753} +Test RMSE: 3.7603 (95 % CI: 2.9765–4.6589) + +Test MAE : 2.7327 (95 % CI: 2.3129–3.2050) + +Test R² : 0.1265 (95 % CI: 0.0058–0.2313) + diff --git a/logs/freesolv-bench/gin/gin_smiles_freesolv_20250729_145655.txt b/logs/freesolv-bench/gin/gin_smiles_freesolv_20250729_145655.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca76a96d7e2017f8eba38f6119c706e3e2cd6cea --- /dev/null +++ b/logs/freesolv-bench/gin/gin_smiles_freesolv_20250729_145655.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8659 +RMSE: 3.4377, MAE: 2.7013, R2: 0.0682 + +FOLD 2/5 +GNN Train Loss: 0.8895 +RMSE: 3.8813, MAE: 2.6282, R2: 0.0819 + +FOLD 3/5 +GNN Train Loss: 0.8878 +RMSE: 3.7151, MAE: 2.5864, R2: 0.1050 + +FOLD 4/5 +GNN Train Loss: 0.8683 +RMSE: 3.2512, MAE: 2.4255, R2: 0.0877 + +FOLD 5/5 +GNN Train Loss: 0.8904 +RMSE: 3.5669, MAE: 2.7989, R2: 0.1227 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5770 [3.3813, 3.7593] +MAE: 2.6282 [2.5066, 2.7257] +R2: 0.0932 [0.0783, 0.1087] + +★ Using fold 4 model for test inference +RMSE: 3.7932, MAE: 2.7270, R2: 0.1312 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.7932367672107077, 'mae': 2.7269906997680664, 'r2': 0.13116759061813354} +Test RMSE: 3.7822 (95 % CI: 2.9994–4.6367) + +Test MAE : 2.7178 (95 % CI: 2.2620–3.1859) + +Test R² : 0.1216 (95 % CI: -0.0223–0.2268) + diff --git a/logs/freesolv-bench/gp+tanimoto/gp_ecfp_freesolv_20250728_142421.txt b/logs/freesolv-bench/gp+tanimoto/gp_ecfp_freesolv_20250728_142421.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f6d92c15c092807880e26dfbf865d9d6eae9876 --- /dev/null +++ b/logs/freesolv-bench/gp+tanimoto/gp_ecfp_freesolv_20250728_142421.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on freesolv + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8454, MAE: 1.3096, R2: 0.7315 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8259, MAE: 0.8868, R2: 0.7968 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8723, MAE: 1.1146, R2: 0.7727 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5124, MAE: 1.1106, R2: 0.8026 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.7059, MAE: 1.1616, R2: 0.7993 + +====== K-FOLD SUMMARY ====== +RMSE: 1.7529 [1.6231, 1.8484] +MAE: 1.1168 [0.9779, 1.2308] +R2: 0.7804 [0.7576, 0.8001] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 2.1096, MAE: 1.3340, R2: 0.7313 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1095500600522454, 'mae': 1.3340439758099554, 'r2': 0.731282640910214} +Test RMSE: 2.0696 (95 % CI: 1.4945–2.8408) + +Test MAE : 1.3354 (95 % CI: 1.0815–1.6512) + +Test R² : 0.7344 (95 % CI: 0.6273–0.8392) + diff --git a/logs/freesolv-bench/gp+tanimoto/gp_selfies_freesolv_20250728_142404.txt b/logs/freesolv-bench/gp+tanimoto/gp_selfies_freesolv_20250728_142404.txt new file mode 100644 index 0000000000000000000000000000000000000000..156c6a1e4db7ce37eb7d3bc227e190601ccb392a --- /dev/null +++ b/logs/freesolv-bench/gp+tanimoto/gp_selfies_freesolv_20250728_142404.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on freesolv + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 3.6069, MAE: 2.7750, R2: -0.0258 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 4.0669, MAE: 2.7979, R2: -0.0080 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 3.9273, MAE: 2.7863, R2: -0.0002 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 3.4218, MAE: 2.5423, R2: -0.0105 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 3.8557, MAE: 3.0618, R2: -0.0251 + +====== K-FOLD SUMMARY ====== +RMSE: 3.7788 [3.5826, 3.9688] +MAE: 2.7894 [2.6422, 2.9516] +R2: -0.0139 [-0.0224, -0.0049] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 4.1211, MAE: 3.0954, R2: -0.0255 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 4.121051340849616, 'mae': 3.095356932795325, 'r2': -0.02549158593200107} +Test RMSE: 4.1141 (95 % CI: 3.3755–4.9763) + +Test MAE : 3.0900 (95 % CI: 2.6772–3.5569) + +Test R² : -0.0384 (95 % CI: -0.1529–-0.0002) + diff --git a/logs/freesolv-bench/gp+tanimoto/gp_smiles_freesolv_20250728_142331.txt b/logs/freesolv-bench/gp+tanimoto/gp_smiles_freesolv_20250728_142331.txt new file mode 100644 index 0000000000000000000000000000000000000000..3e9f5e9a41e2eb119a40e58704068692b0101b9c --- /dev/null +++ b/logs/freesolv-bench/gp+tanimoto/gp_smiles_freesolv_20250728_142331.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on freesolv + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8454, MAE: 1.3096, R2: 0.7315 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8259, MAE: 0.8868, R2: 0.7968 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.8723, MAE: 1.1146, R2: 0.7727 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.5124, MAE: 1.1106, R2: 0.8026 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.7059, MAE: 1.1616, R2: 0.7993 + +====== K-FOLD SUMMARY ====== +RMSE: 1.7556 [1.6231, 1.8523] +MAE: 1.1178 [0.9873, 1.2308] +R2: 0.7811 [0.7581, 0.8001] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 2.1096, MAE: 1.3340, R2: 0.7313 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1095500600522454, 'mae': 1.3340439758099554, 'r2': 0.731282640910214} +Test RMSE: 2.0787 (95 % CI: 1.4546–2.8710) + +Test MAE : 1.3375 (95 % CI: 1.0839–1.6501) + +Test R² : 0.7338 (95 % CI: 0.6266–0.8388) + diff --git a/logs/freesolv-bench/sage/sage_ecfp_freesolv_20250729_150029.txt b/logs/freesolv-bench/sage/sage_ecfp_freesolv_20250729_150029.txt new file mode 100644 index 0000000000000000000000000000000000000000..c354a39168e515eec797ceaed341b130d76a48d9 --- /dev/null +++ b/logs/freesolv-bench/sage/sage_ecfp_freesolv_20250729_150029.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on freesolv + +FOLD 1/5 +GNN Train Loss: 0.0044 +RMSE: 2.1845, MAE: 1.5875, R2: 0.6237 + +FOLD 2/5 +GNN Train Loss: 0.0059 +RMSE: 1.8647, MAE: 1.1633, R2: 0.7881 + +FOLD 3/5 +GNN Train Loss: 0.0060 +RMSE: 2.0170, MAE: 1.3163, R2: 0.7362 + +FOLD 4/5 +GNN Train Loss: 0.0036 +RMSE: 1.6653, MAE: 1.2153, R2: 0.7606 + +FOLD 5/5 +GNN Train Loss: 0.0050 +RMSE: 1.9074, MAE: 1.2864, R2: 0.7491 + +====== K-FOLD SUMMARY ====== +RMSE: 1.9318 [1.7841, 2.0840] +MAE: 1.3189 [1.2043, 1.4671] +R2: 0.7308 [0.6739, 0.7716] + +★ Using fold 4 model for test inference +RMSE: 2.5718, MAE: 1.7177, R2: 0.6006 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.5717555114503106, 'mae': 1.717659831047058, 'r2': 0.600629985332489} +Test RMSE: 2.5430 (95 % CI: 2.0052–3.2978) + +Test MAE : 1.7124 (95 % CI: 1.4085–2.0726) + +Test R² : 0.5959 (95 % CI: 0.4749–0.7242) + diff --git a/logs/freesolv-bench/sage/sage_selfies_freesolv_20250729_145839.txt b/logs/freesolv-bench/sage/sage_selfies_freesolv_20250729_145839.txt new file mode 100644 index 0000000000000000000000000000000000000000..371490c3839323a7a07ee4b69e16b605fa6c6dad --- /dev/null +++ b/logs/freesolv-bench/sage/sage_selfies_freesolv_20250729_145839.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8020 +RMSE: 3.4031, MAE: 2.6529, R2: 0.0869 + +FOLD 2/5 +GNN Train Loss: 0.8593 +RMSE: 3.8372, MAE: 2.5796, R2: 0.1027 + +FOLD 3/5 +GNN Train Loss: 0.8465 +RMSE: 3.6723, MAE: 2.5190, R2: 0.1255 + +FOLD 4/5 +GNN Train Loss: 0.8613 +RMSE: 3.2817, MAE: 2.4461, R2: 0.0706 + +FOLD 5/5 +GNN Train Loss: 0.8600 +RMSE: 3.4353, MAE: 2.6249, R2: 0.1862 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5216 [3.3596, 3.6909] +MAE: 2.5644 [2.4964, 2.6271] +R2: 0.1132 [0.0835, 0.1510] + +★ Using fold 4 model for test inference +RMSE: 3.8581, MAE: 2.7362, R2: 0.1012 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.8581167787840935, 'mae': 2.736206531524658, 'r2': 0.10119223594665527} +Test RMSE: 3.8307 (95 % CI: 3.0286–4.7111) + +Test MAE : 2.7317 (95 % CI: 2.2806–3.2118) + +Test R² : 0.0901 (95 % CI: -0.0492–0.2142) + diff --git a/logs/freesolv-bench/sage/sage_smiles_freesolv_20250729_145730.txt b/logs/freesolv-bench/sage/sage_smiles_freesolv_20250729_145730.txt new file mode 100644 index 0000000000000000000000000000000000000000..6ab3cbb3a6e974389e564b21ef7e31454c8cadac --- /dev/null +++ b/logs/freesolv-bench/sage/sage_smiles_freesolv_20250729_145730.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on freesolv + +FOLD 1/5 +GNN Train Loss: 0.8019 +RMSE: 3.5338, MAE: 2.7398, R2: 0.0154 + +FOLD 2/5 +GNN Train Loss: 0.8207 +RMSE: 3.8484, MAE: 2.5789, R2: 0.0974 + +FOLD 3/5 +GNN Train Loss: 0.8065 +RMSE: 3.5378, MAE: 2.5209, R2: 0.1884 + +FOLD 4/5 +GNN Train Loss: 0.8482 +RMSE: 3.2052, MAE: 2.3895, R2: 0.1133 + +FOLD 5/5 +GNN Train Loss: 0.8157 +RMSE: 3.4170, MAE: 2.6447, R2: 0.1949 + +====== K-FOLD SUMMARY ====== +RMSE: 3.5101 [3.3375, 3.7000] +MAE: 2.5765 [2.4668, 2.6827] +R2: 0.1228 [0.0646, 0.1760] + +★ Using fold 4 model for test inference +RMSE: 3.7707, MAE: 2.6762, R2: 0.1415 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.770711921437411, 'mae': 2.676204204559326, 'r2': 0.1414555311203003} +Test RMSE: 3.7483 (95 % CI: 2.9797–4.7022) + +Test MAE : 2.6734 (95 % CI: 2.2214–3.1567) + +Test R² : 0.1340 (95 % CI: 0.0224–0.2356) + diff --git a/logs/ic50-bench/gat/gat_ecfp_ic50_20250729_211621.txt b/logs/ic50-bench/gat/gat_ecfp_ic50_20250729_211621.txt new file mode 100644 index 0000000000000000000000000000000000000000..505300c1325e3ee1f6b1177fe0cd5412440e1d75 --- /dev/null +++ b/logs/ic50-bench/gat/gat_ecfp_ic50_20250729_211621.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on ic50 + +FOLD 1/5 +GNN Train Loss: 0.0587 +RMSE: 1.0308, MAE: 0.8219, R2: -0.9983 + +FOLD 2/5 +GNN Train Loss: 0.0441 +RMSE: 1.1066, MAE: 0.8453, R2: -0.9856 + +FOLD 3/5 +GNN Train Loss: 0.0552 +RMSE: 1.0249, MAE: 0.7841, R2: -0.6766 + +FOLD 4/5 +GNN Train Loss: 0.0467 +RMSE: 1.1199, MAE: 0.8428, R2: -0.7829 + +FOLD 5/5 +GNN Train Loss: 0.0503 +RMSE: 1.0607, MAE: 0.8244, R2: -0.4716 + +====== K-FOLD SUMMARY ====== +RMSE: 1.0679 [1.0344, 1.1027] +MAE: 0.8229 [0.8039, 0.8401] +R2: -0.7903 [-0.9501, -0.6179] + +★ Using fold 3 model for test inference +RMSE: 1.1019, MAE: 0.8421, R2: -0.9775 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.101900900949078, 'mae': 0.8421272039413452, 'r2': -0.9775114059448242} +Test RMSE: 1.1000 (95 % CI: 1.0056–1.1871) + +Test MAE : 0.8420 (95 % CI: 0.7753–0.9124) + +Test R² : -1.0037 (95 % CI: -1.3472–-0.6552) + diff --git a/logs/ic50-bench/gat/gat_selfies_ic50_20250729_211531.txt b/logs/ic50-bench/gat/gat_selfies_ic50_20250729_211531.txt new file mode 100644 index 0000000000000000000000000000000000000000..2cc04e1b32cca70defbdc7fcee3cc2aed9dca5c7 --- /dev/null +++ b/logs/ic50-bench/gat/gat_selfies_ic50_20250729_211531.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9579 +RMSE: 0.7075, MAE: 0.5892, R2: 0.0585 + +FOLD 2/5 +GNN Train Loss: 0.9476 +RMSE: 0.7914, MAE: 0.6364, R2: -0.0155 + +FOLD 3/5 +GNN Train Loss: 0.9393 +RMSE: 0.7855, MAE: 0.6163, R2: 0.0152 + +FOLD 4/5 +GNN Train Loss: 0.9609 +RMSE: 0.8127, MAE: 0.6171, R2: 0.0611 + +FOLD 5/5 +GNN Train Loss: 0.9462 +RMSE: 0.8565, MAE: 0.6299, R2: 0.0405 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7901 [0.7453, 0.8293] +MAE: 0.6173 [0.6027, 0.6310] +R2: 0.0317 [0.0059, 0.0559] + +★ Using fold 1 model for test inference +RMSE: 0.7470, MAE: 0.6023, R2: 0.0912 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.746999859448564, 'mae': 0.6023342609405518, 'r2': 0.09118610620498657} +Test RMSE: 0.7474 (95 % CI: 0.6867–0.8105) + +Test MAE : 0.6026 (95 % CI: 0.5630–0.6453) + +Test R² : 0.0872 (95 % CI: 0.0403–0.1334) + diff --git a/logs/ic50-bench/gat/gat_smiles_ic50_20250729_211435.txt b/logs/ic50-bench/gat/gat_smiles_ic50_20250729_211435.txt new file mode 100644 index 0000000000000000000000000000000000000000..4ba5c7f16c9fc267290a26b887d231d687fac329 --- /dev/null +++ b/logs/ic50-bench/gat/gat_smiles_ic50_20250729_211435.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9521 +RMSE: 0.7231, MAE: 0.6038, R2: 0.0165 + +FOLD 2/5 +GNN Train Loss: 0.9390 +RMSE: 0.7831, MAE: 0.5890, R2: 0.0057 + +FOLD 3/5 +GNN Train Loss: 0.9375 +RMSE: 0.7850, MAE: 0.6060, R2: 0.0164 + +FOLD 4/5 +GNN Train Loss: 0.9733 +RMSE: 0.8061, MAE: 0.6225, R2: 0.0763 + +FOLD 5/5 +GNN Train Loss: 0.9548 +RMSE: 0.8522, MAE: 0.6323, R2: 0.0500 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7897 [0.7562, 0.8249] +MAE: 0.6109 [0.5983, 0.6247] +R2: 0.0330 [0.0121, 0.0569] + +★ Using fold 1 model for test inference +RMSE: 0.7584, MAE: 0.6182, R2: 0.0631 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7584492083110622, 'mae': 0.6182253956794739, 'r2': 0.06311357021331787} +Test RMSE: 0.7569 (95 % CI: 0.6983–0.8222) + +Test MAE : 0.6190 (95 % CI: 0.5754–0.6647) + +Test R² : 0.0584 (95 % CI: -0.0024–0.1092) + diff --git a/logs/ic50-bench/gcn/gcn_ecfp_ic50_20250729_211052.txt b/logs/ic50-bench/gcn/gcn_ecfp_ic50_20250729_211052.txt new file mode 100644 index 0000000000000000000000000000000000000000..00ece5e9a090735ab12d7842ca2df347d80ae1b8 --- /dev/null +++ b/logs/ic50-bench/gcn/gcn_ecfp_ic50_20250729_211052.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on ic50 + +FOLD 1/5 +GNN Train Loss: 0.0800 +RMSE: 0.9218, MAE: 0.7355, R2: -0.5980 + +FOLD 2/5 +GNN Train Loss: 0.0714 +RMSE: 1.0056, MAE: 0.7682, R2: -0.6397 + +FOLD 3/5 +GNN Train Loss: 0.0893 +RMSE: 0.9281, MAE: 0.7121, R2: -0.3749 + +FOLD 4/5 +GNN Train Loss: 0.0696 +RMSE: 1.0180, MAE: 0.7730, R2: -0.4732 + +FOLD 5/5 +GNN Train Loss: 0.0613 +RMSE: 0.9692, MAE: 0.7437, R2: -0.2287 + +====== K-FOLD SUMMARY ====== +RMSE: 0.9690 [0.9351, 1.0033] +MAE: 0.7462 [0.7278, 0.7643] +R2: -0.4629 [-0.5815, -0.3318] + +★ Using fold 1 model for test inference +RMSE: 1.0097, MAE: 0.7723, R2: -0.6605 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.009732037396995, 'mae': 0.7722691893577576, 'r2': -0.6605280637741089} +Test RMSE: 1.0079 (95 % CI: 0.9229–1.0953) + +Test MAE : 0.7721 (95 % CI: 0.7131–0.8361) + +Test R² : -0.6738 (95 % CI: -1.0152–-0.4012) + diff --git a/logs/ic50-bench/gcn/gcn_selfies_ic50_20250729_210933.txt b/logs/ic50-bench/gcn/gcn_selfies_ic50_20250729_210933.txt new file mode 100644 index 0000000000000000000000000000000000000000..fe6cdfaa0940797ac9480b0968ba4413fcce6842 --- /dev/null +++ b/logs/ic50-bench/gcn/gcn_selfies_ic50_20250729_210933.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9608 +RMSE: 0.7043, MAE: 0.5787, R2: 0.0672 + +FOLD 2/5 +GNN Train Loss: 0.9500 +RMSE: 0.7905, MAE: 0.6343, R2: -0.0134 + +FOLD 3/5 +GNN Train Loss: 0.9429 +RMSE: 0.7808, MAE: 0.6116, R2: 0.0270 + +FOLD 4/5 +GNN Train Loss: 0.9591 +RMSE: 0.8115, MAE: 0.6210, R2: 0.0639 + +FOLD 5/5 +GNN Train Loss: 0.9485 +RMSE: 0.8684, MAE: 0.6329, R2: 0.0136 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7909 [0.7410, 0.8353] +MAE: 0.6158 [0.5961, 0.6311] +R2: 0.0317 [0.0028, 0.0578] + +★ Using fold 1 model for test inference +RMSE: 0.7497, MAE: 0.5826, R2: 0.0846 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7497137636113717, 'mae': 0.5825851559638977, 'r2': 0.08457046747207642} +Test RMSE: 0.7475 (95 % CI: 0.6710–0.8238) + +Test MAE : 0.5828 (95 % CI: 0.5379–0.6297) + +Test R² : 0.0823 (95 % CI: 0.0324–0.1312) + diff --git a/logs/ic50-bench/gcn/gcn_smiles_ic50_20250729_210837.txt b/logs/ic50-bench/gcn/gcn_smiles_ic50_20250729_210837.txt new file mode 100644 index 0000000000000000000000000000000000000000..a04fc8e230e1dd9e072affda7501164b7b8eb2a3 --- /dev/null +++ b/logs/ic50-bench/gcn/gcn_smiles_ic50_20250729_210837.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9722 +RMSE: 0.7035, MAE: 0.5809, R2: 0.0694 + +FOLD 2/5 +GNN Train Loss: 0.9519 +RMSE: 0.7803, MAE: 0.6139, R2: 0.0126 + +FOLD 3/5 +GNN Train Loss: 0.9645 +RMSE: 0.7892, MAE: 0.6010, R2: 0.0060 + +FOLD 4/5 +GNN Train Loss: 0.9766 +RMSE: 0.8140, MAE: 0.6242, R2: 0.0580 + +FOLD 5/5 +GNN Train Loss: 0.9479 +RMSE: 0.8542, MAE: 0.6344, R2: 0.0455 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7883 [0.7427, 0.8265] +MAE: 0.6109 [0.5941, 0.6262] +R2: 0.0382 [0.0165, 0.0600] + +★ Using fold 1 model for test inference +RMSE: 0.7463, MAE: 0.5866, R2: 0.0929 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7462877750260829, 'mae': 0.5866196155548096, 'r2': 0.09291791915893555} +Test RMSE: 0.7451 (95 % CI: 0.6744–0.8239) + +Test MAE : 0.5863 (95 % CI: 0.5418–0.6358) + +Test R² : 0.0908 (95 % CI: 0.0492–0.1337) + diff --git a/logs/ic50-bench/gin/gin_ecfp_ic50_20250729_211251.txt b/logs/ic50-bench/gin/gin_ecfp_ic50_20250729_211251.txt new file mode 100644 index 0000000000000000000000000000000000000000..1f876af2a2d8f9c9d7a9a8b542777cc518810f58 --- /dev/null +++ b/logs/ic50-bench/gin/gin_ecfp_ic50_20250729_211251.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on ic50 + +FOLD 1/5 +GNN Train Loss: 0.0207 +RMSE: 0.8474, MAE: 0.6717, R2: -0.3506 + +FOLD 2/5 +GNN Train Loss: 0.0176 +RMSE: 0.9393, MAE: 0.7124, R2: -0.4306 + +FOLD 3/5 +GNN Train Loss: 0.0187 +RMSE: 0.8540, MAE: 0.6558, R2: -0.1639 + +FOLD 4/5 +GNN Train Loss: 0.0240 +RMSE: 0.9306, MAE: 0.6883, R2: -0.2310 + +FOLD 5/5 +GNN Train Loss: 0.0195 +RMSE: 0.9074, MAE: 0.6872, R2: -0.0770 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8961 [0.8620, 0.9312] +MAE: 0.6828 [0.6655, 0.6992] +R2: -0.2500 [-0.3599, -0.1426] + +★ Using fold 1 model for test inference +RMSE: 0.9368, MAE: 0.7072, R2: -0.4293 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.9368081082823856, 'mae': 0.7072325348854065, 'r2': -0.4293389320373535} +Test RMSE: 0.9375 (95 % CI: 0.8596–1.0233) + +Test MAE : 0.7075 (95 % CI: 0.6435–0.7702) + +Test R² : -0.4352 (95 % CI: -0.6594–-0.2330) + diff --git a/logs/ic50-bench/gin/gin_selfies_ic50_20250729_211211.txt b/logs/ic50-bench/gin/gin_selfies_ic50_20250729_211211.txt new file mode 100644 index 0000000000000000000000000000000000000000..845d33c80165f78bea92331352f22389b1417a94 --- /dev/null +++ b/logs/ic50-bench/gin/gin_selfies_ic50_20250729_211211.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9588 +RMSE: 0.7039, MAE: 0.5803, R2: 0.0683 + +FOLD 2/5 +GNN Train Loss: 0.9544 +RMSE: 0.7884, MAE: 0.6322, R2: -0.0080 + +FOLD 3/5 +GNN Train Loss: 0.9429 +RMSE: 0.8008, MAE: 0.6394, R2: -0.0234 + +FOLD 4/5 +GNN Train Loss: 0.9597 +RMSE: 0.8141, MAE: 0.6190, R2: 0.0579 + +FOLD 5/5 +GNN Train Loss: 0.9530 +RMSE: 0.8583, MAE: 0.6357, R2: 0.0364 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7930 [0.7479, 0.8328] +MAE: 0.6212 [0.5999, 0.6365] +R2: 0.0270 [-0.0053, 0.0577] + +★ Using fold 1 model for test inference +RMSE: 0.7510, MAE: 0.5883, R2: 0.0815 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.750959180375275, 'mae': 0.588279128074646, 'r2': 0.08152657747268677} +Test RMSE: 0.7501 (95 % CI: 0.6817–0.8203) + +Test MAE : 0.5891 (95 % CI: 0.5440–0.6341) + +Test R² : 0.0790 (95 % CI: 0.0399–0.1154) + diff --git a/logs/ic50-bench/gin/gin_smiles_ic50_20250729_211145.txt b/logs/ic50-bench/gin/gin_smiles_ic50_20250729_211145.txt new file mode 100644 index 0000000000000000000000000000000000000000..24c92fd15363d446bf5a4a32cee29f4677dad174 --- /dev/null +++ b/logs/ic50-bench/gin/gin_smiles_ic50_20250729_211145.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9580 +RMSE: 0.7041, MAE: 0.5814, R2: 0.0677 + +FOLD 2/5 +GNN Train Loss: 0.9458 +RMSE: 0.7750, MAE: 0.5970, R2: 0.0261 + +FOLD 3/5 +GNN Train Loss: 0.9487 +RMSE: 0.7852, MAE: 0.6188, R2: 0.0160 + +FOLD 4/5 +GNN Train Loss: 0.9698 +RMSE: 0.8125, MAE: 0.6195, R2: 0.0616 + +FOLD 5/5 +GNN Train Loss: 0.9485 +RMSE: 0.8554, MAE: 0.6449, R2: 0.0429 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7851 [0.7399, 0.8273] +MAE: 0.6131 [0.5951, 0.6301] +R2: 0.0425 [0.0263, 0.0603] + +★ Using fold 1 model for test inference +RMSE: 0.7493, MAE: 0.5900, R2: 0.0857 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.749268492955718, 'mae': 0.5899991393089294, 'r2': 0.08565753698348999} +Test RMSE: 0.7487 (95 % CI: 0.6773–0.8210) + +Test MAE : 0.5905 (95 % CI: 0.5485–0.6357) + +Test R² : 0.0822 (95 % CI: 0.0467–0.1159) + diff --git a/logs/ic50-bench/gp+tanimoto/gp_ecfp_ic50_20250729_211744.txt b/logs/ic50-bench/gp+tanimoto/gp_ecfp_ic50_20250729_211744.txt new file mode 100644 index 0000000000000000000000000000000000000000..68e1850834971e5c07eeeeb246fcd8e3b00d5d37 --- /dev/null +++ b/logs/ic50-bench/gp+tanimoto/gp_ecfp_ic50_20250729_211744.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on ic50 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7014, MAE: 0.5693, R2: 0.0747 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7477, MAE: 0.5876, R2: 0.0935 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7350, MAE: 0.5783, R2: 0.1378 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7867, MAE: 0.5887, R2: 0.1202 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7671, MAE: 0.5831, R2: 0.2303 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7478 [0.7241, 0.7710] +MAE: 0.5816 [0.5750, 0.5871] +R2: 0.1311 [0.0913, 0.1807] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 0.7658, MAE: 0.5963, R2: 0.0448 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7658389939698179, 'mae': 0.5962968676225696, 'r2': 0.044767875429670534} +Test RMSE: 0.7660 (95 % CI: 0.6981–0.8395) + +Test MAE : 0.5961 (95 % CI: 0.5495–0.6466) + +Test R² : 0.0424 (95 % CI: -0.0505–0.1508) + diff --git a/logs/ic50-bench/gp+tanimoto/gp_selfies_ic50_20250729_211546.txt b/logs/ic50-bench/gp+tanimoto/gp_selfies_ic50_20250729_211546.txt new file mode 100644 index 0000000000000000000000000000000000000000..76aaaaf33a4567e1f9d3aaf67fb0a311e3240f19 --- /dev/null +++ b/logs/ic50-bench/gp+tanimoto/gp_selfies_ic50_20250729_211546.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on ic50 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7294, MAE: 0.5937, R2: -0.0006 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7905, MAE: 0.6174, R2: -0.0133 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7916, MAE: 0.6192, R2: -0.0000 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 0.8422, MAE: 0.6374, R2: -0.0084 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 0.8750, MAE: 0.6490, R2: -0.0014 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8073 [0.7644, 0.8515] +MAE: 0.6232 [0.6072, 0.6384] +R2: -0.0047 [-0.0098, -0.0006] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 0.7842, MAE: 0.6138, R2: -0.0017 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7842372298268165, 'mae': 0.6137832109271052, 'r2': -0.0016797167612061514} +Test RMSE: 0.7833 (95 % CI: 0.7049–0.8586) + +Test MAE : 0.6129 (95 % CI: 0.5667–0.6618) + +Test R² : -0.0044 (95 % CI: -0.0208–-0.0000) + diff --git a/logs/ic50-bench/gp+tanimoto/gp_smiles_ic50_20250729_211437.txt b/logs/ic50-bench/gp+tanimoto/gp_smiles_ic50_20250729_211437.txt new file mode 100644 index 0000000000000000000000000000000000000000..c3085676d867258a10032e96e3cec274c3ade26f --- /dev/null +++ b/logs/ic50-bench/gp+tanimoto/gp_smiles_ic50_20250729_211437.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on ic50 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7014, MAE: 0.5693, R2: 0.0747 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7477, MAE: 0.5876, R2: 0.0935 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7350, MAE: 0.5783, R2: 0.1378 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7867, MAE: 0.5887, R2: 0.1202 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7671, MAE: 0.5831, R2: 0.2303 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7468 [0.7199, 0.7724] +MAE: 0.5816 [0.5747, 0.5871] +R2: 0.1317 [0.0913, 0.1809] + +★ Using fold 1 model for test inference +Evaluating GP model... +RMSE: 0.7658, MAE: 0.5963, R2: 0.0448 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7658389939698179, 'mae': 0.5962968676225696, 'r2': 0.044767875429670534} +Test RMSE: 0.7647 (95 % CI: 0.6985–0.8382) + +Test MAE : 0.5965 (95 % CI: 0.5488–0.6447) + +Test R² : 0.0402 (95 % CI: -0.0481–0.1392) + diff --git a/logs/ic50-bench/sage/sage_ecfp_ic50_20250729_211701.txt b/logs/ic50-bench/sage/sage_ecfp_ic50_20250729_211701.txt new file mode 100644 index 0000000000000000000000000000000000000000..31a1b51a40988466095703984141eb0e3bc01a7e --- /dev/null +++ b/logs/ic50-bench/sage/sage_ecfp_ic50_20250729_211701.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on ic50 + +FOLD 1/5 +GNN Train Loss: 0.0510 +RMSE: 0.9489, MAE: 0.7523, R2: -0.6935 + +FOLD 2/5 +GNN Train Loss: 0.0427 +RMSE: 1.0528, MAE: 0.7952, R2: -0.7973 + +FOLD 3/5 +GNN Train Loss: 0.0492 +RMSE: 0.9462, MAE: 0.7342, R2: -0.4290 + +FOLD 4/5 +GNN Train Loss: 0.0451 +RMSE: 1.0330, MAE: 0.7819, R2: -0.5171 + +FOLD 5/5 +GNN Train Loss: 0.0329 +RMSE: 0.9770, MAE: 0.7392, R2: -0.2486 + +====== K-FOLD SUMMARY ====== +RMSE: 0.9913 [0.9535, 1.0315] +MAE: 0.7613 [0.7408, 0.7830] +R2: -0.5398 [-0.6997, -0.3913] + +★ Using fold 3 model for test inference +RMSE: 1.0255, MAE: 0.7877, R2: -0.7128 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.02549298456732, 'mae': 0.7876872420310974, 'r2': -0.7127711772918701} +Test RMSE: 1.0252 (95 % CI: 0.9381–1.1124) + +Test MAE : 0.7877 (95 % CI: 0.7225–0.8542) + +Test R² : -0.7225 (95 % CI: -1.0383–-0.4411) + diff --git a/logs/ic50-bench/sage/sage_selfies_ic50_20250729_211550.txt b/logs/ic50-bench/sage/sage_selfies_ic50_20250729_211550.txt new file mode 100644 index 0000000000000000000000000000000000000000..84f0223da1ab7b2c805b3ea52103e2f49c5deb5d --- /dev/null +++ b/logs/ic50-bench/sage/sage_selfies_ic50_20250729_211550.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9577 +RMSE: 0.6977, MAE: 0.5781, R2: 0.0844 + +FOLD 2/5 +GNN Train Loss: 0.9350 +RMSE: 0.7821, MAE: 0.6234, R2: 0.0080 + +FOLD 3/5 +GNN Train Loss: 0.9495 +RMSE: 0.7856, MAE: 0.6087, R2: 0.0149 + +FOLD 4/5 +GNN Train Loss: 0.9579 +RMSE: 0.8086, MAE: 0.6277, R2: 0.0704 + +FOLD 5/5 +GNN Train Loss: 0.9546 +RMSE: 0.8536, MAE: 0.6359, R2: 0.0470 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7851 [0.7375, 0.8257] +MAE: 0.6149 [0.5942, 0.6309] +R2: 0.0454 [0.0199, 0.0714] + +★ Using fold 1 model for test inference +RMSE: 0.7417, MAE: 0.5873, R2: 0.1039 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7417450238386533, 'mae': 0.5873402953147888, 'r2': 0.10392731428146362} +Test RMSE: 0.7415 (95 % CI: 0.6707–0.8179) + +Test MAE : 0.5863 (95 % CI: 0.5470–0.6322) + +Test R² : 0.1009 (95 % CI: 0.0581–0.1476) + diff --git a/logs/ic50-bench/sage/sage_smiles_ic50_20250729_211439.txt b/logs/ic50-bench/sage/sage_smiles_ic50_20250729_211439.txt new file mode 100644 index 0000000000000000000000000000000000000000..be3c4d142fb8d6fb266f8ef84d34591d6733d653 --- /dev/null +++ b/logs/ic50-bench/sage/sage_smiles_ic50_20250729_211439.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on ic50 + +FOLD 1/5 +GNN Train Loss: 0.9581 +RMSE: 0.6984, MAE: 0.5778, R2: 0.0826 + +FOLD 2/5 +GNN Train Loss: 0.9439 +RMSE: 0.7823, MAE: 0.6210, R2: 0.0076 + +FOLD 3/5 +GNN Train Loss: 0.9420 +RMSE: 0.7912, MAE: 0.6063, R2: 0.0009 + +FOLD 4/5 +GNN Train Loss: 0.9628 +RMSE: 0.8055, MAE: 0.6218, R2: 0.0776 + +FOLD 5/5 +GNN Train Loss: 0.9532 +RMSE: 0.8581, MAE: 0.6535, R2: 0.0367 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7878 [0.7366, 0.8314] +MAE: 0.6161 [0.5949, 0.6377] +R2: 0.0414 [0.0166, 0.0714] + +★ Using fold 1 model for test inference +RMSE: 0.7417, MAE: 0.5871, R2: 0.1041 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7416587954185646, 'mae': 0.5871381163597107, 'r2': 0.10413569211959839} +Test RMSE: 0.7418 (95 % CI: 0.6700–0.8067) + +Test MAE : 0.5868 (95 % CI: 0.5416–0.6296) + +Test R² : 0.1023 (95 % CI: 0.0585–0.1453) + diff --git a/logs/lipophil-bench/gat/gat_ecfp_lipophil_20250729_144532.txt b/logs/lipophil-bench/gat/gat_ecfp_lipophil_20250729_144532.txt new file mode 100644 index 0000000000000000000000000000000000000000..28408b534adfc845d1000bb4eb0d70b4f09d7f81 --- /dev/null +++ b/logs/lipophil-bench/gat/gat_ecfp_lipophil_20250729_144532.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on lipophil + +FOLD 1/5 +GNN Train Loss: 0.0733 +RMSE: 0.9729, MAE: 0.7342, R2: 0.3566 + +FOLD 2/5 +GNN Train Loss: 0.0766 +RMSE: 1.0224, MAE: 0.7443, R2: 0.3446 + +FOLD 3/5 +GNN Train Loss: 0.0773 +RMSE: 1.0058, MAE: 0.7261, R2: 0.2751 + +FOLD 4/5 +GNN Train Loss: 0.0752 +RMSE: 0.9836, MAE: 0.7139, R2: 0.3275 + +FOLD 5/5 +GNN Train Loss: 0.0649 +RMSE: 1.0762, MAE: 0.7633, R2: 0.1630 + +====== K-FOLD SUMMARY ====== +RMSE: 1.0128 [0.9837, 1.0448] +MAE: 0.7360 [0.7220, 0.7501] +R2: 0.2946 [0.2302, 0.3460] + +★ Using fold 1 model for test inference +RMSE: 0.9953, MAE: 0.7423, R2: 0.2942 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.9952930598254346, 'mae': 0.7422714829444885, 'r2': 0.29423272609710693} +Test RMSE: 0.9952 (95 % CI: 0.9277–1.0610) + +Test MAE : 0.7434 (95 % CI: 0.7020–0.7866) + +Test R² : 0.2916 (95 % CI: 0.1867–0.3866) + diff --git a/logs/lipophil-bench/gat/gat_selfies_lipophil_20250729_144243.txt b/logs/lipophil-bench/gat/gat_selfies_lipophil_20250729_144243.txt new file mode 100644 index 0000000000000000000000000000000000000000..f51c75632f081d417573cf9c807066fcfd662783 --- /dev/null +++ b/logs/lipophil-bench/gat/gat_selfies_lipophil_20250729_144243.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9046 +RMSE: 1.1631, MAE: 0.9465, R2: 0.0806 + +FOLD 2/5 +GNN Train Loss: 0.8937 +RMSE: 1.2244, MAE: 0.9675, R2: 0.0599 + +FOLD 3/5 +GNN Train Loss: 0.9217 +RMSE: 1.1358, MAE: 0.9208, R2: 0.0756 + +FOLD 4/5 +GNN Train Loss: 0.9085 +RMSE: 1.1185, MAE: 0.9116, R2: 0.1303 + +FOLD 5/5 +GNN Train Loss: 0.8873 +RMSE: 1.0831, MAE: 0.8740, R2: 0.1523 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1456 [1.1078, 1.1910] +MAE: 0.9234 [0.8965, 0.9521] +R2: 0.1003 [0.0703, 0.1325] + +★ Using fold 5 model for test inference +RMSE: 1.1278, MAE: 0.9182, R2: 0.0939 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1277524338198939, 'mae': 0.9181647896766663, 'r2': 0.09387707710266113} +Test RMSE: 1.1282 (95 % CI: 1.0802–1.1763) + +Test MAE : 0.9185 (95 % CI: 0.8759–0.9594) + +Test R² : 0.0929 (95 % CI: 0.0552–0.1304) + diff --git a/logs/lipophil-bench/gat/gat_smiles_lipophil_20250729_144032.txt b/logs/lipophil-bench/gat/gat_smiles_lipophil_20250729_144032.txt new file mode 100644 index 0000000000000000000000000000000000000000..0104390439c7e5b7e31bcf0083fe284f779346cb --- /dev/null +++ b/logs/lipophil-bench/gat/gat_smiles_lipophil_20250729_144032.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9043 +RMSE: 1.1505, MAE: 0.9285, R2: 0.1004 + +FOLD 2/5 +GNN Train Loss: 0.8908 +RMSE: 1.2168, MAE: 0.9671, R2: 0.0716 + +FOLD 3/5 +GNN Train Loss: 0.8833 +RMSE: 1.1212, MAE: 0.9150, R2: 0.0992 + +FOLD 4/5 +GNN Train Loss: 0.9213 +RMSE: 1.1300, MAE: 0.9221, R2: 0.1123 + +FOLD 5/5 +GNN Train Loss: 0.8848 +RMSE: 1.0984, MAE: 0.8827, R2: 0.1281 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1437 [1.1139, 1.1799] +MAE: 0.9233 [0.8996, 0.9477] +R2: 0.1025 [0.0855, 0.1187] + +★ Using fold 5 model for test inference +RMSE: 1.1343, MAE: 0.9207, R2: 0.0833 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1343294181808476, 'mae': 0.9206894040107727, 'r2': 0.08327740430831909} +Test RMSE: 1.1348 (95 % CI: 1.0856–1.1893) + +Test MAE : 0.9200 (95 % CI: 0.8745–0.9628) + +Test R² : 0.0828 (95 % CI: 0.0441–0.1190) + diff --git a/logs/lipophil-bench/gcn/gcn_ecfp_lipophil_20250729_144337.txt b/logs/lipophil-bench/gcn/gcn_ecfp_lipophil_20250729_144337.txt new file mode 100644 index 0000000000000000000000000000000000000000..7b0bc8babc088734d287d7de048cd9f8767ee9df --- /dev/null +++ b/logs/lipophil-bench/gcn/gcn_ecfp_lipophil_20250729_144337.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on lipophil + +FOLD 1/5 +GNN Train Loss: 0.0810 +RMSE: 0.8803, MAE: 0.6539, R2: 0.4733 + +FOLD 2/5 +GNN Train Loss: 0.0993 +RMSE: 0.9675, MAE: 0.7270, R2: 0.4131 + +FOLD 3/5 +GNN Train Loss: 0.0965 +RMSE: 0.9384, MAE: 0.6848, R2: 0.3690 + +FOLD 4/5 +GNN Train Loss: 0.0954 +RMSE: 0.9100, MAE: 0.6657, R2: 0.4243 + +FOLD 5/5 +GNN Train Loss: 0.0945 +RMSE: 0.9985, MAE: 0.7148, R2: 0.2796 + +====== K-FOLD SUMMARY ====== +RMSE: 0.9391 [0.9038, 0.9745] +MAE: 0.6886 [0.6648, 0.7137] +R2: 0.3911 [0.3352, 0.4427] + +★ Using fold 1 model for test inference +RMSE: 0.8876, MAE: 0.6653, R2: 0.4388 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.8875540945196227, 'mae': 0.6652875542640686, 'r2': 0.4387592077255249} +Test RMSE: 0.8879 (95 % CI: 0.8351–0.9399) + +Test MAE : 0.6652 (95 % CI: 0.6265–0.7059) + +Test R² : 0.4365 (95 % CI: 0.3612–0.5059) + diff --git a/logs/lipophil-bench/gcn/gcn_selfies_lipophil_20250729_144207.txt b/logs/lipophil-bench/gcn/gcn_selfies_lipophil_20250729_144207.txt new file mode 100644 index 0000000000000000000000000000000000000000..001cb84e64b3024754a55f4a8f4b3dc962120bca --- /dev/null +++ b/logs/lipophil-bench/gcn/gcn_selfies_lipophil_20250729_144207.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9409 +RMSE: 1.1697, MAE: 0.9427, R2: 0.0700 + +FOLD 2/5 +GNN Train Loss: 0.9189 +RMSE: 1.2370, MAE: 0.9954, R2: 0.0405 + +FOLD 3/5 +GNN Train Loss: 0.9263 +RMSE: 1.1620, MAE: 0.9607, R2: 0.0325 + +FOLD 4/5 +GNN Train Loss: 0.9460 +RMSE: 1.1464, MAE: 0.9439, R2: 0.0864 + +FOLD 5/5 +GNN Train Loss: 0.9238 +RMSE: 1.1317, MAE: 0.9087, R2: 0.0746 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1703 [1.1438, 1.2055] +MAE: 0.9515 [0.9260, 0.9746] +R2: 0.0608 [0.0425, 0.0784] + +★ Using fold 5 model for test inference +RMSE: 1.1623, MAE: 0.9360, R2: 0.0375 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1623023121418028, 'mae': 0.9359506368637085, 'r2': 0.03750663995742798} +Test RMSE: 1.1611 (95 % CI: 1.1101–1.2170) + +Test MAE : 0.9350 (95 % CI: 0.8883–0.9810) + +Test R² : 0.0363 (95 % CI: -0.0005–0.0723) + diff --git a/logs/lipophil-bench/gcn/gcn_smiles_lipophil_20250729_143939.txt b/logs/lipophil-bench/gcn/gcn_smiles_lipophil_20250729_143939.txt new file mode 100644 index 0000000000000000000000000000000000000000..7fd7c1bab01fc7c3820d50cc8a8b23c2c80a70a5 --- /dev/null +++ b/logs/lipophil-bench/gcn/gcn_smiles_lipophil_20250729_143939.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9439 +RMSE: 1.1685, MAE: 0.9335, R2: 0.0720 + +FOLD 2/5 +GNN Train Loss: 0.9205 +RMSE: 1.2594, MAE: 0.9845, R2: 0.0055 + +FOLD 3/5 +GNN Train Loss: 0.9297 +RMSE: 1.1534, MAE: 0.9457, R2: 0.0467 + +FOLD 4/5 +GNN Train Loss: 0.9435 +RMSE: 1.1322, MAE: 0.9166, R2: 0.1088 + +FOLD 5/5 +GNN Train Loss: 0.9292 +RMSE: 1.1321, MAE: 0.9175, R2: 0.0739 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1678 [1.1364, 1.2127] +MAE: 0.9397 [0.9202, 0.9634] +R2: 0.0609 [0.0274, 0.0894] + +★ Using fold 5 model for test inference +RMSE: 1.1597, MAE: 0.9432, R2: 0.0418 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.159716898638803, 'mae': 0.9431800246238708, 'r2': 0.041783809661865234} +Test RMSE: 1.1608 (95 % CI: 1.1118–1.2106) + +Test MAE : 0.9434 (95 % CI: 0.8950–0.9914) + +Test R² : 0.0403 (95 % CI: 0.0106–0.0705) + diff --git a/logs/lipophil-bench/gin/gin_ecfp_lipophil_20250729_144424.txt b/logs/lipophil-bench/gin/gin_ecfp_lipophil_20250729_144424.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e4c6523c0cec944a3aa498c2fef8371085836e8 --- /dev/null +++ b/logs/lipophil-bench/gin/gin_ecfp_lipophil_20250729_144424.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on lipophil + +FOLD 1/5 +GNN Train Loss: 0.0195 +RMSE: 0.8490, MAE: 0.6262, R2: 0.5101 + +FOLD 2/5 +GNN Train Loss: 0.0137 +RMSE: 0.9177, MAE: 0.6870, R2: 0.4719 + +FOLD 3/5 +GNN Train Loss: 0.0129 +RMSE: 0.9082, MAE: 0.6689, R2: 0.4089 + +FOLD 4/5 +GNN Train Loss: 0.0134 +RMSE: 0.8464, MAE: 0.6088, R2: 0.5020 + +FOLD 5/5 +GNN Train Loss: 0.0134 +RMSE: 0.8992, MAE: 0.6566, R2: 0.4157 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8845 [0.8580, 0.9102] +MAE: 0.6491 [0.6254, 0.6737] +R2: 0.4622 [0.4242, 0.4977] + +★ Using fold 4 model for test inference +RMSE: 0.8654, MAE: 0.6462, R2: 0.4664 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.8654021709650296, 'mae': 0.6462228894233704, 'r2': 0.46642494201660156} +Test RMSE: 0.8650 (95 % CI: 0.8108–0.9210) + +Test MAE : 0.6453 (95 % CI: 0.6075–0.6823) + +Test R² : 0.4649 (95 % CI: 0.3911–0.5311) + diff --git a/logs/lipophil-bench/gin/gin_selfies_lipophil_20250729_144210.txt b/logs/lipophil-bench/gin/gin_selfies_lipophil_20250729_144210.txt new file mode 100644 index 0000000000000000000000000000000000000000..dd8838b1bcca48197b006b08b2e61a1a0cd521c8 --- /dev/null +++ b/logs/lipophil-bench/gin/gin_selfies_lipophil_20250729_144210.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9354 +RMSE: 1.1653, MAE: 0.9319, R2: 0.0770 + +FOLD 2/5 +GNN Train Loss: 0.9326 +RMSE: 1.2696, MAE: 0.9904, R2: -0.0107 + +FOLD 3/5 +GNN Train Loss: 0.9241 +RMSE: 1.1574, MAE: 0.9511, R2: 0.0402 + +FOLD 4/5 +GNN Train Loss: 0.9332 +RMSE: 1.1407, MAE: 0.9335, R2: 0.0954 + +FOLD 5/5 +GNN Train Loss: 0.9380 +RMSE: 1.1380, MAE: 0.9175, R2: 0.0642 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1741 [1.1435, 1.2230] +MAE: 0.9449 [0.9265, 0.9673] +R2: 0.0530 [0.0170, 0.0818] + +★ Using fold 5 model for test inference +RMSE: 1.1686, MAE: 0.9416, R2: 0.0271 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1685877661890365, 'mae': 0.9416383504867554, 'r2': 0.027068614959716797} +Test RMSE: 1.1683 (95 % CI: 1.1167–1.2200) + +Test MAE : 0.9407 (95 % CI: 0.8937–0.9877) + +Test R² : 0.0263 (95 % CI: -0.0084–0.0592) + diff --git a/logs/lipophil-bench/gin/gin_smiles_lipophil_20250729_144009.txt b/logs/lipophil-bench/gin/gin_smiles_lipophil_20250729_144009.txt new file mode 100644 index 0000000000000000000000000000000000000000..9a1a63707cc23d497383d42c34bcd26d86536383 --- /dev/null +++ b/logs/lipophil-bench/gin/gin_smiles_lipophil_20250729_144009.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on lipophil + +FOLD 1/5 +GNN Train Loss: 0.9268 +RMSE: 1.1635, MAE: 0.9229, R2: 0.0799 + +FOLD 2/5 +GNN Train Loss: 0.9184 +RMSE: 1.2309, MAE: 0.9833, R2: 0.0500 + +FOLD 3/5 +GNN Train Loss: 0.9177 +RMSE: 1.1425, MAE: 0.9345, R2: 0.0646 + +FOLD 4/5 +GNN Train Loss: 0.9301 +RMSE: 1.1873, MAE: 0.9833, R2: 0.0200 + +FOLD 5/5 +GNN Train Loss: 0.9246 +RMSE: 1.1353, MAE: 0.9108, R2: 0.0686 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1720 [1.1438, 1.2045] +MAE: 0.9474 [0.9204, 0.9735] +R2: 0.0568 [0.0380, 0.0723] + +★ Using fold 5 model for test inference +RMSE: 1.1698, MAE: 0.9387, R2: 0.0251 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1697787545981366, 'mae': 0.9386965036392212, 'r2': 0.02508443593978882} +Test RMSE: 1.1698 (95 % CI: 1.1100–1.2263) + +Test MAE : 0.9380 (95 % CI: 0.8912–0.9883) + +Test R² : 0.0239 (95 % CI: -0.0147–0.0625) + diff --git a/logs/lipophil-bench/gp+tanimoto/gp_ecfp_lipophil_20250728_151353.txt b/logs/lipophil-bench/gp+tanimoto/gp_ecfp_lipophil_20250728_151353.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f645d13604a986fb7aad2e4dc2a8a27df094241 --- /dev/null +++ b/logs/lipophil-bench/gp+tanimoto/gp_ecfp_lipophil_20250728_151353.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on lipophil + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7270, MAE: 0.5327, R2: 0.6408 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 0.8035, MAE: 0.5910, R2: 0.5952 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7576, MAE: 0.5731, R2: 0.5888 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7141, MAE: 0.5306, R2: 0.6455 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7635, MAE: 0.5711, R2: 0.5788 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7528 [0.7279, 0.7802] +MAE: 0.5595 [0.5395, 0.5798] +R2: 0.6101 [0.5861, 0.6342] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 0.7500, MAE: 0.5596, R2: 0.5992 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.750037190910615, 'mae': 0.5596041773131916, 'r2': 0.5992023876075723} +Test RMSE: 0.7498 (95 % CI: 0.7048–0.7956) + +Test MAE : 0.5594 (95 % CI: 0.5255–0.5936) + +Test R² : 0.5964 (95 % CI: 0.5473–0.6434) + diff --git a/logs/lipophil-bench/gp+tanimoto/gp_selfies_lipophil_20250728_151311.txt b/logs/lipophil-bench/gp+tanimoto/gp_selfies_lipophil_20250728_151311.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f35725ab354886a30c52391a72fa9d94f657e7e --- /dev/null +++ b/logs/lipophil-bench/gp+tanimoto/gp_selfies_lipophil_20250728_151311.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on lipophil + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 1.2131, MAE: 0.9734, R2: -0.0002 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 1.2638, MAE: 1.0187, R2: -0.0015 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 1.1822, MAE: 0.9767, R2: -0.0014 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 1.2005, MAE: 0.9741, R2: -0.0018 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 1.1767, MAE: 0.9494, R2: -0.0005 + +====== K-FOLD SUMMARY ====== +RMSE: 1.2077 [1.1836, 1.2373] +MAE: 0.9782 [0.9598, 1.0012] +R2: -0.0011 [-0.0016, -0.0005] + +★ Using fold 5 model for test inference +Evaluating GP model... +RMSE: 1.1853, MAE: 0.9536, R2: -0.0009 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1852768402423433, 'mae': 0.953605998096012, 'r2': -0.0009194432153685206} +Test RMSE: 1.1848 (95 % CI: 1.1314–1.2404) + +Test MAE : 0.9536 (95 % CI: 0.9081–0.9977) + +Test R² : -0.0020 (95 % CI: -0.0085–-0.0000) + diff --git a/logs/lipophil-bench/gp+tanimoto/gp_smiles_lipophil_20250728_151222.txt b/logs/lipophil-bench/gp+tanimoto/gp_smiles_lipophil_20250728_151222.txt new file mode 100644 index 0000000000000000000000000000000000000000..53beaaadc2d9ea395f7f53d8a228e87055df66f2 --- /dev/null +++ b/logs/lipophil-bench/gp+tanimoto/gp_smiles_lipophil_20250728_151222.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on lipophil + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7270, MAE: 0.5327, R2: 0.6408 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 0.8035, MAE: 0.5910, R2: 0.5952 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7576, MAE: 0.5731, R2: 0.5888 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7141, MAE: 0.5306, R2: 0.6455 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 0.7635, MAE: 0.5711, R2: 0.5788 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7529 [0.7279, 0.7790] +MAE: 0.5596 [0.5395, 0.5798] +R2: 0.6100 [0.5861, 0.6336] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 0.7500, MAE: 0.5596, R2: 0.5992 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.750037190910615, 'mae': 0.5596041773131916, 'r2': 0.5992023876075723} +Test RMSE: 0.7494 (95 % CI: 0.7043–0.7955) + +Test MAE : 0.5600 (95 % CI: 0.5294–0.5925) + +Test R² : 0.5987 (95 % CI: 0.5520–0.6420) + diff --git a/logs/lipophil-bench/sage/sage_ecfp_lipophil_20250729_144516.txt b/logs/lipophil-bench/sage/sage_ecfp_lipophil_20250729_144516.txt new file mode 100644 index 0000000000000000000000000000000000000000..c627e935659288896f20e75e1030b31787bc3edf --- /dev/null +++ b/logs/lipophil-bench/sage/sage_ecfp_lipophil_20250729_144516.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on lipophil + +FOLD 1/5 +GNN Train Loss: 0.0894 +RMSE: 0.9230, MAE: 0.6961, R2: 0.4209 + +FOLD 2/5 +GNN Train Loss: 0.0784 +RMSE: 1.0060, MAE: 0.7459, R2: 0.3654 + +FOLD 3/5 +GNN Train Loss: 0.0530 +RMSE: 0.9831, MAE: 0.7154, R2: 0.3075 + +FOLD 4/5 +GNN Train Loss: 0.0745 +RMSE: 0.9216, MAE: 0.6708, R2: 0.4096 + +FOLD 5/5 +GNN Train Loss: 0.0388 +RMSE: 0.9985, MAE: 0.7188, R2: 0.2796 + +====== K-FOLD SUMMARY ====== +RMSE: 0.9662 [0.9345, 0.9969] +MAE: 0.7092 [0.6860, 0.7305] +R2: 0.3567 [0.3079, 0.4053] + +★ Using fold 4 model for test inference +RMSE: 0.9368, MAE: 0.7012, R2: 0.3747 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.9368432923817854, 'mae': 0.7012372612953186, 'r2': 0.37469273805618286} +Test RMSE: 0.9368 (95 % CI: 0.8804–0.9945) + +Test MAE : 0.7010 (95 % CI: 0.6612–0.7449) + +Test R² : 0.3716 (95 % CI: 0.2895–0.4509) + diff --git a/logs/lipophil-bench/sage/sage_selfies_lipophil_20250729_144310.txt b/logs/lipophil-bench/sage/sage_selfies_lipophil_20250729_144310.txt new file mode 100644 index 0000000000000000000000000000000000000000..26dbc872e8fd8df92a07fae1c8ca02813b8d7585 --- /dev/null +++ b/logs/lipophil-bench/sage/sage_selfies_lipophil_20250729_144310.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on lipophil + +FOLD 1/5 +GNN Train Loss: 0.8825 +RMSE: 1.1587, MAE: 0.9459, R2: 0.0874 + +FOLD 2/5 +GNN Train Loss: 0.8673 +RMSE: 1.1984, MAE: 0.9549, R2: 0.0994 + +FOLD 3/5 +GNN Train Loss: 0.8836 +RMSE: 1.1211, MAE: 0.9127, R2: 0.0993 + +FOLD 4/5 +GNN Train Loss: 0.9064 +RMSE: 1.1168, MAE: 0.8875, R2: 0.1330 + +FOLD 5/5 +GNN Train Loss: 0.8944 +RMSE: 1.1698, MAE: 0.9199, R2: 0.0112 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1530 [1.1269, 1.1790] +MAE: 0.9244 [0.9041, 0.9447] +R2: 0.0852 [0.0441, 0.1172] + +★ Using fold 4 model for test inference +RMSE: 1.1445, MAE: 0.9115, R2: 0.0667 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1445227612906463, 'mae': 0.9114981293678284, 'r2': 0.0667276382446289} +Test RMSE: 1.1439 (95 % CI: 1.0905–1.1974) + +Test MAE : 0.9102 (95 % CI: 0.8663–0.9532) + +Test R² : 0.0656 (95 % CI: 0.0217–0.1076) + diff --git a/logs/lipophil-bench/sage/sage_smiles_lipophil_20250729_144104.txt b/logs/lipophil-bench/sage/sage_smiles_lipophil_20250729_144104.txt new file mode 100644 index 0000000000000000000000000000000000000000..136c3a7bd5715d505d01fa16302d7dc4d3c58764 --- /dev/null +++ b/logs/lipophil-bench/sage/sage_smiles_lipophil_20250729_144104.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on lipophil + +FOLD 1/5 +GNN Train Loss: 0.8946 +RMSE: 1.1640, MAE: 0.9516, R2: 0.0791 + +FOLD 2/5 +GNN Train Loss: 0.8616 +RMSE: 1.2005, MAE: 0.9491, R2: 0.0963 + +FOLD 3/5 +GNN Train Loss: 0.8683 +RMSE: 1.1732, MAE: 0.9156, R2: 0.0137 + +FOLD 4/5 +GNN Train Loss: 0.8872 +RMSE: 1.1102, MAE: 0.8885, R2: 0.1432 + +FOLD 5/5 +GNN Train Loss: 0.8803 +RMSE: 1.1101, MAE: 0.9079, R2: 0.1094 + +====== K-FOLD SUMMARY ====== +RMSE: 1.1517 [1.1209, 1.1823] +MAE: 0.9228 [0.9017, 0.9434] +R2: 0.0886 [0.0494, 0.1244] + +★ Using fold 5 model for test inference +RMSE: 1.1347, MAE: 0.9399, R2: 0.0826 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.1347242337949228, 'mae': 0.9398527145385742, 'r2': 0.08263909816741943} +Test RMSE: 1.1332 (95 % CI: 1.0872–1.1782) + +Test MAE : 0.9405 (95 % CI: 0.8954–0.9844) + +Test R² : 0.0821 (95 % CI: 0.0300–0.1292) + diff --git a/logs/old-res/benchmark_summary.txt b/logs/old-res/benchmark_summary.txt new file mode 100644 index 0000000000000000000000000000000000000000..c9d3ca4e9a402b6865e8d99dd96c4df3437d49eb --- /dev/null +++ b/logs/old-res/benchmark_summary.txt @@ -0,0 +1,164 @@ + +BINDINGDB Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 2.6672 ± 0.4774 1.9156 ± 0.1894 +gat selfies 1.8164 ± 0.2667 1.3696 ± 0.1159 +gat smiles 1.7932 ± 0.2338 1.3722 ± 0.1176 +gcn ecfp 2.1744 ± 0.3132 1.5856 ± 0.1452 +gcn selfies 1.7671 ± 0.2332 1.3612 ± 0.1056 +gcn smiles 1.8313 ± 0.2654 1.3773 ± 0.1171 +gin ecfp 2.0116 ± 0.3040 1.4942 ± 0.1247 +gin selfies 1.7480 ± 0.2425 1.3502 ± 0.1123 +gin smiles 1.7566 ± 0.2513 1.3585 ± 0.1048 +gp+tanimoto ecfp 1.6921 ± 0.2544 1.2645 ± 0.1051 +gp+tanimoto selfies 1.8034 ± 0.2504 1.3793 ± 0.1135 +gp+tanimoto smiles 1.6945 ± 0.2640 1.2650 ± 0.1057 +sage ecfp 2.1945 ± 0.3115 1.6303 ± 0.1384 +sage selfies 1.9251 ± 0.3445 1.4001 ± 0.1262 +sage smiles 1.8614 ± 0.3434 1.3816 ± 0.1282 + +BOILINGPOINT Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 73.1437 ± 6.6197 53.9304 ± 4.6799 +gat selfies 60.0938 ± 4.9932 44.2603 ± 3.9387 +gat smiles 60.0681 ± 4.7094 45.0223 ± 3.8590 +gcn ecfp 63.2157 ± 5.0890 48.2488 ± 3.9244 +gcn selfies 66.5821 ± 5.0110 50.7737 ± 4.1893 +gcn smiles 68.6942 ± 5.0914 52.5543 ± 4.2683 +gin ecfp 59.5471 ± 5.0798 44.7224 ± 3.9753 +gin selfies 72.0029 ± 5.4545 54.6066 ± 4.6104 +gin smiles 70.0021 ± 4.9849 55.1386 ± 4.2748 +gp ecfp 51.6225 ± 4.9579 37.8647 ± 3.4987 +gp selfies 79.3254 ± 5.8622 63.3404 ± 4.5846 +gp smiles 51.5120 ± 5.3235 37.8171 ± 3.5411 +sage ecfp 64.4034 ± 5.4008 47.8241 ± 4.1397 +sage selfies 59.2558 ± 4.7487 44.8262 ± 3.8195 +sage smiles 62.0991 ± 4.6785 46.6419 ± 4.0569 + +ESOL Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 1.2483 ± 0.1534 0.9410 ± 0.1059 +gat selfies 1.5646 ± 0.1858 1.1441 ± 0.1370 +gat smiles 1.5192 ± 0.1740 1.1516 ± 0.1287 +gcn ecfp 1.1634 ± 0.1252 0.8822 ± 0.0988 +gcn selfies 1.6861 ± 0.1825 1.3087 ± 0.1381 +gcn smiles 1.7133 ± 0.1825 1.3146 ± 0.1394 +gin ecfp 1.1526 ± 0.1277 0.8507 ± 0.1042 +gin selfies 1.6538 ± 0.1885 1.2690 ± 0.1427 +gin smiles 1.6409 ± 0.1715 1.2461 ± 0.1419 +gp+tanimoto ecfp 1.0513 ± 0.1187 0.7792 ± 0.0866 +gp+tanimoto selfies 2.1744 ± 0.1980 1.7338 ± 0.1715 +gp+tanimoto smiles 1.0503 ± 0.1235 0.7798 ± 0.1002 +sage ecfp 1.1407 ± 0.1321 0.8713 ± 0.0983 +sage selfies 1.6127 ± 0.1710 1.2302 ± 0.1312 +sage smiles 1.5419 ± 0.1694 1.1597 ± 0.1326 + +FREESOLV Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 2.5469 ± 0.5988 1.7310 ± 0.3236 +gat selfies 3.7543 ± 0.7218 2.8503 ± 0.3962 +gat smiles 3.5968 ± 0.7350 2.6242 ± 0.4419 +gcn ecfp 2.5038 ± 0.6450 1.6743 ± 0.3326 +gcn selfies 3.8168 ± 0.8156 2.7834 ± 0.4549 +gcn smiles 3.8458 ± 0.8551 2.8537 ± 0.4530 +gin ecfp 2.3410 ± 0.5840 1.5615 ± 0.3094 +gin selfies 3.7603 ± 0.8412 2.7327 ± 0.4461 +gin smiles 3.7822 ± 0.8187 2.7178 ± 0.4620 +gp+tanimoto ecfp 2.0696 ± 0.6732 1.3354 ± 0.2849 +gp+tanimoto selfies 4.1141 ± 0.8004 3.0900 ± 0.4399 +gp+tanimoto smiles 2.0787 ± 0.7082 1.3375 ± 0.2831 +sage ecfp 2.5430 ± 0.6463 1.7124 ± 0.3320 +sage selfies 3.8307 ± 0.8413 2.7317 ± 0.4656 +sage smiles 3.7483 ± 0.8613 2.6734 ± 0.4676 + +IC50 Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 1.1000 ± 0.0907 0.8420 ± 0.0685 +gat selfies 0.7474 ± 0.0619 0.6026 ± 0.0412 +gat smiles 0.7569 ± 0.0620 0.6190 ± 0.0446 +gcn ecfp 1.0079 ± 0.0862 0.7721 ± 0.0615 +gcn selfies 0.7475 ± 0.0764 0.5828 ± 0.0459 +gcn smiles 0.7451 ± 0.0747 0.5863 ± 0.0470 +gin ecfp 0.9375 ± 0.0819 0.7075 ± 0.0634 +gin selfies 0.7501 ± 0.0693 0.5891 ± 0.0450 +gin smiles 0.7487 ± 0.0718 0.5905 ± 0.0436 +gp+tanimoto ecfp 0.7660 ± 0.0707 0.5961 ± 0.0485 +gp+tanimoto selfies 0.7833 ± 0.0769 0.6129 ± 0.0476 +gp+tanimoto smiles 0.7647 ± 0.0698 0.5965 ± 0.0480 +sage ecfp 1.0252 ± 0.0872 0.7877 ± 0.0658 +sage selfies 0.7415 ± 0.0736 0.5863 ± 0.0426 +sage smiles 0.7418 ± 0.0683 0.5868 ± 0.0440 + +LIPOPHIL Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 0.9952 ± 0.0666 0.7434 ± 0.0423 +gat selfies 1.1282 ± 0.0480 0.9185 ± 0.0418 +gat smiles 1.1348 ± 0.0519 0.9200 ± 0.0441 +gcn ecfp 0.8879 ± 0.0524 0.6652 ± 0.0397 +gcn selfies 1.1611 ± 0.0534 0.9350 ± 0.0464 +gcn smiles 1.1608 ± 0.0494 0.9434 ± 0.0482 +gin ecfp 0.8650 ± 0.0551 0.6453 ± 0.0374 +gin selfies 1.1683 ± 0.0516 0.9407 ± 0.0470 +gin smiles 1.1698 ± 0.0581 0.9380 ± 0.0485 +gp+tanimoto ecfp 0.7498 ± 0.0454 0.5594 ± 0.0341 +gp+tanimoto selfies 1.1848 ± 0.0545 0.9536 ± 0.0448 +gp+tanimoto smiles 0.7494 ± 0.0456 0.5600 ± 0.0316 +sage ecfp 0.9368 ± 0.0571 0.7010 ± 0.0418 +sage selfies 1.1439 ± 0.0534 0.9102 ± 0.0435 +sage smiles 1.1332 ± 0.0455 0.9405 ± 0.0445 + +POLYATOMIC Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +polyatomic unknown 1.5655 ± 0.1263 1.2717 ± 0.0984 +polyatomic unknown 1.0860 ± 0.1354 0.8171 ± 0.0812 +polyatomic unknown 1.5153 ± 0.3395 1.0409 ± 0.2181 +polyatomic unknown 0.6975 ± 0.0551 0.5724 ± 0.0436 +polyatomic unknown 0.7913 ± 0.0575 0.5953 ± 0.0382 +polyatomic unknown 0.7043 ± 0.1095 0.5150 ± 0.0722 +polyatomic unknown 48.1815 ± 5.4987 33.3759 ± 3.7307 + +POLYATOMICBASIC Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +polyatomicbasic unknown 1.5608 ± 0.1286 1.2846 ± 0.0970 +polyatomicbasic unknown 1.6139 ± 0.3575 1.1024 ± 0.2127 +polyatomicbasic unknown 0.8041 ± 0.0534 0.6136 ± 0.0394 +polyatomicbasic unknown 48.0145 ± 5.1040 34.3959 ± 3.6937 +polyatomicbasic unknown 1.2799 ± 0.1198 0.9838 ± 0.0891 +polyatomicbasic unknown 0.7214 ± 0.0589 0.5949 ± 0.0452 +polyatomicbasic unknown 0.6955 ± 0.1043 0.5174 ± 0.0707 + +QM9 Benchmark Summary: + +Model Encoding RMSE ± MAE ± +----------------------------------------------------------------- +gat ecfp 3.4215 ± 0.2718 2.6676 ± 0.2061 +gat selfies 2.0540 ± 0.1546 1.6340 ± 0.1216 +gat smiles 2.0858 ± 0.1508 1.6694 ± 0.1175 +gcn ecfp 3.0271 ± 0.2273 2.3643 ± 0.1876 +gcn selfies 2.8783 ± 0.1980 2.3116 ± 0.1699 +gcn smiles 2.8837 ± 0.2133 2.3072 ± 0.1694 +gin ecfp 2.8340 ± 0.2436 2.1962 ± 0.1761 +gin selfies 2.8427 ± 0.2038 2.2164 ± 0.1699 +gin smiles 3.2328 ± 0.2544 2.5469 ± 0.1975 +gp+tanimoto ecfp 2.2497 ± 0.2188 1.6977 ± 0.1431 +gp+tanimoto selfies 3.9735 ± 0.3086 3.1156 ± 0.2450 +gp+tanimoto smiles 2.2494 ± 0.2074 1.7009 ± 0.1444 +sage ecfp 3.2668 ± 0.2386 2.6014 ± 0.1890 +sage selfies 2.1091 ± 0.1556 1.6486 ± 0.1295 +sage smiles 2.0653 ± 0.1655 1.6209 ± 0.1244 diff --git a/logs/old-res/create_table.py b/logs/old-res/create_table.py new file mode 100644 index 0000000000000000000000000000000000000000..3e36eb437132e4ab20877ca335ae77d8acdaf46d --- /dev/null +++ b/logs/old-res/create_table.py @@ -0,0 +1,85 @@ +import os +import re +from collections import defaultdict + +LOG_ROOT = "logs" +SUMMARY_FILE = "benchmark_summary.txt" + + +def parse_ci_section(content): + """Extracts Test RMSE, MAE, and their 95% CI intervals from log content.""" + rmse_match = re.search( + r"Test RMSE: ([\d.]+)\s+\(95 % CI: ([\d.]+)[–-]([\d.]+)\)", content + ) + mae_match = re.search( + r"Test MAE\s*: ([\d.]+)\s+\(95 % CI: ([\d.]+)[–-]([\d.]+)\)", content + ) + + if not (rmse_match and mae_match): + return None + + rmse, rmse_lo, rmse_hi = map(float, rmse_match.groups()) + mae, mae_lo, mae_hi = map(float, mae_match.groups()) + + rmse_pm = (rmse_hi - rmse_lo) / 2 + mae_pm = (mae_hi - mae_lo) / 2 + + return {"rmse": rmse, "rmse_pm": rmse_pm, "mae": mae, "mae_pm": mae_pm} + + +def extract_encoding(fname): + for enc in ["ecfp", "smiles", "selfies"]: + if enc in fname.lower(): + return enc + return "unknown" + + +# Map benchmark name → list of rows +benchmark_tables = defaultdict(list) + +for benchmark_dir in os.listdir(LOG_ROOT): + if not benchmark_dir.endswith("-bench"): + continue + + benchmark_name = benchmark_dir.replace("-bench", "") + benchmark_path = os.path.join(LOG_ROOT, benchmark_dir) + + for model in os.listdir(benchmark_path): + model_path = os.path.join(benchmark_path, model) + if not os.path.isdir(model_path): + continue + + for log_file in os.listdir(model_path): + if not log_file.endswith(".txt"): + continue + + encoding = extract_encoding(log_file) + with open(os.path.join(model_path, log_file), "r") as f: + content = f.read() + + parsed = parse_ci_section(content) + if parsed is None: + continue + + benchmark_tables[benchmark_name].append( + {"model": model, "encoding": encoding, **parsed} + ) + +# Write to file +with open(SUMMARY_FILE, "w") as f: + + def log(line=""): + f.write(line + "\n") + print(line) + + for benchmark, rows in sorted(benchmark_tables.items()): + log(f"\n{benchmark.upper()} Benchmark Summary:\n") + log(f"{'Model':<13} {'Encoding':<8} {'RMSE ±':<20} {'MAE ±':<20}") + log("-" * 65) + + for row in sorted(rows, key=lambda r: (r["model"], r["encoding"])): + log( + f"{row['model']:<13} {row['encoding']:<8} " + f"{row['rmse']:.4f} ± {row['rmse_pm']:.4f} " + f"{row['mae']:.4f} ± {row['mae_pm']:.4f}" + ) diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_bindingdb_20250730_121135.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_bindingdb_20250730_121135.txt new file mode 100644 index 0000000000000000000000000000000000000000..47bf96216e9f1ddba3321334da06ad999db0aebc --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_bindingdb_20250730_121135.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on bindingdb + +FOLD 1/5 +RMSE: 1.5744, MAE: 1.2909, R2: 0.0316 + +FOLD 2/5 +RMSE: 1.6103, MAE: 1.3237, R2: 0.0171 + +FOLD 3/5 +RMSE: 1.6149, MAE: 1.3295, R2: 0.0158 + +FOLD 4/5 +RMSE: 1.5555, MAE: 1.2655, R2: 0.0634 + +FOLD 5/5 +RMSE: 1.5907, MAE: 1.2956, R2: 0.0400 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5889 [1.5701, 1.6073] +MAE: 1.3003 [1.2775, 1.3204] +R2: 0.0338 [0.0195, 0.0494] + +★ Using fold 4 model for test inference +RMSE: 1.5648, MAE: 1.2730, R2: 0.0633 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5647968957507463, 'mae': 1.2729694843292236, 'r2': 0.06330239772796631} +Test RMSE: 1.5655 (95 % CI: 1.4428–1.6954) + +Test MAE : 1.2717 (95 % CI: 1.1765–1.3733) + +Test R² : 0.0597 (95 % CI: -0.0280–0.1509) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_boilingpoint_20250730_063040.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_boilingpoint_20250730_063040.txt new file mode 100644 index 0000000000000000000000000000000000000000..a3b70112b396930a2427bc4ecd7fe6aaee907a92 --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_boilingpoint_20250730_063040.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on boilingpoint + +FOLD 1/5 +RMSE: 51.6539, MAE: 33.6179, R2: 0.6318 + +FOLD 2/5 +RMSE: 48.4909, MAE: 33.5824, R2: 0.6860 + +FOLD 3/5 +RMSE: 50.8034, MAE: 34.7265, R2: 0.6569 + +FOLD 4/5 +RMSE: 49.6399, MAE: 34.2908, R2: 0.6607 + +FOLD 5/5 +RMSE: 52.4927, MAE: 36.6232, R2: 0.6316 + +====== K-FOLD SUMMARY ====== +RMSE: 50.5846 [49.4130, 51.8170] +MAE: 34.5713 [33.7383, 35.6440] +R2: 0.6534 [0.6368, 0.6701] + +★ Using fold 2 model for test inference +RMSE: 48.2116, MAE: 33.3949, R2: 0.6859 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 48.211554672155614, 'mae': 33.394927978515625, 'r2': 0.6859204173088074} +Test RMSE: 48.1815 (95 % CI: 42.9072–53.9047) + +Test MAE : 33.3759 (95 % CI: 29.6556–37.1169) + +Test R² : 0.6824 (95 % CI: 0.6007–0.7504) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_esol_20250730_064253.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_esol_20250730_064253.txt new file mode 100644 index 0000000000000000000000000000000000000000..b9b26ac3f625adeba0234632bcd4f2280c1728ba --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_esol_20250730_064253.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on esol + +FOLD 1/5 +RMSE: 0.9593, MAE: 0.7000, R2: 0.7531 + +FOLD 2/5 +RMSE: 0.6840, MAE: 0.4976, R2: 0.8612 + +FOLD 3/5 +RMSE: 0.7321, MAE: 0.5618, R2: 0.8531 + +FOLD 4/5 +RMSE: 0.7950, MAE: 0.5903, R2: 0.8246 + +FOLD 5/5 +RMSE: 0.8642, MAE: 0.6658, R2: 0.7967 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8065 [0.7255, 0.8936] +MAE: 0.6036 [0.5347, 0.6644] +R2: 0.8184 [0.7835, 0.8490] + +★ Using fold 2 model for test inference +RMSE: 0.7075, MAE: 0.5147, R2: 0.8612 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7074806092102082, 'mae': 0.5146545767784119, 'r2': 0.8611921668052673} +Test RMSE: 0.7043 (95 % CI: 0.5948–0.8139) + +Test MAE : 0.5150 (95 % CI: 0.4441–0.5884) + +Test R² : 0.8595 (95 % CI: 0.8011–0.9025) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_freesolv_20250730_064642.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_freesolv_20250730_064642.txt new file mode 100644 index 0000000000000000000000000000000000000000..452762ba5e2ca46208e8e047b2deb0a8677ab690 --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_freesolv_20250730_064642.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on freesolv + +FOLD 1/5 +RMSE: 1.8681, MAE: 1.3170, R2: 0.7248 + +FOLD 2/5 +RMSE: 1.4955, MAE: 1.0240, R2: 0.8121 + +FOLD 3/5 +RMSE: 1.5607, MAE: 1.0552, R2: 0.7994 + +FOLD 4/5 +RMSE: 1.7659, MAE: 1.2820, R2: 0.7592 + +FOLD 5/5 +RMSE: 1.7600, MAE: 1.2360, R2: 0.7477 + +====== K-FOLD SUMMARY ====== +RMSE: 1.6886 [1.5745, 1.8045] +MAE: 1.1827 [1.0789, 1.2868] +R2: 0.7683 [0.7409, 0.7964] + +★ Using fold 2 model for test inference +RMSE: 1.5264, MAE: 1.0450, R2: 0.8121 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5264313062598338, 'mae': 1.0450139045715332, 'r2': 0.8120720386505127} +Test RMSE: 1.5153 (95 % CI: 1.1836–1.8625) + +Test MAE : 1.0409 (95 % CI: 0.8381–1.2742) + +Test R² : 0.8100 (95 % CI: 0.7173–0.8866) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_ic50_20250730_103222.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_ic50_20250730_103222.txt new file mode 100644 index 0000000000000000000000000000000000000000..2fd0ba28deeb92f56ef890db781915717266cc8e --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_ic50_20250730_103222.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on ic50 + +FOLD 1/5 +RMSE: 0.7340, MAE: 0.5997, R2: -0.0132 + +FOLD 2/5 +RMSE: 0.7114, MAE: 0.5753, R2: 0.0150 + +FOLD 3/5 +RMSE: 0.7676, MAE: 0.6365, R2: -0.1480 + +FOLD 4/5 +RMSE: 0.6961, MAE: 0.5682, R2: 0.0256 + +FOLD 5/5 +RMSE: 0.6831, MAE: 0.5598, R2: 0.0402 + +====== K-FOLD SUMMARY ====== +RMSE: 0.7177 [0.6939, 0.7429] +MAE: 0.5879 [0.5677, 0.6144] +R2: -0.0159 [-0.0863, 0.0293] + +★ Using fold 5 model for test inference +RMSE: 0.6984, MAE: 0.5724, R2: 0.0410 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.6983667435957716, 'mae': 0.5723831653594971, 'r2': 0.04096406698226929} +Test RMSE: 0.6975 (95 % CI: 0.6406–0.7508) + +Test MAE : 0.5724 (95 % CI: 0.5299–0.6172) + +Test R² : 0.0375 (95 % CI: -0.0229–0.0971) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_lipophil_20250730_071349.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_lipophil_20250730_071349.txt new file mode 100644 index 0000000000000000000000000000000000000000..91ca17d29a60d9c36eeb7afb959d9da5d4be072e --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_lipophil_20250730_071349.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on lipophil + +FOLD 1/5 +RMSE: 0.8381, MAE: 0.6517, R2: 0.5226 + +FOLD 2/5 +RMSE: 0.7816, MAE: 0.5874, R2: 0.5756 + +FOLD 3/5 +RMSE: 0.7933, MAE: 0.5945, R2: 0.5777 + +FOLD 4/5 +RMSE: 0.8226, MAE: 0.6172, R2: 0.5426 + +FOLD 5/5 +RMSE: 0.8238, MAE: 0.6292, R2: 0.5456 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8121 [0.7945, 0.8293] +MAE: 0.6161 [0.5962, 0.6358] +R2: 0.5531 [0.5346, 0.5704] + +★ Using fold 2 model for test inference +RMSE: 0.7911, MAE: 0.5945, R2: 0.5756 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7911001278045477, 'mae': 0.5945204496383667, 'r2': 0.5756356716156006} +Test RMSE: 0.7913 (95 % CI: 0.7365–0.8514) + +Test MAE : 0.5953 (95 % CI: 0.5563–0.6327) + +Test R² : 0.5766 (95 % CI: 0.5145–0.6325) + diff --git a/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_qm9_20250730_101641.txt b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_qm9_20250730_101641.txt new file mode 100644 index 0000000000000000000000000000000000000000..f9bf4a636e32918eb3d329dd26919c6daf4cb6b7 --- /dev/null +++ b/logs/polyatomic-bench/polyatomic/polyatomic_polyatomic_qm9_20250730_101641.txt @@ -0,0 +1,33 @@ +Experiment: polyatomic+polyatomic on qm9 + +FOLD 1/5 +RMSE: 1.6468, MAE: 1.4297, R2: 0.8533 + +FOLD 2/5 +RMSE: 2.9690, MAE: 2.7931, R2: 0.5317 + +FOLD 3/5 +RMSE: 1.5836, MAE: 1.3249, R2: 0.8696 + +FOLD 4/5 +RMSE: 1.0997, MAE: 0.8261, R2: 0.9376 + +FOLD 5/5 +RMSE: 1.2515, MAE: 0.9500, R2: 0.9164 + +====== K-FOLD SUMMARY ====== +RMSE: 1.7117 [1.2572, 2.3484] +MAE: 1.4661 [0.9753, 2.1518] +R2: 0.8179 [0.6729, 0.9155] + +★ Using fold 4 model for test inference +RMSE: 1.0867, MAE: 0.8167, R2: 0.9376 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.0866557428672936, 'mae': 0.8167256116867065, 'r2': 0.9376417994499207} +Test RMSE: 1.0860 (95 % CI: 0.9564–1.2272) + +Test MAE : 0.8171 (95 % CI: 0.7381–0.9006) + +Test R² : 0.9367 (95 % CI: 0.9147–0.9544) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_bindingdb_20250730_214718.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_bindingdb_20250730_214718.txt new file mode 100644 index 0000000000000000000000000000000000000000..dff575e526888e2777c65784d459005251baa461 --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_bindingdb_20250730_214718.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on bindingdb + +FOLD 1/5 +GNN Train Loss: 0.8965 +RMSE: 1.5462, MAE: 1.2688, R2: 0.0660 + +FOLD 2/5 +GNN Train Loss: 0.9111 +RMSE: 1.5596, MAE: 1.2989, R2: 0.0780 + +FOLD 3/5 +GNN Train Loss: 0.8896 +RMSE: 1.6106, MAE: 1.3290, R2: 0.0211 + +FOLD 4/5 +GNN Train Loss: 0.9180 +RMSE: 1.6593, MAE: 1.3322, R2: -0.0659 + +FOLD 5/5 +GNN Train Loss: 0.9116 +RMSE: 1.5981, MAE: 1.3265, R2: 0.0310 + +====== K-FOLD SUMMARY ====== +RMSE: 1.5943 [1.5619, 1.6296] +MAE: 1.3110 [1.2869, 1.3298] +R2: 0.0261 [-0.0201, 0.0638] + +★ Using fold 1 model for test inference +RMSE: 1.5625, MAE: 1.2823, R2: 0.0660 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.5625251767991144, 'mae': 1.2822535037994385, 'r2': 0.0660201907157898} +Test RMSE: 1.5608 (95 % CI: 1.4350–1.6923) + +Test MAE : 1.2846 (95 % CI: 1.1873–1.3814) + +Test R² : 0.0614 (95 % CI: -0.0021–0.1309) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_boilingpoint_20250730_214216.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_boilingpoint_20250730_214216.txt new file mode 100644 index 0000000000000000000000000000000000000000..d927af208417e8bf4ec1c6cac02a4d78688d445e --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_boilingpoint_20250730_214216.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on boilingpoint + +FOLD 1/5 +GNN Train Loss: 0.4130 +RMSE: 50.0972, MAE: 37.4559, R2: 0.6537 + +FOLD 2/5 +GNN Train Loss: 0.3834 +RMSE: 48.2395, MAE: 34.7289, R2: 0.6893 + +FOLD 3/5 +GNN Train Loss: 0.3783 +RMSE: 48.5302, MAE: 36.6299, R2: 0.6869 + +FOLD 4/5 +GNN Train Loss: 0.3835 +RMSE: 48.6366, MAE: 36.8569, R2: 0.6743 + +FOLD 5/5 +GNN Train Loss: 0.4080 +RMSE: 52.3786, MAE: 39.1581, R2: 0.6332 + +====== K-FOLD SUMMARY ====== +RMSE: 49.5443 [48.4352, 51.0945] +MAE: 36.9712 [35.6535, 38.1368] +R2: 0.6678 [0.6496, 0.6853] + +★ Using fold 2 model for test inference +RMSE: 47.9525, MAE: 34.5223, R2: 0.6893 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 47.95245549793305, 'mae': 34.52228546142578, 'r2': 0.6892871856689453} +Test RMSE: 48.0145 (95 % CI: 42.8203–53.0284) + +Test MAE : 34.3959 (95 % CI: 30.7221–38.1095) + +Test R² : 0.6854 (95 % CI: 0.5992–0.7578) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_esol_20250730_204642.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_esol_20250730_204642.txt new file mode 100644 index 0000000000000000000000000000000000000000..6767886d61e8b5e523043433e96bd3d5ddebc614 --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_esol_20250730_204642.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on esol + +FOLD 1/5 +GNN Train Loss: 0.1418 +RMSE: 0.8246, MAE: 0.5939, R2: 0.8176 + +FOLD 2/5 +GNN Train Loss: 0.1645 +RMSE: 0.8813, MAE: 0.6720, R2: 0.7696 + +FOLD 3/5 +GNN Train Loss: 0.1537 +RMSE: 0.7004, MAE: 0.5182, R2: 0.8655 + +FOLD 4/5 +GNN Train Loss: 0.1721 +RMSE: 0.7796, MAE: 0.6028, R2: 0.8314 + +FOLD 5/5 +GNN Train Loss: 0.1769 +RMSE: 0.8983, MAE: 0.7115, R2: 0.7803 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8169 [0.7524, 0.8767] +MAE: 0.6196 [0.5641, 0.6799] +R2: 0.8133 [0.7835, 0.8423] + +★ Using fold 3 model for test inference +RMSE: 0.6963, MAE: 0.5152, R2: 0.8655 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.6963055623414837, 'mae': 0.5152462720870972, 'r2': 0.8655426502227783} +Test RMSE: 0.6955 (95 % CI: 0.5947–0.8033) + +Test MAE : 0.5174 (95 % CI: 0.4523–0.5936) + +Test R² : 0.8647 (95 % CI: 0.8202–0.9010) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_freesolv_20250730_205335.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_freesolv_20250730_205335.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b44c66a3ee4726d44311f8a608b7ece47030945 --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_freesolv_20250730_205335.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on freesolv + +FOLD 1/5 +GNN Train Loss: 0.1480 +RMSE: 2.4752, MAE: 2.0829, R2: 0.5170 + +FOLD 2/5 +GNN Train Loss: 0.1089 +RMSE: 1.5965, MAE: 1.0820, R2: 0.7859 + +FOLD 3/5 +GNN Train Loss: 0.1446 +RMSE: 1.7065, MAE: 1.2664, R2: 0.7602 + +FOLD 4/5 +GNN Train Loss: 0.1632 +RMSE: 2.0845, MAE: 1.4736, R2: 0.6645 + +FOLD 5/5 +GNN Train Loss: 0.1325 +RMSE: 1.8133, MAE: 1.2575, R2: 0.7322 + +====== K-FOLD SUMMARY ====== +RMSE: 1.9365 [1.6839, 2.2646] +MAE: 1.4233 [1.1891, 1.7618] +R2: 0.6924 [0.6030, 0.7649] + +★ Using fold 2 model for test inference +RMSE: 1.6293, MAE: 1.1042, R2: 0.7859 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.6293278795693167, 'mae': 1.104212760925293, 'r2': 0.7858816385269165} +Test RMSE: 1.6139 (95 % CI: 1.2757–1.9908) + +Test MAE : 1.1024 (95 % CI: 0.8973–1.3226) + +Test R² : 0.7810 (95 % CI: 0.6604–0.8753) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_ic50_20250730_214645.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_ic50_20250730_214645.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6368c39979cd6308378302fb45be1179be38383 --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_ic50_20250730_214645.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on ic50 + +FOLD 1/5 +GNN Train Loss: 0.8857 +RMSE: 0.7223, MAE: 0.5989, R2: 0.0188 + +FOLD 2/5 +GNN Train Loss: 0.9291 +RMSE: 0.7255, MAE: 0.5962, R2: -0.0244 + +FOLD 3/5 +GNN Train Loss: 0.8818 +RMSE: 1.2848, MAE: 1.0687, R2: -2.2161 + +FOLD 4/5 +GNN Train Loss: 0.8802 +RMSE: 0.7078, MAE: 0.5809, R2: -0.0074 + +FOLD 5/5 +GNN Train Loss: 0.8611 +RMSE: 0.7062, MAE: 0.5808, R2: -0.0260 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8335 [0.7100, 1.0598] +MAE: 0.6818 [0.5839, 0.8771] +R2: -0.4438 [-1.3360, 0.0012] + +★ Using fold 5 model for test inference +RMSE: 0.7223, MAE: 0.5941, R2: -0.0260 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.7223211387810183, 'mae': 0.5940642356872559, 'r2': -0.02595531940460205} +Test RMSE: 0.7214 (95 % CI: 0.6656–0.7834) + +Test MAE : 0.5949 (95 % CI: 0.5525–0.6428) + +Test R² : -0.0314 (95 % CI: -0.1248–0.0510) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_lipophil_20250730_215150.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_lipophil_20250730_215150.txt new file mode 100644 index 0000000000000000000000000000000000000000..1df0e5212262a049925919e80cdec34468e4f63a --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_lipophil_20250730_215150.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on lipophil + +FOLD 1/5 +GNN Train Loss: 0.4286 +RMSE: 0.8033, MAE: 0.6121, R2: 0.5614 + +FOLD 2/5 +GNN Train Loss: 0.4082 +RMSE: 0.8277, MAE: 0.6283, R2: 0.5242 + +FOLD 3/5 +GNN Train Loss: 0.4646 +RMSE: 1.0686, MAE: 0.8525, R2: 0.2336 + +FOLD 4/5 +GNN Train Loss: 0.4228 +RMSE: 0.8646, MAE: 0.6720, R2: 0.4946 + +FOLD 5/5 +GNN Train Loss: 0.4391 +RMSE: 0.8195, MAE: 0.6323, R2: 0.5503 + +====== K-FOLD SUMMARY ====== +RMSE: 0.8743 [0.8147, 0.9748] +MAE: 0.6832 [0.6226, 0.7724] +R2: 0.4736 [0.3514, 0.5495] + +★ Using fold 1 model for test inference +RMSE: 0.8043, MAE: 0.6128, R2: 0.5614 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 0.804273702649856, 'mae': 0.6127852201461792, 'r2': 0.5613847374916077} +Test RMSE: 0.8041 (95 % CI: 0.7516–0.8585) + +Test MAE : 0.6136 (95 % CI: 0.5733–0.6522) + +Test R² : 0.5617 (95 % CI: 0.4998–0.6203) + diff --git a/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_qm9_20250730_205534.txt b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_qm9_20250730_205534.txt new file mode 100644 index 0000000000000000000000000000000000000000..a3309a52bf26becb445b522e52d3668bbfec3f9c --- /dev/null +++ b/logs/polyatomicbasic-bench/polyatomicbasic/polyatomic_polyatomic_qm9_20250730_205534.txt @@ -0,0 +1,38 @@ +Experiment: polyatomic+polyatomic on qm9 + +FOLD 1/5 +GNN Train Loss: 0.1272 +RMSE: 1.3036, MAE: 0.9929, R2: 0.9081 + +FOLD 2/5 +GNN Train Loss: 0.1336 +RMSE: 1.2810, MAE: 0.9819, R2: 0.9128 + +FOLD 3/5 +GNN Train Loss: 0.1297 +RMSE: 1.4949, MAE: 1.2115, R2: 0.8838 + +FOLD 4/5 +GNN Train Loss: 0.1260 +RMSE: 1.8907, MAE: 1.6264, R2: 0.8157 + +FOLD 5/5 +GNN Train Loss: 0.1265 +RMSE: 1.4262, MAE: 1.1400, R2: 0.8914 + +====== K-FOLD SUMMARY ====== +RMSE: 1.4814 [1.3191, 1.6941] +MAE: 1.1924 [1.0201, 1.4145] +R2: 0.8822 [0.8478, 0.9067] + +★ Using fold 2 model for test inference +RMSE: 1.2848, MAE: 0.9849, R2: 0.9128 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 1.2848398114709658, 'mae': 0.9848641157150269, 'r2': 0.912821888923645} +Test RMSE: 1.2799 (95 % CI: 1.1559–1.3954) + +Test MAE : 0.9838 (95 % CI: 0.8926–1.0708) + +Test R² : 0.9126 (95 % CI: 0.8916–0.9307) + diff --git a/logs/qm9-bench/gat/gat_ecfp_qm9_20250729_194700.txt b/logs/qm9-bench/gat/gat_ecfp_qm9_20250729_194700.txt new file mode 100644 index 0000000000000000000000000000000000000000..73311d7300be546b3fa7dc946aea9b95f29a0926 --- /dev/null +++ b/logs/qm9-bench/gat/gat_ecfp_qm9_20250729_194700.txt @@ -0,0 +1,38 @@ +Experiment: gat+ecfp on qm9 + +FOLD 1/5 +GNN Train Loss: 0.0074 +RMSE: 3.6551, MAE: 2.8615, R2: 0.2774 + +FOLD 2/5 +GNN Train Loss: 0.0061 +RMSE: 3.5943, MAE: 2.7750, R2: 0.2553 + +FOLD 3/5 +GNN Train Loss: 0.0064 +RMSE: 3.7308, MAE: 3.0321, R2: 0.1241 + +FOLD 4/5 +GNN Train Loss: 0.0077 +RMSE: 3.6065, MAE: 2.8540, R2: 0.1510 + +FOLD 5/5 +GNN Train Loss: 0.0101 +RMSE: 3.7474, MAE: 2.8625, R2: 0.2038 + +====== K-FOLD SUMMARY ====== +RMSE: 3.6673 [3.6113, 3.7190] +MAE: 2.8769 [2.8096, 2.9626] +R2: 0.2014 [0.1508, 0.2538] + +★ Using fold 2 model for test inference +RMSE: 3.4218, MAE: 2.6697, R2: 0.2521 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.4217732732274975, 'mae': 2.669717311859131, 'r2': 0.25205492973327637} +Test RMSE: 3.4215 (95 % CI: 3.1587–3.7024) + +Test MAE : 2.6676 (95 % CI: 2.4684–2.8805) + +Test R² : 0.2465 (95 % CI: 0.0813–0.3879) + diff --git a/logs/qm9-bench/gat/gat_selfies_qm9_20250729_194549.txt b/logs/qm9-bench/gat/gat_selfies_qm9_20250729_194549.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f63cb45ab65cc3e0f52d9a64222566a5b8b9398 --- /dev/null +++ b/logs/qm9-bench/gat/gat_selfies_qm9_20250729_194549.txt @@ -0,0 +1,38 @@ +Experiment: gat+selfies on qm9 + +FOLD 1/5 +GNN Train Loss: 0.2854 +RMSE: 2.1931, MAE: 1.7215, R2: 0.7399 + +FOLD 2/5 +GNN Train Loss: 0.2718 +RMSE: 2.1731, MAE: 1.7300, R2: 0.7278 + +FOLD 3/5 +GNN Train Loss: 0.2742 +RMSE: 2.2739, MAE: 1.7726, R2: 0.6746 + +FOLD 4/5 +GNN Train Loss: 0.3050 +RMSE: 2.3055, MAE: 1.8609, R2: 0.6531 + +FOLD 5/5 +GNN Train Loss: 0.2741 +RMSE: 2.0128, MAE: 1.5978, R2: 0.7703 + +====== K-FOLD SUMMARY ====== +RMSE: 2.1908 [2.0971, 2.2727] +MAE: 1.7359 [1.6592, 1.8083] +R2: 0.7147 [0.6766, 0.7520] + +★ Using fold 5 model for test inference +RMSE: 2.0538, MAE: 1.6322, R2: 0.7306 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.0537570253462154, 'mae': 1.6322085857391357, 'r2': 0.730557918548584} +Test RMSE: 2.0540 (95 % CI: 1.8996–2.2088) + +Test MAE : 1.6340 (95 % CI: 1.5147–1.7579) + +Test R² : 0.7285 (95 % CI: 0.6688–0.7808) + diff --git a/logs/qm9-bench/gat/gat_smiles_qm9_20250729_194512.txt b/logs/qm9-bench/gat/gat_smiles_qm9_20250729_194512.txt new file mode 100644 index 0000000000000000000000000000000000000000..f56b4dce65b36705c842389714de7c484336e263 --- /dev/null +++ b/logs/qm9-bench/gat/gat_smiles_qm9_20250729_194512.txt @@ -0,0 +1,38 @@ +Experiment: gat+smiles on qm9 + +FOLD 1/5 +GNN Train Loss: 0.3084 +RMSE: 2.2514, MAE: 1.7896, R2: 0.7259 + +FOLD 2/5 +GNN Train Loss: 0.2735 +RMSE: 2.1329, MAE: 1.7215, R2: 0.7378 + +FOLD 3/5 +GNN Train Loss: 0.2957 +RMSE: 2.3379, MAE: 1.8553, R2: 0.6560 + +FOLD 4/5 +GNN Train Loss: 0.2833 +RMSE: 2.0665, MAE: 1.6689, R2: 0.7213 + +FOLD 5/5 +GNN Train Loss: 0.3057 +RMSE: 2.2844, MAE: 1.8206, R2: 0.7041 + +====== K-FOLD SUMMARY ====== +RMSE: 2.2150 [2.1196, 2.2992] +MAE: 1.7717 [1.7141, 1.8283] +R2: 0.7091 [0.6821, 0.7297] + +★ Using fold 4 model for test inference +RMSE: 2.0868, MAE: 1.6729, R2: 0.7218 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.0867681670969653, 'mae': 1.6728832721710205, 'r2': 0.7218265533447266} +Test RMSE: 2.0858 (95 % CI: 1.9299–2.2315) + +Test MAE : 1.6694 (95 % CI: 1.5566–1.7916) + +Test R² : 0.7203 (95 % CI: 0.6680–0.7650) + diff --git a/logs/qm9-bench/gcn/gcn_ecfp_qm9_20250729_191731.txt b/logs/qm9-bench/gcn/gcn_ecfp_qm9_20250729_191731.txt new file mode 100644 index 0000000000000000000000000000000000000000..7d241bb85aab7ac09d2fa452977ea0f331d9fc60 --- /dev/null +++ b/logs/qm9-bench/gcn/gcn_ecfp_qm9_20250729_191731.txt @@ -0,0 +1,38 @@ +Experiment: gcn+ecfp on qm9 + +FOLD 1/5 +GNN Train Loss: 0.0109 +RMSE: 3.3349, MAE: 2.6179, R2: 0.3985 + +FOLD 2/5 +GNN Train Loss: 0.0109 +RMSE: 3.2271, MAE: 2.4627, R2: 0.3997 + +FOLD 3/5 +GNN Train Loss: 0.0079 +RMSE: 3.3010, MAE: 2.6413, R2: 0.3143 + +FOLD 4/5 +GNN Train Loss: 0.0082 +RMSE: 3.0394, MAE: 2.3730, R2: 0.3970 + +FOLD 5/5 +GNN Train Loss: 0.0161 +RMSE: 3.4245, MAE: 2.5344, R2: 0.3351 + +====== K-FOLD SUMMARY ====== +RMSE: 3.2647 [3.1440, 3.3671] +MAE: 2.5279 [2.4411, 2.6106] +R2: 0.3691 [0.3355, 0.3984] + +★ Using fold 4 model for test inference +RMSE: 3.0253, MAE: 2.3681, R2: 0.4153 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.025347281453962, 'mae': 2.36812162399292, 'r2': 0.4153206944465637} +Test RMSE: 3.0271 (95 % CI: 2.8036–3.2582) + +Test MAE : 2.3643 (95 % CI: 2.1796–2.5548) + +Test R² : 0.4078 (95 % CI: 0.2733–0.5225) + diff --git a/logs/qm9-bench/gcn/gcn_selfies_qm9_20250729_191013.txt b/logs/qm9-bench/gcn/gcn_selfies_qm9_20250729_191013.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ca0a2fc0cfcff364b9e019acf12b6cbd02f5953 --- /dev/null +++ b/logs/qm9-bench/gcn/gcn_selfies_qm9_20250729_191013.txt @@ -0,0 +1,38 @@ +Experiment: gcn+selfies on qm9 + +FOLD 1/5 +GNN Train Loss: 0.5622 +RMSE: 3.2195, MAE: 2.6335, R2: 0.4394 + +FOLD 2/5 +GNN Train Loss: 0.5517 +RMSE: 3.0470, MAE: 2.4250, R2: 0.4648 + +FOLD 3/5 +GNN Train Loss: 0.5529 +RMSE: 3.0739, MAE: 2.4017, R2: 0.4054 + +FOLD 4/5 +GNN Train Loss: 0.5481 +RMSE: 2.8668, MAE: 2.3676, R2: 0.4635 + +FOLD 5/5 +GNN Train Loss: 0.5785 +RMSE: 3.0099, MAE: 2.4172, R2: 0.4863 + +====== K-FOLD SUMMARY ====== +RMSE: 3.0449 [2.9389, 3.1505] +MAE: 2.4483 [2.3859, 2.5455] +R2: 0.4524 [0.4284, 0.4734] + +★ Using fold 4 model for test inference +RMSE: 2.8881, MAE: 2.3135, R2: 0.4672 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.8881001761120233, 'mae': 2.3134849071502686, 'r2': 0.4671661853790283} +Test RMSE: 2.8783 (95 % CI: 2.6781–3.0741) + +Test MAE : 2.3116 (95 % CI: 2.1404–2.4802) + +Test R² : 0.4645 (95 % CI: 0.3865–0.5357) + diff --git a/logs/qm9-bench/gcn/gcn_smiles_qm9_20250729_190201.txt b/logs/qm9-bench/gcn/gcn_smiles_qm9_20250729_190201.txt new file mode 100644 index 0000000000000000000000000000000000000000..d64108022a0e7db50e5e609f0f1de51520797234 --- /dev/null +++ b/logs/qm9-bench/gcn/gcn_smiles_qm9_20250729_190201.txt @@ -0,0 +1,38 @@ +Experiment: gcn+smiles on qm9 + +FOLD 1/5 +GNN Train Loss: 0.5447 +RMSE: 3.1920, MAE: 2.5963, R2: 0.4489 + +FOLD 2/5 +GNN Train Loss: 0.5482 +RMSE: 3.0516, MAE: 2.4293, R2: 0.4632 + +FOLD 3/5 +GNN Train Loss: 0.5535 +RMSE: 3.1099, MAE: 2.4444, R2: 0.3914 + +FOLD 4/5 +GNN Train Loss: 0.5527 +RMSE: 2.8635, MAE: 2.3650, R2: 0.4648 + +FOLD 5/5 +GNN Train Loss: 0.5598 +RMSE: 3.0072, MAE: 2.4244, R2: 0.4873 + +====== K-FOLD SUMMARY ====== +RMSE: 3.0438 [2.9415, 3.1311] +MAE: 2.4510 [2.3937, 2.5285] +R2: 0.4506 [0.4201, 0.4735] + +★ Using fold 4 model for test inference +RMSE: 2.8863, MAE: 2.3104, R2: 0.4678 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.886309727661628, 'mae': 2.310394048690796, 'r2': 0.46782660484313965} +Test RMSE: 2.8837 (95 % CI: 2.6715–3.0981) + +Test MAE : 2.3072 (95 % CI: 2.1428–2.4815) + +Test R² : 0.4680 (95 % CI: 0.3945–0.5370) + diff --git a/logs/qm9-bench/gin/gin_ecfp_qm9_20250729_194626.txt b/logs/qm9-bench/gin/gin_ecfp_qm9_20250729_194626.txt new file mode 100644 index 0000000000000000000000000000000000000000..c970a4cf0eb33e65e295dbd42f61771cda9798af --- /dev/null +++ b/logs/qm9-bench/gin/gin_ecfp_qm9_20250729_194626.txt @@ -0,0 +1,38 @@ +Experiment: gin+ecfp on qm9 + +FOLD 1/5 +GNN Train Loss: 0.0045 +RMSE: 3.1198, MAE: 2.4173, R2: 0.4736 + +FOLD 2/5 +GNN Train Loss: 0.0042 +RMSE: 2.9351, MAE: 2.2230, R2: 0.5034 + +FOLD 3/5 +GNN Train Loss: 0.0032 +RMSE: 2.9299, MAE: 2.3032, R2: 0.4598 + +FOLD 4/5 +GNN Train Loss: 0.0055 +RMSE: 2.8644, MAE: 2.2220, R2: 0.4644 + +FOLD 5/5 +GNN Train Loss: 0.0058 +RMSE: 3.0417, MAE: 2.2540, R2: 0.4754 + +====== K-FOLD SUMMARY ====== +RMSE: 2.9794 [2.9058, 3.0662] +MAE: 2.2817 [2.2290, 2.3458] +R2: 0.4754 [0.4644, 0.4891] + +★ Using fold 4 model for test inference +RMSE: 2.8386, MAE: 2.1980, R2: 0.4853 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.838615897138395, 'mae': 2.1979875564575195, 'r2': 0.485268771648407} +Test RMSE: 2.8340 (95 % CI: 2.5881–3.0753) + +Test MAE : 2.1962 (95 % CI: 2.0323–2.3846) + +Test R² : 0.4828 (95 % CI: 0.3824–0.5708) + diff --git a/logs/qm9-bench/gin/gin_selfies_qm9_20250729_194508.txt b/logs/qm9-bench/gin/gin_selfies_qm9_20250729_194508.txt new file mode 100644 index 0000000000000000000000000000000000000000..fd5a93e5307df9211482fa8d120ec043d1899fcd --- /dev/null +++ b/logs/qm9-bench/gin/gin_selfies_qm9_20250729_194508.txt @@ -0,0 +1,38 @@ +Experiment: gin+selfies on qm9 + +FOLD 1/5 +GNN Train Loss: 0.6156 +RMSE: 3.5032, MAE: 2.8585, R2: 0.3363 + +FOLD 2/5 +GNN Train Loss: 0.6698 +RMSE: 3.4555, MAE: 2.7458, R2: 0.3117 + +FOLD 3/5 +GNN Train Loss: 0.6770 +RMSE: 3.3339, MAE: 2.6352, R2: 0.3006 + +FOLD 4/5 +GNN Train Loss: 0.5653 +RMSE: 2.8604, MAE: 2.3347, R2: 0.4659 + +FOLD 5/5 +GNN Train Loss: 0.6825 +RMSE: 3.3380, MAE: 2.7048, R2: 0.3682 + +====== K-FOLD SUMMARY ====== +RMSE: 3.3007 [3.0750, 3.4598] +MAE: 2.6530 [2.4908, 2.7913] +R2: 0.3560 [0.3122, 0.4133] + +★ Using fold 4 model for test inference +RMSE: 2.8455, MAE: 2.2142, R2: 0.4828 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.8455333776907707, 'mae': 2.214185953140259, 'r2': 0.482757031917572} +Test RMSE: 2.8427 (95 % CI: 2.6353–3.0429) + +Test MAE : 2.2164 (95 % CI: 2.0508–2.3906) + +Test R² : 0.4800 (95 % CI: 0.4168–0.5372) + diff --git a/logs/qm9-bench/gin/gin_smiles_qm9_20250729_194423.txt b/logs/qm9-bench/gin/gin_smiles_qm9_20250729_194423.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec009814811b7b290a0388f3acb122e0a6d388e8 --- /dev/null +++ b/logs/qm9-bench/gin/gin_smiles_qm9_20250729_194423.txt @@ -0,0 +1,38 @@ +Experiment: gin+smiles on qm9 + +FOLD 1/5 +GNN Train Loss: 0.6121 +RMSE: 3.3527, MAE: 2.7085, R2: 0.3921 + +FOLD 2/5 +GNN Train Loss: 0.6780 +RMSE: 3.4579, MAE: 2.7309, R2: 0.3107 + +FOLD 3/5 +GNN Train Loss: 0.7171 +RMSE: 3.4569, MAE: 2.7905, R2: 0.2480 + +FOLD 4/5 +GNN Train Loss: 0.6696 +RMSE: 3.2452, MAE: 2.5907, R2: 0.3126 + +FOLD 5/5 +GNN Train Loss: 0.7133 +RMSE: 3.3385, MAE: 2.6902, R2: 0.3681 + +====== K-FOLD SUMMARY ====== +RMSE: 3.3693 [3.3039, 3.4365] +MAE: 2.7024 [2.6423, 2.7577] +R2: 0.3264 [0.2846, 0.3710] + +★ Using fold 4 model for test inference +RMSE: 3.2408, MAE: 2.5424, R2: 0.3291 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.240750428644464, 'mae': 2.5423645973205566, 'r2': 0.32909899950027466} +Test RMSE: 3.2328 (95 % CI: 2.9722–3.4809) + +Test MAE : 2.5469 (95 % CI: 2.3512–2.7462) + +Test R² : 0.3259 (95 % CI: 0.2565–0.3961) + diff --git a/logs/qm9-bench/gp+tanimoto/gp_ecfp_qm9_20250729_195012.txt b/logs/qm9-bench/gp+tanimoto/gp_ecfp_qm9_20250729_195012.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7d7d52ae86b7cdef8727dcf2934a1e806f09730 --- /dev/null +++ b/logs/qm9-bench/gp+tanimoto/gp_ecfp_qm9_20250729_195012.txt @@ -0,0 +1,44 @@ +Experiment: gp+ecfp on qm9 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 2.4946, MAE: 1.7582, R2: 0.6634 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 2.3520, MAE: 1.6626, R2: 0.6811 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 2.2294, MAE: 1.6499, R2: 0.6872 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 2.1215, MAE: 1.5877, R2: 0.7062 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 2.4429, MAE: 1.7087, R2: 0.6616 + +====== K-FOLD SUMMARY ====== +RMSE: 2.3257 [2.1892, 2.4454] +MAE: 1.6735 [1.6269, 1.7266] +R2: 0.6798 [0.6671, 0.6939] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 2.2501, MAE: 1.6984, R2: 0.6766 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.2500902017685833, 'mae': 1.6984001519775394, 'r2': 0.6765798302070667} +Test RMSE: 2.2497 (95 % CI: 2.0322–2.4699) + +Test MAE : 1.6977 (95 % CI: 1.5522–1.8385) + +Test R² : 0.6751 (95 % CI: 0.6084–0.7329) + diff --git a/logs/qm9-bench/gp+tanimoto/gp_selfies_qm9_20250729_194933.txt b/logs/qm9-bench/gp+tanimoto/gp_selfies_qm9_20250729_194933.txt new file mode 100644 index 0000000000000000000000000000000000000000..980e6617e7457afeaa80b8a175fee565f3cccfa3 --- /dev/null +++ b/logs/qm9-bench/gp+tanimoto/gp_selfies_qm9_20250729_194933.txt @@ -0,0 +1,44 @@ +Experiment: gp+selfies on qm9 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 4.3116, MAE: 3.3226, R2: -0.0054 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 4.1692, MAE: 3.3082, R2: -0.0020 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 3.9913, MAE: 3.2292, R2: -0.0025 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 3.9146, MAE: 3.1610, R2: -0.0002 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 4.2071, MAE: 3.3354, R2: -0.0036 + +====== K-FOLD SUMMARY ====== +RMSE: 4.1201 [3.9961, 4.2413] +MAE: 3.2717 [3.2095, 3.3248] +R2: -0.0027 [-0.0041, -0.0013] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 3.9851, MAE: 3.1175, R2: -0.0145 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.9851265713885824, 'mae': 3.1174835504150393, 'r2': -0.014498672106591837} +Test RMSE: 3.9735 (95 % CI: 3.6688–4.2860) + +Test MAE : 3.1156 (95 % CI: 2.8811–3.3711) + +Test R² : -0.0166 (95 % CI: -0.0450–-0.0006) + diff --git a/logs/qm9-bench/gp+tanimoto/gp_smiles_qm9_20250729_194953.txt b/logs/qm9-bench/gp+tanimoto/gp_smiles_qm9_20250729_194953.txt new file mode 100644 index 0000000000000000000000000000000000000000..b8151fced5076ef36f83a275c604666e348e1512 --- /dev/null +++ b/logs/qm9-bench/gp+tanimoto/gp_smiles_qm9_20250729_194953.txt @@ -0,0 +1,44 @@ +Experiment: gp+smiles on qm9 + +FOLD 1/5 +Training GP model... +Evaluating GP model... +RMSE: 2.4946, MAE: 1.7582, R2: 0.6634 + +FOLD 2/5 +Training GP model... +Evaluating GP model... +RMSE: 2.3520, MAE: 1.6626, R2: 0.6811 + +FOLD 3/5 +Training GP model... +Evaluating GP model... +RMSE: 2.2294, MAE: 1.6499, R2: 0.6872 + +FOLD 4/5 +Training GP model... +Evaluating GP model... +RMSE: 2.1215, MAE: 1.5877, R2: 0.7062 + +FOLD 5/5 +Training GP model... +Evaluating GP model... +RMSE: 2.4429, MAE: 1.7087, R2: 0.6616 + +====== K-FOLD SUMMARY ====== +RMSE: 2.3280 [2.2107, 2.4454] +MAE: 1.6736 [1.6243, 1.7193] +R2: 0.6804 [0.6668, 0.6962] + +★ Using fold 4 model for test inference +Evaluating GP model... +RMSE: 2.2501, MAE: 1.6984, R2: 0.6766 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.2500902017685833, 'mae': 1.6984001519775394, 'r2': 0.6765798302070667} +Test RMSE: 2.2494 (95 % CI: 2.0552–2.4700) + +Test MAE : 1.7009 (95 % CI: 1.5588–1.8477) + +Test R² : 0.6737 (95 % CI: 0.6025–0.7322) + diff --git a/logs/qm9-bench/sage/sage_ecfp_qm9_20250729_194724.txt b/logs/qm9-bench/sage/sage_ecfp_qm9_20250729_194724.txt new file mode 100644 index 0000000000000000000000000000000000000000..62914e51f50e68fede1757caa8938248c60f5866 --- /dev/null +++ b/logs/qm9-bench/sage/sage_ecfp_qm9_20250729_194724.txt @@ -0,0 +1,38 @@ +Experiment: sage+ecfp on qm9 + +FOLD 1/5 +GNN Train Loss: 0.0082 +RMSE: 3.4585, MAE: 2.7464, R2: 0.3531 + +FOLD 2/5 +GNN Train Loss: 0.0083 +RMSE: 3.4747, MAE: 2.6598, R2: 0.3040 + +FOLD 3/5 +GNN Train Loss: 0.0063 +RMSE: 3.4931, MAE: 2.8059, R2: 0.2322 + +FOLD 4/5 +GNN Train Loss: 0.0054 +RMSE: 3.2948, MAE: 2.5736, R2: 0.2914 + +FOLD 5/5 +GNN Train Loss: 0.0082 +RMSE: 3.5366, MAE: 2.6402, R2: 0.2908 + +====== K-FOLD SUMMARY ====== +RMSE: 3.4519 [3.3704, 3.5105] +MAE: 2.6860 [2.6200, 2.7583] +R2: 0.2945 [0.2584, 0.3283] + +★ Using fold 4 model for test inference +RMSE: 3.2710, MAE: 2.5969, R2: 0.3165 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 3.2710478078578284, 'mae': 2.596869468688965, 'r2': 0.3164960741996765} +Test RMSE: 3.2668 (95 % CI: 3.0253–3.5025) + +Test MAE : 2.6014 (95 % CI: 2.4126–2.7905) + +Test R² : 0.3113 (95 % CI: 0.1619–0.4291) + diff --git a/logs/qm9-bench/sage/sage_selfies_qm9_20250729_194607.txt b/logs/qm9-bench/sage/sage_selfies_qm9_20250729_194607.txt new file mode 100644 index 0000000000000000000000000000000000000000..bfc92747de5bb1b93213b374585b08ba3305686a --- /dev/null +++ b/logs/qm9-bench/sage/sage_selfies_qm9_20250729_194607.txt @@ -0,0 +1,38 @@ +Experiment: sage+selfies on qm9 + +FOLD 1/5 +GNN Train Loss: 0.2847 +RMSE: 2.2463, MAE: 1.7667, R2: 0.7271 + +FOLD 2/5 +GNN Train Loss: 0.3041 +RMSE: 2.2506, MAE: 1.8240, R2: 0.7080 + +FOLD 3/5 +GNN Train Loss: 0.2822 +RMSE: 2.1953, MAE: 1.6796, R2: 0.6967 + +FOLD 4/5 +GNN Train Loss: 0.2957 +RMSE: 2.2515, MAE: 1.8522, R2: 0.6691 + +FOLD 5/5 +GNN Train Loss: 0.2636 +RMSE: 2.1238, MAE: 1.6822, R2: 0.7443 + +====== K-FOLD SUMMARY ====== +RMSE: 2.2141 [2.1634, 2.2501] +MAE: 1.7625 [1.6981, 1.8238] +R2: 0.7086 [0.6862, 0.7298] + +★ Using fold 5 model for test inference +RMSE: 2.1151, MAE: 1.6480, R2: 0.7142 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.1151070032489776, 'mae': 1.6480343341827393, 'r2': 0.7142199277877808} +Test RMSE: 2.1091 (95 % CI: 1.9550–2.2662) + +Test MAE : 1.6486 (95 % CI: 1.5287–1.7876) + +Test R² : 0.7125 (95 % CI: 0.6538–0.7630) + diff --git a/logs/qm9-bench/sage/sage_smiles_qm9_20250729_194516.txt b/logs/qm9-bench/sage/sage_smiles_qm9_20250729_194516.txt new file mode 100644 index 0000000000000000000000000000000000000000..e75c829e30f18ef6a6a933000bb885b54c2bf43a --- /dev/null +++ b/logs/qm9-bench/sage/sage_smiles_qm9_20250729_194516.txt @@ -0,0 +1,38 @@ +Experiment: sage+smiles on qm9 + +FOLD 1/5 +GNN Train Loss: 0.3702 +RMSE: 2.6015, MAE: 2.0626, R2: 0.6340 + +FOLD 2/5 +GNN Train Loss: 0.2840 +RMSE: 2.2323, MAE: 1.8078, R2: 0.7128 + +FOLD 3/5 +GNN Train Loss: 0.3115 +RMSE: 2.4131, MAE: 1.8830, R2: 0.6336 + +FOLD 4/5 +GNN Train Loss: 0.2993 +RMSE: 2.1367, MAE: 1.7539, R2: 0.7020 + +FOLD 5/5 +GNN Train Loss: 0.2886 +RMSE: 2.0654, MAE: 1.6310, R2: 0.7581 + +====== K-FOLD SUMMARY ====== +RMSE: 2.2896 [2.1273, 2.4708] +MAE: 1.8286 [1.7155, 1.9650] +R2: 0.6881 [0.6475, 0.7288] + +★ Using fold 5 model for test inference +RMSE: 2.0721, MAE: 1.6229, R2: 0.7257 + +====== HELD-OUT TEST METRICS ====== +{'rmse': 2.0721445866218438, 'mae': 1.622860312461853, 'r2': 0.7257117033004761} +Test RMSE: 2.0653 (95 % CI: 1.9078–2.2388) + +Test MAE : 1.6209 (95 % CI: 1.4989–1.7477) + +Test R² : 0.7252 (95 % CI: 0.6699–0.7749) + diff --git a/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_20250807_045300.txt b/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_20250807_045300.txt new file mode 100644 index 0000000000000000000000000000000000000000..7e845851e30d6f5960dea3ac8bfbfdca3a9ea12a --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_20250807_045300.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5817, MAE: 1.3008 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.5067, MAE: 1.2239 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4248, MAE: 1.1470 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5569, MAE: 1.2781 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.4903, MAE: 1.2241 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5121 ± 0.0547 +Unbiased Validation MAE: 1.2348 ± 0.0532 +VAL FOLD RMSEs: [1.5816965, 1.5066572, 1.4247608, 1.5569185, 1.4903052] +VAL FOLD MAEs: [1.3007947, 1.2238969, 1.1469992, 1.2781212, 1.2241163] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7747 (95% CI: [1.5486, 2.0455]) +Test MAE: 1.3358 (95% CI: [1.2245, 1.4462]) diff --git a/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..11dc61dbdfac61c81e5fcef775258c2ac1183f85 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_ecfp_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5120676,0.05474511,1.2347857,0.053242885,1.7746966,1.5486429065465928,2.0454548835754394,1.3358259,1.224511170387268,1.4462348997592926 diff --git a/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_20250807_034517.txt b/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_20250807_034517.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec85b242104ae8f5e9abb2b2718ba895df20f792 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_20250807_034517.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5283, MAE: 1.2674 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4920, MAE: 1.2204 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4492, MAE: 1.1976 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5062, MAE: 1.2247 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.4635, MAE: 1.2226 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4878 ± 0.0285 +Unbiased Validation MAE: 1.2265 ± 0.0226 +VAL FOLD RMSEs: [1.5282543, 1.491987, 1.4492154, 1.50623, 1.4635013] +VAL FOLD MAEs: [1.2673509, 1.2204257, 1.1975647, 1.2247156, 1.2225773] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7817 (95% CI: [1.5607, 2.0491]) +Test MAE: 1.3597 (95% CI: [1.2529, 1.4823]) diff --git a/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..c515b3b7d7d01f3c0744963b16e88e21564e3e0a --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_selfies_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4878376,0.028540961,1.2265269,0.022634098,1.7816975,1.5606752246618272,2.0491412580013275,1.359728,1.2528696984052659,1.4822619646787643 diff --git a/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_20250807_022659.txt b/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_20250807_022659.txt new file mode 100644 index 0000000000000000000000000000000000000000..0ecae49956b03adb2d0b9c913e86123c967c46b2 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_20250807_022659.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5261, MAE: 1.2592 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4928, MAE: 1.2250 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4538, MAE: 1.1990 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.5162, MAE: 1.2420 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.4679, MAE: 1.2229 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4913 ± 0.0275 +Unbiased Validation MAE: 1.2296 ± 0.0202 +VAL FOLD RMSEs: [1.5261068, 1.4928026, 1.4537531, 1.5161968, 1.4678531] +VAL FOLD MAEs: [1.2592499, 1.2250473, 1.1989826, 1.2420312, 1.2228922] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7542 (95% CI: [1.5358, 2.0151]) +Test MAE: 1.3558 (95% CI: [1.2542, 1.4743]) diff --git a/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..b47c1b8400baacbfd8cb82711319b06531ffccd0 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gat/gat_smiles_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4913424,0.027543219,1.2296407,0.020183122,1.754195,1.535837560892105,2.0150812566280365,1.3557671,1.2541976243257522,1.4743278205394745 diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_20250806_222738.txt b/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_20250806_222738.txt new file mode 100644 index 0000000000000000000000000000000000000000..ac9b6bde67d0e44a20d947ef2b128b7b7f167a07 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_20250806_222738.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5861, MAE: 1.3031 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.4737, MAE: 1.1930 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4271, MAE: 1.1530 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5594, MAE: 1.2839 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4943, MAE: 1.2206 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5081 ± 0.0577 +Unbiased Validation MAE: 1.2307 ± 0.0559 +VAL FOLD RMSEs: [1.5861493, 1.4737211, 1.4270978, 1.5593641, 1.4943413] +VAL FOLD MAEs: [1.303138, 1.1929528, 1.1530348, 1.2838583, 1.2206385] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7620 (95% CI: [1.5127, 2.0372]) +Test MAE: 1.3219 (95% CI: [1.2180, 1.4427]) diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..b8d48e1505ed2c217f6d15f93e2582f3672f90e4 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_ecfp_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5081347,0.057710074,1.2307246,0.055912502,1.7620425,1.5126783490180968,2.03718324303627,1.3219182,1.2180155336856842,1.4426799565553665 diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_20250806_211800.txt b/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_20250806_211800.txt new file mode 100644 index 0000000000000000000000000000000000000000..87bf0975729a4902a489fde42ccd2f673c2c8bcf --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_20250806_211800.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5336, MAE: 1.2671 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4875, MAE: 1.2176 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.4548, MAE: 1.2033 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5220, MAE: 1.2482 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4627, MAE: 1.2203 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4921 ± 0.0313 +Unbiased Validation MAE: 1.2313 ± 0.0231 +VAL FOLD RMSEs: [1.5335622, 1.4874831, 1.4547646, 1.5219878, 1.4626653] +VAL FOLD MAEs: [1.2671185, 1.2175618, 1.2032896, 1.2482451, 1.2203304] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7696 (95% CI: [1.5361, 2.0330]) +Test MAE: 1.3592 (95% CI: [1.2507, 1.4725]) diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e69b08b384df727ed21308cc44838701b9aeeded --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_selfies_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4920927,0.031285908,1.231309,0.023081375,1.7696327,1.5361118644475937,2.0329567790031433,1.3591579,1.2507229715585708,1.4725051909685134 diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_20250806_191916.txt b/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_20250806_191916.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb96e9fb68fff9238f2154730484fd5d5824d10c --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_20250806_191916.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5371, MAE: 1.2719 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4918, MAE: 1.2200 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4574, MAE: 1.2082 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5207, MAE: 1.2491 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.4658, MAE: 1.2213 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4946 ± 0.0307 +Unbiased Validation MAE: 1.2341 ± 0.0232 +VAL FOLD RMSEs: [1.5371219, 1.491795, 1.4574271, 1.5207254, 1.4658148] +VAL FOLD MAEs: [1.2718537, 1.220011, 1.2082138, 1.2491114, 1.2213442] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.8236 (95% CI: [1.5621, 2.1125]) +Test MAE: 1.3737 (95% CI: [1.2646, 1.5067]) diff --git a/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..7b7cc2f7b384446cf3e490621f733ad178c9d80a --- /dev/null +++ b/logs_hyperparameter/bindingdb/gcn/gcn_smiles_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4945768,0.030688496,1.2341068,0.023160256,1.8236055,1.56207395195961,2.1124946415424346,1.373664,1.2646095514297486,1.506677481532097 diff --git a/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_20250807_012605.txt b/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_20250807_012605.txt new file mode 100644 index 0000000000000000000000000000000000000000..b78aaac2d34e0d03b1beb51f77a9220316569785 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_20250807_012605.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5956, MAE: 1.3143 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4873, MAE: 1.2024 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.4983, MAE: 1.2634 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5597, MAE: 1.2823 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4598, MAE: 1.2049 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5202 ± 0.0499 +Unbiased Validation MAE: 1.2534 ± 0.0438 +VAL FOLD RMSEs: [1.5956372, 1.4873174, 1.4983133, 1.5596871, 1.4598463] +VAL FOLD MAEs: [1.3142992, 1.2023761, 1.2633641, 1.2822583, 1.2049341] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7825 (95% CI: [1.5482, 2.0640]) +Test MAE: 1.3536 (95% CI: [1.2437, 1.4708]) diff --git a/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..ae373773e8f8fcf3e3987d9d94b3d8cdae6e9846 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_ecfp_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5201603,0.049905635,1.2534463,0.043802205,1.7825253,1.5481907904148102,2.0640143573284147,1.3535985,1.2437149852514267,1.4707638442516326 diff --git a/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_20250807_002620.txt b/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_20250807_002620.txt new file mode 100644 index 0000000000000000000000000000000000000000..d8d7100e3b637dac1daac60425dacf11a007a861 --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_20250807_002620.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5372, MAE: 1.2712 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4884, MAE: 1.2204 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.4498, MAE: 1.1955 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5155, MAE: 1.2419 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4810, MAE: 1.2254 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4944 ± 0.0299 +Unbiased Validation MAE: 1.2309 ± 0.0251 +VAL FOLD RMSEs: [1.5371727, 1.4883924, 1.4498001, 1.5154599, 1.4809992] +VAL FOLD MAEs: [1.2712324, 1.220368, 1.1955374, 1.2418671, 1.2254276] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7549 (95% CI: [1.5383, 2.0198]) +Test MAE: 1.3454 (95% CI: [1.2415, 1.4603]) diff --git a/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..a387fc9fbd4245e6e633a054af8ecaa0161cb7ca --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_selfies_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.494365,0.029926026,1.2308866,0.025053363,1.7548525,1.5382527559995651,2.019793528318405,1.3453532,1.2414783656597137,1.4603008449077606 diff --git a/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_20250806_233513.txt b/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_20250806_233513.txt new file mode 100644 index 0000000000000000000000000000000000000000..811e477cec26abe304d42e829c0ec7bf2453bdca --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_20250806_233513.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5386, MAE: 1.2724 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4841, MAE: 1.2102 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4478, MAE: 1.1961 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5224, MAE: 1.2472 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4781, MAE: 1.2242 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4942 ± 0.0325 +Unbiased Validation MAE: 1.2300 ± 0.0271 +VAL FOLD RMSEs: [1.5385734, 1.4840797, 1.4478317, 1.5224414, 1.4781064] +VAL FOLD MAEs: [1.27239, 1.2101815, 1.1960989, 1.2471735, 1.2242327] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7444 (95% CI: [1.5304, 2.0141]) +Test MAE: 1.3390 (95% CI: [1.2356, 1.4498]) diff --git a/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..fc45f09f246befc50c33e2bab06bc6de5a0e499d --- /dev/null +++ b/logs_hyperparameter/bindingdb/gin/gin_smiles_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4942065,0.032490037,1.2300154,0.027081955,1.7444197,1.5304156213998794,2.0140842914581296,1.3389993,1.235577765107155,1.4498291999101638 diff --git a/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_20250806_190514.txt b/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_20250806_190514.txt new file mode 100644 index 0000000000000000000000000000000000000000..da04a9ce9088e7d1bbef06530d5dd7a1e15817f0 --- /dev/null +++ b/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_20250806_190514.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5380, MAE: 1.2675 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4578, MAE: 1.1900 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4386, MAE: 1.1816 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.4881, MAE: 1.2082 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4713, MAE: 1.2093 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4787 ± 0.0338 +Unbiased Validation MAE: 1.2113 ± 0.0300 +VAL FOLD RMSEs: [1.5379897, 1.4577564, 1.4386023, 1.488085, 1.4712801] +VAL FOLD MAEs: [1.2674835, 1.1899962, 1.1816412, 1.2082386, 1.2092552] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7714 (95% CI: [1.5514, 2.0351]) +Test MAE: 1.3648 (95% CI: [1.2580, 1.4743]) diff --git a/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..cba231c3061c565f53faa95b2b9c0455cfa0ea23 --- /dev/null +++ b/logs_hyperparameter/bindingdb/polyatomic/polyatomic_polyatomic_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4787428,0.03377826,1.211323,0.030012084,1.7714031,1.5513714998960495,2.0350591421127318,1.3648127,1.2580497473478318,1.4743134200572967 diff --git a/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_20250807_071730.txt b/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_20250807_071730.txt new file mode 100644 index 0000000000000000000000000000000000000000..f61bcee8279f1ef74849113796daeb7684f188b4 --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_20250807_071730.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5857, MAE: 1.3032 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.4795, MAE: 1.2034 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.4468, MAE: 1.1864 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.5527, MAE: 1.2762 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4639, MAE: 1.2057 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5057 ± 0.0539 +Unbiased Validation MAE: 1.2350 ± 0.0460 +VAL FOLD RMSEs: [1.5857314, 1.4794525, 1.4467543, 1.5527153, 1.4639254] +VAL FOLD MAEs: [1.3032318, 1.2034056, 1.1864125, 1.2761855, 1.2057139] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7721 (95% CI: [1.5363, 2.0584]) +Test MAE: 1.3451 (95% CI: [1.2354, 1.4627]) diff --git a/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..2473852fbd3bf5fe6f1fac3288bc0fd18ad7264a --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_ecfp_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5057157,0.05389639,1.2349899,0.04597491,1.772139,1.5363477438688278,2.0583533227443693,1.3451282,1.235362818837166,1.46270210146904 diff --git a/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_20250807_063019.txt b/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_20250807_063019.txt new file mode 100644 index 0000000000000000000000000000000000000000..a84adf8035263a283a44ae32b3cb4fa268d96601 --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_20250807_063019.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.5394, MAE: 1.2747 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.4918, MAE: 1.2213 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.4494, MAE: 1.2028 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5132, MAE: 1.2406 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.4725, MAE: 1.2285 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4933 ± 0.0312 +Unbiased Validation MAE: 1.2336 ± 0.0239 +VAL FOLD RMSEs: [1.5393915, 1.4918157, 1.4494269, 1.5131909, 1.4725237] +VAL FOLD MAEs: [1.2747042, 1.2212694, 1.2027868, 1.240591, 1.2284663] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.9116 (95% CI: [1.5801, 2.3369]) +Test MAE: 1.3758 (95% CI: [1.2563, 1.4999]) diff --git a/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..24d20ff971bb4d02506557bbc35ba2aa5c0300f0 --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_selfies_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4932697,0.031237086,1.2335637,0.023942754,1.911593,1.5801288306713104,2.3368979513645174,1.3758264,1.2563088655471801,1.499871453642845 diff --git a/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_20250807_055300.txt b/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_20250807_055300.txt new file mode 100644 index 0000000000000000000000000000000000000000..8aa0907aa3d2797015d2414dfd7a110a0c1f4c99 --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_20250807_055300.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5398, MAE: 1.2744 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4874, MAE: 1.2178 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.4532, MAE: 1.2031 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5109, MAE: 1.2339 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.4746, MAE: 1.2301 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.4932 ± 0.0299 +Unbiased Validation MAE: 1.2319 ± 0.0238 +VAL FOLD RMSEs: [1.5398226, 1.4874203, 1.4532293, 1.5108744, 1.4746426] +VAL FOLD MAEs: [1.2743918, 1.2177699, 1.2031285, 1.2339408, 1.2301431] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7873 (95% CI: [1.5615, 2.0522]) +Test MAE: 1.3814 (95% CI: [1.2756, 1.4967]) diff --git a/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_final_results.csv b/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..42a37c195cb75e73e05437588a28b56006dd3d46 --- /dev/null +++ b/logs_hyperparameter/bindingdb/sage/sage_smiles_bindingdb_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.4931978,0.029871345,1.2318747,0.02383385,1.7872857,1.5615118205547334,2.052208167314529,1.3814352,1.2756493985652924,1.4966969937086105 diff --git a/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_20250807_041819.txt b/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_20250807_041819.txt new file mode 100644 index 0000000000000000000000000000000000000000..45e6560219e39e990acbadb36e80a30fba6ef1f0 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_20250807_041819.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 54.4090, MAE: 42.1878 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 55.7308, MAE: 42.9823 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 57.1239, MAE: 43.1118 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 57.0813, MAE: 43.0568 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 59.8101, MAE: 46.3310 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 56.8310 ± 1.7944 +Unbiased Validation MAE: 43.5339 ± 1.4385 +VAL FOLD RMSEs: [54.409046, 55.73082, 57.12386, 57.081303, 59.810085] +VAL FOLD MAEs: [42.187794, 42.98228, 43.11179, 43.056786, 46.330982] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 53.2658 (95% CI: [48.8060, 57.8985]) +Test MAE: 40.3050 (95% CI: [36.9831, 43.5649]) diff --git a/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..50f73e0386b0d0011deedf0d865a0108d55efbfc --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_ecfp_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +56.831017,1.7944149,43.533928,1.4384555,53.265842,48.80595426559448,57.89852228164673,40.30503,36.98313436508179,43.56492938995361 diff --git a/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_20250807_032303.txt b/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_20250807_032303.txt new file mode 100644 index 0000000000000000000000000000000000000000..e40749644e50c90b5f82a44b96d8ef10a76496e5 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_20250807_032303.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 55.4286, MAE: 42.2726 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 52.3458, MAE: 39.3588 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 56.5607, MAE: 41.2356 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 58.0873, MAE: 44.9281 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 55.5859, MAE: 43.4264 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 55.6016 ± 1.8830 +Unbiased Validation MAE: 42.2443 ± 1.8944 +VAL FOLD RMSEs: [55.42858, 52.345848, 56.560688, 58.087257, 55.585876] +VAL FOLD MAEs: [42.27263, 39.35882, 41.235588, 44.92806, 43.426357] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 56.0483 (95% CI: [50.5977, 61.5451]) +Test MAE: 40.4771 (95% CI: [36.6391, 44.5185]) diff --git a/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..bac1bce8e751c5afbffd6bb1c7e32ba6563b7c26 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_selfies_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +55.601646,1.8829999,42.244293,1.8944185,56.048344,50.597716903686525,61.5450740814209,40.477142,36.6391058921814,44.518538570404054 diff --git a/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_20250807_020055.txt b/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_20250807_020055.txt new file mode 100644 index 0000000000000000000000000000000000000000..584f213afc15f6d4a20553c296788e30c7d45016 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_20250807_020055.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 55.2659, MAE: 42.3563 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 50.6227, MAE: 37.4347 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 58.1089, MAE: 43.0610 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 57.9011, MAE: 44.2164 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 54.3032, MAE: 39.6190 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 55.2403 ± 2.7390 +Unbiased Validation MAE: 41.3375 ± 2.4691 +VAL FOLD RMSEs: [55.26589, 50.62265, 58.10893, 57.901066, 54.303173] +VAL FOLD MAEs: [42.35632, 37.43467, 43.061043, 44.21635, 39.619022] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 60.7778 (95% CI: [55.7451, 66.0148]) +Test MAE: 45.3334 (95% CI: [41.3389, 49.4235]) diff --git a/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e639ffd3f99f718002ba95cd2444b03c448290cd --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gat/gat_smiles_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +55.240337,2.7389872,41.33748,2.4690738,60.77779,55.74512529373169,66.01476764678955,45.33335,41.3388973236084,49.42347354888916 diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_20250806_215254.txt b/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_20250806_215254.txt new file mode 100644 index 0000000000000000000000000000000000000000..23d0fec782da84732e801d5a244d3595a5594929 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_20250806_215254.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 54.9221, MAE: 41.9791 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 56.1294, MAE: 43.0491 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 57.4037, MAE: 43.1792 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 57.0560, MAE: 42.6860 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 59.5393, MAE: 45.6798 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 57.0101 ± 1.5290 +Unbiased Validation MAE: 43.3146 ± 1.2539 +VAL FOLD RMSEs: [54.92211, 56.129395, 57.403675, 57.055965, 59.53927] +VAL FOLD MAEs: [41.979103, 43.04912, 43.179176, 42.68598, 45.679756] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 54.6144 (95% CI: [50.1747, 59.2226]) +Test MAE: 41.7490 (95% CI: [38.1903, 45.4990]) diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..cf9acd3b2109e04096b1f1d7004774ab166a223d --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_ecfp_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +57.010082,1.528989,43.314625,1.2539135,54.614388,50.17465190887451,59.22256898880005,41.748993,38.190276336669925,45.49902229309082 diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_20250806_200256.txt b/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_20250806_200256.txt new file mode 100644 index 0000000000000000000000000000000000000000..8fabd27ee4adcc6f619d9a097034446fc65a895e --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_20250806_200256.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 61.2025, MAE: 47.9530 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 60.4286, MAE: 46.6123 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 63.5122, MAE: 47.7735 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 62.6595, MAE: 48.5019 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 58.1984, MAE: 45.6311 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 61.2002 ± 1.8483 +Unbiased Validation MAE: 47.2943 ± 1.0347 +VAL FOLD RMSEs: [61.20251, 60.428585, 63.512154, 62.659496, 58.198395] +VAL FOLD MAEs: [47.953003, 46.612297, 47.773464, 48.501892, 45.631065] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 62.3818 (95% CI: [57.0474, 67.6341]) +Test MAE: 46.8433 (95% CI: [42.8453, 51.1885]) diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..b5519b8781579503cb6218b4445f07c9a739f45b --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_selfies_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +61.200233,1.8482914,47.294342,1.0347216,62.381813,57.0474347114563,67.63406925201416,46.843258,42.84530420303345,51.1885269165039 diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_20250806_162743.txt b/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_20250806_162743.txt new file mode 100644 index 0000000000000000000000000000000000000000..e5c8814005fe3e4cbdd979f62c88d6b371790986 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_20250806_162743.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 62.5434, MAE: 49.0219 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 60.3031, MAE: 46.8175 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 62.0810, MAE: 46.0266 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 63.1632, MAE: 49.2908 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 59.8387, MAE: 47.1517 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 61.5859 ± 1.2922 +Unbiased Validation MAE: 47.6617 ± 1.2768 +VAL FOLD RMSEs: [62.54344, 60.303097, 62.081013, 63.16325, 59.838676] +VAL FOLD MAEs: [49.02189, 46.8175, 46.02655, 49.290844, 47.151695] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 59.0358 (95% CI: [54.1297, 63.8984]) +Test MAE: 43.9269 (95% CI: [40.0583, 47.6376]) diff --git a/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..80ae736f82d19b74b5637b3f7e4efd601e15dd7d --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gcn/gcn_smiles_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +61.585896,1.2921633,47.661694,1.2767705,59.035835,54.12967185974121,63.898391532897946,43.92686,40.058342933654785,47.63761415481567 diff --git a/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_20250807_005911.txt b/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_20250807_005911.txt new file mode 100644 index 0000000000000000000000000000000000000000..eddad5ced91b8c18a8d89bbd3cca0ce9a760fc14 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_20250807_005911.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 56.0018, MAE: 42.8022 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 58.9148, MAE: 46.0053 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 59.4584, MAE: 45.4088 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 57.9097, MAE: 43.0641 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 61.4369, MAE: 48.2083 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 58.7443 ± 1.7892 +Unbiased Validation MAE: 45.0977 ± 2.0001 +VAL FOLD RMSEs: [56.001797, 58.914806, 59.458374, 57.90971, 61.436855] +VAL FOLD MAEs: [42.802177, 46.005306, 45.408836, 43.064068, 48.20832] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 57.3836 (95% CI: [52.2475, 62.3235]) +Test MAE: 43.2205 (95% CI: [39.6084, 46.9656]) diff --git a/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..4f229e94da02251674acb4f95917cf893be99230 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_ecfp_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +58.744305,1.7892284,45.09774,2.0000799,57.383583,52.247502136230466,62.323451137542726,43.220516,39.60842390060425,46.96560859680176 diff --git a/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_20250806_235339.txt b/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_20250806_235339.txt new file mode 100644 index 0000000000000000000000000000000000000000..de78179a5bac222575b8ed3d87f316ceed657a5d --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_20250806_235339.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 60.0402, MAE: 46.2074 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 58.0718, MAE: 43.9157 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 58.5460, MAE: 43.6905 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 59.0030, MAE: 44.9703 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 57.4851, MAE: 43.7151 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 58.6292 ± 0.8669 +Unbiased Validation MAE: 44.4998 ± 0.9746 +VAL FOLD RMSEs: [60.04024, 58.07177, 58.545975, 59.00296, 57.485104] +VAL FOLD MAEs: [46.207417, 43.915707, 43.690506, 44.97028, 43.7151] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 57.8796 (95% CI: [53.1832, 62.8975]) +Test MAE: 42.4452 (95% CI: [38.6345, 46.2482]) diff --git a/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..40ae90a0a516391cf420b2b3f14ad0b8b372da5a --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_selfies_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +58.62921,0.8668732,44.4998,0.9745956,57.8796,53.1832480430603,62.897465229034424,42.445194,38.63452405929566,46.24818019866943 diff --git a/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_20250806_230437.txt b/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_20250806_230437.txt new file mode 100644 index 0000000000000000000000000000000000000000..e214021be3c0e1e91d74945e804db546abbf3542 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_20250806_230437.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 59.4847, MAE: 45.7614 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 63.4225, MAE: 48.2323 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 58.2794, MAE: 43.1165 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 58.6120, MAE: 46.2580 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 56.6100, MAE: 42.8093 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 59.2817 ± 2.2706 +Unbiased Validation MAE: 45.2355 ± 2.0337 +VAL FOLD RMSEs: [59.484688, 63.422462, 58.279392, 58.612, 56.610012] +VAL FOLD MAEs: [45.761383, 48.232254, 43.11647, 46.257973, 42.809254] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 57.1613 (95% CI: [52.0397, 61.9523]) +Test MAE: 42.1928 (95% CI: [38.5232, 46.0849]) diff --git a/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..1626e58da238b28d976b167ae1e27e9688292a8d --- /dev/null +++ b/logs_hyperparameter/boilingpoint/gin/gin_smiles_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +59.281708,2.2706015,45.235466,2.0336912,57.16127,52.03966951370239,61.95229043960571,42.192806,38.523158168792726,46.084850215911864 diff --git a/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_20250807_084023.txt b/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_20250807_084023.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a50d405c5ff215d9bba8e084028200b7a9ab818 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_20250807_084023.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 44.9624, MAE: 32.6128 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 49.3224, MAE: 35.7891 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 52.2364, MAE: 35.8812 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0008288862807735003, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 50.4970, MAE: 32.8064 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008303524274307721, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 48.4271, MAE: 32.3772 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 49.0891 ± 2.4253 +Unbiased Validation MAE: 33.8933 ± 1.5915 +VAL FOLD RMSEs: [44.96242, 49.322365, 52.236427, 50.49704, 48.42714] +VAL FOLD MAEs: [32.612843, 35.78907, 35.881187, 32.806404, 32.377193] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 50.6351 (95% CI: [44.4785, 57.4178]) +Test MAE: 33.2604 (95% CI: [29.7402, 37.1187]) diff --git a/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..9920fd556a65a248e42f41d70a402104dd449101 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/polyatomic/polyatomic_polyatomic_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +49.089077,2.4252853,33.89334,1.5915486,50.635094,44.47852420806885,57.41776266098022,33.260437,29.740178394317628,37.11869220733642 diff --git a/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_20250807_065228.txt b/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_20250807_065228.txt new file mode 100644 index 0000000000000000000000000000000000000000..c57634f1c40adae70deca721b903687dfd0f6424 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_20250807_065228.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 55.4048, MAE: 42.6514 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 56.5306, MAE: 43.4503 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 57.8703, MAE: 43.7115 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 56.8904, MAE: 43.4473 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 59.1082, MAE: 45.3093 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 57.1609 ± 1.2530 +Unbiased Validation MAE: 43.7140 ± 0.8735 +VAL FOLD RMSEs: [55.404804, 56.530598, 57.870255, 56.890423, 59.10821] +VAL FOLD MAEs: [42.651375, 43.450344, 43.711514, 43.447273, 45.309288] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 55.2449 (95% CI: [50.9979, 59.8509]) +Test MAE: 42.1964 (95% CI: [38.8545, 45.7118]) diff --git a/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e1a9097c2827d07ea306adf7a7d94bd74e1ac34e --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_ecfp_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +57.16086,1.2529578,43.71396,0.8734735,55.244877,50.99788312911987,59.8508861541748,42.196377,38.854457473754884,45.71182737350464 diff --git a/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_20250807_061735.txt b/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_20250807_061735.txt new file mode 100644 index 0000000000000000000000000000000000000000..8c3f695ec91dba1068a4a7fd6b544c7f8c799a1f --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_20250807_061735.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 55.2736, MAE: 41.9118 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 51.7395, MAE: 39.2856 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 58.2735, MAE: 44.0310 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 53.1994, MAE: 39.5290 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 53.2396, MAE: 39.9818 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 54.3451 ± 2.2636 +Unbiased Validation MAE: 40.9479 ± 1.7969 +VAL FOLD RMSEs: [55.273643, 51.739475, 58.273487, 53.199425, 53.239635] +VAL FOLD MAEs: [41.91183, 39.28564, 44.03103, 39.528954, 39.981823] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 53.0400 (95% CI: [47.6509, 59.1403]) +Test MAE: 37.4580 (95% CI: [33.8000, 40.9812]) diff --git a/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..68b96326df4b0ea2db885f89dc82ddf323d74628 --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_selfies_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +54.34513,2.2635512,40.947853,1.7969232,53.040047,47.65094861984253,59.14033136367798,37.457996,33.80003128051758,40.98119983673096 diff --git a/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_20250807_053033.txt b/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_20250807_053033.txt new file mode 100644 index 0000000000000000000000000000000000000000..c49b7b81044154fa461c66a519d9782e0c7570be --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_20250807_053033.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 57.9135, MAE: 43.7758 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 48.8282, MAE: 36.0385 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 58.1919, MAE: 43.3961 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 55.0623, MAE: 40.7055 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 51.4227, MAE: 37.5390 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 54.2837 ± 3.6607 +Unbiased Validation MAE: 40.2910 ± 3.0859 +VAL FOLD RMSEs: [57.913513, 48.828194, 58.191944, 55.062294, 51.422695] +VAL FOLD MAEs: [43.77578, 36.038464, 43.39607, 40.705544, 37.538982] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 53.0105 (95% CI: [47.5086, 58.6872]) +Test MAE: 36.5634 (95% CI: [32.8283, 40.2876]) diff --git a/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_final_results.csv b/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f62d66f1fa0dcdceafdd6d70968d40ff41ae9dad --- /dev/null +++ b/logs_hyperparameter/boilingpoint/sage/sage_smiles_boilingpoint_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +54.28373,3.660711,40.29097,3.0859246,53.01054,47.50855779647827,58.68716316223144,36.5634,32.82834196090698,40.28756132125854 diff --git a/logs_hyperparameter/esol/gat/gat_ecfp_esol_20250807_035425.txt b/logs_hyperparameter/esol/gat/gat_ecfp_esol_20250807_035425.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f77f053194de950c03ddad472f07b0b949de904 --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_ecfp_esol_20250807_035425.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0956, MAE: 0.8342 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.2767, MAE: 0.9453 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.2117, MAE: 0.9380 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.2808, MAE: 0.9858 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.2637, MAE: 0.9434 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2257 ± 0.0696 +Unbiased Validation MAE: 0.9293 ± 0.0505 +VAL FOLD RMSEs: [1.0955936, 1.2766641, 1.211735, 1.280819, 1.2637357] +VAL FOLD MAEs: [0.83423984, 0.94528604, 0.9380378, 0.98581696, 0.94336104] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1727 (95% CI: [1.0371, 1.2971]) +Test MAE: 0.8795 (95% CI: [0.7751, 0.9873]) diff --git a/logs_hyperparameter/esol/gat/gat_ecfp_esol_final_results.csv b/logs_hyperparameter/esol/gat/gat_ecfp_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..86ffc46191bdd9d0a0d03f49f5d5b0605a64c5fc --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_ecfp_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2257096,0.069577105,0.92934835,0.050517727,1.1727425,1.0371442258358001,1.2971396148204803,0.87948644,0.7750797539949417,0.9873339846730232 diff --git a/logs_hyperparameter/esol/gat/gat_selfies_esol_20250807_024705.txt b/logs_hyperparameter/esol/gat/gat_selfies_esol_20250807_024705.txt new file mode 100644 index 0000000000000000000000000000000000000000..b136e9b24ae361d141a92bfa35c184744b7610e3 --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_selfies_esol_20250807_024705.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0130, MAE: 0.8001 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.3669, MAE: 1.0464 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.2047, MAE: 0.9134 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.1625, MAE: 0.8961 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1048, MAE: 0.8533 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.1704 ± 0.1174 +Unbiased Validation MAE: 0.9019 ± 0.0822 +VAL FOLD RMSEs: [1.012987, 1.3668803, 1.2046516, 1.1624877, 1.1047916] +VAL FOLD MAEs: [0.80006975, 1.0464221, 0.91336095, 0.8961487, 0.85332394] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.9850 (95% CI: [0.8682, 1.1097]) +Test MAE: 0.7440 (95% CI: [0.6561, 0.8341]) diff --git a/logs_hyperparameter/esol/gat/gat_selfies_esol_final_results.csv b/logs_hyperparameter/esol/gat/gat_selfies_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..13f0ca3fb838a3764a4766d01add2c941ea7eb60 --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_selfies_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.1703596,0.11740833,0.9018651,0.082195014,0.9849942,0.8681845411658287,1.109735968708992,0.74402577,0.6561006113886834,0.8340629562735558 diff --git a/logs_hyperparameter/esol/gat/gat_smiles_esol_20250807_013123.txt b/logs_hyperparameter/esol/gat/gat_smiles_esol_20250807_013123.txt new file mode 100644 index 0000000000000000000000000000000000000000..875b1faf30ce4c8c648b978e40c64ce783f0a1c4 --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_smiles_esol_20250807_013123.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.8918, MAE: 0.7113 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.2833, MAE: 0.9736 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.1070, MAE: 0.8682 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.0591, MAE: 0.7937 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.0824, MAE: 0.8248 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0847 ± 0.1247 +Unbiased Validation MAE: 0.8343 ± 0.0865 +VAL FOLD RMSEs: [0.89180523, 1.2832943, 1.1070185, 1.0591129, 1.0823991] +VAL FOLD MAEs: [0.7113257, 0.97364956, 0.8681888, 0.7936739, 0.8248111] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1397 (95% CI: [1.0201, 1.2604]) +Test MAE: 0.8710 (95% CI: [0.7820, 0.9707]) diff --git a/logs_hyperparameter/esol/gat/gat_smiles_esol_final_results.csv b/logs_hyperparameter/esol/gat/gat_smiles_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f486ba114833fb1620c72d4b5a9bac0e3675882a --- /dev/null +++ b/logs_hyperparameter/esol/gat/gat_smiles_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.084726,0.124744706,0.8343298,0.08652161,1.1396955,1.0200696140527725,1.2604074388742448,0.87104344,0.7819629177451134,0.9706986114382744 diff --git a/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_20250806_213639.txt b/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_20250806_213639.txt new file mode 100644 index 0000000000000000000000000000000000000000..672f08b2caba269828c62f961ac54ca8b1ca0ae5 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_20250806_213639.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.1099, MAE: 0.8387 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.2666, MAE: 0.9475 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.2447, MAE: 0.9710 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.2549, MAE: 0.9610 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.2413, MAE: 0.9430 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2235 ± 0.0575 +Unbiased Validation MAE: 0.9322 ± 0.0478 +VAL FOLD RMSEs: [1.1099247, 1.2665595, 1.2446508, 1.2549481, 1.2413471] +VAL FOLD MAEs: [0.8387399, 0.94746375, 0.97100914, 0.96098024, 0.94302315] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1710 (95% CI: [1.0527, 1.2972]) +Test MAE: 0.8882 (95% CI: [0.7936, 0.9861]) diff --git a/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_final_results.csv b/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..9df7b122a2250cc2759bab34c7a6cd5c76d502f0 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_ecfp_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2234862,0.057460133,0.93224317,0.047789868,1.1709992,1.0527043491601944,1.2972006440162658,0.88821757,0.7935711681842804,0.9860577195882797 diff --git a/logs_hyperparameter/esol/gcn/gcn_selfies_esol_20250806_193030.txt b/logs_hyperparameter/esol/gcn/gcn_selfies_esol_20250806_193030.txt new file mode 100644 index 0000000000000000000000000000000000000000..335a8777df6f16a90ce11afd741335f017b4ded9 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_selfies_esol_20250806_193030.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.1152, MAE: 0.8787 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.3925, MAE: 1.0492 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.3149, MAE: 1.0467 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.3943, MAE: 1.0444 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1762, MAE: 0.8669 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2786 ± 0.1139 +Unbiased Validation MAE: 0.9772 ± 0.0853 +VAL FOLD RMSEs: [1.1151705, 1.3924754, 1.3148535, 1.3942686, 1.1761895] +VAL FOLD MAEs: [0.87868625, 1.0492274, 1.0467249, 1.0443875, 0.8669203] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.2749 (95% CI: [1.1171, 1.4231]) +Test MAE: 0.9486 (95% CI: [0.8418, 1.0564]) diff --git a/logs_hyperparameter/esol/gcn/gcn_selfies_esol_final_results.csv b/logs_hyperparameter/esol/gcn/gcn_selfies_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..a9283fdbfcdce5a4569c4bea0aaf1231c0c1bd61 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_selfies_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2785914,0.113893166,0.97718924,0.08532571,1.274919,1.1171263486146927,1.4231246769428254,0.9486296,0.8417802855372429,1.0563817232847215 diff --git a/logs_hyperparameter/esol/gcn/gcn_smiles_esol_20250806_155509.txt b/logs_hyperparameter/esol/gcn/gcn_smiles_esol_20250806_155509.txt new file mode 100644 index 0000000000000000000000000000000000000000..48566ade27ee5ba60258a00fd5e6148feaeeffd3 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_smiles_esol_20250806_155509.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.1598, MAE: 0.9201 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.5494, MAE: 1.1934 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.0428, MAE: 0.8302 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.2783, MAE: 0.9618 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1696, MAE: 0.8839 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2400 ± 0.1717 +Unbiased Validation MAE: 0.9579 ± 0.1254 +VAL FOLD RMSEs: [1.1598195, 1.5493898, 1.0428247, 1.2782555, 1.1695782] +VAL FOLD MAEs: [0.92014915, 1.193356, 0.83022594, 0.96179456, 0.883861] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.2969 (95% CI: [1.1333, 1.4714]) +Test MAE: 0.9465 (95% CI: [0.8357, 1.0615]) diff --git a/logs_hyperparameter/esol/gcn/gcn_smiles_esol_final_results.csv b/logs_hyperparameter/esol/gcn/gcn_smiles_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..37c09f9cc0b7fa1ada814f147cbf25a32abfae62 --- /dev/null +++ b/logs_hyperparameter/esol/gcn/gcn_smiles_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2399735,0.17172755,0.95787734,0.1254291,1.2969111,1.133328714966774,1.4713991671800613,0.94647545,0.8356901213526726,1.0614635705947875 diff --git a/logs_hyperparameter/esol/gin/gin_ecfp_esol_20250807_003722.txt b/logs_hyperparameter/esol/gin/gin_ecfp_esol_20250807_003722.txt new file mode 100644 index 0000000000000000000000000000000000000000..be4791ca825135e5f904091a21c23ed5dfc2be70 --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_ecfp_esol_20250807_003722.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0564, MAE: 0.8224 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1970, MAE: 0.8908 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.1588, MAE: 0.8720 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.1731, MAE: 0.9070 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1922, MAE: 0.8988 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.1555 ± 0.0514 +Unbiased Validation MAE: 0.8782 ± 0.0302 +VAL FOLD RMSEs: [1.0563703, 1.1969724, 1.1588433, 1.1730788, 1.1921836] +VAL FOLD MAEs: [0.8224449, 0.89083415, 0.8720074, 0.906967, 0.8987576] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1065 (95% CI: [0.9911, 1.2294]) +Test MAE: 0.8503 (95% CI: [0.7595, 0.9420]) diff --git a/logs_hyperparameter/esol/gin/gin_ecfp_esol_final_results.csv b/logs_hyperparameter/esol/gin/gin_ecfp_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..aad3f836acd17bd74d3a1044c01d41ab58ebb005 --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_ecfp_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.1554897,0.051405333,0.87820214,0.030188583,1.1065212,0.9910676315426826,1.229444435238838,0.8502788,0.7594864636659622,0.9420430347323417 diff --git a/logs_hyperparameter/esol/gin/gin_selfies_esol_20250806_234212.txt b/logs_hyperparameter/esol/gin/gin_selfies_esol_20250806_234212.txt new file mode 100644 index 0000000000000000000000000000000000000000..04fc63ca68b6788eb5d622117cb24a76420f9996 --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_selfies_esol_20250806_234212.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0540, MAE: 0.8026 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4066, MAE: 1.0617 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.1787, MAE: 0.9025 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.4919, MAE: 1.1372 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1045, MAE: 0.7936 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2471 ± 0.1719 +Unbiased Validation MAE: 0.9395 ± 0.1381 +VAL FOLD RMSEs: [1.053951, 1.4065511, 1.1787022, 1.4919145, 1.1045294] +VAL FOLD MAEs: [0.80259055, 1.0617265, 0.9025328, 1.1372406, 0.79364115] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.3939 (95% CI: [1.2072, 1.5854]) +Test MAE: 0.9986 (95% CI: [0.8773, 1.1236]) diff --git a/logs_hyperparameter/esol/gin/gin_selfies_esol_final_results.csv b/logs_hyperparameter/esol/gin/gin_selfies_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..322b5d84527ca7e40f5f3cde5844dac41f015202 --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_selfies_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2471297,0.17185457,0.9395463,0.13814937,1.3938813,1.2071673542261123,1.5854190587997437,0.99855083,0.8772710293531418,1.123569330573082 diff --git a/logs_hyperparameter/esol/gin/gin_smiles_esol_20250806_224510.txt b/logs_hyperparameter/esol/gin/gin_smiles_esol_20250806_224510.txt new file mode 100644 index 0000000000000000000000000000000000000000..9a4b90d085eed5a2e2a6267e8dd9e6140466a96b --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_smiles_esol_20250806_224510.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.1077, MAE: 0.8774 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.3252, MAE: 0.9976 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.1755, MAE: 0.9135 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.2509, MAE: 0.9532 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1185, MAE: 0.7977 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.1956 ± 0.0824 +Unbiased Validation MAE: 0.9079 ± 0.0681 +VAL FOLD RMSEs: [1.107694, 1.3252425, 1.1754986, 1.2509443, 1.1185027] +VAL FOLD MAEs: [0.87740535, 0.99762267, 0.9135071, 0.953234, 0.7976966] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.3372 (95% CI: [1.1833, 1.4974]) +Test MAE: 0.9960 (95% CI: [0.8799, 1.1137]) diff --git a/logs_hyperparameter/esol/gin/gin_smiles_esol_final_results.csv b/logs_hyperparameter/esol/gin/gin_smiles_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..0592190ff83b162b8e34a732c7414278a098fb51 --- /dev/null +++ b/logs_hyperparameter/esol/gin/gin_smiles_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.1955764,0.08239622,0.9078932,0.068134405,1.3372297,1.183308881521225,1.4973589628934858,0.9960031,0.8798676863312721,1.1137097030878067 diff --git a/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_20250806_164250.txt b/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_20250806_164250.txt new file mode 100644 index 0000000000000000000000000000000000000000..67095c7bc687b6817868fe9dc46a754c86462d28 --- /dev/null +++ b/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_20250806_164250.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6407, MAE: 0.4643 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7282, MAE: 0.5329 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.6542, MAE: 0.4921 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.6792, MAE: 0.5235 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.7010, MAE: 0.5293 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.6807 ± 0.0315 +Unbiased Validation MAE: 0.5084 ± 0.0264 +VAL FOLD RMSEs: [0.64070433, 0.7281794, 0.6542352, 0.6791948, 0.7009942] +VAL FOLD MAEs: [0.46425894, 0.53287125, 0.49209586, 0.52349097, 0.52926] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.8291 (95% CI: [0.6948, 0.9908]) +Test MAE: 0.5928 (95% CI: [0.5230, 0.6683]) diff --git a/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_final_results.csv b/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..9c0dc23ce967f0f86b70f931c6af327386ae8033 --- /dev/null +++ b/logs_hyperparameter/esol/polyatomic/polyatomic_polyatomic_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.6806616,0.031522833,0.5083954,0.026366554,0.8290681,0.6948435366153717,0.9907772034406662,0.59278077,0.5230290323495865,0.6683276146650314 diff --git a/logs_hyperparameter/esol/sage/sage_ecfp_esol_20250807_063402.txt b/logs_hyperparameter/esol/sage/sage_ecfp_esol_20250807_063402.txt new file mode 100644 index 0000000000000000000000000000000000000000..ea03dac695a86d102e5b74a41f879d94388397de --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_ecfp_esol_20250807_063402.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0736, MAE: 0.8145 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.2766, MAE: 0.9486 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.2121, MAE: 0.9125 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.2688, MAE: 0.9749 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.2603, MAE: 0.9595 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.2183 ± 0.0757 +Unbiased Validation MAE: 0.9220 ± 0.0575 +VAL FOLD RMSEs: [1.0736184, 1.2765619, 1.2121183, 1.2687736, 1.2603368] +VAL FOLD MAEs: [0.8144865, 0.9485978, 0.91251653, 0.9748641, 0.9594727] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1867 (95% CI: [1.0708, 1.3058]) +Test MAE: 0.8964 (95% CI: [0.7936, 1.0017]) diff --git a/logs_hyperparameter/esol/sage/sage_ecfp_esol_final_results.csv b/logs_hyperparameter/esol/sage/sage_ecfp_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..5eba672746bf787ced2f7d3f5aee5afd18d9e94b --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_ecfp_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.2182817,0.0757365,0.92198753,0.0575419,1.1867028,1.070798045396805,1.3058079957962037,0.89644253,0.7935509786009789,1.0016635686159132 diff --git a/logs_hyperparameter/esol/sage/sage_selfies_esol_20250807_055509.txt b/logs_hyperparameter/esol/sage/sage_selfies_esol_20250807_055509.txt new file mode 100644 index 0000000000000000000000000000000000000000..574591400e5a1564a65863629ebd1f39a254e93c --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_selfies_esol_20250807_055509.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.9425, MAE: 0.7282 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1267, MAE: 0.8618 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.0795, MAE: 0.8564 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.2176, MAE: 0.8787 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.9062, MAE: 0.6841 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0545 ± 0.1157 +Unbiased Validation MAE: 0.8018 ± 0.0797 +VAL FOLD RMSEs: [0.94250053, 1.126744, 1.0795038, 1.2175982, 0.9061735] +VAL FOLD MAEs: [0.72816056, 0.8617631, 0.85643065, 0.8786591, 0.68407273] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.9969 (95% CI: [0.8815, 1.1241]) +Test MAE: 0.7463 (95% CI: [0.6685, 0.8358]) diff --git a/logs_hyperparameter/esol/sage/sage_selfies_esol_final_results.csv b/logs_hyperparameter/esol/sage/sage_selfies_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..06f906f18b043798820c8094035cf53d3048f59a --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_selfies_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.054504,0.11574976,0.8018173,0.07971183,0.99694556,0.8814633339643478,1.12407266497612,0.74625367,0.6684502378106117,0.8358007594943047 diff --git a/logs_hyperparameter/esol/sage/sage_smiles_esol_20250807_050327.txt b/logs_hyperparameter/esol/sage/sage_smiles_esol_20250807_050327.txt new file mode 100644 index 0000000000000000000000000000000000000000..07654a1a0e18f9b3c4349ce44a66461ff706c52c --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_smiles_esol_20250807_050327.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.9168, MAE: 0.6990 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.2088, MAE: 0.9213 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.9770, MAE: 0.7780 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.1810, MAE: 0.8846 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.0589, MAE: 0.8101 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0685 ± 0.1130 +Unbiased Validation MAE: 0.8186 ± 0.0786 +VAL FOLD RMSEs: [0.9167784, 1.2088169, 0.9769964, 1.1809964, 1.0588653] +VAL FOLD MAEs: [0.69899046, 0.92125136, 0.7780215, 0.8845886, 0.8101361] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0887 (95% CI: [0.9563, 1.2323]) +Test MAE: 0.8138 (95% CI: [0.7225, 0.9110]) diff --git a/logs_hyperparameter/esol/sage/sage_smiles_esol_final_results.csv b/logs_hyperparameter/esol/sage/sage_smiles_esol_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..79050694abe321c0056618e64f15c6812f38690b --- /dev/null +++ b/logs_hyperparameter/esol/sage/sage_smiles_esol_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0684907,0.11298624,0.8185976,0.07863395,1.0887176,0.9563103124499321,1.2323233515024186,0.8137771,0.7225208789110183,0.9109762698411942 diff --git a/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_20250807_035653.txt b/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_20250807_035653.txt new file mode 100644 index 0000000000000000000000000000000000000000..67babd2c1bc30af2df918eed3fff9350b06eec50 --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_20250807_035653.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.2127, MAE: 1.5927 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.2458, MAE: 1.3054 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.9295, MAE: 1.2238 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.6327, MAE: 1.2448 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.8799, MAE: 1.2514 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.9801 ± 0.2271 +Unbiased Validation MAE: 1.3236 ± 0.1372 +VAL FOLD RMSEs: [2.2126997, 2.2457836, 1.9294776, 1.6327468, 1.8798636] +VAL FOLD MAEs: [1.5927358, 1.3054308, 1.2238004, 1.244778, 1.2513678] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.5364 (95% CI: [1.8584, 3.3588]) +Test MAE: 1.7257 (95% CI: [1.4286, 2.0974]) diff --git a/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..26cab3de8958fffa09cc9cdac3e6a9eb0dcee4aa --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_ecfp_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.9801143,0.22713631,1.3236227,0.13722575,2.5364418,1.8584149718284606,3.3587809443473815,1.7257099,1.4286485224962235,2.0974468886852264 diff --git a/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_20250807_030135.txt b/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_20250807_030135.txt new file mode 100644 index 0000000000000000000000000000000000000000..930e444cb081fe0ac2143ca44b0410381deec455 --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_20250807_030135.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.2979, MAE: 2.5710 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.5130, MAE: 1.7429 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.4319, MAE: 1.8759 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.1476, MAE: 2.3367 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.5437, MAE: 1.7671 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.7868 ± 0.3609 +Unbiased Validation MAE: 2.0587 ± 0.3340 +VAL FOLD RMSEs: [3.2978725, 2.5130358, 2.4319022, 3.1476152, 2.5436673] +VAL FOLD MAEs: [2.5709634, 1.7428569, 1.8759111, 2.3367019, 1.7670976] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.6724 (95% CI: [2.9411, 4.5232]) +Test MAE: 2.7007 (95% CI: [2.2804, 3.1605]) diff --git a/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..1876e0d89805c4f647f7105edf02e558b7425af1 --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_selfies_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.7868187,0.360942,2.0587063,0.33403575,3.6724062,2.941127610206604,4.523194456100464,2.7007153,2.280365788936615,3.1604898691177365 diff --git a/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_20250807_013255.txt b/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_20250807_013255.txt new file mode 100644 index 0000000000000000000000000000000000000000..05fe901add9e1933b97c1c79e78b81d3fbde4acd --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_20250807_013255.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.2778, MAE: 2.5522 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.7523, MAE: 1.8758 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.4437, MAE: 1.8333 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.1058, MAE: 2.3053 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.3036, MAE: 1.7822 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.7767 ± 0.3728 +Unbiased Validation MAE: 2.0698 ± 0.3048 +VAL FOLD RMSEs: [3.2778385, 2.7523484, 2.443737, 3.1057725, 2.3035712] +VAL FOLD MAEs: [2.5522287, 1.8757933, 1.8333203, 2.3053098, 1.7822378] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.7272 (95% CI: [2.9648, 4.5906]) +Test MAE: 2.7225 (95% CI: [2.3152, 3.2001]) diff --git a/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..0f7707afe908d9f4899bb7be137e98f986c99b36 --- /dev/null +++ b/logs_hyperparameter/freesolv/gat/gat_smiles_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.7766538,0.3727564,2.069778,0.30478042,3.727151,2.9648488819599152,4.590631580352783,2.7224922,2.315230852365494,3.2000962793827057 diff --git a/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_20250806_214409.txt b/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_20250806_214409.txt new file mode 100644 index 0000000000000000000000000000000000000000..635ae725bf80448731c954c12e928ebfee49b918 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_20250806_214409.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 2.3095, MAE: 1.6017 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.2024, MAE: 1.2642 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 2.0071, MAE: 1.2340 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.6457, MAE: 1.2222 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.8579, MAE: 1.2230 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.0045 ± 0.2377 +Unbiased Validation MAE: 1.3090 ± 0.1471 +VAL FOLD RMSEs: [2.3095307, 2.2024443, 2.007055, 1.6456529, 1.8578913] +VAL FOLD MAEs: [1.6017222, 1.2641772, 1.2340314, 1.2221789, 1.2229918] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.5377 (95% CI: [1.7891, 3.4031]) +Test MAE: 1.6093 (95% CI: [1.3096, 1.9732]) diff --git a/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..18a400d81e093169ce8b11baa709be5073e2dac8 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_ecfp_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.004515,0.23769626,1.3090203,0.14714006,2.5377047,1.78909829556942,3.4031273543834684,1.6092832,1.3096170127391815,1.9731657773256301 diff --git a/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_20250806_194534.txt b/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_20250806_194534.txt new file mode 100644 index 0000000000000000000000000000000000000000..e6f26622ee159ffb1b457c08455b82e54b7f3f80 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_20250806_194534.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.2458, MAE: 2.5261 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 3.7657, MAE: 2.5372 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 3.6907, MAE: 2.5617 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.2503, MAE: 2.4022 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 3.4757, MAE: 2.7051 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 3.4856 ± 0.2161 +Unbiased Validation MAE: 2.5465 ± 0.0966 +VAL FOLD RMSEs: [3.2457948, 3.765652, 3.6907105, 3.2502618, 3.475655] +VAL FOLD MAEs: [2.5261106, 2.5371964, 2.5617275, 2.402201, 2.7050653] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.7729 (95% CI: [3.0027, 4.6995]) +Test MAE: 2.7263 (95% CI: [2.2908, 3.2207]) diff --git a/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..91e26d837f9d86b808884e9f78c50b2d9a6cfc88 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_selfies_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +3.4856148,0.21609671,2.54646,0.096642956,3.7729466,3.0026921212673185,4.699522256851196,2.7262964,2.290786999464035,3.2206818997859954 diff --git a/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_20250806_155506.txt b/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_20250806_155506.txt new file mode 100644 index 0000000000000000000000000000000000000000..542cc9f440b4886b5e2389040b31332402551385 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_20250806_155506.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.3235, MAE: 2.6214 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 3.8000, MAE: 2.5422 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 3.1321, MAE: 2.1968 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.1821, MAE: 2.3628 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 3.4649, MAE: 2.7062 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 3.3805 ± 0.2398 +Unbiased Validation MAE: 2.4859 ± 0.1837 +VAL FOLD RMSEs: [3.323492, 3.8000345, 3.1320543, 3.182137, 3.464863] +VAL FOLD MAEs: [2.6213622, 2.5421739, 2.196803, 2.362803, 2.7061658] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.8800 (95% CI: [3.1099, 4.8245]) +Test MAE: 2.8553 (95% CI: [2.4186, 3.3404]) diff --git a/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..4432ed24616f4809fb0743b197b197d6c23d6a54 --- /dev/null +++ b/logs_hyperparameter/freesolv/gcn/gcn_smiles_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +3.380516,0.23977046,2.4858615,0.18371917,3.8800457,3.1099351048469543,4.824497163295746,2.8552997,2.4185900390148163,3.3404463708400725 diff --git a/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_20250807_004428.txt b/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_20250807_004428.txt new file mode 100644 index 0000000000000000000000000000000000000000..aebf44c9157658d57828b09b77e328164d8b43d1 --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_20250807_004428.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.9661, MAE: 1.4201 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.6539, MAE: 0.9402 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.6687, MAE: 1.0866 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.6129, MAE: 1.2131 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.7842, MAE: 1.2387 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.7372 ± 0.1278 +Unbiased Validation MAE: 1.1797 ± 0.1603 +VAL FOLD RMSEs: [1.9661305, 1.6539204, 1.668735, 1.6129066, 1.7841859] +VAL FOLD MAEs: [1.4201308, 0.94015294, 1.0865558, 1.2131346, 1.2387023] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.1722 (95% CI: [1.6138, 2.8017]) +Test MAE: 1.4272 (95% CI: [1.1672, 1.7399]) diff --git a/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f0a4ecf714233a26269a3bb2e8fa59c147c55ab8 --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_ecfp_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.7371757,0.12781912,1.1797354,0.16029023,2.1721535,1.6137906193733216,2.801746559143066,1.4271855,1.1672417402267456,1.739899867773056 diff --git a/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_20250806_234946.txt b/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_20250806_234946.txt new file mode 100644 index 0000000000000000000000000000000000000000..716ef53b14e00cac79cbb5086e1bb5c896c6523e --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_20250806_234946.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 3.3241, MAE: 2.6016 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 3.7163, MAE: 2.6038 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 3.2818, MAE: 2.3496 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.2863, MAE: 2.4698 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 3.5243, MAE: 2.7421 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 3.4266 ± 0.1701 +Unbiased Validation MAE: 2.5534 ± 0.1334 +VAL FOLD RMSEs: [3.324104, 3.7162986, 3.2817898, 3.286334, 3.524314] +VAL FOLD MAEs: [2.6015627, 2.603796, 2.3495958, 2.4698265, 2.7420828] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.8144 (95% CI: [3.0444, 4.7144]) +Test MAE: 2.7930 (95% CI: [2.3607, 3.2541]) diff --git a/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..09f3c8e665f42dc422a920533d4b5b68a221926b --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_selfies_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +3.4265678,0.17007248,2.5533729,0.13340263,3.8143773,3.044363462924957,4.7144004821777346,2.7929711,2.360692298412323,3.2541097819805143 diff --git a/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_20250806_225933.txt b/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_20250806_225933.txt new file mode 100644 index 0000000000000000000000000000000000000000..f41737435696e7e61e5eb13e7b5f20836783e77b --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_20250806_225933.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 3.3289, MAE: 2.6207 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 3.8296, MAE: 2.6475 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 3.4014, MAE: 2.3683 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 3.2559, MAE: 2.3864 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 3.4544, MAE: 2.6156 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 3.4540 ± 0.1994 +Unbiased Validation MAE: 2.5277 ± 0.1234 +VAL FOLD RMSEs: [3.3288672, 3.8296094, 3.4014137, 3.255889, 3.454412] +VAL FOLD MAEs: [2.6207418, 2.6475198, 2.368295, 2.3863945, 2.615606] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.6901 (95% CI: [2.9443, 4.4989]) +Test MAE: 2.6760 (95% CI: [2.2550, 3.1645]) diff --git a/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_final_results.csv b/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..da040536c4e0bb1bd9670d44c4b706a15d414262 --- /dev/null +++ b/logs_hyperparameter/freesolv/gin/gin_smiles_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +3.4540381,0.19937608,2.5277114,0.12338417,3.6900911,2.9442856431007387,4.498881423473358,2.675992,2.2549796521663668,3.164493203163147 diff --git a/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_20250806_161356.txt b/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_20250806_161356.txt new file mode 100644 index 0000000000000000000000000000000000000000..e34217136e1cc0aa4c78865b1895f514d3b16c6a --- /dev/null +++ b/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_20250806_161356.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.4898, MAE: 0.9660 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.2614, MAE: 0.8835 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.3907, MAE: 0.8215 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.2326, MAE: 0.8356 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1919, MAE: 0.7771 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.3133 ± 0.1105 +Unbiased Validation MAE: 0.8567 ± 0.0643 +VAL FOLD RMSEs: [1.4897709, 1.2614098, 1.3906764, 1.2325993, 1.1918608] +VAL FOLD MAEs: [0.96595633, 0.8835088, 0.82152045, 0.8355825, 0.77711916] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.4393 (95% CI: [0.9981, 1.8838]) +Test MAE: 0.8563 (95% CI: [0.6757, 1.0609]) diff --git a/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_final_results.csv b/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..8ceff4606f452943a6cb0e2b64f5ab73ec297575 --- /dev/null +++ b/logs_hyperparameter/freesolv/polyatomic/polyatomic_polyatomic_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.3132634,0.110527605,0.8567375,0.064299785,1.4392893,0.998097462952137,1.8837726086378095,0.85634613,0.6757315412163735,1.0609380275011062 diff --git a/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_20250807_063445.txt b/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_20250807_063445.txt new file mode 100644 index 0000000000000000000000000000000000000000..40466b19b1274ec66ff986d4ccea9435cad1b77c --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_20250807_063445.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 2.1379, MAE: 1.5537 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.7912, MAE: 1.0902 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 2.0212, MAE: 1.2623 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.6906, MAE: 1.2715 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.8309, MAE: 1.2480 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.8944 ± 0.1622 +Unbiased Validation MAE: 1.2851 ± 0.1498 +VAL FOLD RMSEs: [2.1378717, 1.7912254, 2.0212233, 1.6906252, 1.830911] +VAL FOLD MAEs: [1.5536938, 1.0902231, 1.2623392, 1.2714791, 1.2480074] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.3655 (95% CI: [1.7588, 3.0801]) +Test MAE: 1.5957 (95% CI: [1.3153, 1.9430]) diff --git a/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_final_results.csv b/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..c840988b1bce8faef4dfc9b7d300390a2dcfdc41 --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_ecfp_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.8943713,0.16221137,1.2851485,0.14979924,2.3654597,1.7588188529014588,3.080111825466156,1.5956866,1.3152932167053222,1.9429958701133727 diff --git a/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_20250807_061116.txt b/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_20250807_061116.txt new file mode 100644 index 0000000000000000000000000000000000000000..dedf77f09b31a300cd5923431687e17862cef106 --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_20250807_061116.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.3294, MAE: 2.5934 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.1021, MAE: 1.4849 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.2756, MAE: 1.8204 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.4069, MAE: 1.7527 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.3778, MAE: 1.6050 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.4984 ± 0.4290 +Unbiased Validation MAE: 1.8513 ± 0.3889 +VAL FOLD RMSEs: [3.3293865, 2.1021073, 2.2756133, 2.4068606, 2.3777907] +VAL FOLD MAEs: [2.5933583, 1.4848744, 1.8203533, 1.7527055, 1.6049908] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.7786 (95% CI: [2.9765, 4.6493]) +Test MAE: 2.7625 (95% CI: [2.3608, 3.2216]) diff --git a/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_final_results.csv b/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..949a7e6beb27a04c2dd86fbf379bf34a8cf6641a --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_selfies_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.4983516,0.42898634,1.8512566,0.38891262,3.7786047,2.9764536142349245,4.649268615245819,2.7624922,2.3607943773269655,3.2215691745281214 diff --git a/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_20250807_051012.txt b/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_20250807_051012.txt new file mode 100644 index 0000000000000000000000000000000000000000..3ed1dd2c598a07028288d8ce90d8b364dadda609 --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_20250807_051012.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 3.3560, MAE: 2.5819 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.7861, MAE: 2.0130 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.3129, MAE: 1.8218 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.7179, MAE: 1.9628 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.3421, MAE: 1.7674 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.7030 ± 0.3784 +Unbiased Validation MAE: 2.0294 ± 0.2904 +VAL FOLD RMSEs: [3.3560221, 2.7860606, 2.312885, 2.717932, 2.3421214] +VAL FOLD MAEs: [2.5818908, 2.0129867, 1.821756, 1.9627758, 1.7674354] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 3.7892 (95% CI: [3.0197, 4.6653]) +Test MAE: 2.8017 (95% CI: [2.3743, 3.2820]) diff --git a/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_final_results.csv b/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f0f7fc4256d3579a7bbf5ea3c5ed9f44f458e61e --- /dev/null +++ b/logs_hyperparameter/freesolv/sage/sage_smiles_freesolv_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.7030041,0.3784133,2.0293689,0.29041204,3.7891567,3.019695943593979,4.665342020988464,2.8016796,2.3742708563804626,3.282033455371857 diff --git a/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_20250807_044918.txt b/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_20250807_044918.txt new file mode 100644 index 0000000000000000000000000000000000000000..00fa298de478888f9c99cfcf467f723769eda347 --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_20250807_044918.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6971, MAE: 0.5672 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7761, MAE: 0.6041 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7653, MAE: 0.5968 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.7965, MAE: 0.5944 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8066, MAE: 0.6169 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7683 ± 0.0385 +Unbiased Validation MAE: 0.5959 ± 0.0163 +VAL FOLD RMSEs: [0.69714445, 0.77605015, 0.76531273, 0.79653317, 0.80662316] +VAL FOLD MAEs: [0.5671944, 0.6041106, 0.5968487, 0.5943737, 0.6169202] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7566 (95% CI: [0.6852, 0.8312]) +Test MAE: 0.5890 (95% CI: [0.5437, 0.6389]) diff --git a/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_final_results.csv b/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..02ffd4d0ec2c097a3cc671ef7534fb94f5accd11 --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_ecfp_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7683327,0.038465235,0.5958895,0.016349325,0.7565669,0.6851880639791489,0.8311858668923378,0.58895665,0.5437126487493515,0.6388532057404518 diff --git a/logs_hyperparameter/ic50/gat/gat_selfies_ic50_20250807_034412.txt b/logs_hyperparameter/ic50/gat/gat_selfies_ic50_20250807_034412.txt new file mode 100644 index 0000000000000000000000000000000000000000..875cdde0118aae9fc8cbcbc6acbe27f0450c80a9 --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_selfies_ic50_20250807_034412.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6971, MAE: 0.5773 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7739, MAE: 0.6038 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7797, MAE: 0.6062 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8026, MAE: 0.6206 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8512, MAE: 0.6367 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7809 ± 0.0500 +Unbiased Validation MAE: 0.6089 ± 0.0197 +VAL FOLD RMSEs: [0.69710433, 0.7738917, 0.77971977, 0.80258536, 0.8512124] +VAL FOLD MAEs: [0.57725424, 0.6037833, 0.6061724, 0.62056863, 0.63674796] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7400 (95% CI: [0.6772, 0.8113]) +Test MAE: 0.5883 (95% CI: [0.5447, 0.6321]) diff --git a/logs_hyperparameter/ic50/gat/gat_selfies_ic50_final_results.csv b/logs_hyperparameter/ic50/gat/gat_selfies_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..039ca062f197396c8fba0fa10ec9c70ac8eeff97 --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_selfies_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7809027,0.049972612,0.6089053,0.019731905,0.73995656,0.6772415176033973,0.8113442778587341,0.58833206,0.5446938008069993,0.6320715591311454 diff --git a/logs_hyperparameter/ic50/gat/gat_smiles_ic50_20250807_021355.txt b/logs_hyperparameter/ic50/gat/gat_smiles_ic50_20250807_021355.txt new file mode 100644 index 0000000000000000000000000000000000000000..218c229f6fb1c3fa28d928d18ce8e3af88ab4a57 --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_smiles_ic50_20250807_021355.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6991, MAE: 0.5789 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7755, MAE: 0.6046 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7806, MAE: 0.6029 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8014, MAE: 0.6199 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8520, MAE: 0.6356 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7817 ± 0.0494 +Unbiased Validation MAE: 0.6084 ± 0.0189 +VAL FOLD RMSEs: [0.6990943, 0.7754881, 0.7805639, 0.8014007, 0.85203683] +VAL FOLD MAEs: [0.5788892, 0.6045853, 0.60285914, 0.6198977, 0.6356304] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7415 (95% CI: [0.6722, 0.8143]) +Test MAE: 0.5808 (95% CI: [0.5351, 0.6253]) diff --git a/logs_hyperparameter/ic50/gat/gat_smiles_ic50_final_results.csv b/logs_hyperparameter/ic50/gat/gat_smiles_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..67ce1a8b5aacf0aa395c25f37051c383dfbb641d --- /dev/null +++ b/logs_hyperparameter/ic50/gat/gat_smiles_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7817167,0.04939427,0.60837233,0.018919995,0.7414857,0.6722162619233132,0.8143389344215393,0.5807506,0.5351404964923858,0.6252640798687935 diff --git a/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_20250806_221500.txt b/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_20250806_221500.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff7c7ef583b67fba1c7860ff61b473c6a21a5815 --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_20250806_221500.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6986, MAE: 0.5637 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7602, MAE: 0.5936 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7645, MAE: 0.5940 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.7949, MAE: 0.6118 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8004, MAE: 0.6176 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7637 ± 0.0362 +Unbiased Validation MAE: 0.5961 ± 0.0188 +VAL FOLD RMSEs: [0.69864047, 0.76020634, 0.76454, 0.79489416, 0.8003817] +VAL FOLD MAEs: [0.5637206, 0.593561, 0.5939624, 0.61175394, 0.6175922] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7718 (95% CI: [0.6990, 0.8464]) +Test MAE: 0.5954 (95% CI: [0.5456, 0.6472]) diff --git a/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_final_results.csv b/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..66abdd7f1f8a3018f6628302511af6589c354041 --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_ecfp_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.76373255,0.036233336,0.5961181,0.018795755,0.77180755,0.6989554286003112,0.8463731825351715,0.5953723,0.5455556213855743,0.6472474813461304 diff --git a/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_20250806_210042.txt b/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_20250806_210042.txt new file mode 100644 index 0000000000000000000000000000000000000000..97694a4495162d1addad173e20ff22fd374b0ba7 --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_20250806_210042.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6972, MAE: 0.5789 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7768, MAE: 0.5913 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7784, MAE: 0.6026 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8054, MAE: 0.6206 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8546, MAE: 0.6405 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7825 ± 0.0511 +Unbiased Validation MAE: 0.6068 ± 0.0218 +VAL FOLD RMSEs: [0.69724864, 0.7767817, 0.7784024, 0.8054023, 0.8546479] +VAL FOLD MAEs: [0.57888144, 0.5912563, 0.6025561, 0.6206411, 0.6404889] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7452 (95% CI: [0.6767, 0.8158]) +Test MAE: 0.5890 (95% CI: [0.5467, 0.6341]) diff --git a/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_final_results.csv b/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..58132984ec211b789618bb6088deaf0501fe96ae --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_selfies_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7824966,0.05108251,0.60676473,0.021751212,0.74523056,0.67672458589077,0.8157954573631286,0.58896816,0.5466514259576798,0.634145998954773 diff --git a/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_20250806_182626.txt b/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_20250806_182626.txt new file mode 100644 index 0000000000000000000000000000000000000000..33a9d635462e726622742db38c265e6e74d8b3f5 --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_20250806_182626.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6972, MAE: 0.5784 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7773, MAE: 0.5962 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7776, MAE: 0.6024 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8052, MAE: 0.6224 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8535, MAE: 0.6364 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7822 ± 0.0508 +Unbiased Validation MAE: 0.6072 ± 0.0203 +VAL FOLD RMSEs: [0.697184, 0.7773402, 0.77758664, 0.8052164, 0.8535282] +VAL FOLD MAEs: [0.5784226, 0.5961952, 0.6024025, 0.6224248, 0.63640195] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7409 (95% CI: [0.6719, 0.8110]) +Test MAE: 0.5865 (95% CI: [0.5453, 0.6318]) diff --git a/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_final_results.csv b/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..cef144eaf2d83d6505576d40622f5b7a6394c7ac --- /dev/null +++ b/logs_hyperparameter/ic50/gcn/gcn_smiles_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.78217113,0.050774164,0.6071694,0.020282026,0.7409363,0.6718762397766114,0.8110423266887664,0.5864587,0.5453205436468125,0.6318082734942436 diff --git a/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_20250807_010518.txt b/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_20250807_010518.txt new file mode 100644 index 0000000000000000000000000000000000000000..9e2e32f2ea9c741ead1c4cd32130baa3144e9fe9 --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_20250807_010518.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.7240, MAE: 0.5878 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7865, MAE: 0.6156 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7657, MAE: 0.5893 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8192, MAE: 0.6134 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8169, MAE: 0.6186 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7825 ± 0.0354 +Unbiased Validation MAE: 0.6049 ± 0.0135 +VAL FOLD RMSEs: [0.7239972, 0.7865184, 0.76570946, 0.8191573, 0.8169361] +VAL FOLD MAEs: [0.5878297, 0.6156413, 0.58932984, 0.6133631, 0.6185621] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7644 (95% CI: [0.6877, 0.8350]) +Test MAE: 0.5930 (95% CI: [0.5448, 0.6421]) diff --git a/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_final_results.csv b/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..be11cb9527d88cfb5d91badb915834201430d245 --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_ecfp_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.78246367,0.035356034,0.6049452,0.013471948,0.76441914,0.6876585453748703,0.835017965734005,0.5929568,0.5448331966996193,0.6421438589692116 diff --git a/logs_hyperparameter/ic50/gin/gin_selfies_ic50_20250807_000443.txt b/logs_hyperparameter/ic50/gin/gin_selfies_ic50_20250807_000443.txt new file mode 100644 index 0000000000000000000000000000000000000000..22c8afc14c591621bb7974921b96e5f5f69ddc7a --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_selfies_ic50_20250807_000443.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6977, MAE: 0.5776 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7755, MAE: 0.6043 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7793, MAE: 0.6082 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8103, MAE: 0.6257 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8525, MAE: 0.6343 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7830 ± 0.0508 +Unbiased Validation MAE: 0.6100 ± 0.0196 +VAL FOLD RMSEs: [0.6977462, 0.77546686, 0.77926, 0.8102552, 0.8524575] +VAL FOLD MAEs: [0.5775548, 0.6043493, 0.60816514, 0.62569463, 0.63433427] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7408 (95% CI: [0.6767, 0.8127]) +Test MAE: 0.5897 (95% CI: [0.5458, 0.6358]) diff --git a/logs_hyperparameter/ic50/gin/gin_selfies_ic50_final_results.csv b/logs_hyperparameter/ic50/gin/gin_selfies_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e4a5a2385edb79b9b0d634ee8f417da895473aa6 --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_selfies_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7830372,0.05080577,0.6100196,0.01962887,0.7407952,0.6767094328999519,0.8127275973558425,0.589688,0.5458391204476356,0.6357943519949913 diff --git a/logs_hyperparameter/ic50/gin/gin_smiles_ic50_20250806_231735.txt b/logs_hyperparameter/ic50/gin/gin_smiles_ic50_20250806_231735.txt new file mode 100644 index 0000000000000000000000000000000000000000..291a09b3b6ccd9b0878add82e41c189a1bcb33da --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_smiles_ic50_20250806_231735.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.6981, MAE: 0.5772 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7733, MAE: 0.5986 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7802, MAE: 0.6092 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8101, MAE: 0.6249 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8539, MAE: 0.6343 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7831 ± 0.0511 +Unbiased Validation MAE: 0.6088 ± 0.0201 +VAL FOLD RMSEs: [0.6981208, 0.7732885, 0.78016627, 0.8100906, 0.8539174] +VAL FOLD MAEs: [0.57722247, 0.59861994, 0.60917723, 0.62485385, 0.6343427] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7398 (95% CI: [0.6706, 0.8179]) +Test MAE: 0.5862 (95% CI: [0.5415, 0.6301]) diff --git a/logs_hyperparameter/ic50/gin/gin_smiles_ic50_final_results.csv b/logs_hyperparameter/ic50/gin/gin_smiles_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..d9a4b1340cede32240057f58de7ce1837dba63b2 --- /dev/null +++ b/logs_hyperparameter/ic50/gin/gin_smiles_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7831167,0.051127173,0.6088432,0.02005523,0.73977476,0.6705531492829323,0.8179088845849037,0.586204,0.5415007993578911,0.6301335588097572 diff --git a/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_20250806_173101.txt b/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_20250806_173101.txt new file mode 100644 index 0000000000000000000000000000000000000000..e6218186055812c2e2b11d924f84ef04b45f8dbb --- /dev/null +++ b/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_20250806_173101.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6985, MAE: 0.5698 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7606, MAE: 0.5935 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7339, MAE: 0.5911 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8041, MAE: 0.6273 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.7848, MAE: 0.5992 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7564 ± 0.0373 +Unbiased Validation MAE: 0.5962 ± 0.0185 +VAL FOLD RMSEs: [0.6985499, 0.76059276, 0.73387456, 0.8041257, 0.7848152] +VAL FOLD MAEs: [0.5697988, 0.5935292, 0.5910881, 0.6273127, 0.59920466] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7499 (95% CI: [0.6886, 0.8171]) +Test MAE: 0.6064 (95% CI: [0.5659, 0.6522]) diff --git a/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_final_results.csv b/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..554ff63d743d7b2ad0c82c40ad82a2a7f82267d1 --- /dev/null +++ b/logs_hyperparameter/ic50/polyatomic/polyatomic_polyatomic_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.75639164,0.037300866,0.59618676,0.018478716,0.74987996,0.6886198222637177,0.8170708999037742,0.6064061,0.5658736512064934,0.6522233366966248 diff --git a/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_20250807_065802.txt b/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_20250807_065802.txt new file mode 100644 index 0000000000000000000000000000000000000000..91be657fd5213bf539d035e5945ad25a89fe2ce8 --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_20250807_065802.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.7011, MAE: 0.5719 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.7555, MAE: 0.5825 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7636, MAE: 0.5893 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8021, MAE: 0.6038 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.7968, MAE: 0.6121 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7638 ± 0.0362 +Unbiased Validation MAE: 0.5919 ± 0.0144 +VAL FOLD RMSEs: [0.7011157, 0.75546557, 0.76357734, 0.802132, 0.7967714] +VAL FOLD MAEs: [0.57191694, 0.5825049, 0.5892569, 0.6037811, 0.61209196] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7840 (95% CI: [0.7054, 0.8604]) +Test MAE: 0.6036 (95% CI: [0.5563, 0.6525]) diff --git a/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_final_results.csv b/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..5c73af669ea2b11b0189216c94606679bc2356ad --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_ecfp_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7638124,0.036208525,0.59191036,0.014446117,0.7840457,0.7054138004779815,0.8603839963674546,0.6036483,0.5563011065125465,0.6525187000632287 diff --git a/logs_hyperparameter/ic50/sage/sage_selfies_ic50_20250807_062113.txt b/logs_hyperparameter/ic50/sage/sage_selfies_ic50_20250807_062113.txt new file mode 100644 index 0000000000000000000000000000000000000000..383f5bac2a0d61adda36153a08ebbce1abe97227 --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_selfies_ic50_20250807_062113.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6950, MAE: 0.5734 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7755, MAE: 0.6057 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.7834, MAE: 0.6104 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8054, MAE: 0.6216 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8531, MAE: 0.6376 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7825 ± 0.0514 +Unbiased Validation MAE: 0.6097 ± 0.0212 +VAL FOLD RMSEs: [0.69501734, 0.7755418, 0.783379, 0.8054232, 0.8530918] +VAL FOLD MAEs: [0.57339525, 0.6056714, 0.61038303, 0.62160957, 0.63758194] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7356 (95% CI: [0.6711, 0.8106]) +Test MAE: 0.5842 (95% CI: [0.5403, 0.6300]) diff --git a/logs_hyperparameter/ic50/sage/sage_selfies_ic50_final_results.csv b/logs_hyperparameter/ic50/sage/sage_selfies_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e99cb984168f245804bd4b3793f8d8d790bac7c0 --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_selfies_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7824906,0.051402483,0.6097282,0.021231897,0.7356324,0.6711157470941543,0.8105518594384193,0.58424413,0.5403454273939132,0.6300178900361061 diff --git a/logs_hyperparameter/ic50/sage/sage_smiles_ic50_20250807_053945.txt b/logs_hyperparameter/ic50/sage/sage_smiles_ic50_20250807_053945.txt new file mode 100644 index 0000000000000000000000000000000000000000..5d12aecd558de8090fd0e58718724ac049e9d08a --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_smiles_ic50_20250807_053945.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.6973, MAE: 0.5768 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7763, MAE: 0.6030 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7808, MAE: 0.6065 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8029, MAE: 0.6178 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8522, MAE: 0.6364 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7819 ± 0.0502 +Unbiased Validation MAE: 0.6081 ± 0.0195 +VAL FOLD RMSEs: [0.6972979, 0.77634597, 0.78081864, 0.8028901, 0.8522309] +VAL FOLD MAEs: [0.5767516, 0.6030207, 0.6065341, 0.6177553, 0.6363648] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7420 (95% CI: [0.6724, 0.8194]) +Test MAE: 0.5816 (95% CI: [0.5392, 0.6283]) diff --git a/logs_hyperparameter/ic50/sage/sage_smiles_ic50_final_results.csv b/logs_hyperparameter/ic50/sage/sage_smiles_ic50_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..d52e57f186af03f0f5d4fc342bf6b9e08990e56f --- /dev/null +++ b/logs_hyperparameter/ic50/sage/sage_smiles_ic50_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.78191674,0.05015288,0.60808533,0.019509472,0.7419668,0.6723687395453453,0.8193594828248024,0.58161926,0.5392254292964935,0.6282830119132995 diff --git a/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_20250807_041736.txt b/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_20250807_041736.txt new file mode 100644 index 0000000000000000000000000000000000000000..c073bb9de88d440e78289c2bb3f413bddafebc73 --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_20250807_041736.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 0.8423, MAE: 0.6495 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.9014, MAE: 0.6906 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.8923, MAE: 0.6802 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8479, MAE: 0.6330 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000512061330949742, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.8902, MAE: 0.6744 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.8748 ± 0.0246 +Unbiased Validation MAE: 0.6655 ± 0.0212 +VAL FOLD RMSEs: [0.84227663, 0.90136606, 0.8923173, 0.8478831, 0.89022315] +VAL FOLD MAEs: [0.64946544, 0.69063115, 0.680182, 0.6330018, 0.67435324] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.8630 (95% CI: [0.8122, 0.9123]) +Test MAE: 0.6582 (95% CI: [0.6191, 0.6964]) diff --git a/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e153fa4a8f019a0a1bdabf204d93c1c1cb387738 --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_ecfp_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.87481326,0.024628326,0.6655267,0.02116011,0.86296743,0.8121834725141526,0.9123018935322762,0.6582283,0.6191025748848915,0.6964211478829384 diff --git a/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_20250807_031325.txt b/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_20250807_031325.txt new file mode 100644 index 0000000000000000000000000000000000000000..cfd9591020fec8fda875a8469768058c78c2b094 --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_20250807_031325.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0073, MAE: 0.8102 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1408, MAE: 0.9177 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.0114, MAE: 0.8183 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.0004, MAE: 0.7949 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.0265, MAE: 0.8217 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0373 ± 0.0524 +Unbiased Validation MAE: 0.8326 ± 0.0436 +VAL FOLD RMSEs: [1.0072901, 1.1407707, 1.0114471, 1.0004274, 1.0264974] +VAL FOLD MAEs: [0.81021464, 0.917704, 0.81825674, 0.7949195, 0.8217348] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0813 (95% CI: [1.0369, 1.1286]) +Test MAE: 0.8811 (95% CI: [0.8410, 0.9245]) diff --git a/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f0a69d19116c3504e4260d6b4e6233d2f1764b37 --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_selfies_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0372865,0.052443177,0.83256596,0.04356005,1.0813401,1.0369376122951508,1.128629705309868,0.881104,0.8409702867269516,0.9244733691215515 diff --git a/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_20250807_014435.txt b/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_20250807_014435.txt new file mode 100644 index 0000000000000000000000000000000000000000..fa118c3fe6ae9cfbdadecf059c35cf12a5bb858c --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_20250807_014435.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0240, MAE: 0.8151 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.0929, MAE: 0.8771 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.9564, MAE: 0.7703 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.0401, MAE: 0.8286 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.0400, MAE: 0.8322 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0307 ± 0.0438 +Unbiased Validation MAE: 0.8247 ± 0.0343 +VAL FOLD RMSEs: [1.0240291, 1.0928721, 0.9564402, 1.0401219, 1.0399616] +VAL FOLD MAEs: [0.81510943, 0.8770899, 0.7702836, 0.8286036, 0.8321912] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0687 (95% CI: [1.0178, 1.1189]) +Test MAE: 0.8601 (95% CI: [0.8162, 0.9050]) diff --git a/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..55588ec579cb70313f90d87c2d7b4d698c34bca5 --- /dev/null +++ b/logs_hyperparameter/lipophil/gat/gat_smiles_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0306851,0.043815386,0.82465553,0.034261283,1.0687467,1.0177781909704209,1.1188561737537384,0.8601121,0.8162091881036758,0.9050221487879753 diff --git a/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_20250806_214442.txt b/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_20250806_214442.txt new file mode 100644 index 0000000000000000000000000000000000000000..c2dbbff00311fec04a18e1b0d75a56cdc2161b8a --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_20250806_214442.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.8377, MAE: 0.6425 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.9034, MAE: 0.6951 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.8689, MAE: 0.6717 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8412, MAE: 0.6369 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8774, MAE: 0.6679 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.8657 ± 0.0243 +Unbiased Validation MAE: 0.6628 ± 0.0211 +VAL FOLD RMSEs: [0.8377028, 0.9034464, 0.8689035, 0.8411651, 0.87742245] +VAL FOLD MAEs: [0.6425362, 0.69510144, 0.67174226, 0.6368776, 0.6679089] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.8376 (95% CI: [0.7875, 0.8874]) +Test MAE: 0.6376 (95% CI: [0.6008, 0.6733]) diff --git a/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..26eb8bba4aaee4ee62ec237640a561d4d4aeeca9 --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_ecfp_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.865728,0.024323924,0.6628333,0.021128342,0.8376183,0.7875494062900543,0.8873757675290108,0.6375895,0.6007521942257881,0.6732938289642334 diff --git a/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_20250806_195106.txt b/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_20250806_195106.txt new file mode 100644 index 0000000000000000000000000000000000000000..36cc531f9421a8f0314cef557d3a0c1b75eca4d0 --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_20250806_195106.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0619, MAE: 0.8518 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1500, MAE: 0.9252 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.0574, MAE: 0.8609 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.0483, MAE: 0.8435 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.0321, MAE: 0.8323 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0700 ± 0.0413 +Unbiased Validation MAE: 0.8627 ± 0.0326 +VAL FOLD RMSEs: [1.0618868, 1.1500381, 1.0574173, 1.0483361, 1.0321456] +VAL FOLD MAEs: [0.8518001, 0.9251974, 0.8608941, 0.8434937, 0.8322994] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1055 (95% CI: [1.0573, 1.1495]) +Test MAE: 0.9057 (95% CI: [0.8631, 0.9466]) diff --git a/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..06a74462dbadde526db1c5dd76d2c4ff6ed33e8e --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_selfies_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0699648,0.041309852,0.862737,0.03262229,1.1055319,1.0573412656784058,1.1494525164365768,0.90571225,0.8630787745118141,0.9466129168868065 diff --git a/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_20250806_155554.txt b/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_20250806_155554.txt new file mode 100644 index 0000000000000000000000000000000000000000..8094c0655d990e1bd64a99eb5437215dbd125357 --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_20250806_155554.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.0863, MAE: 0.8700 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1548, MAE: 0.9286 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.0675, MAE: 0.8672 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.0416, MAE: 0.8446 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.0250, MAE: 0.8339 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0750 ± 0.0451 +Unbiased Validation MAE: 0.8689 ± 0.0328 +VAL FOLD RMSEs: [1.0863073, 1.1548202, 1.0674616, 1.04156, 1.0250423] +VAL FOLD MAEs: [0.870024, 0.9286414, 0.8672387, 0.8445846, 0.8339409] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.1096 (95% CI: [1.0627, 1.1570]) +Test MAE: 0.9059 (95% CI: [0.8598, 0.9497]) diff --git a/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..07f05d8c2e47b654340f0f7e147d502e03b70afc --- /dev/null +++ b/logs_hyperparameter/lipophil/gcn/gcn_smiles_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0750383,0.045099758,0.8688859,0.03282204,1.10958,1.0626829326152802,1.1570090502500534,0.9059361,0.8598464623093605,0.9497103571891785 diff --git a/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_20250807_005748.txt b/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_20250807_005748.txt new file mode 100644 index 0000000000000000000000000000000000000000..278dba70d850fbb65b29c27ce0c9551acdbfdd27 --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_20250807_005748.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.7848, MAE: 0.5788 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.8534, MAE: 0.6486 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.8578, MAE: 0.6534 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.7862, MAE: 0.5752 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8632, MAE: 0.6465 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.8291 ± 0.0357 +Unbiased Validation MAE: 0.6205 ± 0.0356 +VAL FOLD RMSEs: [0.7847963, 0.8533852, 0.8578297, 0.78617984, 0.8632071] +VAL FOLD MAEs: [0.5787641, 0.6485589, 0.65339196, 0.575249, 0.6464743] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.8080 (95% CI: [0.7599, 0.8597]) +Test MAE: 0.6049 (95% CI: [0.5708, 0.6421]) diff --git a/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..27729ddc832be9c6076f9475c18398cc7408a715 --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_ecfp_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.8290796,0.035730705,0.6204877,0.035590407,0.80795074,0.7598788127303123,0.8597462177276611,0.60490024,0.5708410665392876,0.6421283125877381 diff --git a/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_20250806_235254.txt b/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_20250806_235254.txt new file mode 100644 index 0000000000000000000000000000000000000000..2c7267b3f0db99cb32c6be205b8093ce915707a3 --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_20250806_235254.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.0761, MAE: 0.8539 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.1230, MAE: 0.8821 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.0397, MAE: 0.8416 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.9472, MAE: 0.7505 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.1233, MAE: 0.9112 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0619 ± 0.0653 +Unbiased Validation MAE: 0.8479 ± 0.0543 +VAL FOLD RMSEs: [1.0761496, 1.1230004, 1.0397457, 0.94723046, 1.1232656] +VAL FOLD MAEs: [0.853885, 0.8821075, 0.84163904, 0.7504835, 0.91118205] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0850 (95% CI: [1.0324, 1.1378]) +Test MAE: 0.8714 (95% CI: [0.8266, 0.9134]) diff --git a/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..b51aae3adcf95e5f40dfb2eac0665f01efcb5a2d --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_selfies_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0618784,0.065332934,0.8478594,0.054295033,1.0849861,1.0324115484952927,1.1377701491117478,0.87140954,0.8266010701656341,0.9134212538599968 diff --git a/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_20250806_230021.txt b/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_20250806_230021.txt new file mode 100644 index 0000000000000000000000000000000000000000..95d60749c7dbbd5f161716efb67874a56c0c682b --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_20250806_230021.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.0721, MAE: 0.8541 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.0995, MAE: 0.8803 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.1260, MAE: 0.9186 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.9970, MAE: 0.8091 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.0639, MAE: 0.8491 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.0717 ± 0.0433 +Unbiased Validation MAE: 0.8622 ± 0.0362 +VAL FOLD RMSEs: [1.0720962, 1.0994934, 1.1260345, 0.9969926, 1.0639036] +VAL FOLD MAEs: [0.8541129, 0.88030696, 0.91859746, 0.80909556, 0.8491143] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0734 (95% CI: [1.0268, 1.1259]) +Test MAE: 0.8653 (95% CI: [0.8259, 0.9082]) diff --git a/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_final_results.csv b/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..af18dc946ca6b1d4a6d856dd25ce2c41b7f30e88 --- /dev/null +++ b/logs_hyperparameter/lipophil/gin/gin_smiles_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.0717041,0.04328244,0.86224544,0.036236014,1.0733794,1.026773989200592,1.1258708387613297,0.86529917,0.8258953347802163,0.9081551477313041 diff --git a/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_20250806_192357.txt b/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_20250806_192357.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f3884cb123304063d58314b8b7332b44689d71f --- /dev/null +++ b/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_20250806_192357.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.7018, MAE: 0.5207 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 0.7581, MAE: 0.5697 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0005205409661999493, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.7377, MAE: 0.5421 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.7037, MAE: 0.5185 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 0.6828, MAE: 0.5050 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.7168 ± 0.0272 +Unbiased Validation MAE: 0.5312 ± 0.0226 +VAL FOLD RMSEs: [0.7017787, 0.7580868, 0.7376821, 0.70374936, 0.682781] +VAL FOLD MAEs: [0.5206777, 0.56972057, 0.5421082, 0.5184605, 0.50495034] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.7502 (95% CI: [0.7015, 0.8015]) +Test MAE: 0.5462 (95% CI: [0.5117, 0.5792]) diff --git a/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_final_results.csv b/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..dc304ea11586bbf7b363b5d5983114cf681335f6 --- /dev/null +++ b/logs_hyperparameter/lipophil/polyatomic/polyatomic_polyatomic_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.7168156,0.027180556,0.5311835,0.02264897,0.75016576,0.7014528602361679,0.8015499889850617,0.5462008,0.5117125272750854,0.5791631370782853 diff --git a/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_20250807_064727.txt b/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_20250807_064727.txt new file mode 100644 index 0000000000000000000000000000000000000000..05283453903dff5369338f51328127771f796b4f --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_20250807_064727.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.8320, MAE: 0.6333 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.8886, MAE: 0.6900 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 0.8831, MAE: 0.6842 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 0.8485, MAE: 0.6448 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.8722, MAE: 0.6627 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.8649 ± 0.0214 +Unbiased Validation MAE: 0.6630 ± 0.0219 +VAL FOLD RMSEs: [0.83199096, 0.8885897, 0.8831197, 0.84849155, 0.8722358] +VAL FOLD MAEs: [0.6333107, 0.69003665, 0.6842443, 0.6448102, 0.662713] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 0.8504 (95% CI: [0.8030, 0.8994]) +Test MAE: 0.6512 (95% CI: [0.6164, 0.6886]) diff --git a/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_final_results.csv b/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..bb71ca81306bd8e33b23102c3644ea5be92d8c49 --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_ecfp_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.8648855,0.021443943,0.663023,0.021884717,0.85043377,0.8029665648937225,0.8993544921278953,0.65115297,0.6163872227072715,0.6886072561144828 diff --git a/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_20250807_061653.txt b/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_20250807_061653.txt new file mode 100644 index 0000000000000000000000000000000000000000..d61760a8f8fe3150581098c33a9baad7cb645ef1 --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_20250807_061653.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.9322, MAE: 0.7380 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 0.9835, MAE: 0.7878 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.9816, MAE: 0.7646 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8794, MAE: 0.7070 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.9561, MAE: 0.7520 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.9466 ± 0.0385 +Unbiased Validation MAE: 0.7499 ± 0.0270 +VAL FOLD RMSEs: [0.9321949, 0.983528, 0.9815944, 0.87940174, 0.95611686] +VAL FOLD MAEs: [0.73795587, 0.7877715, 0.7645999, 0.707037, 0.7519918] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0301 (95% CI: [0.9724, 1.0951]) +Test MAE: 0.8117 (95% CI: [0.7664, 0.8533]) diff --git a/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_final_results.csv b/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..ce2f1d99710fbf66f189dd9d02bc85b3ceb14a05 --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_selfies_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.9465672,0.03847587,0.7498712,0.026961502,1.0300989,0.9724158331751823,1.095108425617218,0.81173235,0.7664284735918045,0.8533432692289352 diff --git a/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_20250807_052211.txt b/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_20250807_052211.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff80166aa37949ff5969e9cc4733948a8177e21b --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_20250807_052211.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.9282, MAE: 0.7433 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.0003, MAE: 0.8138 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 0.9862, MAE: 0.7823 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8902, MAE: 0.7096 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 0.9711, MAE: 0.7651 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.9552 ± 0.0405 +Unbiased Validation MAE: 0.7628 ± 0.0352 +VAL FOLD RMSEs: [0.9281805, 1.0002553, 0.9862171, 0.8901509, 0.9711083] +VAL FOLD MAEs: [0.74333346, 0.8137801, 0.78225636, 0.7095933, 0.7651388] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0165 (95% CI: [0.9537, 1.0803]) +Test MAE: 0.7974 (95% CI: [0.7556, 0.8429]) diff --git a/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_final_results.csv b/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..3edc96e0c6f047a6d9df2da3847658bc8185dcca --- /dev/null +++ b/logs_hyperparameter/lipophil/sage/sage_smiles_lipophil_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.95518243,0.040513095,0.7628204,0.03519344,1.0164648,0.9536988407373428,1.080274561047554,0.79739565,0.7555633842945099,0.8429233476519584 diff --git a/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_20250807_042937.txt b/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_20250807_042937.txt new file mode 100644 index 0000000000000000000000000000000000000000..a4eb1e5ff379236b29fb981bc8853a916165cea9 --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_20250807_042937.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.5513, MAE: 1.8676 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.5809, MAE: 1.8360 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.4655, MAE: 1.7986 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.2138, MAE: 1.7425 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.6397, MAE: 1.8842 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.4902 ± 0.1492 +Unbiased Validation MAE: 1.8258 ± 0.0509 +VAL FOLD RMSEs: [2.5512536, 2.5809188, 2.465463, 2.213786, 2.63966] +VAL FOLD MAEs: [1.8676136, 1.8359644, 1.7985966, 1.7425057, 1.8841503] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.4370 (95% CI: [2.1607, 2.7298]) +Test MAE: 1.7869 (95% CI: [1.6359, 1.9604]) diff --git a/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_final_results.csv b/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e36aaf6c1206491c550a5f8c82eab21af5f948d8 --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_ecfp_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.4902163,0.14920615,1.825766,0.050861392,2.4369779,2.1606655359268188,2.7297734379768372,1.7869321,1.6359185129404068,1.9604075729846955 diff --git a/logs_hyperparameter/qm9/gat/gat_selfies_qm9_20250807_032700.txt b/logs_hyperparameter/qm9/gat/gat_selfies_qm9_20250807_032700.txt new file mode 100644 index 0000000000000000000000000000000000000000..f14ce0abf792cd57b4be12b1cbdb685b8e42e9c4 --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_selfies_qm9_20250807_032700.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0008903488639350984, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 1 Val RMSE: 1.9764, MAE: 1.5217 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.8777, MAE: 1.4999 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.9856, MAE: 1.5523 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 4 Val RMSE: 1.8503, MAE: 1.4848 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.7992, MAE: 1.4080 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.8979 ± 0.0725 +Unbiased Validation MAE: 1.4933 ± 0.0483 +VAL FOLD RMSEs: [1.9764494, 1.877692, 1.9855684, 1.8503289, 1.7992449] +VAL FOLD MAEs: [1.5216558, 1.4998655, 1.5523374, 1.4848197, 1.4079775] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.8172 (95% CI: [1.6863, 1.9580]) +Test MAE: 1.4215 (95% CI: [1.3083, 1.5347]) diff --git a/logs_hyperparameter/qm9/gat/gat_selfies_qm9_final_results.csv b/logs_hyperparameter/qm9/gat/gat_selfies_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..20fbea0d7076a28c2361fcdc3ac52ac11fd7b22f --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_selfies_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.8978567,0.07247061,1.4933312,0.048341326,1.8171899,1.6863229781389237,1.9580171406269073,1.42149,1.3083435624837876,1.5346636354923249 diff --git a/logs_hyperparameter/qm9/gat/gat_smiles_qm9_20250807_020601.txt b/logs_hyperparameter/qm9/gat/gat_smiles_qm9_20250807_020601.txt new file mode 100644 index 0000000000000000000000000000000000000000..636e931072747aabc05b29d1589266817317c87b --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_smiles_qm9_20250807_020601.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.9635, MAE: 1.5101 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.9329, MAE: 1.5534 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.9371, MAE: 1.5118 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.7641, MAE: 1.3989 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.8830, MAE: 1.4659 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.8961 ± 0.0709 +Unbiased Validation MAE: 1.4880 ± 0.0525 +VAL FOLD RMSEs: [1.9634508, 1.932869, 1.9371089, 1.7640986, 1.8830061] +VAL FOLD MAEs: [1.5100807, 1.5534277, 1.5118332, 1.398874, 1.4659252] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.7821 (95% CI: [1.6526, 1.9226]) +Test MAE: 1.4027 (95% CI: [1.2932, 1.5141]) diff --git a/logs_hyperparameter/qm9/gat/gat_smiles_qm9_final_results.csv b/logs_hyperparameter/qm9/gat/gat_smiles_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..8c749080a7fcdc88f34b1a1379420c0928fbd5bd --- /dev/null +++ b/logs_hyperparameter/qm9/gat/gat_smiles_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.8961067,0.07094451,1.4880282,0.05247302,1.7820971,1.6526167452335359,1.922596263885498,1.4026697,1.2932410925626754,1.5141295045614243 diff --git a/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_20250806_220151.txt b/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_20250806_220151.txt new file mode 100644 index 0000000000000000000000000000000000000000..a893bf42c29a4505167a89923b294c6f2601f467 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_20250806_220151.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.5784, MAE: 1.8869 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.5615, MAE: 1.8237 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 2.4149, MAE: 1.7749 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.1853, MAE: 1.6687 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 2.6770, MAE: 1.9019 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.4834 ± 0.1710 +Unbiased Validation MAE: 1.8112 ± 0.0846 +VAL FOLD RMSEs: [2.57838, 2.561535, 2.4149296, 2.185348, 2.67698] +VAL FOLD MAEs: [1.8868897, 1.8236568, 1.7749122, 1.6686699, 1.9019158] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.4258 (95% CI: [2.2017, 2.6782]) +Test MAE: 1.8388 (95% CI: [1.6849, 2.0077]) diff --git a/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_final_results.csv b/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..ee61d7819cca15dfc45b93cc77bbd0f2be629ef2 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_ecfp_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.4834344,0.17095184,1.811209,0.08455185,2.4257605,2.2017188012599944,2.6782147526741027,1.8387908,1.6849226891994475,2.0077029049396513 diff --git a/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_20250806_203903.txt b/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_20250806_203903.txt new file mode 100644 index 0000000000000000000000000000000000000000..fdfb4b3219bfc16323190467c6fb87710a074935 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_20250806_203903.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.3541, MAE: 1.8725 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.5422, MAE: 2.0118 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.2721, MAE: 1.7723 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.3029, MAE: 1.8520 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.3173, MAE: 1.8458 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.3577 ± 0.0959 +Unbiased Validation MAE: 1.8709 ± 0.0782 +VAL FOLD RMSEs: [2.354123, 2.5421934, 2.272108, 2.3028762, 2.317317] +VAL FOLD MAEs: [1.8724579, 2.0117831, 1.7723186, 1.8519533, 1.8457639] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.1552 (95% CI: [2.0058, 2.3079]) +Test MAE: 1.7275 (95% CI: [1.6042, 1.8616]) diff --git a/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_final_results.csv b/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..e53d2a93f299b3383d3aa7e81b72c89543fcd422 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_selfies_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.3577237,0.095930204,1.8708556,0.078178726,2.1552043,2.0057984828948974,2.3078540802001952,1.7274907,1.6041636884212493,1.8616394072771072 diff --git a/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_20250806_175241.txt b/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_20250806_175241.txt new file mode 100644 index 0000000000000000000000000000000000000000..ecdff69c9756669a40445d200825b117b9aa3996 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_20250806_175241.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.4004, MAE: 1.9117 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.4855, MAE: 1.9547 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.4000, MAE: 1.8812 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.3299, MAE: 1.8825 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.4999, MAE: 1.9998 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.4231 ± 0.0625 +Unbiased Validation MAE: 1.9260 ± 0.0456 +VAL FOLD RMSEs: [2.400446, 2.4855356, 2.3999538, 2.329863, 2.4998913] +VAL FOLD MAEs: [1.9117088, 1.95466, 1.8811871, 1.8824711, 1.999798] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.1258 (95% CI: [1.9707, 2.2865]) +Test MAE: 1.6980 (95% CI: [1.5733, 1.8264]) diff --git a/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_final_results.csv b/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..0ff76018258da0642da14e467cda94ff8cc7a4a1 --- /dev/null +++ b/logs_hyperparameter/qm9/gcn/gcn_smiles_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.4231381,0.062509485,1.925965,0.045551613,2.1257544,1.9706973403692245,2.2864842295646666,1.6980115,1.5733041971921922,1.8264079600572585 diff --git a/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_20250807_010150.txt b/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_20250807_010150.txt new file mode 100644 index 0000000000000000000000000000000000000000..b2400bbaf24a74a1c63b15209cfc725f0577abc9 --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_20250807_010150.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.6952, MAE: 2.0077 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.6237, MAE: 1.9539 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 2.5349, MAE: 1.8949 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.3862, MAE: 1.8117 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.6752, MAE: 1.8954 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.5830 ± 0.1129 +Unbiased Validation MAE: 1.9127 ± 0.0656 +VAL FOLD RMSEs: [2.6951864, 2.6236815, 2.5349338, 2.386213, 2.6751897] +VAL FOLD MAEs: [2.0076506, 1.9539416, 1.8949391, 1.8116764, 1.8953559] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.000756755929227675, 'hidden_dim': 64, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.5473 (95% CI: [2.3074, 2.8026]) +Test MAE: 1.9268 (95% CI: [1.7693, 2.1007]) diff --git a/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_final_results.csv b/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..ea2d8748debb9a49f0dfba36f8850271fc9b08df --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_ecfp_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.583041,0.11293819,1.9127127,0.06563311,2.5472507,2.3074239432811736,2.8026447236537932,1.9268486,1.7692924708127975,2.1007129848003387 diff --git a/logs_hyperparameter/qm9/gin/gin_selfies_qm9_20250807_000423.txt b/logs_hyperparameter/qm9/gin/gin_selfies_qm9_20250807_000423.txt new file mode 100644 index 0000000000000000000000000000000000000000..d63cf06dc57d3a0b55cdcbe3b9af18d0e2740fc7 --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_selfies_qm9_20250807_000423.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.9413, MAE: 1.5503 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.9900, MAE: 1.5758 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.7768, MAE: 1.3913 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.8035, MAE: 1.4396 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.9045, MAE: 1.4886 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.8832 ± 0.0811 +Unbiased Validation MAE: 1.4891 ± 0.0682 +VAL FOLD RMSEs: [1.9412689, 1.9899793, 1.7768141, 1.803489, 1.9045007] +VAL FOLD MAEs: [1.550258, 1.5758418, 1.3912874, 1.4396323, 1.4885713] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.8119 (95% CI: [1.6849, 1.9451]) +Test MAE: 1.4349 (95% CI: [1.3279, 1.5402]) diff --git a/logs_hyperparameter/qm9/gin/gin_selfies_qm9_final_results.csv b/logs_hyperparameter/qm9/gin/gin_selfies_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..1307f4667ac12ef9fa5a4f3b9d35dd4597665693 --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_selfies_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.8832104,0.081116386,1.4891182,0.06823353,1.811927,1.6849426180124283,1.9451061367988587,1.4349041,1.3279449880123138,1.5402273595333098 diff --git a/logs_hyperparameter/qm9/gin/gin_smiles_qm9_20250806_231038.txt b/logs_hyperparameter/qm9/gin/gin_smiles_qm9_20250806_231038.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ae56c6f18f7f58b4e88e0ea66e3b29eec117832 --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_smiles_qm9_20250806_231038.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.9427, MAE: 1.5532 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.9342, MAE: 1.5586 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.7816, MAE: 1.4047 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.8228, MAE: 1.4652 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.8983, MAE: 1.4807 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.8759 ± 0.0633 +Unbiased Validation MAE: 1.4925 ± 0.0577 +VAL FOLD RMSEs: [1.9426814, 1.9341561, 1.7816337, 1.8228201, 1.8982962] +VAL FOLD MAEs: [1.553155, 1.5585524, 1.4046777, 1.465203, 1.4807452] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.8116 (95% CI: [1.6730, 1.9520]) +Test MAE: 1.4192 (95% CI: [1.3105, 1.5279]) diff --git a/logs_hyperparameter/qm9/gin/gin_smiles_qm9_final_results.csv b/logs_hyperparameter/qm9/gin/gin_smiles_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..a062b5c581d565c1db8aa60532a10c7b42ab1045 --- /dev/null +++ b/logs_hyperparameter/qm9/gin/gin_smiles_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.8759174,0.06333834,1.4924667,0.05768532,1.811594,1.6730497777462006,1.9520086735486983,1.4191768,1.3105366498231887,1.527921375632286 diff --git a/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_20250806_164528.txt b/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_20250806_164528.txt new file mode 100644 index 0000000000000000000000000000000000000000..f9c985d9e029d1894a1b92a54992de79f14cf8cf --- /dev/null +++ b/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_20250806_164528.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 0.8820, MAE: 0.6332 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006745255603940729, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 2 Val RMSE: 1.1308, MAE: 0.7949 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 3 Val RMSE: 1.0477, MAE: 0.6210 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007303755012255117, 'hidden_dim': 128, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 0.8865, MAE: 0.6080 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006175439707655367, 'hidden_dim': 128, 'batch_size': 64} +INFO: Fold 5 Val RMSE: 1.0486, MAE: 0.6356 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 0.9991 ± 0.0985 +Unbiased Validation MAE: 0.6586 ± 0.0689 +VAL FOLD RMSEs: [0.8820023, 1.1307861, 1.0477359, 0.8864545, 1.0485985] +VAL FOLD MAEs: [0.6332033, 0.7949072, 0.62104213, 0.6080294, 0.635636] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.0482 (95% CI: [0.8790, 1.2398]) +Test MAE: 0.6512 (95% CI: [0.5711, 0.7343]) diff --git a/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_final_results.csv b/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..f1b871c3dd5fa6372e6c1d09658f8cb666a218b0 --- /dev/null +++ b/logs_hyperparameter/qm9/polyatomic/polyatomic_polyatomic_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +0.99911547,0.0985471,0.6585636,0.06887665,1.048171,0.8790427416563034,1.2398007452487945,0.6512238,0.5711409240961075,0.7342670008540153 diff --git a/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_20250807_065233.txt b/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_20250807_065233.txt new file mode 100644 index 0000000000000000000000000000000000000000..8e1de03e8b2441c8285717e8db7a2e6345160cea --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_20250807_065233.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 2.6061, MAE: 1.9142 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 2.5916, MAE: 1.8754 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 2.4965, MAE: 1.8260 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0006858999160561152, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 2.2072, MAE: 1.6743 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 2.6765, MAE: 1.8881 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 2.5156 ± 0.1645 +Unbiased Validation MAE: 1.8356 ± 0.0856 +VAL FOLD RMSEs: [2.6061354, 2.5915596, 2.4964888, 2.2072282, 2.6765041] +VAL FOLD MAEs: [1.9141982, 1.8754232, 1.8260098, 1.6743358, 1.8880825] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0006482131165247735, 'hidden_dim': 64, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 2.4858 (95% CI: [2.2268, 2.7433]) +Test MAE: 1.8312 (95% CI: [1.6658, 1.9941]) diff --git a/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_final_results.csv b/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..6d5a91163fa097b8b1beb6aefd69ff0eaa9289cd --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_ecfp_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +2.515583,0.1645084,1.8356098,0.08557578,2.4857929,2.2268227458000185,2.743317526578903,1.831163,1.6658435702323913,1.994140887260437 diff --git a/logs_hyperparameter/qm9/sage/sage_selfies_qm9_20250807_061754.txt b/logs_hyperparameter/qm9/sage/sage_selfies_qm9_20250807_061754.txt new file mode 100644 index 0000000000000000000000000000000000000000..c41527cd8a32700c11da3e03e27f692e69ea7e1e --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_selfies_qm9_20250807_061754.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.6094, MAE: 1.2492 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.5330, MAE: 1.2057 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.5830, MAE: 1.1975 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5482, MAE: 1.2189 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.5304, MAE: 1.1610 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5608 ± 0.0307 +Unbiased Validation MAE: 1.2065 ± 0.0288 +VAL FOLD RMSEs: [1.6094201, 1.5330086, 1.582954, 1.5482352, 1.5303533] +VAL FOLD MAEs: [1.2492176, 1.2056562, 1.1975416, 1.2189474, 1.160976] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.4877 (95% CI: [1.3684, 1.6036]) +Test MAE: 1.1559 (95% CI: [1.0694, 1.2518]) diff --git a/logs_hyperparameter/qm9/sage/sage_selfies_qm9_final_results.csv b/logs_hyperparameter/qm9/sage/sage_selfies_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..2135ac7513b47bff27dd17d4c493400d3510afd0 --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_selfies_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5607942,0.030698376,1.2064677,0.028751083,1.4877061,1.3684388190507888,1.6035672694444656,1.1559283,1.0694493919610977,1.2517643034458161 diff --git a/logs_hyperparameter/qm9/sage/sage_smiles_qm9_20250807_053135.txt b/logs_hyperparameter/qm9/sage/sage_smiles_qm9_20250807_053135.txt new file mode 100644 index 0000000000000000000000000000000000000000..8cca4c005c97596d826bae2c8fdc0923718e2945 --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_smiles_qm9_20250807_053135.txt @@ -0,0 +1,35 @@ + +--- OUTER FOLD 1/5 --- +INFO: Best params for fold 1: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 1 Val RMSE: 1.5844, MAE: 1.2453 + +--- OUTER FOLD 2/5 --- +INFO: Best params for fold 2: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 2 Val RMSE: 1.4772, MAE: 1.1579 + +--- OUTER FOLD 3/5 --- +INFO: Best params for fold 3: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 3 Val RMSE: 1.5712, MAE: 1.2006 + +--- OUTER FOLD 4/5 --- +INFO: Best params for fold 4: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 4 Val RMSE: 1.5124, MAE: 1.1942 + +--- OUTER FOLD 5/5 --- +INFO: Best params for fold 5: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Fold 5 Val RMSE: 1.6147, MAE: 1.2485 + +------ Nested Cross-Validation Summary ------ +Unbiased Validation RMSE: 1.5520 ± 0.0500 +Unbiased Validation MAE: 1.2093 ± 0.0340 +VAL FOLD RMSEs: [1.5844079, 1.4772165, 1.57122, 1.5123905, 1.6147054] +VAL FOLD MAEs: [1.2453417, 1.157882, 1.2005837, 1.1941805, 1.2484735] + +===== STEP 2: Final Model Training & Testing ===== +INFO: Finding best hyperparameters on the FULL train/val set for final model... +INFO: Optimal hyperparameters for final model: {'lr': 0.0007618320309633699, 'hidden_dim': 256, 'batch_size': 32} +INFO: Training final model... + +===== STEP 3: Final Held-Out Test Evaluation ===== +Test RMSE: 1.4290 (95% CI: [1.3152, 1.5390]) +Test MAE: 1.0890 (95% CI: [0.9984, 1.1791]) diff --git a/logs_hyperparameter/qm9/sage/sage_smiles_qm9_final_results.csv b/logs_hyperparameter/qm9/sage/sage_smiles_qm9_final_results.csv new file mode 100644 index 0000000000000000000000000000000000000000..af1cdbfccc7920b703b1c66376416f9e75a55702 --- /dev/null +++ b/logs_hyperparameter/qm9/sage/sage_smiles_qm9_final_results.csv @@ -0,0 +1,2 @@ +val_rmse_mean,val_rmse_std,val_mae_mean,val_mae_std,test_rmse_mean,test_rmse_ci_low,test_rmse_ci_high,test_mae_mean,test_mae_ci_low,test_mae_ci_high +1.5519881,0.050026275,1.2092923,0.034005743,1.4290196,1.3151922315359115,1.5389916241168975,1.0889899,0.9984469681978225,1.1790605694055558 diff --git a/main.py b/main.py new file mode 100644 index 0000000000000000000000000000000000000000..6ef2593d7918f248227b2161034e3c0c993bf1c4 --- /dev/null +++ b/main.py @@ -0,0 +1,68 @@ +import argparse + +# The runners module will contain the high-level logic for each model type +from runners import run_gnn_experiment, run_gp_experiment + + +def main(): + """ + Main entry point for running all experiments. + Parses command-line arguments and calls the appropriate runner function. + """ + parser = argparse.ArgumentParser( + description="Run GNN or GP experiments for molecular property prediction." + ) + parser.add_argument( + "--model", + choices=["gcn", "gin", "gat", "sage", "gp", "polyatomic"], + required=True, + help="The model to train and evaluate.", + ) + parser.add_argument( + "--rep", + choices=["smiles", "selfies", "ecfp", "polyatomic"], + required=True, + help="The molecular representation to use.", + ) + parser.add_argument( + "--dataset", + choices=[ + "esol", + "freesolv", + "lipophil", + "boilingpoint", + "qm9", + "ic50", + "bindingdb", + ], + required=True, + help="The dataset to use for the experiment.", + ) + parser.add_argument( + "--n-trials", + type=int, + default=10, + help="Number of Optuna trials to run for hyperparameter search in each fold.", + ) + + args = parser.parse_args() + + # --- Argument Validation --- + if args.model == "gp" and args.rep == "polyatomic": + raise ValueError( + "The 'polyatomic' representation is not compatible with the 'gp' model." + ) + if args.model == "polyatomic" and args.rep != "polyatomic": + raise ValueError( + "The 'polyatomic' model must be used with the 'polyatomic' representation." + ) + + # --- Delegate to the correct runner --- + if args.model == "gp": + run_gp_experiment(args) + else: + run_gnn_experiment(args) + + +if __name__ == "__main__": + main() diff --git a/models/gnn.py b/models/gnn.py new file mode 100644 index 0000000000000000000000000000000000000000..54bcc4fea3f6152bc78a68a8357d8228ec646a14 --- /dev/null +++ b/models/gnn.py @@ -0,0 +1,74 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +from torch_geometric.nn import GCNConv, GINConv, GATConv, SAGEConv, global_mean_pool + + +class GCN(torch.nn.Module): + def __init__(self, in_channels, hidden_channels, out_channels): + super(GCN, self).__init__() + self.conv1 = GCNConv(in_channels, hidden_channels) + self.conv2 = GCNConv(hidden_channels, hidden_channels) + self.lin = nn.Linear(hidden_channels, out_channels) + + def forward(self, data): + x, edge_index, batch = data.x, data.edge_index, data.batch + x = F.relu(self.conv1(x, edge_index)) + x = F.relu(self.conv2(x, edge_index)) + x = global_mean_pool(x, batch) + return self.lin(x) + + +class GIN(torch.nn.Module): + def __init__(self, in_channels, hidden_channels, out_channels): + super(GIN, self).__init__() + nn1 = nn.Sequential( + nn.Linear(in_channels, hidden_channels), + nn.ReLU(), + nn.Linear(hidden_channels, hidden_channels), + ) + nn2 = nn.Sequential( + nn.Linear(hidden_channels, hidden_channels), + nn.ReLU(), + nn.Linear(hidden_channels, hidden_channels), + ) + self.conv1 = GINConv(nn1) + self.conv2 = GINConv(nn2) + self.lin = nn.Linear(hidden_channels, out_channels) + + def forward(self, data): + x, edge_index, batch = data.x, data.edge_index, data.batch + x = F.relu(self.conv1(x, edge_index)) + x = F.relu(self.conv2(x, edge_index)) + x = global_mean_pool(x, batch) + return self.lin(x) + + +class GAT(torch.nn.Module): + def __init__(self, in_channels, hidden_channels, out_channels, heads=4): + super(GAT, self).__init__() + self.conv1 = GATConv(in_channels, hidden_channels, heads=heads) + self.conv2 = GATConv(hidden_channels * heads, hidden_channels, heads=1) + self.lin = nn.Linear(hidden_channels, out_channels) + + def forward(self, data): + x, edge_index, batch = data.x, data.edge_index, data.batch + x = F.elu(self.conv1(x, edge_index)) + x = F.elu(self.conv2(x, edge_index)) + x = global_mean_pool(x, batch) + return self.lin(x) + + +class GraphSAGE(torch.nn.Module): + def __init__(self, in_channels, hidden_channels, out_channels): + super(GraphSAGE, self).__init__() + self.conv1 = SAGEConv(in_channels, hidden_channels) + self.conv2 = SAGEConv(hidden_channels, hidden_channels) + self.lin = nn.Linear(hidden_channels, out_channels) + + def forward(self, data): + x, edge_index, batch = data.x, data.edge_index, data.batch + x = F.relu(self.conv1(x, edge_index)) + x = F.relu(self.conv2(x, edge_index)) + x = global_mean_pool(x, batch) + return self.lin(x) diff --git a/models/gp.py b/models/gp.py new file mode 100644 index 0000000000000000000000000000000000000000..6f4e9b66085de3a6d202d281de005d1163fc5abb --- /dev/null +++ b/models/gp.py @@ -0,0 +1,53 @@ +import torch +import gpytorch +from gauche.kernels.fingerprint_kernels.tanimoto_kernel import TanimotoKernel +from gpytorch.kernels import ScaleKernel +from gpytorch.means import ConstantMean +from gpytorch.distributions import MultivariateNormal + + +class ExactGPModel(gpytorch.models.ExactGP): + def __init__(self, train_x, train_y, likelihood): + super().__init__(train_x, train_y, likelihood) + self.mean_module = ConstantMean() + self.covar_module = ScaleKernel(TanimotoKernel()) + + def forward(self, x): + mean_x = self.mean_module(x) + covar_x = self.covar_module(x) + return MultivariateNormal(mean_x, covar_x) # type: ignore + + +class TanimotoGP: + def __init__(self): + self.likelihood = gpytorch.likelihoods.GaussianLikelihood() + self.model = None + self.train_x = None + self.train_y = None + + def fit(self, X, y): + self.train_x = torch.tensor(X, dtype=torch.float) + self.train_y = torch.tensor(y, dtype=torch.float) + + self.model = ExactGPModel(self.train_x, self.train_y, self.likelihood) + self.model.train() + self.likelihood.train() + + optimizer = torch.optim.Adam(self.model.parameters(), lr=0.1) + mll = gpytorch.mlls.ExactMarginalLogLikelihood(self.likelihood, self.model) + + for i in range(50): + optimizer.zero_grad() + output = self.model(self.train_x) + loss = -1 * mll(output, self.train_y) # type: ignore + loss.backward() # type: ignore + optimizer.step() + + def predict(self, X): + self.model.eval() # type: ignore + self.likelihood.eval() + + test_x = torch.tensor(X, dtype=torch.float) + with torch.no_grad(), gpytorch.settings.fast_pred_var(): + preds = self.likelihood(self.model(test_x)) # type: ignore + return preds.mean.numpy(), preds.variance.numpy() diff --git a/models/polyatomic.py b/models/polyatomic.py new file mode 100644 index 0000000000000000000000000000000000000000..e884d4359b2afcc0c12776cd8e7b057b74fc5e23 --- /dev/null +++ b/models/polyatomic.py @@ -0,0 +1,139 @@ +import torch +import torch_geometric +import torch.nn as nn +import torch.nn.functional as F +from torch_geometric.nn import ( + PNAConv, + global_mean_pool, + global_max_pool, + global_add_pool, +) +from torch_geometric.utils import degree + + +class PolyatomicNet(nn.Module): + def __init__( + self, + node_feat_dim, + edge_feat_dim, + graph_feat_dim, + deg, + hidden_dim=128, + num_layers=5, + dropout=0.1, + ): + super().__init__() + self.graph_feat_dim = graph_feat_dim + self.node_emb = nn.Linear(node_feat_dim, hidden_dim) + self.deg = deg + self.virtualnode_emb = nn.Embedding(1, hidden_dim) + self.vn_mlp = nn.Sequential( + nn.Linear(hidden_dim, hidden_dim), + nn.ReLU(), + nn.Linear(hidden_dim, hidden_dim), + ) + + # For graph-level feature projection + self.graph_proj = nn.Sequential( + nn.Linear(graph_feat_dim, hidden_dim), + nn.ReLU(), + nn.Linear(hidden_dim, hidden_dim), + ) + + # PNAConv requires degree preprocessing + self.deg_emb = nn.Embedding(20, hidden_dim) # cap degree buckets + + aggregators = ["mean", "min", "max", "std"] + scalers = ["identity", "amplification", "attenuation"] + + self.convs = nn.ModuleList() + self.bns = nn.ModuleList() + + for _ in range(num_layers): + conv = PNAConv( + in_channels=hidden_dim, + out_channels=hidden_dim, + aggregators=aggregators, + scalers=scalers, + edge_dim=edge_feat_dim, + towers=4, + pre_layers=1, + post_layers=1, + divide_input=True, + deg=deg, + ) + self.convs.append(conv) + self.bns.append(nn.BatchNorm1d(hidden_dim)) + + self.dropout = nn.Dropout(dropout) + + # Final readout + self.readout = nn.Sequential( + nn.Linear(hidden_dim * 3, hidden_dim), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(hidden_dim, hidden_dim // 2), + nn.ReLU(), + nn.Linear(hidden_dim // 2, 1), + ) + + def forward(self, data): + x, edge_index, edge_attr, batch = ( + data.x, + data.edge_index, + data.edge_attr, + data.batch, + ) + + deg = degree(edge_index[0], x.size(0), dtype=torch.long).clamp(max=19) + h = self.node_emb(x) + self.deg_emb(deg) + + vn = self.virtualnode_emb( + torch.zeros(batch.max().item() + 1, dtype=torch.long, device=x.device) + ) + + for conv, bn in zip(self.convs, self.bns): + h = h + vn[batch] + h = conv(h, edge_index, edge_attr) + h = bn(h) + h = F.relu(h) + h = self.dropout(h) + vn = vn + self.vn_mlp(global_mean_pool(h, batch)) + + mean_pool = global_mean_pool(h, batch) + max_pool = global_max_pool(h, batch) + # add_pool = global_add_pool(h, batch) + + max_feat_dim = self.graph_feat_dim + + if hasattr(data, "graph_feats") and isinstance( + data, torch_geometric.data.Batch # type: ignore + ): + g_proj_list = [] + for g in data.to_data_list(): + g_feat = g.graph_feats.to(x.device) + + if g_feat.size(0) < max_feat_dim: + padded = torch.zeros(max_feat_dim, device=g_feat.device) + padded[: g_feat.size(0)] = g_feat + g_feat = padded + elif g_feat.size(0) > max_feat_dim: + g_feat = g_feat[:max_feat_dim] + g_feat = torch.nan_to_num(g_feat, nan=0.0, posinf=1e5, neginf=-1e5) + g_proj_list.append(self.graph_proj(g_feat)) + + g_proj = torch.stack(g_proj_list, dim=0) + + else: + g_feat = data.graph_feats.to(x.device) + if g_feat.size(0) < max_feat_dim: + padded = torch.zeros(max_feat_dim, device=g_feat.device) + padded[: g_feat.size(0)] = g_feat + g_feat = padded + elif g_feat.size(0) > max_feat_dim: + g_feat = g_feat[:max_feat_dim] + g_feat = torch.nan_to_num(g_feat, nan=0.0, posinf=1e5, neginf=-1e5) + g_proj = self.graph_proj(g_feat).unsqueeze(0) + + final_input = torch.cat([mean_pool, max_pool, g_proj], dim=1) + return self.readout(final_input).view(-1) diff --git a/notebooks/experiment_lipophil_n=50.ipynb b/notebooks/experiment_lipophil_n=50.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..327ed292f1e723bdf17520e1209860fa813be779 --- /dev/null +++ b/notebooks/experiment_lipophil_n=50.ipynb @@ -0,0 +1,528 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "RqYoTBJrCcJx" + }, + "outputs": [], + "source": [ + "%%capture\n", + "!pip install torch_geometric rdkit\n", + "!pip install torch-scatter -f https://data.pyg.org/whl/torch-$(python -c \"import torch; print(torch.__version__)\").html" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "M0suAYOT5R-N" + }, + "outputs": [], + "source": [ + "# Standard library\n", + "from collections import defaultdict\n", + "from typing import List, Tuple\n", + "import importlib.resources as pkg_resources\n", + "from multiprocessing.pool import ThreadPool\n", + "\n", + "# Third-party scientific stack\n", + "import numpy as np\n", + "import pandas as pd\n", + "from scipy.sparse import coo_matrix\n", + "from scipy.sparse.linalg import eigsh\n", + "\n", + "# RDKit\n", + "from rdkit import Chem\n", + "\n", + "# PyTorch core\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "\n", + "# PyTorch Geometric\n", + "import torch_geometric\n", + "from torch_geometric.data import Data, Batch, DataLoader\n", + "from torch_geometric.nn import GCNConv, GINConv, BatchNorm, global_mean_pool\n", + "from torch_geometric.loader import DataLoader as PyGDataLoader" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "4Wginy3UChb_", + "outputId": "981c9246-0f1c-403b-bac3-fc4941611c14" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" + ] + } + ], + "source": [ + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "obXQxOveCM9l" + }, + "outputs": [], + "source": [ + "def set_seed(seed):\n", + " \"\"\"\n", + " Fix all random seeds for reproducibility across Python, NumPy, and PyTorch.\n", + " \"\"\"\n", + " import random\n", + " random.seed(seed)\n", + " np.random.seed(seed)\n", + " torch.manual_seed(seed)\n", + " if torch.cuda.is_available():\n", + " torch.cuda.manual_seed_all(seed)\n", + " torch.backends.cudnn.deterministic = True\n", + " torch.backends.cudnn.benchmark = False\n", + "\n", + "set_seed(42)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "fYyEoAXuCM9m" + }, + "outputs": [], + "source": [ + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "from torch_geometric.nn import (\n", + " PNAConv,\n", + " global_mean_pool,\n", + " global_max_pool,\n", + " global_add_pool\n", + ")\n", + "from torch_geometric.utils import degree\n", + "\n", + "class PolyatomicNet(nn.Module):\n", + " def __init__(self, node_feat_dim, edge_feat_dim, graph_feat_dim,deg,\n", + " hidden_dim=128, num_layers=5, dropout=0.1):\n", + " super().__init__()\n", + "\n", + " self.node_emb = nn.Linear(node_feat_dim, hidden_dim)\n", + " self.deg = deg\n", + " self.virtualnode_emb = nn.Embedding(1, hidden_dim)\n", + " self.vn_mlp = nn.Sequential(\n", + " nn.Linear(hidden_dim, hidden_dim),\n", + " nn.ReLU(),\n", + " nn.Linear(hidden_dim, hidden_dim)\n", + " )\n", + "\n", + " # For graph-level feature projection\n", + " self.graph_proj = nn.Sequential(\n", + " nn.Linear(graph_feat_dim, hidden_dim),\n", + " nn.ReLU(),\n", + " nn.Linear(hidden_dim, hidden_dim)\n", + " )\n", + "\n", + " # PNAConv requires degree preprocessing\n", + " self.deg_emb = nn.Embedding(20, hidden_dim) # cap degree buckets\n", + "\n", + " aggregators = ['mean', 'min', 'max', 'std']\n", + " scalers = ['identity', 'amplification', 'attenuation']\n", + "\n", + " self.convs = nn.ModuleList()\n", + " self.bns = nn.ModuleList()\n", + "\n", + " for _ in range(num_layers):\n", + " conv = PNAConv(\n", + " in_channels=hidden_dim,\n", + " out_channels=hidden_dim,\n", + " aggregators=aggregators,\n", + " scalers=scalers,\n", + " edge_dim=edge_feat_dim,\n", + " towers=4,\n", + " pre_layers=1,\n", + " post_layers=1,\n", + " divide_input=True,\n", + " deg=deg\n", + " )\n", + " self.convs.append(conv)\n", + " self.bns.append(nn.BatchNorm1d(hidden_dim))\n", + "\n", + " self.dropout = nn.Dropout(dropout)\n", + "\n", + " # Final readout\n", + " self.readout = nn.Sequential(\n", + " nn.Linear(hidden_dim * 3, hidden_dim),\n", + " nn.ReLU(),\n", + " nn.Dropout(dropout),\n", + " nn.Linear(hidden_dim, hidden_dim // 2),\n", + " nn.ReLU(),\n", + " nn.Linear(hidden_dim // 2, 1),\n", + " )\n", + "\n", + " def forward(self, data):\n", + " x, edge_index, edge_attr, batch = (\n", + " data.x,\n", + " data.edge_index,\n", + " data.edge_attr,\n", + " data.batch,\n", + " )\n", + "\n", + " deg = degree(edge_index[0], x.size(0), dtype=torch.long).clamp(max=19)\n", + " h = self.node_emb(x) + self.deg_emb(deg)\n", + "\n", + " vn = self.virtualnode_emb(\n", + " torch.zeros(batch.max().item() + 1, dtype=torch.long, device=x.device)\n", + " )\n", + "\n", + " for conv, bn in zip(self.convs, self.bns):\n", + " h = h + vn[batch]\n", + " h = conv(h, edge_index, edge_attr)\n", + " h = bn(h)\n", + " h = F.relu(h)\n", + " h = self.dropout(h)\n", + " vn = vn + self.vn_mlp(global_mean_pool(h, batch))\n", + "\n", + " mean_pool = global_mean_pool(h, batch)\n", + " max_pool = global_max_pool(h, batch)\n", + " # add_pool = global_add_pool(h, batch)\n", + "\n", + " # graph_feats shape: [batch_size, graph_feat_dim]\n", + " if hasattr(data, 'graph_feats') and isinstance(data, torch_geometric.data.Batch):\n", + " g_feats = torch.stack([g.graph_feats for g in data.to_data_list()], dim=0).to(x.device)\n", + " else:\n", + " g_feats = data.graph_feats.unsqueeze(0).to(x.device)\n", + " g_proj = self.graph_proj(g_feats)\n", + "\n", + " final_input = torch.cat([mean_pool, max_pool, g_proj], dim=1)\n", + " return self.readout(final_input).view(-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "daTRiHSFCM9m" + }, + "outputs": [], + "source": [ + "from torch.amp import autocast, GradScaler\n", + "from sklearn.metrics import mean_absolute_error, mean_squared_error\n", + "\n", + "scaler_grad = GradScaler()\n", + "\n", + "def train(model, loader, optimizer, loss_fn, scaler=scaler_grad, accum_steps=8):\n", + " model.train()\n", + " total_loss = 0.0\n", + " optimizer.zero_grad()\n", + "\n", + " for i, batch in enumerate(loader):\n", + " batch = batch.to(device)\n", + " with autocast(device_type='cuda', dtype=torch.float16):\n", + " output = model(batch)\n", + " loss = loss_fn(output, batch.y.view(-1)) / accum_steps\n", + "\n", + " scaler_grad.scale(loss).backward()\n", + "\n", + " if (i + 1) % accum_steps == 0 or (i + 1 == len(loader)):\n", + " scaler.step(optimizer)\n", + " scaler.update()\n", + " optimizer.zero_grad()\n", + "\n", + " total_loss += loss.item() * batch.num_graphs * accum_steps\n", + "\n", + " return total_loss / len(loader.dataset)\n", + "\n", + "def compute_metrics_with_ci(trues, preds, n_boot=2000, alpha=0.05, seed=42):\n", + " trues = np.array(trues)\n", + " preds = np.array(preds)\n", + " mae = mean_absolute_error(trues, preds)\n", + " rmse = np.sqrt(mean_squared_error(trues, preds))\n", + "\n", + " rng = np.random.RandomState(seed)\n", + " mae_samples, rmse_samples = [], []\n", + " n = len(trues)\n", + " for _ in range(n_boot):\n", + " idx = rng.randint(0, n, n)\n", + " t, p = trues[idx], preds[idx]\n", + " mae_samples.append(mean_absolute_error(t, p))\n", + " rmse_samples.append(np.sqrt(mean_squared_error(t, p)))\n", + "\n", + " lower, upper = 100 * alpha / 2, 100 * (1 - alpha / 2)\n", + " mae_ci = (np.percentile(mae_samples, lower), np.percentile(mae_samples, upper))\n", + " rmse_ci = (np.percentile(rmse_samples, lower), np.percentile(rmse_samples, upper))\n", + " return {'mae': mae, 'mae_ci': mae_ci, 'rmse': rmse, 'rmse_ci': rmse_ci}\n", + "\n", + "def evaluate(model, loader):\n", + " model.eval()\n", + " preds, trues = [], []\n", + " with torch.no_grad(), autocast(device_type='cuda', dtype=torch.float16):\n", + " for batch in loader:\n", + " batch = batch.to(device)\n", + " out = model(batch)\n", + " preds.append(out.view(-1))\n", + " trues.append(batch.y.view(-1))\n", + " preds = torch.cat(preds)\n", + " trues = torch.cat(trues)\n", + " return torch.sqrt(torch.mean((preds - trues) ** 2)).item()\n", + "\n", + "def evaluate_with_ci(model, loader):\n", + " model.eval()\n", + " preds, trues = [], []\n", + " with torch.no_grad(), autocast(device_type='cuda', dtype=torch.float16):\n", + " for batch in loader:\n", + " batch = batch.to(device)\n", + " out = model(batch)\n", + " y_true = batch.y.view(-1).cpu().tolist()\n", + " y_pred = out.view(-1).cpu().tolist()\n", + " trues.extend(y_true)\n", + " preds.extend(y_pred)\n", + " return compute_metrics_with_ci(trues, preds)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "b7jK5FEjCM9m" + }, + "outputs": [], + "source": [ + "loading = True\n", + "if loading:\n", + " train_set = torch.load('/content/drive/MyDrive/lipophil_polyatomic_data/polyatomic_data_lipophil.pt', weights_only=False)\n", + " test_set = torch.load('/content/drive/MyDrive/lipophil_polyatomic_data/polyatomic_test_data_lipophil.pt', weights_only=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "aT9Ljr-SgTsE" + }, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings(\"ignore\", message=\".*An output with one or more elements was resized.*\")\n", + "warnings.filterwarnings(\"ignore\", message=\".*FutureWarning:.*\")\n", + "warnings.filterwarnings(\"ignore\", category=UserWarning, module=\"torch.optim.lr_scheduler\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "_ZBbQn-98XEu" + }, + "outputs": [], + "source": [ + "from torch_geometric.loader import DataLoader\n", + "\n", + "train_loader = DataLoader(train_set, batch_size=128, shuffle=True, num_workers=8, pin_memory=True)\n", + "test_loader = DataLoader(test_set, batch_size=128)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "XchdS-ZoCM9m" + }, + "outputs": [], + "source": [ + "node_feat_dim = train_set[0].x.shape[1]\n", + "edge_feat_dim = train_set[0].edge_attr.shape[1]\n", + "graph_feat_dim = train_set[0].graph_feats.shape[0]\n", + "\n", + "from torch_geometric.utils import degree\n", + "\n", + "deg = torch.zeros(128, dtype=torch.long)\n", + "\n", + "for data in train_loader:\n", + " d = degree(data.edge_index[1], num_nodes=data.num_nodes, dtype=torch.long)\n", + " bc = torch.bincount(d, minlength=deg.size(0))\n", + " if bc.size(0) > deg.size(0):\n", + " new_deg = torch.zeros(bc.size(0), dtype=torch.long)\n", + " new_deg[:deg.size(0)] = deg\n", + " deg = new_deg\n", + " deg += bc\n", + "\n", + "model = PolyatomicNet(\n", + " node_feat_dim=node_feat_dim,\n", + " edge_feat_dim=edge_feat_dim,\n", + " graph_feat_dim=graph_feat_dim,\n", + " deg=deg,\n", + ")\n", + "\n", + "input_dim = train_set[0].x.size(1)\n", + "optimizer = torch.optim.Adam(model.parameters(), lr=1e-3)\n", + "scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(\n", + " optimizer, mode='min', patience=10, factor=0.5, verbose=True\n", + ")\n", + "loss_fn = nn.SmoothL1Loss(beta=0.5)\n", + "\n", + "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", + "model = model.to(device)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Sp8U1CA2JmoL", + "outputId": "2239fd38-c080-43d6-ac3c-8a1a1a8e1421" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 01 | Train Loss: 0.5943 | Test MAE: 0.8046 (95% CI [0.7590, 0.8513]) | Test RMSE: 1.0218 (95% CI [0.9617, 1.0806])\n", + "Epoch 02 | Train Loss: 0.5771 | Test MAE: 0.8002 (95% CI [0.7539, 0.8467]) | Test RMSE: 1.0185 (95% CI [0.9580, 1.0792])\n", + "Epoch 03 | Train Loss: 0.5605 | Test MAE: 0.7535 (95% CI [0.7103, 0.7986]) | Test RMSE: 0.9599 (95% CI [0.9031, 1.0171])\n", + "Epoch 04 | Train Loss: 0.5315 | Test MAE: 0.7404 (95% CI [0.7016, 0.7805]) | Test RMSE: 0.9239 (95% CI [0.8766, 0.9719])\n", + "Epoch 05 | Train Loss: 0.5032 | Test MAE: 0.8859 (95% CI [0.8412, 0.9308]) | Test RMSE: 1.0662 (95% CI [1.0193, 1.1121])\n", + "Epoch 06 | Train Loss: 0.5014 | Test MAE: 0.7826 (95% CI [0.7362, 0.8297]) | Test RMSE: 1.0081 (95% CI [0.9490, 1.0657])\n", + "Epoch 07 | Train Loss: 0.4802 | Test MAE: 0.7119 (95% CI [0.6728, 0.7523]) | Test RMSE: 0.8873 (95% CI [0.8403, 0.9350])\n", + "Epoch 08 | Train Loss: 0.4727 | Test MAE: 0.7104 (95% CI [0.6703, 0.7509]) | Test RMSE: 0.8859 (95% CI [0.8378, 0.9337])\n", + "Epoch 09 | Train Loss: 0.4673 | Test MAE: 0.7104 (95% CI [0.6729, 0.7490]) | Test RMSE: 0.8803 (95% CI [0.8345, 0.9273])\n", + "Epoch 10 | Train Loss: 0.4557 | Test MAE: 0.7119 (95% CI [0.6721, 0.7506]) | Test RMSE: 0.8815 (95% CI [0.8354, 0.9291])\n", + "Epoch 11 | Train Loss: 0.4598 | Test MAE: 0.7039 (95% CI [0.6664, 0.7417]) | Test RMSE: 0.8657 (95% CI [0.8221, 0.9104])\n", + "Epoch 12 | Train Loss: 0.4408 | Test MAE: 0.7127 (95% CI [0.6723, 0.7565]) | Test RMSE: 0.9122 (95% CI [0.8589, 0.9676])\n", + "Epoch 13 | Train Loss: 0.4392 | Test MAE: 0.6718 (95% CI [0.6346, 0.7091]) | Test RMSE: 0.8371 (95% CI [0.7915, 0.8842])\n", + "Epoch 14 | Train Loss: 0.4239 | Test MAE: 0.9362 (95% CI [0.8893, 0.9794]) | Test RMSE: 1.1119 (95% CI [1.0635, 1.1551])\n", + "Epoch 15 | Train Loss: 0.4135 | Test MAE: 0.8397 (95% CI [0.7930, 0.8918]) | Test RMSE: 1.0707 (95% CI [1.0128, 1.1294])\n", + "Epoch 16 | Train Loss: 0.3985 | Test MAE: 0.7541 (95% CI [0.7098, 0.7995]) | Test RMSE: 0.9647 (95% CI [0.9087, 1.0179])\n", + "Epoch 17 | Train Loss: 0.4162 | Test MAE: 0.7120 (95% CI [0.6718, 0.7565]) | Test RMSE: 0.9148 (95% CI [0.8641, 0.9684])\n", + "Epoch 18 | Train Loss: 0.3940 | Test MAE: 0.6237 (95% CI [0.5877, 0.6614]) | Test RMSE: 0.7984 (95% CI [0.7517, 0.8465])\n", + "Epoch 19 | Train Loss: 0.3880 | Test MAE: 0.6442 (95% CI [0.6067, 0.6835]) | Test RMSE: 0.8313 (95% CI [0.7835, 0.8805])\n", + "Epoch 20 | Train Loss: 0.3973 | Test MAE: 0.6318 (95% CI [0.5954, 0.6711]) | Test RMSE: 0.8211 (95% CI [0.7725, 0.8727])\n", + "Epoch 21 | Train Loss: 0.3763 | Test MAE: 0.5911 (95% CI [0.5569, 0.6279]) | Test RMSE: 0.7676 (95% CI [0.7202, 0.8155])\n", + "Epoch 22 | Train Loss: 0.3671 | Test MAE: 0.6434 (95% CI [0.6052, 0.6847]) | Test RMSE: 0.8352 (95% CI [0.7863, 0.8878])\n", + "Epoch 23 | Train Loss: 0.3604 | Test MAE: 0.6489 (95% CI [0.6116, 0.6905]) | Test RMSE: 0.8388 (95% CI [0.7894, 0.8894])\n", + "Epoch 24 | Train Loss: 0.3413 | Test MAE: 0.6602 (95% CI [0.6228, 0.6978]) | Test RMSE: 0.8235 (95% CI [0.7787, 0.8676])\n", + "Epoch 25 | Train Loss: 0.3413 | Test MAE: 0.6013 (95% CI [0.5652, 0.6375]) | Test RMSE: 0.7824 (95% CI [0.7354, 0.8300])\n", + "Epoch 26 | Train Loss: 0.3379 | Test MAE: 0.6744 (95% CI [0.6387, 0.7120]) | Test RMSE: 0.8354 (95% CI [0.7897, 0.8826])\n", + "Epoch 27 | Train Loss: 0.3287 | Test MAE: 0.6842 (95% CI [0.6454, 0.7249]) | Test RMSE: 0.8793 (95% CI [0.8273, 0.9300])\n", + "Epoch 28 | Train Loss: 0.3380 | Test MAE: 0.5912 (95% CI [0.5562, 0.6268]) | Test RMSE: 0.7654 (95% CI [0.7200, 0.8120])\n", + "Epoch 29 | Train Loss: 0.3172 | Test MAE: 0.6528 (95% CI [0.6163, 0.6938]) | Test RMSE: 0.8352 (95% CI [0.7907, 0.8830])\n", + "Epoch 30 | Train Loss: 0.3174 | Test MAE: 0.9994 (95% CI [0.9520, 1.0473]) | Test RMSE: 1.1705 (95% CI [1.1227, 1.2189])\n", + "Epoch 31 | Train Loss: 0.3206 | Test MAE: 0.7928 (95% CI [0.7496, 0.8394]) | Test RMSE: 0.9942 (95% CI [0.9428, 1.0472])\n", + "Epoch 32 | Train Loss: 0.3183 | Test MAE: 0.5625 (95% CI [0.5288, 0.5980]) | Test RMSE: 0.7300 (95% CI [0.6829, 0.7789])\n", + "Epoch 33 | Train Loss: 0.3149 | Test MAE: 0.6162 (95% CI [0.5791, 0.6523]) | Test RMSE: 0.8013 (95% CI [0.7536, 0.8487])\n", + "Epoch 34 | Train Loss: 0.3104 | Test MAE: 0.6204 (95% CI [0.5827, 0.6592]) | Test RMSE: 0.7950 (95% CI [0.7504, 0.8436])\n", + "Epoch 35 | Train Loss: 0.3050 | Test MAE: 0.5997 (95% CI [0.5628, 0.6359]) | Test RMSE: 0.7868 (95% CI [0.7366, 0.8359])\n", + "Epoch 36 | Train Loss: 0.3138 | Test MAE: 0.5355 (95% CI [0.5031, 0.5705]) | Test RMSE: 0.7058 (95% CI [0.6588, 0.7543])\n", + "Epoch 37 | Train Loss: 0.2936 | Test MAE: 0.7361 (95% CI [0.6955, 0.7777]) | Test RMSE: 0.9210 (95% CI [0.8731, 0.9689])\n", + "Epoch 38 | Train Loss: 0.2766 | Test MAE: 0.5961 (95% CI [0.5623, 0.6318]) | Test RMSE: 0.7625 (95% CI [0.7154, 0.8112])\n", + "Epoch 39 | Train Loss: 0.2824 | Test MAE: 0.5254 (95% CI [0.4937, 0.5598]) | Test RMSE: 0.6938 (95% CI [0.6469, 0.7405])\n", + "Epoch 40 | Train Loss: 0.2883 | Test MAE: 0.6495 (95% CI [0.6102, 0.6912]) | Test RMSE: 0.8463 (95% CI [0.7953, 0.8971])\n", + "Epoch 41 | Train Loss: 0.2879 | Test MAE: 0.7258 (95% CI [0.6879, 0.7659]) | Test RMSE: 0.8936 (95% CI [0.8490, 0.9398])\n", + "Epoch 42 | Train Loss: 0.2796 | Test MAE: 0.6922 (95% CI [0.6523, 0.7335]) | Test RMSE: 0.8885 (95% CI [0.8383, 0.9384])\n", + "Epoch 43 | Train Loss: 0.2775 | Test MAE: 0.6467 (95% CI [0.6087, 0.6852]) | Test RMSE: 0.8160 (95% CI [0.7681, 0.8654])\n", + "Epoch 44 | Train Loss: 0.2754 | Test MAE: 0.6010 (95% CI [0.5643, 0.6381]) | Test RMSE: 0.7886 (95% CI [0.7390, 0.8376])\n", + "Epoch 45 | Train Loss: 0.2635 | Test MAE: 0.5278 (95% CI [0.4958, 0.5620]) | Test RMSE: 0.6978 (95% CI [0.6502, 0.7458])\n", + "Epoch 46 | Train Loss: 0.2594 | Test MAE: 0.5359 (95% CI [0.5006, 0.5720]) | Test RMSE: 0.7229 (95% CI [0.6721, 0.7738])\n", + "Epoch 47 | Train Loss: 0.2599 | Test MAE: 0.5426 (95% CI [0.5093, 0.5773]) | Test RMSE: 0.7057 (95% CI [0.6610, 0.7515])\n", + "Epoch 48 | Train Loss: 0.2649 | Test MAE: 0.5860 (95% CI [0.5506, 0.6228]) | Test RMSE: 0.7665 (95% CI [0.7181, 0.8148])\n", + "Epoch 49 | Train Loss: 0.2507 | Test MAE: 0.5366 (95% CI [0.5050, 0.5700]) | Test RMSE: 0.7033 (95% CI [0.6608, 0.7471])\n" + ] + } + ], + "source": [ + "history = {}\n", + "N = 50\n", + "for epoch in range(1, N):\n", + " tr_loss = train(model, train_loader, optimizer, loss_fn)\n", + " metrics = evaluate_with_ci(model, test_loader)\n", + " print(f\"Epoch {epoch:02d} | Train Loss: {tr_loss:.4f} | \"\n", + " f\"Test MAE: {metrics['mae']:.4f} (95% CI [{metrics['mae_ci'][0]:.4f}, {metrics['mae_ci'][1]:.4f}]) | \"\n", + " f\"Test RMSE: {metrics['rmse']:.4f} (95% CI [{metrics['rmse_ci'][0]:.4f}, {metrics['rmse_ci'][1]:.4f}])\")\n", + " history[epoch] = metrics\n", + " scheduler.step(metrics['mae'])" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "bCUfyuUlKjJb", + "outputId": "58469f70-ea2a-4a04-951f-7ee9f902dba7" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "********************\n", + "Test MAE: 0.5366 (95% CI [0.5050, 0.5700])\n", + "Test RMSE: 0.7033 (95% CI [0.6608, 0.7471])\n", + "********************\n" + ] + } + ], + "source": [ + "final = history[N-1]\n", + "print(\"*\"*20)\n", + "print(f\"Test MAE: {final['mae']:.4f} (95% CI [{final['mae_ci'][0]:.4f}, {final['mae_ci'][1]:.4f}])\")\n", + "print(f\"Test RMSE: {final['rmse']:.4f} (95% CI [{final['rmse_ci'][0]:.4f}, {final['rmse_ci'][1]:.4f}])\")\n", + "print(\"*\"*20)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "p12w2xn4Lb-U" + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuType": "T4", + "machine_shape": "hm", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/plotting/latex_table/bindingdb.tex b/plotting/latex_table/bindingdb.tex new file mode 100644 index 0000000000000000000000000000000000000000..f3cd58dd7f8559d72cbdf8c727c881ddd0919efe --- /dev/null +++ b/plotting/latex_table/bindingdb.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{BINDINGDB} & GAT (ECFP) & 1.512 \pm 0.055 & 1.235 \pm 0.053 & 1.7750 \pm 0.2480 & 1.3360 \pm 0.1105 \\ + & GAT (SELFIES) & 1.488 \pm 0.029 & 1.227 \pm 0.023 & 1.7820 \pm 0.2440 & 1.3600 \pm 0.1145 \\ + & GAT (SMILES) & 1.491 \pm 0.028 & 1.230 \pm 0.020 & 1.7540 \pm 0.2395 & 1.3560 \pm 0.1100 \\ + & GCN (ECFP) & 1.508 \pm 0.058 & 1.231 \pm 0.056 & 1.7620 \pm 0.2620 & 1.3220 \pm 0.1125 \\ + & GCN (SELFIES) & 1.492 \pm 0.031 & 1.231 \pm 0.023 & 1.7700 \pm 0.2485 & 1.3590 \pm 0.1110 \\ + & GCN (SMILES) & 1.495 \pm 0.031 & 1.234 \pm 0.023 & 1.8240 \pm 0.2750 & 1.3740 \pm 0.1210 \\ + & GIN (ECFP) & 1.520 \pm 0.050 & 1.253 \pm 0.044 & 1.7830 \pm 0.2580 & 1.3540 \pm 0.1135 \\ + & GIN (SELFIES) & 1.494 \pm 0.030 & 1.231 \pm 0.025 & 1.7550 \pm 0.2410 & 1.3450 \pm 0.1095 \\ + & GIN (SMILES) & 1.494 \pm 0.032 & 1.230 \pm 0.027 & 1.7440 \pm 0.2420 & 1.3390 \pm 0.1070 \\ + & POLYATOMIC & 1.479 \pm 0.034 & 1.211 \pm 0.030 & 1.7710 \pm 0.2420 & 1.3650 \pm 0.1080 \\ + & SAGE (ECFP) & 1.506 \pm 0.054 & 1.235 \pm 0.046 & 1.7720 \pm 0.2610 & 1.3450 \pm 0.1140 \\ + & SAGE (SELFIES) & 1.493 \pm 0.031 & 1.234 \pm 0.024 & 1.9120 \pm 0.3785 & 1.3760 \pm 0.1220 \\ + & SAGE (SMILES) & 1.493 \pm 0.030 & 1.232 \pm 0.024 & 1.7870 \pm 0.2450 & 1.3810 \pm 0.1105 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/boilingpoint.tex b/plotting/latex_table/boilingpoint.tex new file mode 100644 index 0000000000000000000000000000000000000000..718bebc3c2c5f7bd1365ccd55d6476e82c6cfb59 --- /dev/null +++ b/plotting/latex_table/boilingpoint.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{BOILINGPOINT} & GAT (ECFP) & 56.831 \pm 1.794 & 43.534 \pm 1.438 & 53.2660 \pm 4.5465 & 40.3050 \pm 3.2910 \\ + & GAT (SELFIES) & 55.602 \pm 1.883 & 42.244 \pm 1.894 & 56.0480 \pm 5.4735 & 40.4770 \pm 3.9400 \\ + & GAT (SMILES) & 55.240 \pm 2.739 & 41.337 \pm 2.469 & 60.7780 \pm 5.1350 & 45.3330 \pm 4.0420 \\ + & GCN (ECFP) & 57.010 \pm 1.529 & 43.315 \pm 1.254 & 54.6140 \pm 4.5240 & 41.7490 \pm 3.6545 \\ + & GCN (SELFIES) & 61.200 \pm 1.848 & 47.294 \pm 1.035 & 62.3820 \pm 5.2935 & 46.8430 \pm 4.1720 \\ + & GCN (SMILES) & 61.586 \pm 1.292 & 47.662 \pm 1.277 & 59.0360 \pm 4.8840 & 43.9270 \pm 3.7900 \\ + & GIN (ECFP) & 58.744 \pm 1.789 & 45.098 \pm 2.000 & 57.3840 \pm 5.0375 & 43.2210 \pm 3.6790 \\ + & GIN (SELFIES) & 58.629 \pm 0.867 & 44.500 \pm 0.975 & 57.8800 \pm 4.8570 & 42.4450 \pm 3.8065 \\ + & GIN (SMILES) & 59.282 \pm 2.271 & 45.235 \pm 2.034 & 57.1610 \pm 4.9560 & 42.1930 \pm 3.7810 \\ + & POLYATOMIC & 49.089 \pm 2.425 & 33.893 \pm 1.592 & 50.6350 \pm 6.4695 & 33.2600 \pm 3.6895 \\ + & SAGE (ECFP) & 57.161 \pm 1.253 & 43.714 \pm 0.873 & 55.2450 \pm 4.4265 & 42.1960 \pm 3.4290 \\ + & SAGE (SELFIES) & 54.345 \pm 2.264 & 40.948 \pm 1.797 & 53.0400 \pm 5.7445 & 37.4580 \pm 3.5905 \\ + & SAGE (SMILES) & 54.284 \pm 3.661 & 40.291 \pm 3.086 & 53.0110 \pm 5.5890 & 36.5630 \pm 3.7300 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/esol.tex b/plotting/latex_table/esol.tex new file mode 100644 index 0000000000000000000000000000000000000000..c5fb1deb3313d24e762ec7e08a7875a4f15edf34 --- /dev/null +++ b/plotting/latex_table/esol.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{ESOL} & GAT (ECFP) & 1.226 \pm 0.070 & 0.929 \pm 0.051 & 1.1730 \pm 0.1300 & 0.8790 \pm 0.1060 \\ + & GAT (SELFIES) & 1.170 \pm 0.117 & 0.902 \pm 0.082 & 0.9850 \pm 0.1210 & 0.7440 \pm 0.0890 \\ + & GAT (SMILES) & 1.085 \pm 0.125 & 0.834 \pm 0.087 & 1.1400 \pm 0.1200 & 0.8710 \pm 0.0945 \\ + & GCN (ECFP) & 1.223 \pm 0.057 & 0.932 \pm 0.048 & 1.1710 \pm 0.1220 & 0.8880 \pm 0.0960 \\ + & GCN (SELFIES) & 1.279 \pm 0.114 & 0.977 \pm 0.085 & 1.2750 \pm 0.1530 & 0.9490 \pm 0.1070 \\ + & GCN (SMILES) & 1.240 \pm 0.172 & 0.958 \pm 0.125 & 1.2970 \pm 0.1690 & 0.9460 \pm 0.1125 \\ + & GIN (ECFP) & 1.155 \pm 0.051 & 0.878 \pm 0.030 & 1.1070 \pm 0.1190 & 0.8500 \pm 0.0915 \\ + & GIN (SELFIES) & 1.247 \pm 0.172 & 0.940 \pm 0.138 & 1.3940 \pm 0.1890 & 0.9990 \pm 0.1235 \\ + & GIN (SMILES) & 1.196 \pm 0.082 & 0.908 \pm 0.068 & 1.3370 \pm 0.1570 & 0.9960 \pm 0.1170 \\ + & POLYATOMIC & 0.681 \pm 0.032 & 0.508 \pm 0.026 & 0.8290 \pm 0.1480 & 0.5930 \pm 0.0725 \\ + & SAGE (ECFP) & 1.218 \pm 0.076 & 0.922 \pm 0.058 & 1.1870 \pm 0.1175 & 0.8960 \pm 0.1040 \\ + & SAGE (SELFIES) & 1.055 \pm 0.116 & 0.802 \pm 0.080 & 0.9970 \pm 0.1215 & 0.7460 \pm 0.0840 \\ + & SAGE (SMILES) & 1.068 \pm 0.113 & 0.819 \pm 0.079 & 1.0890 \pm 0.1380 & 0.8140 \pm 0.0940 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/freesolv.tex b/plotting/latex_table/freesolv.tex new file mode 100644 index 0000000000000000000000000000000000000000..603315dae78b69580cf47b8dfdbd544d27bfa5fd --- /dev/null +++ b/plotting/latex_table/freesolv.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{FREESOLV} & GAT (ECFP) & 1.980 \pm 0.227 & 1.324 \pm 0.137 & 2.5360 \pm 0.7505 & 1.7260 \pm 0.3340 \\ + & GAT (SELFIES) & 2.787 \pm 0.361 & 2.059 \pm 0.334 & 3.6720 \pm 0.7910 & 2.7010 \pm 0.4400 \\ + & GAT (SMILES) & 2.777 \pm 0.373 & 2.070 \pm 0.305 & 3.7270 \pm 0.8130 & 2.7220 \pm 0.4425 \\ + & GCN (ECFP) & 2.005 \pm 0.238 & 1.309 \pm 0.147 & 2.5380 \pm 0.8070 & 1.6090 \pm 0.3315 \\ + & GCN (SELFIES) & 3.486 \pm 0.216 & 2.546 \pm 0.097 & 3.7730 \pm 0.8485 & 2.7260 \pm 0.4650 \\ + & GCN (SMILES) & 3.381 \pm 0.240 & 2.486 \pm 0.184 & 3.8800 \pm 0.8570 & 2.8550 \pm 0.4605 \\ + & GIN (ECFP) & 1.737 \pm 0.128 & 1.180 \pm 0.160 & 2.1720 \pm 0.5940 & 1.4270 \pm 0.2865 \\ + & GIN (SELFIES) & 3.427 \pm 0.170 & 2.553 \pm 0.133 & 3.8140 \pm 0.8350 & 2.7930 \pm 0.4465 \\ + & GIN (SMILES) & 3.454 \pm 0.199 & 2.528 \pm 0.123 & 3.6900 \pm 0.7775 & 2.6760 \pm 0.4545 \\ + & POLYATOMIC & 1.313 \pm 0.111 & 0.857 \pm 0.064 & 1.4390 \pm 0.4430 & 0.8560 \pm 0.1925 \\ + & SAGE (ECFP) & 1.894 \pm 0.162 & 1.285 \pm 0.150 & 2.3650 \pm 0.6605 & 1.5960 \pm 0.3140 \\ + & SAGE (SELFIES) & 2.498 \pm 0.429 & 1.851 \pm 0.389 & 3.7790 \pm 0.8365 & 2.7620 \pm 0.4305 \\ + & SAGE (SMILES) & 2.703 \pm 0.378 & 2.029 \pm 0.290 & 3.7890 \pm 0.8225 & 2.8020 \pm 0.4540 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/ic50.tex b/plotting/latex_table/ic50.tex new file mode 100644 index 0000000000000000000000000000000000000000..e7b91bc1d5147917db9c981ee221146379bea203 --- /dev/null +++ b/plotting/latex_table/ic50.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{IC50} & GAT (ECFP) & 0.768 \pm 0.038 & 0.596 \pm 0.016 & 0.7570 \pm 0.0730 & 0.5890 \pm 0.0475 \\ + & GAT (SELFIES) & 0.781 \pm 0.050 & 0.609 \pm 0.020 & 0.7400 \pm 0.0670 & 0.5880 \pm 0.0435 \\ + & GAT (SMILES) & 0.782 \pm 0.049 & 0.608 \pm 0.019 & 0.7410 \pm 0.0710 & 0.5810 \pm 0.0450 \\ + & GCN (ECFP) & 0.764 \pm 0.036 & 0.596 \pm 0.019 & 0.7720 \pm 0.0735 & 0.5950 \pm 0.0505 \\ + & GCN (SELFIES) & 0.782 \pm 0.051 & 0.607 \pm 0.022 & 0.7450 \pm 0.0695 & 0.5890 \pm 0.0435 \\ + & GCN (SMILES) & 0.782 \pm 0.051 & 0.607 \pm 0.020 & 0.7410 \pm 0.0695 & 0.5860 \pm 0.0435 \\ + & GIN (ECFP) & 0.782 \pm 0.035 & 0.605 \pm 0.013 & 0.7640 \pm 0.0735 & 0.5930 \pm 0.0485 \\ + & GIN (SELFIES) & 0.783 \pm 0.051 & 0.610 \pm 0.020 & 0.7410 \pm 0.0680 & 0.5900 \pm 0.0450 \\ + & GIN (SMILES) & 0.783 \pm 0.051 & 0.609 \pm 0.020 & 0.7400 \pm 0.0735 & 0.5860 \pm 0.0440 \\ + & POLYATOMIC & 0.756 \pm 0.037 & 0.596 \pm 0.018 & 0.7500 \pm 0.0640 & 0.6060 \pm 0.0430 \\ + & SAGE (ECFP) & 0.764 \pm 0.036 & 0.592 \pm 0.014 & 0.7840 \pm 0.0775 & 0.6040 \pm 0.0485 \\ + & SAGE (SELFIES) & 0.782 \pm 0.051 & 0.610 \pm 0.021 & 0.7360 \pm 0.0700 & 0.5840 \pm 0.0450 \\ + & SAGE (SMILES) & 0.782 \pm 0.050 & 0.608 \pm 0.020 & 0.7420 \pm 0.0735 & 0.5820 \pm 0.0445 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/lipophil.tex b/plotting/latex_table/lipophil.tex new file mode 100644 index 0000000000000000000000000000000000000000..92df7384ed6d804b72a67d3305410c107e7ded96 --- /dev/null +++ b/plotting/latex_table/lipophil.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{LIPOPHIL} & GAT (ECFP) & 0.875 \pm 0.025 & 0.666 \pm 0.021 & 0.8630 \pm 0.0500 & 0.6580 \pm 0.0385 \\ + & GAT (SELFIES) & 1.037 \pm 0.052 & 0.833 \pm 0.044 & 1.0810 \pm 0.0460 & 0.8810 \pm 0.0415 \\ + & GAT (SMILES) & 1.031 \pm 0.044 & 0.825 \pm 0.034 & 1.0690 \pm 0.0505 & 0.8600 \pm 0.0445 \\ + & GCN (ECFP) & 0.866 \pm 0.024 & 0.663 \pm 0.021 & 0.8380 \pm 0.0495 & 0.6380 \pm 0.0360 \\ + & GCN (SELFIES) & 1.070 \pm 0.041 & 0.863 \pm 0.033 & 1.1060 \pm 0.0460 & 0.9060 \pm 0.0420 \\ + & GCN (SMILES) & 1.075 \pm 0.045 & 0.869 \pm 0.033 & 1.1100 \pm 0.0470 & 0.9060 \pm 0.0450 \\ + & GIN (ECFP) & 0.829 \pm 0.036 & 0.620 \pm 0.036 & 0.8080 \pm 0.0500 & 0.6050 \pm 0.0355 \\ + & GIN (SELFIES) & 1.062 \pm 0.065 & 0.848 \pm 0.054 & 1.0850 \pm 0.0530 & 0.8710 \pm 0.0430 \\ + & GIN (SMILES) & 1.072 \pm 0.043 & 0.862 \pm 0.036 & 1.0730 \pm 0.0495 & 0.8650 \pm 0.0410 \\ + & POLYATOMIC & 0.717 \pm 0.027 & 0.531 \pm 0.023 & 0.7500 \pm 0.0505 & 0.5460 \pm 0.0335 \\ + & SAGE (ECFP) & 0.865 \pm 0.021 & 0.663 \pm 0.022 & 0.8500 \pm 0.0480 & 0.6510 \pm 0.0365 \\ + & SAGE (SELFIES) & 0.947 \pm 0.038 & 0.750 \pm 0.027 & 1.0300 \pm 0.0615 & 0.8120 \pm 0.0435 \\ + & SAGE (SMILES) & 0.955 \pm 0.041 & 0.763 \pm 0.035 & 1.0160 \pm 0.0630 & 0.7970 \pm 0.0435 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/latex_table/qm9.tex b/plotting/latex_table/qm9.tex new file mode 100644 index 0000000000000000000000000000000000000000..9839902399aca53332b8309b7302067c8374a32d --- /dev/null +++ b/plotting/latex_table/qm9.tex @@ -0,0 +1,28 @@ +\begin{table}[h] +\centering +\small % Font size +\caption{Comprehensive performance comparison across all datasets and models.} +\label{tab:full_results} +% siunitx settings +\sisetup{separate-uncertainty, table-align-text-post=false} +\resizebox{\textwidth}{!}{\begin{tabular}{@{}ll S[table-format=2.3(4)] S[table-format=2.3(4)] S[table-format=2.4(4)] S[table-format=2.4(4)]@{}} +\toprule +\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\ +\midrule +\multirow{13}{*}{QM9} & GAT (ECFP) & 2.490 \pm 0.149 & 1.826 \pm 0.051 & 2.4370 \pm 0.2845 & 1.7870 \pm 0.1620 \\ + & GAT (SELFIES) & 1.898 \pm 0.072 & 1.493 \pm 0.048 & 1.8170 \pm 0.1360 & 1.4210 \pm 0.1135 \\ + & GAT (SMILES) & 1.896 \pm 0.071 & 1.488 \pm 0.052 & 1.7820 \pm 0.1350 & 1.4030 \pm 0.1105 \\ + & GCN (ECFP) & 2.483 \pm 0.171 & 1.811 \pm 0.085 & 2.4260 \pm 0.2380 & 1.8390 \pm 0.1615 \\ + & GCN (SELFIES) & 2.358 \pm 0.096 & 1.871 \pm 0.078 & 2.1550 \pm 0.1510 & 1.7270 \pm 0.1290 \\ + & GCN (SMILES) & 2.423 \pm 0.063 & 1.926 \pm 0.046 & 2.1260 \pm 0.1575 & 1.6980 \pm 0.1265 \\ + & GIN (ECFP) & 2.583 \pm 0.113 & 1.913 \pm 0.066 & 2.5470 \pm 0.2480 & 1.9270 \pm 0.1660 \\ + & GIN (SELFIES) & 1.883 \pm 0.081 & 1.489 \pm 0.068 & 1.8120 \pm 0.1300 & 1.4350 \pm 0.1060 \\ + & GIN (SMILES) & 1.876 \pm 0.063 & 1.492 \pm 0.058 & 1.8120 \pm 0.1395 & 1.4190 \pm 0.1085 \\ + & POLYATOMIC & 0.999 \pm 0.099 & 0.659 \pm 0.069 & 1.0480 \pm 0.1805 & 0.6510 \pm 0.0815 \\ + & SAGE (ECFP) & 2.516 \pm 0.165 & 1.836 \pm 0.086 & 2.4860 \pm 0.2580 & 1.8310 \pm 0.1640 \\ + & SAGE (SELFIES) & 1.561 \pm 0.031 & 1.206 \pm 0.029 & 1.4880 \pm 0.1180 & 1.1560 \pm 0.0915 \\ + & SAGE (SMILES) & 1.552 \pm 0.050 & 1.209 \pm 0.034 & 1.4290 \pm 0.1120 & 1.0890 \pm 0.0905 \\ +\bottomrule +\end{tabular} +} +\end{table} \ No newline at end of file diff --git a/plotting/make_latex_table.py b/plotting/make_latex_table.py new file mode 100644 index 0000000000000000000000000000000000000000..8bc72615b6526698e9657287d1731fd56535572e --- /dev/null +++ b/plotting/make_latex_table.py @@ -0,0 +1,406 @@ +""" +Convert the plain-text summary (like the one you pasted) into a LaTeX table. + +Features +- Parses blocks like: --- Dataset: QM9 --- +- Reads Val metrics as "mean ± std" +- Reads Test metrics as either "mean [low, high]" (CI) or "mean ± std" +- Option --test-intervals {ci, pm}: + ci -> keep "mean [low, high]" strings (uses text columns for the 2 Test cols) + pm -> convert CI to ± half-width to match siunitx S columns +- Multirow per dataset; booktabs rules; siunitx S columns; optional renaming & bolding + +Usage + python latex_table_from_txt.py \ + --input results.txt --output table.tex \ + --test-intervals pm \ + --rename "polyatomic=PACTNet (ECC)" \ + --bold-contains "PACTNet" \ + --val-dec 3 --test-dec 4 +""" + +import argparse +import re +from pathlib import Path +import pandas as pd + + +def parse_args(): + p = argparse.ArgumentParser( + description="Convert TXT performance summary to LaTeX table (booktabs + siunitx + multirow)." + ) + p.add_argument("--input", "-i", type=Path, required=True, help="Input TXT file") + p.add_argument("--output", "-o", type=Path, required=True, help="Output .tex file") + p.add_argument( + "--caption", + default="Comprehensive performance comparison across all datasets and models.", + help="LaTeX caption", + ) + p.add_argument("--label", default="tab:full_results", help="LaTeX label") + p.add_argument( + "--val-dec", + type=int, + default=3, + help="Decimal places for Val metrics (mean & std)", + ) + p.add_argument( + "--test-dec", + type=int, + default=4, + help="Decimal places for Test metrics (mean & std)", + ) + p.add_argument( + "--no-fixed-decimals", + action="store_true", + help="Use raw decimals as provided (don't round to fixed places)", + ) + p.add_argument( + "--table-formats", + nargs=4, + default=["2.3(4)", "2.3(4)", "2.4(4)", "2.4(4)"], + help="siunitx table-format for Val RMSE, Val MAE, Test RMSE, Test MAE", + ) + p.add_argument( + "--font-size", default="\\small", help="LaTeX font size inside the table" + ) + p.add_argument("--width", default="\\textwidth", help="Width for \\resizebox") + p.add_argument( + "--no-resize", action="store_true", help="Disable \\resizebox wrapper" + ) + p.add_argument( + "--booktabs", action="store_true", default=True, help="Use booktabs rules" + ) + p.add_argument( + "--no-booktabs", + dest="booktabs", + action="store_false", + help="Disable booktabs rules", + ) + p.add_argument( + "--test-intervals", + choices=["ci", "pm"], + default="pm", + help="For Test metrics with CIs: keep CIs (ci) or convert to ± half-width (pm)", + ) + p.add_argument( + "--bold-contains", + default=None, + help="Regex to bold any row where model/rep cell matches", + ) + p.add_argument( + "--rename", + nargs="*", + default=[], + help='Rename patterns like old=new (regex on the "Model (Rep.)" cell)', + ) + p.add_argument("--dataset-order", nargs="*", help="Optional explicit dataset order") + p.add_argument( + "--sort-by", + nargs="*", + default=None, + help="Sort keys within each dataset, e.g., --sort-by model representation", + ) + p.add_argument( + "--ascending", + nargs="*", + type=int, + help="Ascending flags matching --sort-by, e.g. 1 0", + ) + return p.parse_args() + + +def fmt_unc(mean, std, fixed_decimals: bool, dec_places: int) -> str: + if pd.isna(mean) or pd.isna(std): + return r"\textemdash" + if fixed_decimals: + return f"{float(mean):.{dec_places}f} \\pm {float(std):.{dec_places}f}" + + # keep raw, but tidy trailing zeros + def tidy(x): + s = f"{x}" + if "e" in s or "E" in s: + return s + if "." in s: + s = s.rstrip("0").rstrip(".") + return s + + return f"{tidy(mean)} \\pm {tidy(std)}" + + +def build_model_rep(name: str) -> tuple[str, str, str]: + """ + Split 'gat_ecfp' -> ('GAT', 'ECFP', 'GAT (ECFP)') + If no underscore, rep is ''. + """ + name = name.strip() + model, rep = name, "" + if "_" in name: + model, rep = name.split("_", 1) + # Pretty-up casing: GAT -> GAT, selfies->SELFIES, etc. + model_fmt = model.upper() if model.isalpha() else model + rep_fmt = rep.upper() if rep else "" + label = f"{model_fmt} ({rep_fmt})" if rep_fmt else model_fmt + return model_fmt, rep_fmt, label + + +def apply_renames(s: str, mapping: dict) -> str: + for k, v in mapping.items(): + s = re.sub(k, v, s) + return s + + +def parse_metric(cell: str): + """ + Returns dict with possible keys: mean, std, ci_low, ci_high + Accepts: + - '1.234 ± 0.056' + - '1.234 [1.111, 1.345]' + - '1.234' + """ + s = cell.strip() + m = re.match(r"([+-]?\d+(?:\.\d+)?)\s*±\s*([+-]?\d+(?:\.\d+)?)", s) + if m: + return { + "mean": float(m.group(1)), + "std": float(m.group(2)), + "ci_low": None, + "ci_high": None, + } + m = re.match( + r"([+-]?\d+(?:\.\d+)?)\s*\[\s*([+-]?\d+(?:\.\d+)?)\s*,\s*([+-]?\d+(?:\.\d+)?)\s*\]", + s, + ) + if m: + return { + "mean": float(m.group(1)), + "std": None, + "ci_low": float(m.group(2)), + "ci_high": float(m.group(3)), + } + m = re.match(r"([+-]?\d+(?:\.\d+)?)$", s) + if m: + return {"mean": float(m.group(1)), "std": None, "ci_low": None, "ci_high": None} + return {"mean": None, "std": None, "ci_low": None, "ci_high": None} + + +def parse_txt(path: Path) -> pd.DataFrame: + """ + Parse the text file structure you showed into a tidy DataFrame. + """ + text = path.read_text(encoding="utf-8", errors="ignore") + # Find dataset blocks + blocks = [] + for m in re.finditer(r"---\s*Dataset:\s*(.+?)\s*---", text): + blocks.append((m.start(), m.group(1).strip())) + rows = [] + for i, (pos, dataset) in enumerate(blocks): + start = pos + end = blocks[i + 1][0] if i + 1 < len(blocks) else len(text) + body = text[start:end] + + # Capture the table lines after the header row with pipes + table_lines = [] + after_header = False + for line in body.splitlines(): + if re.search(r"\|\s*Val RMSE", line): + after_header = True + continue + if after_header: + if line.strip().startswith("--- Statistical"): + break + if re.match(r"\s*$", line): + break + # skip dashed separators + if re.match(r"[-\s]{5,}$", line.replace("|", "")): + continue + if "|" in line: + table_lines.append(line) + + for line in table_lines: + parts = [p.strip() for p in line.split("|")] + if len(parts) < 5: + continue + name = parts[0] + val_rmse = parse_metric(parts[1]) + val_mae = parse_metric(parts[2]) + test_rmse = parse_metric(parts[3]) + test_mae = parse_metric(parts[4]) + model, rep, label = build_model_rep(name) + rows.append( + { + "dataset": dataset, + "model": model, + "representation": rep, + "label": label, # "Model (Rep.)" cell (pre-rename) + "val_rmse_mean": val_rmse["mean"], + "val_rmse_std": val_rmse["std"], + "val_mae_mean": val_mae["mean"], + "val_mae_std": val_mae["std"], + "test_rmse_mean": test_rmse["mean"], + "test_rmse_std": test_rmse["std"], + "test_rmse_ci_low": test_rmse["ci_low"], + "test_rmse_ci_high": test_rmse["ci_high"], + "test_mae_mean": test_mae["mean"], + "test_mae_std": test_mae["std"], + "test_mae_ci_low": test_mae["ci_low"], + "test_mae_ci_high": test_mae["ci_high"], + } + ) + return pd.DataFrame(rows) + + +def main(): + args = parse_args() + df = parse_txt(args.input) + + # Optional sorting & dataset order + if args.sort_by: + asc = ( + [True] * len(args.sort_by) + if args.ascending is None + else [bool(int(a)) for a in args.ascending] + ) + df = df.sort_values(by=args.sort_by, ascending=asc) + if args.dataset_order: + cat = pd.Categorical(df["dataset"], categories=args.dataset_order, ordered=True) + df = df.assign(_dataset=cat).sort_values("_dataset").drop(columns="_dataset") + + # Renaming map + rename_map = dict(kv.split("=", 1) for kv in args.rename) if args.rename else {} + bold_re = ( + re.compile(args.bold_contains) if args.bold_contains else None + ) # noqa: E999 (hyphen in attribute name) + # The above line will fail because of hyphen; fix properly: + bold_re = re.compile(args.bold_contains) if args.bold_contains else None + + # Column spec (if CI mode, last two are text columns) + if args.test_intervals == "ci": + colspec = ( + "@{}ll " + + " ".join( + [ + f"S[table-format={args.table_formats[0]}]", + f"S[table-format={args.table_formats[1]}]", + "l", + "l", + ] + ) + + "@{}" + ) + else: + colspec = ( + "@{}ll " + + " ".join([f"S[table-format={tf}]" for tf in args.table_formats]) + + "@{}" + ) + + # Start LaTeX + lines = [] + lines.append(r"\begin{table}[h]") + lines.append(r"\centering") + if args.font_size: + lines.append(f"{args.font_size} % Font size") + lines.append(r"\caption{" + args.caption + r"}") + lines.append(r"\label{" + args.label + r"}") + lines.append(r"% siunitx settings") + lines.append(r"\sisetup{separate-uncertainty, table-align-text-post=false}") + + inner_begin = r"\begin{tabular}{" + colspec + r"}" + inner_end = r"\end{tabular}" + + if args.no_resize: + lines.append(inner_begin) + else: + lines.append(r"\resizebox{" + args.width + r"}{!}{" + inner_begin) + + if args.booktabs: + lines.append(r"\toprule") + lines.append( + r"\textbf{Dataset} & \textbf{Model (Rep.)} & {Val RMSE} & {Val MAE} & {Test RMSE} & {Test MAE} \\" + ) + if args.booktabs: + lines.append(r"\midrule") + + # Emit grouped rows with \multirow + for dataset, g in df.groupby("dataset", sort=False): + n = len(g) + first = True + for _, row in g.iterrows(): + # Model/Rep cell with renames + optional bold + cell_model = apply_renames(row["label"], rename_map) + do_bold = bool(bold_re and bold_re.search(cell_model)) if bold_re else False + + # Val metrics (always ± form in your text) + val_rmse = fmt_unc( + row["val_rmse_mean"], + row["val_rmse_std"], + fixed_decimals=not args.no_fixed_decimals, + dec_places=args.val_dec, + ) + val_mae = fmt_unc( + row["val_mae_mean"], + row["val_mae_std"], + fixed_decimals=not args.no_fixed_decimals, + dec_places=args.val_dec, + ) + + # Test metrics + def ci_or_pm(mean, std, lo, hi): + if args.test_intervals == "ci" and (lo is not None and hi is not None): + return f"{mean} [{lo}, {hi}]" + if std is None and (lo is not None and hi is not None): + std = (hi - lo) / 2.0 + return fmt_unc( + mean, + std, + fixed_decimals=not args.no_fixed_decimals, + dec_places=args.test_dec, + ) + + test_rmse = ci_or_pm( + row["test_rmse_mean"], + row["test_rmse_std"], + row["test_rmse_ci_low"], + row["test_rmse_ci_high"], + ) + test_mae = ci_or_pm( + row["test_mae_mean"], + row["test_mae_std"], + row["test_mae_ci_low"], + row["test_mae_ci_high"], + ) + + parts = [] + if first: + parts.append(rf"\multirow{{{n}}}{{*}}{{{dataset}}}") + first = False + else: + parts.append("") # empty dataset cell + + if do_bold: + parts.append(rf"\bfseries {cell_model}") + parts.append(rf"\bfseries {val_rmse}") + parts.append(rf"\bfseries {val_mae}") + parts.append(rf"\bfseries {test_rmse}") + parts.append(rf"\bfseries {test_mae}") + else: + parts.append(cell_model) + parts.append(val_rmse) + parts.append(val_mae) + parts.append(test_rmse) + parts.append(test_mae) + + lines.append(" & ".join(parts) + r" \\") + + if args.booktabs: + lines.append(r"\bottomrule") + lines.append(inner_end) + if not args.no_resize: + lines.append("}") + lines.append(r"\end{table}") + + args.output.write_text("\n".join(lines), encoding="utf-8") + + +if __name__ == "__main__": + main() diff --git a/plotting/make_stats_table.py b/plotting/make_stats_table.py new file mode 100644 index 0000000000000000000000000000000000000000..bada2640549ecddcd6882e06c2847491bc097dad --- /dev/null +++ b/plotting/make_stats_table.py @@ -0,0 +1,421 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- + +""" +Parse *_NB_single_dataset.txt reports and emit LaTeX tables. + +Now supports: + • Full "everything" longtable (as before) + • Option B: TWO COMPACT portrait tables (RMSE table + MAE table) + +Examples +-------- +# Make compact + full tables for all reports in a dir +python3 make_nb_tables_from_reports.py --in ./plotting --out ./plotting/tex + +# Only compact tables +python3 make_nb_tables_from_reports.py --in ./plotting --out ./plotting/tex --compact_only + +# Specific files +python3 make_nb_tables_from_reports.py \ + --files ./plotting/qm9_NB_single_dataset.txt ./plotting/boilingpoint_NB_single_dataset.txt \ + --out ./plotting/tex --compact_only +""" + +import argparse +import re +from pathlib import Path +from typing import Dict, List, Tuple +import pandas as pd + +NUM = r"[-+]?(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][-+]?\d+)?" + + +def esc_tex(s: str) -> str: + return s.replace("_", r"\_") + + +def parse_header(lines: List[str]) -> Dict[str, str]: + out = {} + for ln in lines[:60]: + m = re.search(r"^Dataset:\s*(.+?)\s+—", ln) + if m: + out["dataset"] = m.group(1).strip() + m = re.search(r"^Control exp_id:\s*(.+)$", ln) + if m: + out["control"] = m.group(1).strip() + m = re.search(r"^k folds:\s*(\d+),\s*alpha:\s*(" + NUM + r")", ln) + if m: + out["k"] = int(m.group(1)) + out["alpha"] = float(m.group(2)) + return out + + +def find_block(lines: List[str], start_pat: str) -> Tuple[int, int]: + start = -1 + pat = re.compile(start_pat) + for i, ln in enumerate(lines): + if pat.search(ln): + start = i + break + if start < 0: + return (-1, -1) + end = len(lines) + for j in range(start + 1, len(lines)): + if not lines[j].strip(): + end = j + break + return (start, end) + + +def parse_nb_block(lines: List[str]) -> pd.DataFrame: + hdr_idx = None + for i, ln in enumerate(lines): + if re.search(r"^\s*comparison\s+", ln) and "mean_diff_RMSE" in ln: + hdr_idx = i + break + if hdr_idx is None: + return pd.DataFrame() + + data_lines = [] + for ln in lines[hdr_idx + 1 :]: + s = ln.rstrip() + if not s: + break + if set(s) <= set("- "): + continue + data_lines.append(s) + + rows = [] + for ln in data_lines: + # Flexible parse: "comparison num num ... (10 nums total)" + m = re.match(r"^\s*(.+?)\s+(" + NUM + r"(?:\s+" + NUM + r"){9})\s*$", ln) + if not m: + parts = re.split(r"\s{2,}", ln.strip()) + if len(parts) < 11: + continue + comp, *nums = parts + else: + comp = m.group(1).strip() + nums = re.split(r"\s+", m.group(2).strip()) + if len(nums) != 10: + continue + vals = list(map(float, nums)) + rows.append( + { + "comparison": comp, + "mean_diff_RMSE": vals[0], + "t_NB_RMSE": vals[1], + "p_raw_RMSE": vals[2], + "mean_diff_MAE": vals[3], + "t_NB_MAE": vals[4], + "p_raw_MAE": vals[5], + "CI_RMSE_low": vals[6], + "CI_RMSE_high": vals[7], + "CI_MAE_low": vals[8], + "CI_MAE_high": vals[9], + } + ) + return pd.DataFrame(rows) + + +def parse_holm_block(lines: List[str], metric_label: str) -> pd.DataFrame: + hdr = None + for i, ln in enumerate(lines): + if re.search(r"^\s*comparison\s+", ln) and "p_raw" in ln and "p_holm" in ln: + hdr = i + break + if hdr is None: + return pd.DataFrame() + + data_lines = [] + for ln in lines[hdr + 1 :]: + s = ln.rstrip() + if not s: + break + if set(s) <= set("- "): + continue + data_lines.append(s) + + rows = [] + for ln in data_lines: + m = re.match(r"^\s*(.+?)\s+(" + NUM + r")\s+(" + NUM + r")\s+(\w+)\s*$", ln) + if m: + comp = m.group(1).strip() + p_raw = float(m.group(2)) # not used here, but parsed ok + p_holm = float(m.group(3)) + sig = m.group(4).strip().lower().startswith("t") + else: + parts = re.split(r"\s{2,}", ln.strip()) + if len(parts) < 4: + continue + comp = parts[0].strip() + p_holm = float(parts[2]) + sig = parts[3].strip().lower().startswith("t") + rows.append( + { + "comparison": comp, + f"p_holm_{metric_label}": p_holm, + f"sig_{metric_label}": sig, + } + ) + return pd.DataFrame(rows) + + +# ---------- FULL longtable (unchanged behavior) ---------- + + +def write_full_longtable(meta: Dict[str, str], df: pd.DataFrame, outpath: Path): + dataset = meta.get("dataset", "dataset") + control = meta.get("control", "control") + k = int(meta.get("k", 5)) + alpha = float(meta.get("alpha", 0.05)) + + header = rf""" +% Auto-generated from NB_single_dataset report +% Requires: \usepackage{{booktabs,longtable,siunitx}} +\begin{{longtable}}{{@{{}}l +S S S S S S S +S +S S S S S S S +@{{}}}} +\caption{{Full NB-corrected one-sided tests (outer folds, $K={k}$, $\alpha={alpha}$) comparing control \texttt{{{esc_tex(control)}}} against each competitor on dataset \texttt{{{esc_tex(dataset)}}}. +Positive $\Delta$ (competitor $-$ control) favors the control (lower loss). +One-sided alternative $\mathbb{{E}}[\bar d^{{(L)}}] > 0$. +Holm step-down controls FWER per metric family (RMSE and MAE reported separately). +CIs are NB-style two-sided.}} +\label{{tab:{esc_tex(dataset)}_nb_full}}\\ +\toprule +& \multicolumn{{7}}{{c}}{{\textbf{{RMSE family}}}} & & +\multicolumn{{7}}{{c}}{{\textbf{{MAE family}}}}\\ +\cmidrule(lr){{2-8}}\cmidrule(lr){{10-16}} +Comparison +& {{\(\Delta\)RMSE}} +& {{$t_{{\text{{NB}}}}$}} +& {{p (raw)}} +& {{p\(_{{\text{{Holm}}}}\)}} +& {{\(\text{{Sig}}\)}} +& {{CI\(_{{\text{{low}}}}\)}} +& {{CI\(_{{\text{{high}}}}\)}} +& {{}} % spacer +& {{\(\Delta\)MAE}} +& {{$t_{{\text{{NB}}}}$}} +& {{p (raw)}} +& {{p\(_{{\text{{Holm}}}}\)}} +& {{\(\text{{Sig}}\)}} +& {{CI\(_{{\text{{low}}}}\)}} +& {{CI\(_{{\text{{high}}}}\)}}\\ +\midrule +\endfirsthead +\toprule +& \multicolumn{{7}}{{c}}{{\textbf{{RMSE family}}}} & & +\multicolumn{{7}}{{c}}{{\textbf{{MAE family}}}}\\ +\cmidrule(lr){{2-8}}\cmidrule(lr){{10-16}} +Comparison +& {{\(\Delta\)RMSE}} +& {{$t_{{\text{{NB}}}}$}} +& {{p (raw)}} +& {{p\(_{{\text{{Holm}}}}\)}} +& {{\(\text{{Sig}}\)}} +& {{CI\(_{{\text{{low}}}}\)}} +& {{CI\(_{{\text{{high}}}}\)}} +& {{}} % spacer +& {{\(\Delta\)MAE}} +& {{$t_{{\text{{NB}}}}$}} +& {{p (raw)}} +& {{p\(_{{\text{{Holm}}}}\)}} +& {{\(\text{{Sig}}\)}} +& {{CI\(_{{\text{{low}}}}\)}} +& {{CI\(_{{\text{{high}}}}\)}}\\ +\midrule +\endhead +\midrule +\multicolumn{{16}}{{r}}{{\emph{{Continued on next page}}}}\\ +\midrule +\endfoot +\bottomrule +\endlastfoot +""" + lines = [] + for _, r in df.iterrows(): + lines.append( + f"{esc_tex(r['comparison'])} & " + f"{r['mean_diff_RMSE']:.6f} & {r['t_NB_RMSE']:.6f} & {r['p_raw_RMSE']:.6f} & {r['p_holm_RMSE']:.6f} & {1 if r['sig_RMSE'] else 0} & {r['CI_RMSE_low']:.6f} & {r['CI_RMSE_high']:.6f} & & " + f"{r['mean_diff_MAE']:.6f} & {r['t_NB_MAE']:.6f} & {r['p_raw_MAE']:.6f} & {r['p_holm_MAE']:.6f} & {1 if r['sig_MAE'] else 0} & {r['CI_MAE_low']:.6f} & {r['CI_MAE_high']:.6f} \\\\" + ) + outpath.write_text( + header + "\n".join(lines) + "\n\\end{longtable}\n", encoding="utf-8" + ) + + +# ---------- COMPACT portrait tables (Option B) ---------- + + +def write_compact_tables(meta: Dict[str, str], df: pd.DataFrame, outdir: Path): + """ + Produce two small portrait tables: + • _nb_compact_rmse.tex + • _nb_compact_mae.tex + + Columns (per metric): Comparison, Δ, t_NB, CI_low, CI_high, p_Holm + """ + dataset = meta.get("dataset", "dataset") + control = meta.get("control", "control") + k = int(meta.get("k", 5)) + + common_preamble = r""" +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} +""" + + # RMSE table + rmse_header = rf"""{common_preamble} +\begin{{table}}[t] +\centering +\small +\setlength{{\tabcolsep}}{{4pt}} +\caption{{RMSE: NB-corrected one-sided tests (outer folds, $K={k}$) on dataset \texttt{{{esc_tex(dataset)}}}; control \texttt{{{esc_tex(control)}}}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.}} +\label{{tab:{esc_tex(dataset)}_nb_compact_rmse}} +\begin{{tabularx}}{{\linewidth}}{{@{{}}l S S S S S@{{}}}} +\toprule +Comparison & {{\(\Delta\)RMSE}} & {{$t_{{\text{{NB}}}}$}} & {{CI\(_{{\text{{low}}}}\)}} & {{CI\(_{{\text{{high}}}}\)}} & {{p\(_{{\text{{Holm}}}}\)}}\\ +\midrule +""" + rmse_rows = [] + for _, r in df.sort_values("p_holm_RMSE").iterrows(): + rmse_rows.append( + f"{esc_tex(r['comparison'])} & " + f"{r['mean_diff_RMSE']:.3f} & {r['t_NB_RMSE']:.3f} & " + f"{r['CI_RMSE_low']:.3f} & {r['CI_RMSE_high']:.3f} & {r['p_holm_RMSE']:.3g} \\\\" + ) + rmse_tex = ( + rmse_header + + "\n".join(rmse_rows) + + "\n\\bottomrule\n\\end{tabularx}\n\\end{table}\n" + ) + (outdir / f"{dataset}_nb_compact_rmse.tex").write_text(rmse_tex, encoding="utf-8") + + # MAE table + mae_header = rf"""{common_preamble} +\begin{{table}}[t] +\centering +\small +\setlength{{\tabcolsep}}{{4pt}} +\caption{{MAE: NB-corrected one-sided tests (outer folds, $K={k}$) on dataset \texttt{{{esc_tex(dataset)}}}; control \texttt{{{esc_tex(control)}}}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.}} +\label{{tab:{esc_tex(dataset)}_nb_compact_mae}} +\begin{{tabularx}}{{\linewidth}}{{@{{}}l S S S S S@{{}}}} +\toprule +Comparison & {{\(\Delta\)MAE}} & {{$t_{{\text{{NB}}}}$}} & {{CI\(_{{\text{{low}}}}\)}} & {{CI\(_{{\text{{high}}}}\)}} & {{p\(_{{\text{{Holm}}}}\)}}\\ +\midrule +""" + mae_rows = [] + for _, r in df.sort_values("p_holm_MAE").iterrows(): + mae_rows.append( + f"{esc_tex(r['comparison'])} & " + f"{r['mean_diff_MAE']:.3f} & {r['t_NB_MAE']:.3f} & " + f"{r['CI_MAE_low']:.3f} & {r['CI_MAE_high']:.3f} & {r['p_holm_MAE']:.3g} \\\\" + ) + mae_tex = ( + mae_header + + "\n".join(mae_rows) + + "\n\\bottomrule\n\\end{tabularx}\n\\end{table}\n" + ) + (outdir / f"{dataset}_nb_compact_mae.tex").write_text(mae_tex, encoding="utf-8") + + +def process_file(path: Path, outdir: Path, make_full: bool, make_compact: bool): + txt = path.read_text(encoding="utf-8", errors="ignore").splitlines() + meta = parse_header(txt) + + # NB block + nb_start, nb_end = find_block( + txt, r"^\s*--- NB-corrected t \(outer folds\) per competitor ---" + ) + if nb_start < 0: + raise RuntimeError(f"NB block not found in {path}") + df_nb = parse_nb_block(txt[nb_start:nb_end]) + if df_nb.empty: + raise RuntimeError(f"NB table parsing failed in {path}") + + # Holm blocks + hr_start, hr_end = find_block( + txt, r"^\s*--- Holm-adjusted p-values \(RMSE family\)\s*---" + ) + hm_start, hm_end = find_block( + txt, r"^\s*--- Holm-adjusted p-values \(MAE family\)\s*---" + ) + if hr_start < 0 or hm_start < 0: + raise RuntimeError(f"Holm blocks not found in {path}") + df_hr = parse_holm_block(txt[hr_start:hr_end], "RMSE") + df_hm = parse_holm_block(txt[hm_start:hm_end], "MAE") + + # Merge Holm into NB + df = df_nb.merge(df_hr, on="comparison", how="left").merge( + df_hm, on="comparison", how="left" + ) + + # Write outputs + dataset = meta.get("dataset", path.stem.replace("_NB_single_dataset", "")) + outdir.mkdir(parents=True, exist_ok=True) + + if make_full: + full_path = outdir / f"{dataset}_nb_full_summary_from_report.tex" + # order for full table: by raw p (RMSE then MAE) + df_full = df.sort_values(["p_raw_RMSE", "p_raw_MAE"]).reset_index(drop=True) + write_full_longtable(meta, df_full, full_path) + + if make_compact: + # For compact tables we sort within each family by Holm p + write_compact_tables(meta, df, outdir) + + print( + f"Processed: {path.name} -> {dataset} (full={make_full}, compact={make_compact})" + ) + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument( + "--in", + dest="indir", + type=str, + default=None, + help="Directory containing *_NB_single_dataset.txt files.", + ) + ap.add_argument( + "--files", nargs="*", default=None, help="Explicit list of report files." + ) + ap.add_argument( + "--out", + dest="outdir", + type=str, + required=True, + help="Output directory for .tex tables.", + ) + ap.add_argument( + "--compact_only", + action="store_true", + help="Only write the compact RMSE/MAE tables (skip the full longtable).", + ) + args = ap.parse_args() + + outdir = Path(args.outdir) + if args.files: + files = [Path(f) for f in args.files] + elif args.indir: + files = sorted(Path(args.indir).glob("*_NB_single_dataset.txt")) + else: + raise SystemExit("Provide either --in DIR or --files file1 file2 ...") + + if not files: + raise SystemExit("No *_NB_single_dataset.txt files found.") + + for f in files: + process_file(f, outdir, make_full=not args.compact_only, make_compact=True) + + +if __name__ == "__main__": + main() diff --git a/plotting/readme.md b/plotting/readme.md new file mode 100644 index 0000000000000000000000000000000000000000..d44677e6d0e0dcbd84f0f6193a861c9010f64ef0 --- /dev/null +++ b/plotting/readme.md @@ -0,0 +1,77 @@ +```bash + python plotting/make_latex_table.py --input ./plotting/.txt --output ./plotting/.tex --test-intervals pm --rename "polyatomic=PACTNet (ECC)" --bold-contains "PACTNet" --val-dec 3 --test-dec 4 +``` + +```bash +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/qm9 \ + --output_dir ./plotting \ + --exp_name qm9 \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/lipophil \ + --output_dir ./plotting \ + --exp_name lipophil \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/freesolv \ + --output_dir ./plotting \ + --exp_name freesolv \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/esol \ + --output_dir ./plotting \ + --exp_name esol \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/boilingpoint \ + --output_dir ./plotting \ + --exp_name boilingpoint \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/bindingdb \ + --output_dir ./plotting \ + --exp_name bindingdb \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci + + +python3 plotting/stats.py \ + --results_dir ./logs_hyperparameter/ic50 \ + --output_dir ./plotting \ + --exp_name ic50 \ + --control_model polyatomic_polyatomic \ + --k 5 \ + --alpha 0.05 \ + --print_ci +``` \ No newline at end of file diff --git a/plotting/results/bindingdb_NB_single_dataset.txt b/plotting/results/bindingdb_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..670425d7f28c1a94889d7f4fdd8f41b807aaf603 --- /dev/null +++ b/plotting/results/bindingdb_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: bindingdb — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 1.774697 [1.548643, 2.045455] | 1.335826 [1.224511, 1.446235] | 1.512068 ± 0.054745 | 1.234786 ± 0.053243 +gat_selfies | 1.781697 [1.560675, 2.049141] | 1.359728 [1.252870, 1.482262] | 1.487838 ± 0.028541 | 1.226527 ± 0.022634 +gat_smiles | 1.754195 [1.535838, 2.015081] | 1.355767 [1.254198, 1.474328] | 1.491342 ± 0.027543 | 1.229641 ± 0.020183 +gcn_ecfp | 1.762042 [1.512678, 2.037183] | 1.321918 [1.218016, 1.442680] | 1.508135 ± 0.057710 | 1.230725 ± 0.055913 +gcn_selfies | 1.769633 [1.536112, 2.032957] | 1.359158 [1.250723, 1.472505] | 1.492093 ± 0.031286 | 1.231309 ± 0.023081 +gcn_smiles | 1.823605 [1.562074, 2.112495] | 1.373664 [1.264610, 1.506677] | 1.494577 ± 0.030688 | 1.234107 ± 0.023160 +gin_ecfp | 1.782525 [1.548191, 2.064014] | 1.353598 [1.243715, 1.470764] | 1.520160 ± 0.049906 | 1.253446 ± 0.043802 +gin_selfies | 1.754852 [1.538253, 2.019794] | 1.345353 [1.241478, 1.460301] | 1.494365 ± 0.029926 | 1.230887 ± 0.025053 +gin_smiles | 1.744420 [1.530416, 2.014084] | 1.338999 [1.235578, 1.449829] | 1.494206 ± 0.032490 | 1.230015 ± 0.027082 +polyatomic_polyatomic | 1.771403 [1.551371, 2.035059] | 1.364813 [1.258050, 1.474313] | 1.478743 ± 0.033778 | 1.211323 ± 0.030012 +sage_ecfp | 1.772139 [1.536348, 2.058353] | 1.345128 [1.235363, 1.462702] | 1.505716 ± 0.053896 | 1.234990 ± 0.045975 +sage_selfies | 1.911593 [1.580129, 2.336898] | 1.375826 [1.256309, 1.499871] | 1.493270 ± 0.031237 | 1.233564 ± 0.023943 +sage_smiles | 1.787286 [1.561512, 2.052208] | 1.381435 [1.275649, 1.496697] | 1.493198 ± 0.029871 | 1.231875 ± 0.023834 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 0.033325 1.563078 0.096536 0.023463 0.917657 0.205361 -0.025869 0.092519 -0.047526 0.094451 + polyatomic_polyatomic vs gat_selfies 0.009095 0.736549 0.251130 0.015204 2.084888 0.052719 -0.025189 0.043378 -0.005043 0.035451 + polyatomic_polyatomic vs gat_smiles 0.012600 0.937017 0.200900 0.018318 1.546347 0.098461 -0.024734 0.049934 -0.014571 0.051207 + polyatomic_polyatomic vs gcn_ecfp 0.029392 1.385614 0.119058 0.019402 0.742806 0.249427 -0.029503 0.088287 -0.053117 0.091920 + polyatomic_polyatomic vs gcn_selfies 0.013350 1.028700 0.180878 0.019986 1.928599 0.063009 -0.022681 0.049381 -0.008786 0.048759 + polyatomic_polyatomic vs gcn_smiles 0.015834 1.282276 0.134508 0.022784 2.333643 0.039966 -0.018451 0.050119 -0.004323 0.049891 + polyatomic_polyatomic vs gin_ecfp 0.041418 1.852548 0.068791 0.042123 1.670901 0.085031 -0.020656 0.103491 -0.027871 0.112118 + polyatomic_polyatomic vs gin_selfies 0.015622 1.775434 0.075242 0.019564 2.364777 0.038630 -0.008808 0.040052 -0.003406 0.042533 + polyatomic_polyatomic vs gin_smiles 0.015464 1.620186 0.090254 0.018692 2.213716 0.045624 -0.011036 0.041964 -0.004752 0.042136 + polyatomic_polyatomic vs sage_ecfp 0.026973 1.377161 0.120253 0.023667 1.226598 0.143619 -0.027406 0.081353 -0.029904 0.077238 +polyatomic_polyatomic vs sage_selfies 0.014527 1.480477 0.106427 0.022241 3.236261 0.015893 -0.012717 0.041771 0.003160 0.041321 + polyatomic_polyatomic vs sage_smiles 0.014455 1.784641 0.074438 0.020552 3.758244 0.009902 -0.008033 0.036944 0.005369 0.035735 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_ecfp 0.068791 0.825496 False + polyatomic_polyatomic vs sage_smiles 0.074438 0.825496 False + polyatomic_polyatomic vs gin_selfies 0.075242 0.825496 False + polyatomic_polyatomic vs gin_smiles 0.090254 0.825496 False + polyatomic_polyatomic vs gat_ecfp 0.096536 0.825496 False +polyatomic_polyatomic vs sage_selfies 0.106427 0.825496 False + polyatomic_polyatomic vs gcn_ecfp 0.119058 0.825496 False + polyatomic_polyatomic vs sage_ecfp 0.120253 0.825496 False + polyatomic_polyatomic vs gcn_smiles 0.134508 0.825496 False + polyatomic_polyatomic vs gcn_selfies 0.180878 0.825496 False + polyatomic_polyatomic vs gat_smiles 0.200900 0.825496 False + polyatomic_polyatomic vs gat_selfies 0.251130 0.825496 False + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs sage_smiles 0.009902 0.118830 False +polyatomic_polyatomic vs sage_selfies 0.015893 0.174825 False + polyatomic_polyatomic vs gin_selfies 0.038630 0.386297 False + polyatomic_polyatomic vs gcn_smiles 0.039966 0.386297 False + polyatomic_polyatomic vs gin_smiles 0.045624 0.386297 False + polyatomic_polyatomic vs gat_selfies 0.052719 0.386297 False + polyatomic_polyatomic vs gcn_selfies 0.063009 0.386297 False + polyatomic_polyatomic vs gin_ecfp 0.085031 0.425153 False + polyatomic_polyatomic vs gat_smiles 0.098461 0.425153 False + polyatomic_polyatomic vs sage_ecfp 0.143619 0.430857 False + polyatomic_polyatomic vs gat_ecfp 0.205361 0.430857 False + polyatomic_polyatomic vs gcn_ecfp 0.249427 0.430857 False + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/boilingpoint_NB_single_dataset.txt b/plotting/results/boilingpoint_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..de9aff3936660d5ce5d56b268dc540a410e86b3a --- /dev/null +++ b/plotting/results/boilingpoint_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: boilingpoint — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 53.265842 [48.805954, 57.898522] | 40.305030 [36.983134, 43.564929] | 56.831017 ± 1.794415 | 43.533928 ± 1.438456 +gat_selfies | 56.048344 [50.597717, 61.545074] | 40.477142 [36.639106, 44.518539] | 55.601646 ± 1.883000 | 42.244293 ± 1.894419 +gat_smiles | 60.777790 [55.745125, 66.014768] | 45.333350 [41.338897, 49.423474] | 55.240337 ± 2.738987 | 41.337480 ± 2.469074 +gcn_ecfp | 54.614388 [50.174652, 59.222569] | 41.748993 [38.190276, 45.499022] | 57.010082 ± 1.528989 | 43.314625 ± 1.253913 +gcn_selfies | 62.381813 [57.047435, 67.634069] | 46.843258 [42.845304, 51.188527] | 61.200233 ± 1.848291 | 47.294342 ± 1.034722 +gcn_smiles | 59.035835 [54.129672, 63.898392] | 43.926860 [40.058343, 47.637614] | 61.585896 ± 1.292163 | 47.661694 ± 1.276771 +gin_ecfp | 57.383583 [52.247502, 62.323451] | 43.220516 [39.608424, 46.965609] | 58.744305 ± 1.789228 | 45.097740 ± 2.000080 +gin_selfies | 57.879600 [53.183248, 62.897465] | 42.445194 [38.634524, 46.248180] | 58.629210 ± 0.866873 | 44.499800 ± 0.974596 +gin_smiles | 57.161270 [52.039670, 61.952290] | 42.192806 [38.523158, 46.084850] | 59.281708 ± 2.270602 | 45.235466 ± 2.033691 +polyatomic_polyatomic | 50.635094 [44.478524, 57.417763] | 33.260437 [29.740178, 37.118692] | 49.089077 ± 2.425285 | 33.893340 ± 1.591549 +sage_ecfp | 55.244877 [50.997883, 59.850886] | 42.196377 [38.854457, 45.711827] | 57.160860 ± 1.252958 | 43.713960 ± 0.873474 +sage_selfies | 53.040047 [47.650949, 59.140331] | 37.457996 [33.800031, 40.981200] | 54.345130 ± 2.263551 | 40.947853 ± 1.796923 +sage_smiles | 53.010540 [47.508558, 58.687163] | 36.563400 [32.828342, 40.287561] | 54.283730 ± 3.660711 | 40.290970 ± 3.085925 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 7.741944 4.407223 0.005813 9.640587 5.180960 0.003301 2.864704 12.619185 4.474255 14.806919 + polyatomic_polyatomic vs gat_selfies 6.512571 3.321544 0.014668 8.350952 3.355659 0.014210 1.068779 11.956363 1.441442 15.260461 + polyatomic_polyatomic vs gat_smiles 6.151263 2.813297 0.024078 7.444142 2.999526 0.019980 0.080577 12.221949 0.553636 14.334647 + polyatomic_polyatomic vs gcn_ecfp 7.921005 4.721391 0.004581 9.421288 5.679827 0.002371 3.263005 12.579004 4.815920 14.026655 + polyatomic_polyatomic vs gcn_selfies 12.111150 7.334985 0.000919 13.401005 9.425695 0.000353 7.526826 16.695473 9.453587 17.348422 + polyatomic_polyatomic vs gcn_smiles 12.496817 6.176481 0.001745 13.768356 6.841935 0.001194 6.879261 18.114372 8.181182 19.355531 + polyatomic_polyatomic vs gin_ecfp 9.655230 5.861069 0.002115 11.204402 6.414425 0.001518 5.081454 14.229006 6.354644 16.054160 + polyatomic_polyatomic vs gin_selfies 9.540131 4.336032 0.006146 10.606463 6.218071 0.001703 3.431401 15.648862 5.870546 15.342379 + polyatomic_polyatomic vs gin_smiles 10.192632 3.936632 0.008504 11.342127 6.554168 0.001401 3.003927 17.381338 6.537430 16.146825 + polyatomic_polyatomic vs sage_ecfp 8.071780 5.138415 0.003399 9.820619 6.712639 0.001282 3.710347 12.433213 5.758668 13.882570 +polyatomic_polyatomic vs sage_selfies 5.256055 2.449050 0.035259 7.054516 4.786398 0.004367 -0.702643 11.214752 2.962404 11.146628 + polyatomic_polyatomic vs sage_smiles 5.194650 1.561793 0.096683 6.397629 2.356094 0.038997 -4.040033 14.429333 -1.141400 13.936658 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_selfies 0.000919 0.011034 True + polyatomic_polyatomic vs gcn_smiles 0.001745 0.019197 True + polyatomic_polyatomic vs gin_ecfp 0.002115 0.021150 True + polyatomic_polyatomic vs sage_ecfp 0.003399 0.030594 True + polyatomic_polyatomic vs gcn_ecfp 0.004581 0.036649 True + polyatomic_polyatomic vs gat_ecfp 0.005813 0.040690 True + polyatomic_polyatomic vs gin_selfies 0.006146 0.040690 True + polyatomic_polyatomic vs gin_smiles 0.008504 0.042520 True + polyatomic_polyatomic vs gat_selfies 0.014668 0.058672 False + polyatomic_polyatomic vs gat_smiles 0.024078 0.072233 False +polyatomic_polyatomic vs sage_selfies 0.035259 0.072233 False + polyatomic_polyatomic vs sage_smiles 0.096683 0.096683 False + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_selfies 0.000353 0.004238 True + polyatomic_polyatomic vs gcn_smiles 0.001194 0.013133 True + polyatomic_polyatomic vs sage_ecfp 0.001282 0.013133 True + polyatomic_polyatomic vs gin_smiles 0.001401 0.013133 True + polyatomic_polyatomic vs gin_ecfp 0.001518 0.013133 True + polyatomic_polyatomic vs gin_selfies 0.001703 0.013133 True + polyatomic_polyatomic vs gcn_ecfp 0.002371 0.014227 True + polyatomic_polyatomic vs gat_ecfp 0.003301 0.016505 True +polyatomic_polyatomic vs sage_selfies 0.004367 0.017469 True + polyatomic_polyatomic vs gat_selfies 0.014210 0.042629 True + polyatomic_polyatomic vs gat_smiles 0.019980 0.042629 True + polyatomic_polyatomic vs sage_smiles 0.038997 0.042629 True + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/esol_NB_single_dataset.txt b/plotting/results/esol_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..fec0234d1c40a0f307700dfd4370cfce338bc798 --- /dev/null +++ b/plotting/results/esol_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: esol — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 1.172743 [1.037144, 1.297140] | 0.879486 [0.775080, 0.987334] | 1.225710 ± 0.069577 | 0.929348 ± 0.050518 +gat_selfies | 0.984994 [0.868185, 1.109736] | 0.744026 [0.656101, 0.834063] | 1.170360 ± 0.117408 | 0.901865 ± 0.082195 +gat_smiles | 1.139695 [1.020070, 1.260407] | 0.871043 [0.781963, 0.970699] | 1.084726 ± 0.124745 | 0.834330 ± 0.086522 +gcn_ecfp | 1.170999 [1.052704, 1.297201] | 0.888218 [0.793571, 0.986058] | 1.223486 ± 0.057460 | 0.932243 ± 0.047790 +gcn_selfies | 1.274919 [1.117126, 1.423125] | 0.948630 [0.841780, 1.056382] | 1.278591 ± 0.113893 | 0.977189 ± 0.085326 +gcn_smiles | 1.296911 [1.133329, 1.471399] | 0.946475 [0.835690, 1.061464] | 1.239974 ± 0.171728 | 0.957877 ± 0.125429 +gin_ecfp | 1.106521 [0.991068, 1.229444] | 0.850279 [0.759486, 0.942043] | 1.155490 ± 0.051405 | 0.878202 ± 0.030189 +gin_selfies | 1.393881 [1.207167, 1.585419] | 0.998551 [0.877271, 1.123569] | 1.247130 ± 0.171855 | 0.939546 ± 0.138149 +gin_smiles | 1.337230 [1.183309, 1.497359] | 0.996003 [0.879868, 1.113710] | 1.195576 ± 0.082396 | 0.907893 ± 0.068134 +polyatomic_polyatomic | 0.829068 [0.694844, 0.990777] | 0.592781 [0.523029, 0.668328] | 0.680662 ± 0.031523 | 0.508395 ± 0.026367 +sage_ecfp | 1.186703 [1.070798, 1.305808] | 0.896443 [0.793551, 1.001664] | 1.218282 ± 0.075736 | 0.921988 ± 0.057542 +sage_selfies | 0.996946 [0.881463, 1.124073] | 0.746254 [0.668450, 0.835801] | 1.054504 ± 0.115750 | 0.801817 ± 0.079712 +sage_smiles | 1.088718 [0.956310, 1.232323] | 0.813777 [0.722521, 0.910976] | 1.068491 ± 0.112986 | 0.818598 ± 0.078634 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 0.545048 14.953568 0.000058 0.420953 17.653550 0.000030 0.443848 0.646248 0.354748 0.487158 + polyatomic_polyatomic vs gat_selfies 0.489698 6.727679 0.001271 0.393470 7.609369 0.000800 0.287605 0.691791 0.249904 0.537036 + polyatomic_polyatomic vs gat_smiles 0.404064 5.404625 0.002837 0.325934 6.031580 0.001904 0.196490 0.611639 0.175901 0.475968 + polyatomic_polyatomic vs gcn_ecfp 0.542824 17.259305 0.000033 0.423848 16.531998 0.000039 0.455502 0.630147 0.352665 0.495030 + polyatomic_polyatomic vs gcn_selfies 0.597930 7.790357 0.000732 0.468794 7.753341 0.000746 0.384831 0.811029 0.300920 0.636667 + polyatomic_polyatomic vs gcn_smiles 0.559312 5.047050 0.003623 0.449482 5.212771 0.003230 0.251627 0.866996 0.210077 0.688887 + polyatomic_polyatomic vs gin_ecfp 0.474828 19.912779 0.000019 0.369807 46.410500 0.000001 0.408623 0.541034 0.347684 0.391930 + polyatomic_polyatomic vs gin_selfies 0.566468 4.777828 0.004395 0.431151 4.551988 0.005201 0.237288 0.895648 0.168174 0.694128 + polyatomic_polyatomic vs gin_smiles 0.514915 10.396680 0.000242 0.399498 7.850910 0.000711 0.377406 0.652423 0.258217 0.540779 + polyatomic_polyatomic vs sage_ecfp 0.537620 13.237697 0.000094 0.413592 16.233487 0.000042 0.424861 0.650379 0.342855 0.484330 +polyatomic_polyatomic vs sage_selfies 0.373842 4.406668 0.005815 0.293422 5.035386 0.003653 0.138301 0.609384 0.131633 0.455211 + polyatomic_polyatomic vs sage_smiles 0.387829 5.838351 0.002145 0.310202 7.346672 0.000914 0.203396 0.572262 0.192971 0.427433 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_ecfp 0.000019 0.000225 True + polyatomic_polyatomic vs gcn_ecfp 0.000033 0.000364 True + polyatomic_polyatomic vs gat_ecfp 0.000058 0.000583 True + polyatomic_polyatomic vs sage_ecfp 0.000094 0.000847 True + polyatomic_polyatomic vs gin_smiles 0.000242 0.001933 True + polyatomic_polyatomic vs gcn_selfies 0.000732 0.005125 True + polyatomic_polyatomic vs gat_selfies 0.001271 0.007628 True + polyatomic_polyatomic vs sage_smiles 0.002145 0.010726 True + polyatomic_polyatomic vs gat_smiles 0.002837 0.011349 True + polyatomic_polyatomic vs gcn_smiles 0.003623 0.011349 True + polyatomic_polyatomic vs gin_selfies 0.004395 0.011349 True +polyatomic_polyatomic vs sage_selfies 0.005815 0.011349 True + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_ecfp 0.000001 0.000008 True + polyatomic_polyatomic vs gat_ecfp 0.000030 0.000333 True + polyatomic_polyatomic vs gcn_ecfp 0.000039 0.000392 True + polyatomic_polyatomic vs sage_ecfp 0.000042 0.000392 True + polyatomic_polyatomic vs gin_smiles 0.000711 0.005688 True + polyatomic_polyatomic vs gcn_selfies 0.000746 0.005688 True + polyatomic_polyatomic vs gat_selfies 0.000800 0.005688 True + polyatomic_polyatomic vs sage_smiles 0.000914 0.005688 True + polyatomic_polyatomic vs gat_smiles 0.001904 0.007617 True + polyatomic_polyatomic vs gcn_smiles 0.003230 0.009689 True +polyatomic_polyatomic vs sage_selfies 0.003653 0.009689 True + polyatomic_polyatomic vs gin_selfies 0.005201 0.009689 True + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/freesolv_NB_single_dataset.txt b/plotting/results/freesolv_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..a1d0ee075710ec0a87455795df6158843ddf1478 --- /dev/null +++ b/plotting/results/freesolv_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: freesolv — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 2.536442 [1.858415, 3.358781] | 1.725710 [1.428649, 2.097447] | 1.980114 ± 0.227136 | 1.323623 ± 0.137226 +gat_selfies | 3.672406 [2.941128, 4.523194] | 2.700715 [2.280366, 3.160490] | 2.786819 ± 0.360942 | 2.058706 ± 0.334036 +gat_smiles | 3.727151 [2.964849, 4.590632] | 2.722492 [2.315231, 3.200096] | 2.776654 ± 0.372756 | 2.069778 ± 0.304780 +gcn_ecfp | 2.537705 [1.789098, 3.403127] | 1.609283 [1.309617, 1.973166] | 2.004515 ± 0.237696 | 1.309020 ± 0.147140 +gcn_selfies | 3.772947 [3.002692, 4.699522] | 2.726296 [2.290787, 3.220682] | 3.485615 ± 0.216097 | 2.546460 ± 0.096643 +gcn_smiles | 3.880046 [3.109935, 4.824497] | 2.855300 [2.418590, 3.340446] | 3.380516 ± 0.239770 | 2.485861 ± 0.183719 +gin_ecfp | 2.172153 [1.613791, 2.801747] | 1.427185 [1.167242, 1.739900] | 1.737176 ± 0.127819 | 1.179735 ± 0.160290 +gin_selfies | 3.814377 [3.044363, 4.714400] | 2.792971 [2.360692, 3.254110] | 3.426568 ± 0.170072 | 2.553373 ± 0.133403 +gin_smiles | 3.690091 [2.944286, 4.498881] | 2.675992 [2.254980, 3.164493] | 3.454038 ± 0.199376 | 2.527711 ± 0.123384 +polyatomic_polyatomic | 1.439289 [0.998097, 1.883773] | 0.856346 [0.675732, 1.060938] | 1.313263 ± 0.110528 | 0.856738 ± 0.064300 +sage_ecfp | 2.365460 [1.758819, 3.080112] | 1.595687 [1.315293, 1.942996] | 1.894371 ± 0.162211 | 1.285149 ± 0.149799 +sage_selfies | 3.778605 [2.976454, 4.649269] | 2.762492 [2.360794, 3.221569] | 2.498352 ± 0.428986 | 1.851257 ± 0.388913 +sage_smiles | 3.789157 [3.019696, 4.665342] | 2.801680 [2.374271, 3.282033] | 2.703004 ± 0.378413 | 2.029369 ± 0.290412 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 0.666851 4.538050 0.005256 0.466885 7.425197 0.000878 0.258862 1.074840 0.292306 0.641464 + polyatomic_polyatomic vs gat_selfies 1.473555 5.882388 0.002087 1.201969 5.426930 0.002796 0.778048 2.169063 0.587035 1.816902 + polyatomic_polyatomic vs gat_smiles 1.463390 5.798555 0.002199 1.213041 6.223920 0.001697 0.762694 2.164086 0.671912 1.754169 + polyatomic_polyatomic vs gcn_ecfp 0.691251 5.111836 0.003463 0.452283 6.375635 0.001552 0.315805 1.066698 0.255324 0.649242 + polyatomic_polyatomic vs gcn_selfies 2.172351 11.171190 0.000183 1.689723 16.560517 0.000039 1.632443 2.712259 1.406433 1.973012 + polyatomic_polyatomic vs gcn_smiles 2.067253 9.300994 0.000372 1.629124 11.909231 0.000142 1.450156 2.684350 1.249320 2.008928 + polyatomic_polyatomic vs gin_ecfp 0.423912 5.375735 0.002893 0.322998 2.855985 0.023058 0.204971 0.642853 0.008996 0.637000 + polyatomic_polyatomic vs gin_selfies 2.113305 11.591642 0.000158 1.696635 15.350375 0.000053 1.607123 2.619486 1.389762 2.003508 + polyatomic_polyatomic vs gin_smiles 2.140775 11.296228 0.000175 1.670974 19.269291 0.000021 1.614604 2.666945 1.430209 1.911739 + polyatomic_polyatomic vs sage_ecfp 0.581108 10.340987 0.000247 0.428411 4.616530 0.004953 0.425087 0.737129 0.170759 0.686063 +polyatomic_polyatomic vs sage_selfies 1.185088 4.426187 0.005728 0.994519 3.863844 0.009044 0.441710 1.928467 0.279887 1.709151 + polyatomic_polyatomic vs sage_smiles 1.389741 5.689594 0.002356 1.172631 6.811997 0.001214 0.711566 2.067916 0.694688 1.650575 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_selfies 0.000158 0.001899 True + polyatomic_polyatomic vs gin_smiles 0.000175 0.001925 True + polyatomic_polyatomic vs gcn_selfies 0.000183 0.001925 True + polyatomic_polyatomic vs sage_ecfp 0.000247 0.002221 True + polyatomic_polyatomic vs gcn_smiles 0.000372 0.002974 True + polyatomic_polyatomic vs gat_selfies 0.002087 0.014610 True + polyatomic_polyatomic vs gat_smiles 0.002199 0.014610 True + polyatomic_polyatomic vs sage_smiles 0.002356 0.014610 True + polyatomic_polyatomic vs gin_ecfp 0.002893 0.014610 True + polyatomic_polyatomic vs gcn_ecfp 0.003463 0.014610 True + polyatomic_polyatomic vs gat_ecfp 0.005256 0.014610 True +polyatomic_polyatomic vs sage_selfies 0.005728 0.014610 True + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_smiles 0.000021 0.000256 True + polyatomic_polyatomic vs gcn_selfies 0.000039 0.000428 True + polyatomic_polyatomic vs gin_selfies 0.000053 0.000525 True + polyatomic_polyatomic vs gcn_smiles 0.000142 0.001281 True + polyatomic_polyatomic vs gat_ecfp 0.000878 0.007024 True + polyatomic_polyatomic vs sage_smiles 0.001214 0.008495 True + polyatomic_polyatomic vs gcn_ecfp 0.001552 0.009313 True + polyatomic_polyatomic vs gat_smiles 0.001697 0.009313 True + polyatomic_polyatomic vs gat_selfies 0.002796 0.011182 True + polyatomic_polyatomic vs sage_ecfp 0.004953 0.014860 True +polyatomic_polyatomic vs sage_selfies 0.009044 0.018088 True + polyatomic_polyatomic vs gin_ecfp 0.023058 0.023058 True + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/ic50_NB_single_dataset.txt b/plotting/results/ic50_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..5a9ab925876dd51b478ed4c4d5dc30327b06bec4 --- /dev/null +++ b/plotting/results/ic50_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: ic50 — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 0.756567 [0.685188, 0.831186] | 0.588957 [0.543713, 0.638853] | 0.768333 ± 0.038465 | 0.595889 ± 0.016349 +gat_selfies | 0.739957 [0.677242, 0.811344] | 0.588332 [0.544694, 0.632072] | 0.780903 ± 0.049973 | 0.608905 ± 0.019732 +gat_smiles | 0.741486 [0.672216, 0.814339] | 0.580751 [0.535140, 0.625264] | 0.781717 ± 0.049394 | 0.608372 ± 0.018920 +gcn_ecfp | 0.771808 [0.698955, 0.846373] | 0.595372 [0.545556, 0.647247] | 0.763733 ± 0.036233 | 0.596118 ± 0.018796 +gcn_selfies | 0.745231 [0.676725, 0.815795] | 0.588968 [0.546651, 0.634146] | 0.782497 ± 0.051083 | 0.606765 ± 0.021751 +gcn_smiles | 0.740936 [0.671876, 0.811042] | 0.586459 [0.545321, 0.631808] | 0.782171 ± 0.050774 | 0.607169 ± 0.020282 +gin_ecfp | 0.764419 [0.687659, 0.835018] | 0.592957 [0.544833, 0.642144] | 0.782464 ± 0.035356 | 0.604945 ± 0.013472 +gin_selfies | 0.740795 [0.676709, 0.812728] | 0.589688 [0.545839, 0.635794] | 0.783037 ± 0.050806 | 0.610020 ± 0.019629 +gin_smiles | 0.739775 [0.670553, 0.817909] | 0.586204 [0.541501, 0.630134] | 0.783117 ± 0.051127 | 0.608843 ± 0.020055 +polyatomic_polyatomic | 0.749880 [0.688620, 0.817071] | 0.606406 [0.565874, 0.652223] | 0.756392 ± 0.037301 | 0.596187 ± 0.018479 +sage_ecfp | 0.784046 [0.705414, 0.860384] | 0.603648 [0.556301, 0.652519] | 0.763812 ± 0.036209 | 0.591910 ± 0.014446 +sage_selfies | 0.735632 [0.671116, 0.810552] | 0.584244 [0.540345, 0.630018] | 0.782491 ± 0.051402 | 0.609728 ± 0.021232 +sage_smiles | 0.741967 [0.672369, 0.819359] | 0.581619 [0.539225, 0.628283] | 0.781917 ± 0.050153 | 0.608085 ± 0.019509 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 0.011941 1.098923 0.166751 -0.000297 -0.022502 0.508437 -0.018228 0.042110 -0.036964 0.036370 + polyatomic_polyatomic vs gat_selfies 0.024511 1.203391 0.147587 0.012719 1.178996 0.151870 -0.032041 0.081063 -0.017233 0.042670 + polyatomic_polyatomic vs gat_smiles 0.025325 1.237717 0.141754 0.012186 1.158887 0.155487 -0.031484 0.082134 -0.017009 0.041380 + polyatomic_polyatomic vs gcn_ecfp 0.007341 0.692586 0.263339 -0.000069 -0.008186 0.503070 -0.022087 0.036769 -0.023357 0.023219 + polyatomic_polyatomic vs gcn_selfies 0.026105 1.276520 0.135423 0.010578 0.840306 0.224016 -0.030674 0.082884 -0.024373 0.045529 + polyatomic_polyatomic vs gcn_smiles 0.025779 1.282266 0.134509 0.010983 1.028327 0.180956 -0.030040 0.081599 -0.018670 0.040636 + polyatomic_polyatomic vs gin_ecfp 0.026072 5.608322 0.002483 0.008759 0.824569 0.227974 0.013165 0.038979 -0.020733 0.038250 + polyatomic_polyatomic vs gin_selfies 0.026646 1.373598 0.120761 0.013833 1.507133 0.103127 -0.027213 0.080504 -0.011650 0.039316 + polyatomic_polyatomic vs gin_smiles 0.026725 1.338463 0.125879 0.012657 1.295786 0.132382 -0.028712 0.082162 -0.014462 0.039775 + polyatomic_polyatomic vs sage_ecfp 0.007421 0.788797 0.237176 -0.004276 -0.463159 0.666336 -0.018699 0.033541 -0.029911 0.021359 +polyatomic_polyatomic vs sage_selfies 0.026099 1.238986 0.141542 0.013542 1.205766 0.147177 -0.032386 0.084584 -0.017640 0.044723 + polyatomic_polyatomic vs sage_smiles 0.025525 1.244014 0.140707 0.011899 1.050054 0.176473 -0.031443 0.082493 -0.019562 0.043360 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_ecfp 0.002483 0.029792 True + polyatomic_polyatomic vs gin_selfies 0.120761 1.000000 False + polyatomic_polyatomic vs gin_smiles 0.125879 1.000000 False + polyatomic_polyatomic vs gcn_smiles 0.134509 1.000000 False + polyatomic_polyatomic vs gcn_selfies 0.135423 1.000000 False + polyatomic_polyatomic vs sage_smiles 0.140707 1.000000 False +polyatomic_polyatomic vs sage_selfies 0.141542 1.000000 False + polyatomic_polyatomic vs gat_smiles 0.141754 1.000000 False + polyatomic_polyatomic vs gat_selfies 0.147587 1.000000 False + polyatomic_polyatomic vs gat_ecfp 0.166751 1.000000 False + polyatomic_polyatomic vs sage_ecfp 0.237176 1.000000 False + polyatomic_polyatomic vs gcn_ecfp 0.263339 1.000000 False + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gin_selfies 0.103127 1.000000 False + polyatomic_polyatomic vs gin_smiles 0.132382 1.000000 False +polyatomic_polyatomic vs sage_selfies 0.147177 1.000000 False + polyatomic_polyatomic vs gat_selfies 0.151870 1.000000 False + polyatomic_polyatomic vs gat_smiles 0.155487 1.000000 False + polyatomic_polyatomic vs sage_smiles 0.176473 1.000000 False + polyatomic_polyatomic vs gcn_smiles 0.180956 1.000000 False + polyatomic_polyatomic vs gcn_selfies 0.224016 1.000000 False + polyatomic_polyatomic vs gin_ecfp 0.227974 1.000000 False + polyatomic_polyatomic vs gcn_ecfp 0.503070 1.000000 False + polyatomic_polyatomic vs gat_ecfp 0.508437 1.000000 False + polyatomic_polyatomic vs sage_ecfp 0.666336 1.000000 False + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/lipophil_NB_single_dataset.txt b/plotting/results/lipophil_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9eb58146637196417d09652d48979a4125de398 --- /dev/null +++ b/plotting/results/lipophil_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: lipophil — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 0.862967 [0.812183, 0.912302] | 0.658228 [0.619103, 0.696421] | 0.874813 ± 0.024628 | 0.665527 ± 0.021160 +gat_selfies | 1.081340 [1.036938, 1.128630] | 0.881104 [0.840970, 0.924473] | 1.037287 ± 0.052443 | 0.832566 ± 0.043560 +gat_smiles | 1.068747 [1.017778, 1.118856] | 0.860112 [0.816209, 0.905022] | 1.030685 ± 0.043815 | 0.824656 ± 0.034261 +gcn_ecfp | 0.837618 [0.787549, 0.887376] | 0.637590 [0.600752, 0.673294] | 0.865728 ± 0.024324 | 0.662833 ± 0.021128 +gcn_selfies | 1.105532 [1.057341, 1.149453] | 0.905712 [0.863079, 0.946613] | 1.069965 ± 0.041310 | 0.862737 ± 0.032622 +gcn_smiles | 1.109580 [1.062683, 1.157009] | 0.905936 [0.859846, 0.949710] | 1.075038 ± 0.045100 | 0.868886 ± 0.032822 +gin_ecfp | 0.807951 [0.759879, 0.859746] | 0.604900 [0.570841, 0.642128] | 0.829080 ± 0.035731 | 0.620488 ± 0.035590 +gin_selfies | 1.084986 [1.032412, 1.137770] | 0.871410 [0.826601, 0.913421] | 1.061878 ± 0.065333 | 0.847859 ± 0.054295 +gin_smiles | 1.073379 [1.026774, 1.125871] | 0.865299 [0.825895, 0.908155] | 1.071704 ± 0.043282 | 0.862245 ± 0.036236 +polyatomic_polyatomic | 0.750166 [0.701453, 0.801550] | 0.546201 [0.511713, 0.579163] | 0.716816 ± 0.027181 | 0.531184 ± 0.022649 +sage_ecfp | 0.850434 [0.802967, 0.899354] | 0.651153 [0.616387, 0.688607] | 0.864885 ± 0.021444 | 0.663023 ± 0.021885 +sage_selfies | 1.030099 [0.972416, 1.095108] | 0.811732 [0.766428, 0.853343] | 0.946567 ± 0.038476 | 0.749871 ± 0.026962 +sage_smiles | 1.016465 [0.953699, 1.080275] | 0.797396 [0.755563, 0.842923] | 0.955182 ± 0.040513 | 0.762820 ± 0.035193 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 0.157998 8.365009 0.000558 0.134343 9.321019 0.000369 0.105556 0.210439 0.094327 0.174360 + polyatomic_polyatomic vs gat_selfies 0.320471 11.120423 0.000186 0.301382 14.562756 0.000065 0.240459 0.400483 0.243923 0.358842 + polyatomic_polyatomic vs gat_smiles 0.313869 8.565269 0.000510 0.293472 11.414344 0.000168 0.212128 0.415611 0.222087 0.364857 + polyatomic_polyatomic vs gcn_ecfp 0.148912 8.516503 0.000521 0.131650 10.908886 0.000200 0.100366 0.197459 0.098143 0.165156 + polyatomic_polyatomic vs gcn_selfies 0.353149 20.048041 0.000018 0.331553 35.042785 0.000002 0.304242 0.402057 0.305284 0.357823 + polyatomic_polyatomic vs gcn_smiles 0.358223 17.664564 0.000030 0.337702 32.600741 0.000003 0.301919 0.414527 0.308942 0.366463 + polyatomic_polyatomic vs gin_ecfp 0.112264 4.076504 0.007571 0.089304 3.639682 0.010985 0.035803 0.188725 0.021181 0.157428 + polyatomic_polyatomic vs gin_selfies 0.345063 6.854546 0.001186 0.316676 7.517883 0.000838 0.205295 0.484831 0.199724 0.433628 + polyatomic_polyatomic vs gin_smiles 0.354888 13.627886 0.000084 0.331062 15.061764 0.000057 0.282586 0.427191 0.270035 0.392089 + polyatomic_polyatomic vs sage_ecfp 0.148070 9.090749 0.000406 0.131840 10.860730 0.000204 0.102847 0.193293 0.098136 0.165543 +polyatomic_polyatomic vs sage_selfies 0.229752 9.643055 0.000323 0.218688 15.687052 0.000048 0.163601 0.295902 0.179982 0.257393 + polyatomic_polyatomic vs sage_smiles 0.238367 9.619994 0.000326 0.231637 13.137888 0.000097 0.169571 0.307162 0.182685 0.280589 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_selfies 0.000018 0.000219 True + polyatomic_polyatomic vs gcn_smiles 0.000030 0.000332 True + polyatomic_polyatomic vs gin_smiles 0.000084 0.000839 True + polyatomic_polyatomic vs gat_selfies 0.000186 0.001674 True +polyatomic_polyatomic vs sage_selfies 0.000323 0.002587 True + polyatomic_polyatomic vs sage_smiles 0.000326 0.002587 True + polyatomic_polyatomic vs sage_ecfp 0.000406 0.002587 True + polyatomic_polyatomic vs gat_smiles 0.000510 0.002587 True + polyatomic_polyatomic vs gcn_ecfp 0.000521 0.002587 True + polyatomic_polyatomic vs gat_ecfp 0.000558 0.002587 True + polyatomic_polyatomic vs gin_selfies 0.001186 0.002587 True + polyatomic_polyatomic vs gin_ecfp 0.007571 0.007571 True + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_selfies 0.000002 0.000024 True + polyatomic_polyatomic vs gcn_smiles 0.000003 0.000029 True +polyatomic_polyatomic vs sage_selfies 0.000048 0.000482 True + polyatomic_polyatomic vs gin_smiles 0.000057 0.000510 True + polyatomic_polyatomic vs gat_selfies 0.000065 0.000517 True + polyatomic_polyatomic vs sage_smiles 0.000097 0.000678 True + polyatomic_polyatomic vs gat_smiles 0.000168 0.001008 True + polyatomic_polyatomic vs gcn_ecfp 0.000200 0.001008 True + polyatomic_polyatomic vs sage_ecfp 0.000204 0.001008 True + polyatomic_polyatomic vs gat_ecfp 0.000369 0.001106 True + polyatomic_polyatomic vs gin_selfies 0.000838 0.001676 True + polyatomic_polyatomic vs gin_ecfp 0.010985 0.010985 True + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/results/qm9_NB_single_dataset.txt b/plotting/results/qm9_NB_single_dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..808eda0845aa17d698d6c516d3dafabf3e2cdf1f --- /dev/null +++ b/plotting/results/qm9_NB_single_dataset.txt @@ -0,0 +1,73 @@ +============================================================================================================== +Dataset: qm9 — Control vs competitors (NB-corrected t on outer folds; Holm across competitors) +============================================================================================================== + +Control exp_id: polyatomic_polyatomic +k folds: 5, alpha: 0.05 + +Model (exp_id) | Test RMSE (95% CI) | Test MAE (95% CI) | Val RMSE mean±sd | Val MAE mean±sd +----------------------------------------------------------------------------------------------------------------------------------------------- +gat_ecfp | 2.436978 [2.160666, 2.729773] | 1.786932 [1.635919, 1.960408] | 2.490216 ± 0.149206 | 1.825766 ± 0.050861 +gat_selfies | 1.817190 [1.686323, 1.958017] | 1.421490 [1.308344, 1.534664] | 1.897857 ± 0.072471 | 1.493331 ± 0.048341 +gat_smiles | 1.782097 [1.652617, 1.922596] | 1.402670 [1.293241, 1.514130] | 1.896107 ± 0.070945 | 1.488028 ± 0.052473 +gcn_ecfp | 2.425760 [2.201719, 2.678215] | 1.838791 [1.684923, 2.007703] | 2.483434 ± 0.170952 | 1.811209 ± 0.084552 +gcn_selfies | 2.155204 [2.005798, 2.307854] | 1.727491 [1.604164, 1.861639] | 2.357724 ± 0.095930 | 1.870856 ± 0.078179 +gcn_smiles | 2.125754 [1.970697, 2.286484] | 1.698012 [1.573304, 1.826408] | 2.423138 ± 0.062509 | 1.925965 ± 0.045552 +gin_ecfp | 2.547251 [2.307424, 2.802645] | 1.926849 [1.769292, 2.100713] | 2.583041 ± 0.112938 | 1.912713 ± 0.065633 +gin_selfies | 1.811927 [1.684943, 1.945106] | 1.434904 [1.327945, 1.540227] | 1.883210 ± 0.081116 | 1.489118 ± 0.068234 +gin_smiles | 1.811594 [1.673050, 1.952009] | 1.419177 [1.310537, 1.527921] | 1.875917 ± 0.063338 | 1.492467 ± 0.057685 +polyatomic_polyatomic | 1.048171 [0.879043, 1.239801] | 0.651224 [0.571141, 0.734267] | 0.999115 ± 0.098547 | 0.658564 ± 0.068877 +sage_ecfp | 2.485793 [2.226823, 2.743318] | 1.831163 [1.665844, 1.994141] | 2.515583 ± 0.164508 | 1.835610 ± 0.085576 +sage_selfies | 1.487706 [1.368439, 1.603567] | 1.155928 [1.069449, 1.251764] | 1.560794 ± 0.030698 | 1.206468 ± 0.028751 +sage_smiles | 1.429020 [1.315192, 1.538992] | 1.088990 [0.998447, 1.179061] | 1.551988 ± 0.050026 | 1.209292 ± 0.034006 + +--- NB-corrected t (outer folds) per competitor --- + comparison mean_diff_RMSE(comp-ctrl) t_NB_RMSE p_one_sided_RMSE mean_diff_MAE(comp-ctrl) t_NB_MAE p_one_sided_MAE NB_CI_RMSE_low NB_CI_RMSE_high NB_CI_MAE_low NB_CI_MAE_high + polyatomic_polyatomic vs gat_ecfp 1.491101 16.167199 0.000043 1.167203 20.715567 0.000016 1.235029 1.747172 1.010766 1.323639 + polyatomic_polyatomic vs gat_selfies 0.898741 8.978911 0.000426 0.834768 13.358048 0.000091 0.620834 1.176649 0.661263 1.008272 + polyatomic_polyatomic vs gat_smiles 0.896991 12.285963 0.000126 0.829465 22.088894 0.000012 0.694285 1.099698 0.725206 0.933723 + polyatomic_polyatomic vs gcn_ecfp 1.484319 12.954703 0.000102 1.152645 15.861863 0.000046 1.166201 1.802438 0.950887 1.354403 + polyatomic_polyatomic vs gcn_selfies 1.358608 19.070355 0.000022 1.212292 48.841979 0.000001 1.160809 1.556407 1.143378 1.281205 + polyatomic_polyatomic vs gcn_smiles 1.424022 30.028915 0.000004 1.267401 25.966433 0.000007 1.292359 1.555686 1.131885 1.402918 + polyatomic_polyatomic vs gin_ecfp 1.583925 16.790048 0.000037 1.254149 22.973780 0.000011 1.322003 1.845847 1.102582 1.405717 + polyatomic_polyatomic vs gin_selfies 0.884095 11.019624 0.000193 0.830555 20.865785 0.000016 0.661343 1.106847 0.720039 0.941070 + polyatomic_polyatomic vs gin_smiles 0.876802 10.340717 0.000247 0.833903 19.947632 0.000019 0.641384 1.112220 0.717835 0.949971 + polyatomic_polyatomic vs sage_ecfp 1.516468 14.189497 0.000072 1.177046 17.803821 0.000029 1.219742 1.813194 0.993490 1.360603 +polyatomic_polyatomic vs sage_selfies 0.561679 6.329216 0.001595 0.547904 9.634379 0.000325 0.315286 0.808071 0.390009 0.705800 + polyatomic_polyatomic vs sage_smiles 0.552873 6.170705 0.001751 0.550729 7.743256 0.000749 0.304113 0.801632 0.353258 0.748200 + +--- Holm-adjusted p-values (RMSE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_smiles 0.000004 0.000044 True + polyatomic_polyatomic vs gcn_selfies 0.000022 0.000245 True + polyatomic_polyatomic vs gin_ecfp 0.000037 0.000369 True + polyatomic_polyatomic vs gat_ecfp 0.000043 0.000385 True + polyatomic_polyatomic vs sage_ecfp 0.000072 0.000573 True + polyatomic_polyatomic vs gcn_ecfp 0.000102 0.000717 True + polyatomic_polyatomic vs gat_smiles 0.000126 0.000756 True + polyatomic_polyatomic vs gin_selfies 0.000193 0.000964 True + polyatomic_polyatomic vs gin_smiles 0.000247 0.000987 True + polyatomic_polyatomic vs gat_selfies 0.000426 0.001277 True +polyatomic_polyatomic vs sage_selfies 0.001595 0.003190 True + polyatomic_polyatomic vs sage_smiles 0.001751 0.003190 True + +--- Holm-adjusted p-values (MAE family) --- + comparison p_raw p_holm Significant + polyatomic_polyatomic vs gcn_selfies 0.000001 0.000006 True + polyatomic_polyatomic vs gcn_smiles 0.000007 0.000072 True + polyatomic_polyatomic vs gin_ecfp 0.000011 0.000106 True + polyatomic_polyatomic vs gat_smiles 0.000012 0.000112 True + polyatomic_polyatomic vs gin_selfies 0.000016 0.000125 True + polyatomic_polyatomic vs gat_ecfp 0.000016 0.000125 True + polyatomic_polyatomic vs gin_smiles 0.000019 0.000125 True + polyatomic_polyatomic vs sage_ecfp 0.000029 0.000146 True + polyatomic_polyatomic vs gcn_ecfp 0.000046 0.000185 True + polyatomic_polyatomic vs gat_selfies 0.000091 0.000272 True +polyatomic_polyatomic vs sage_selfies 0.000325 0.000649 True + polyatomic_polyatomic vs sage_smiles 0.000749 0.000749 True + +============================================================================================================== +Notes: +• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1). +• Holm controls family-wise error across competitors per metric family. +• Held-out Test metrics above are for context only; no fold-based omnibus tests are used. diff --git a/plotting/stats.py b/plotting/stats.py new file mode 100644 index 0000000000000000000000000000000000000000..45e20ad0593a867faaf81eb9d2ca9f58c71a3a1c --- /dev/null +++ b/plotting/stats.py @@ -0,0 +1,393 @@ +""" +Single-dataset statistical comparison: control vs competitors via +Nadeau–Bengio corrected t-tests on outer folds (k-fold CV), with Holm FWER control. +No Wilcoxon. No Friedman. Test metrics are shown for context only. +""" + +import argparse +import re +from pathlib import Path +from typing import Dict, List, Optional, Tuple + +import numpy as np +import pandas as pd +from math import sqrt + +from statsmodels.stats.multitest import multipletests # Holm +from scipy.stats import t as tdist # t distribution for NB p-values + +np.random.seed(42) + +# ----------------------------- +# parse helpers +# ----------------------------- + + +def _parse_list_in_brackets(inner: str) -> Optional[List[float]]: + parts = [p.strip() for p in inner.split(",") if p.strip()] + out: List[float] = [] + for p in parts: + try: + out.append(float(p)) + except Exception: + return None + return out + + +def parse_log_file( + log_path: Path, expected_k: int = 5 +) -> Tuple[Optional[List[float]], Optional[List[float]]]: + """ + Extract K outer-fold validation RMSE and MAE arrays. + Looks for: + VAL FOLD RMSEs: [v1, ..., vK] + VAL FOLD MAEs: [v1, ..., vK] + """ + try: + text = log_path.read_text() + except Exception: + return None, None + + rmse_match = re.search( + r"VAL\s+FOLD\s+RMSEs:\s*\[(.*?)\]", text, flags=re.IGNORECASE + ) + mae_match = re.search(r"VAL\s+FOLD\s+MAEs:\s*\[(.*?)\]", text, flags=re.IGNORECASE) + if not (rmse_match and mae_match): + return None, None + + rmse_scores = _parse_list_in_brackets(rmse_match.group(1)) + mae_scores = _parse_list_in_brackets(mae_match.group(1)) + if rmse_scores is None or mae_scores is None: + return None, None + if len(rmse_scores) != expected_k or len(mae_scores) != expected_k: + return None, None + return rmse_scores, mae_scores + + +def parse_csv_file(csv_path: Path) -> Optional[Dict[str, float]]: + """ + Parse *_final_results.csv with expected columns: + val_rmse_mean, val_rmse_std, val_mae_mean, val_mae_std, + test_rmse_mean, test_rmse_ci_low, test_rmse_ci_high, + test_mae_mean, test_mae_ci_low, test_mae_ci_high + """ + try: + df = pd.read_csv(csv_path) + except Exception: + return None + cols = [ + "val_rmse_mean", + "val_rmse_std", + "val_mae_mean", + "val_mae_std", + "test_rmse_mean", + "test_rmse_ci_low", + "test_rmse_ci_high", + "test_mae_mean", + "test_mae_ci_low", + "test_mae_ci_high", + ] + if not all(c in df.columns for c in cols): + return None + row = df.iloc[0] + return {k: float(row[k]) for k in cols} + + +def clean_base_and_exp_id(base_name: str) -> Tuple[str, str]: + """ + Strip trailing _YYYYMMDD_HHMMSS. exp_id := first two tokens (e.g., 'gat_ecfp'), + or 'polyatomic_polyatomic'. + """ + clean = re.sub(r"_\d{8}_\d{6}$", "", base_name) + toks = clean.split("_") + exp_id = "_".join(toks[:2]) if len(toks) >= 2 else clean + return clean, exp_id + + +def discover_dataset(results_dir: Path, expected_k: int = 5) -> Dict[str, Dict]: + """ + Scan one dataset dir. Keep first valid (log,csv) per exp_id. + Returns: + data[exp_id] = { + 'rmse_folds': [K] or None, + 'mae_folds' : [K] or None, + 'summary' : {...}, + 'log_path' : str, + 'csv_path' : str + } + """ + data: Dict[str, Dict] = {} + for model_dir in results_dir.iterdir(): + if not model_dir.is_dir(): + continue + for log_file in sorted(model_dir.glob("*.txt")): + base = log_file.stem + clean, exp_id = clean_base_and_exp_id(base) + csv_file = log_file.with_name(f"{clean}_final_results.csv") + if not csv_file.exists(): + continue + rmse_scores, mae_scores = parse_log_file(log_file, expected_k=expected_k) + summary_stats = parse_csv_file(csv_file) + if summary_stats is None: + continue + if exp_id not in data: + data[exp_id] = { + "rmse_folds": rmse_scores, + "mae_folds": mae_scores, + "summary": summary_stats, + "log_path": str(log_file), + "csv_path": str(csv_file), + } + return data + + +# ----------------------------- +# Nadeau–Bengio corrected t (within dataset) +# ----------------------------- + + +def nb_corrected_t(diffs: np.ndarray, k: int) -> Tuple[float, float, float]: + """ + Nadeau–Bengio corrected resampled t for k-fold CV differences. + diffs: array length k with (competitor - control) per fold (loss metric). + Negative mean favors control. Returns (t_stat, SE_NB, mean_diff). + Correction uses rho0 = 1/(k-1) → SE_NB = sqrt((1/k + 1/(k-1)) * s^2), + where s^2 is unbiased sample variance across folds. + """ + diffs = np.asarray(diffs, dtype=float) + if diffs.size != k: + raise ValueError("diffs length must equal k") + mean_d = float(diffs.mean()) + if k <= 1: + return np.nan, np.nan, mean_d + s2 = float(np.var(diffs, ddof=1)) + rho0 = 1.0 / (k - 1.0) + se_nb = sqrt((1.0 / k + rho0) * s2) + t_stat = ( + mean_d / se_nb + if se_nb > 0 + else (-np.inf if mean_d < 0 else np.inf if mean_d > 0 else 0.0) + ) + return t_stat, se_nb, mean_d + + +# ----------------------------- +# main +# ----------------------------- + + +def main(): + ap = argparse.ArgumentParser( + description="Single-dataset comparison: NB-corrected t on outer folds (control vs all) with Holm; prints Test metrics for context." + ) + ap.add_argument( + "--results_dir", + type=str, + required=True, + help="Dataset directory (e.g., ./logs_hyperparameter/qm9) with model-family subfolders.", + ) + ap.add_argument( + "--output_dir", type=str, required=True, help="Directory to save the report." + ) + ap.add_argument( + "--exp_name", + type=str, + required=True, + help="Base name for the output report file.", + ) + ap.add_argument( + "--control_model", + type=str, + required=True, + help="Control exp_id (e.g., 'polyatomic_polyatomic'). Unique substring allowed.", + ) + ap.add_argument( + "--k", type=int, default=5, help="Expected number of outer folds (default: 5)." + ) + ap.add_argument( + "--alpha", + type=float, + default=0.05, + help="FWER level for Holm; also used for NB CIs if --print_ci.", + ) + ap.add_argument( + "--print_ci", + action="store_true", + help="Also print NB-style CIs for the mean fold difference.", + ) + args = ap.parse_args() + + results_dir = Path(args.results_dir) + out_dir = Path(args.output_dir) + out_dir.mkdir(parents=True, exist_ok=True) + report_path = out_dir / f"{args.exp_name}_NB_single_dataset.txt" + + data = discover_dataset(results_dir, expected_k=args.k) + if not data: + raise SystemExit( + f"No models found under {results_dir} with valid logs + *_final_results.csv" + ) + + exp_ids = sorted(data.keys()) + + # match control (exact or unique substring) + ctrl = args.control_model + if ctrl not in data: + matches = [e for e in exp_ids if ctrl.lower() in e.lower()] + if len(matches) == 1: + ctrl = matches[0] + else: + raise SystemExit( + f"Control '{args.control_model}' not found. Available exp_ids: {exp_ids}" + ) + + with open(report_path, "w") as f: + f.write("=" * 110 + "\n") + f.write( + f"Dataset: {results_dir.name} — Control vs competitors (NB-corrected t on outer folds; Holm across competitors)\n" + ) + f.write("=" * 110 + "\n\n") + f.write(f"Control exp_id: {ctrl}\n") + f.write(f"k folds: {args.k}, alpha: {args.alpha}\n\n") + + # context table + header = f"{'Model (exp_id)':<26} | {'Test RMSE (95% CI)':<30} | {'Test MAE (95% CI)':<30} | {'Val RMSE mean±sd':<22} | {'Val MAE mean±sd':<22}\n" + f.write(header) + f.write("-" * len(header) + "\n") + for exp_id in exp_ids: + s = data[exp_id]["summary"] + line = ( + f"{exp_id:<26} | " + f"{s['test_rmse_mean']:.6f} [{s['test_rmse_ci_low']:.6f}, {s['test_rmse_ci_high']:.6f}] | " + f"{s['test_mae_mean']:.6f} [{s['test_mae_ci_low']:.6f}, {s['test_mae_ci_high']:.6f}] | " + f"{s['val_rmse_mean']:.6f} ± {s['val_rmse_std']:.6f} | " + f"{s['val_mae_mean']:.6f} ± {s['val_mae_std']:.6f}\n" + ) + f.write(line) + f.write("\n") + + # NB tests per competitor (RMSE and MAE on outer folds) + comps = [e for e in exp_ids if e != ctrl] + rows = [] + pvals_rmse, labels_rmse = [], [] + pvals_mae, labels_mae = [], [] + + ctrl_rmse = np.array( + data[ctrl]["rmse_folds"] if data[ctrl]["rmse_folds"] is not None else [], + dtype=float, + ) + ctrl_mae = np.array( + data[ctrl]["mae_folds"] if data[ctrl]["mae_folds"] is not None else [], + dtype=float, + ) + + if ctrl_rmse.size != args.k or ctrl_mae.size != args.k: + f.write( + "WARNING: Control model missing complete fold arrays; NB testing cannot proceed.\n" + ) + else: + for comp in comps: + comp_rmse = data[comp]["rmse_folds"] + comp_mae = data[comp]["mae_folds"] + if comp_rmse is None or comp_mae is None: + continue + comp_rmse = np.array(comp_rmse, dtype=float) + comp_mae = np.array(comp_mae, dtype=float) + if comp_rmse.size != args.k or comp_mae.size != args.k: + continue + + # diffs = competitor - control (losses); control better ⇒ positive mean + d_rmse = comp_rmse - ctrl_rmse + d_mae = comp_mae - ctrl_mae + + t_rmse, se_rmse, mean_rmse = nb_corrected_t(d_rmse, k=args.k) + t_mae, se_mae, mean_mae = nb_corrected_t(d_mae, k=args.k) + + df = args.k - 1 + # RIGHT (upper tail): control better ⇢ mean(comp - ctrl) > 0 + p_rmse = float(tdist.sf(t_rmse, df=df)) # sf = 1 - cdf + p_mae = float(tdist.sf(t_mae, df=df)) + + pvals_rmse.append(p_rmse) + labels_rmse.append(f"{ctrl} vs {comp}") + pvals_mae.append(p_mae) + labels_mae.append(f"{ctrl} vs {comp}") + + row = { + "comparison": f"{ctrl} vs {comp}", + "mean_diff_RMSE(comp-ctrl)": mean_rmse, + "t_NB_RMSE": t_rmse, + "p_one_sided_RMSE": p_rmse, + "mean_diff_MAE(comp-ctrl)": mean_mae, + "t_NB_MAE": t_mae, + "p_one_sided_MAE": p_mae, + } + + if args.print_ci: + tcrit = float(tdist.ppf(1 - args.alpha / 2, df=df)) + row["NB_CI_RMSE_low"] = mean_rmse - tcrit * se_rmse + row["NB_CI_RMSE_high"] = mean_rmse + tcrit * se_rmse + row["NB_CI_MAE_low"] = mean_mae - tcrit * se_mae + row["NB_CI_MAE_high"] = mean_mae + tcrit * se_mae + + rows.append(row) + + df_rows = pd.DataFrame(rows) + if not df_rows.empty: + f.write("--- NB-corrected t (outer folds) per competitor ---\n") + f.write( + df_rows.to_string(index=False, float_format=lambda x: f"{x:.6f}") + + "\n\n" + ) + else: + f.write( + "No comparable competitors with complete fold arrays. Nothing to test.\n\n" + ) + + # Holm across competitors per metric family + def holm_table(pvals: List[float], labels: List[str], title: str): + if not pvals: + f.write(f"{title}\n(no p-values)\n\n") + return + reject, p_adj, _, _ = multipletests( + pvals=pvals, alpha=args.alpha, method="holm" + ) + df = pd.DataFrame( + { + "comparison": labels, + "p_raw": pvals, + "p_holm": p_adj, + "Significant": reject.astype(bool), + } + ) + f.write(title + "\n") + f.write( + df.sort_values("p_raw").to_string( + index=False, float_format=lambda x: f"{x:.6f}" + ) + + "\n\n" + ) + + holm_table( + pvals_rmse, labels_rmse, "--- Holm-adjusted p-values (RMSE family) ---" + ) + holm_table( + pvals_mae, labels_mae, "--- Holm-adjusted p-values (MAE family) ---" + ) + + f.write("=" * 110 + "\nNotes:\n") + f.write( + "• Tests are within-dataset, one-sided for control superiority, on outer-fold differences with Nadeau–Bengio SE correction (df = k-1).\n" + ) + f.write( + "• Holm controls family-wise error across competitors per metric family.\n" + ) + f.write( + "• Held-out Test metrics above are for context only; no fold-based omnibus tests are used.\n" + ) + + print(f"Report successfully written to: {report_path}") + + +if __name__ == "__main__": + main() diff --git a/plotting/statstable/bindingdb_nb_compact_mae.tex b/plotting/statstable/bindingdb_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..899eb4a9bfe2c6cd0336cd275f1e2da773d186fb --- /dev/null +++ b/plotting/statstable/bindingdb_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{bindingdb}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:bindingdb_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs sage\_smiles & 0.021 & 3.758 & 0.005 & 0.036 & 0.119 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.022 & 3.236 & 0.003 & 0.041 & 0.175 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.015 & 2.085 & -0.005 & 0.035 & 0.386 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.020 & 1.929 & -0.009 & 0.049 & 0.386 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.023 & 2.334 & -0.004 & 0.050 & 0.386 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.020 & 2.365 & -0.003 & 0.043 & 0.386 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.019 & 2.214 & -0.005 & 0.042 & 0.386 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.018 & 1.546 & -0.015 & 0.051 & 0.425 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.042 & 1.671 & -0.028 & 0.112 & 0.425 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.023 & 0.918 & -0.048 & 0.094 & 0.431 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.019 & 0.743 & -0.053 & 0.092 & 0.431 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.024 & 1.227 & -0.030 & 0.077 & 0.431 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/bindingdb_nb_compact_rmse.tex b/plotting/statstable/bindingdb_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..eca07a845380ce7f51faa9744613763c46f1e95a --- /dev/null +++ b/plotting/statstable/bindingdb_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{bindingdb}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:bindingdb_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gat\_ecfp & 0.033 & 1.563 & -0.026 & 0.093 & 0.825 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.009 & 0.737 & -0.025 & 0.043 & 0.825 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.013 & 0.937 & -0.025 & 0.050 & 0.825 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.029 & 1.386 & -0.030 & 0.088 & 0.825 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.013 & 1.029 & -0.023 & 0.049 & 0.825 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.016 & 1.282 & -0.018 & 0.050 & 0.825 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.041 & 1.853 & -0.021 & 0.103 & 0.825 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.016 & 1.775 & -0.009 & 0.040 & 0.825 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.015 & 1.620 & -0.011 & 0.042 & 0.825 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.027 & 1.377 & -0.027 & 0.081 & 0.825 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.015 & 1.480 & -0.013 & 0.042 & 0.825 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.014 & 1.785 & -0.008 & 0.037 & 0.825 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/boilingpoint_nb_compact_mae.tex b/plotting/statstable/boilingpoint_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..c5b48519a19e1b8f47bb4fa9716978955461825c --- /dev/null +++ b/plotting/statstable/boilingpoint_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{boilingpoint}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:boilingpoint_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_selfies & 13.401 & 9.426 & 9.454 & 17.348 & 0.00424 \\ +polyatomic\_polyatomic vs gcn\_smiles & 13.768 & 6.842 & 8.181 & 19.356 & 0.0131 \\ +polyatomic\_polyatomic vs gin\_ecfp & 11.204 & 6.414 & 6.355 & 16.054 & 0.0131 \\ +polyatomic\_polyatomic vs gin\_selfies & 10.606 & 6.218 & 5.871 & 15.342 & 0.0131 \\ +polyatomic\_polyatomic vs gin\_smiles & 11.342 & 6.554 & 6.537 & 16.147 & 0.0131 \\ +polyatomic\_polyatomic vs sage\_ecfp & 9.821 & 6.713 & 5.759 & 13.883 & 0.0131 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 9.421 & 5.680 & 4.816 & 14.027 & 0.0142 \\ +polyatomic\_polyatomic vs gat\_ecfp & 9.641 & 5.181 & 4.474 & 14.807 & 0.0165 \\ +polyatomic\_polyatomic vs sage\_selfies & 7.055 & 4.786 & 2.962 & 11.147 & 0.0175 \\ +polyatomic\_polyatomic vs gat\_selfies & 8.351 & 3.356 & 1.441 & 15.260 & 0.0426 \\ +polyatomic\_polyatomic vs gat\_smiles & 7.444 & 3.000 & 0.554 & 14.335 & 0.0426 \\ +polyatomic\_polyatomic vs sage\_smiles & 6.398 & 2.356 & -1.141 & 13.937 & 0.0426 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/boilingpoint_nb_compact_rmse.tex b/plotting/statstable/boilingpoint_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..a154fb5d22d5a4734d8d194f7976e5f416654317 --- /dev/null +++ b/plotting/statstable/boilingpoint_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{boilingpoint}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:boilingpoint_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_selfies & 12.111 & 7.335 & 7.527 & 16.695 & 0.011 \\ +polyatomic\_polyatomic vs gcn\_smiles & 12.497 & 6.176 & 6.879 & 18.114 & 0.0192 \\ +polyatomic\_polyatomic vs gin\_ecfp & 9.655 & 5.861 & 5.081 & 14.229 & 0.0211 \\ +polyatomic\_polyatomic vs sage\_ecfp & 8.072 & 5.138 & 3.710 & 12.433 & 0.0306 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 7.921 & 4.721 & 3.263 & 12.579 & 0.0366 \\ +polyatomic\_polyatomic vs gat\_ecfp & 7.742 & 4.407 & 2.865 & 12.619 & 0.0407 \\ +polyatomic\_polyatomic vs gin\_selfies & 9.540 & 4.336 & 3.431 & 15.649 & 0.0407 \\ +polyatomic\_polyatomic vs gin\_smiles & 10.193 & 3.937 & 3.004 & 17.381 & 0.0425 \\ +polyatomic\_polyatomic vs gat\_selfies & 6.513 & 3.322 & 1.069 & 11.956 & 0.0587 \\ +polyatomic\_polyatomic vs gat\_smiles & 6.151 & 2.813 & 0.081 & 12.222 & 0.0722 \\ +polyatomic\_polyatomic vs sage\_selfies & 5.256 & 2.449 & -0.703 & 11.215 & 0.0722 \\ +polyatomic\_polyatomic vs sage\_smiles & 5.195 & 1.562 & -4.040 & 14.429 & 0.0967 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/esol_nb_compact_mae.tex b/plotting/statstable/esol_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..9f3abf508eaf334019d70a012d05a403704d9d37 --- /dev/null +++ b/plotting/statstable/esol_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{esol}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:esol_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gin\_ecfp & 0.370 & 46.410 & 0.348 & 0.392 & 8e-06 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.421 & 17.654 & 0.355 & 0.487 & 0.000333 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.424 & 16.532 & 0.353 & 0.495 & 0.000392 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.414 & 16.233 & 0.343 & 0.484 & 0.000392 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.393 & 7.609 & 0.250 & 0.537 & 0.00569 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.469 & 7.753 & 0.301 & 0.637 & 0.00569 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.399 & 7.851 & 0.258 & 0.541 & 0.00569 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.310 & 7.347 & 0.193 & 0.427 & 0.00569 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.326 & 6.032 & 0.176 & 0.476 & 0.00762 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.449 & 5.213 & 0.210 & 0.689 & 0.00969 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.431 & 4.552 & 0.168 & 0.694 & 0.00969 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.293 & 5.035 & 0.132 & 0.455 & 0.00969 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/esol_nb_compact_rmse.tex b/plotting/statstable/esol_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..4aaf00b960d9e94fc7e1b8a748e32d90610d93db --- /dev/null +++ b/plotting/statstable/esol_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{esol}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:esol_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gin\_ecfp & 0.475 & 19.913 & 0.409 & 0.541 & 0.000225 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.543 & 17.259 & 0.456 & 0.630 & 0.000364 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.545 & 14.954 & 0.444 & 0.646 & 0.000583 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.538 & 13.238 & 0.425 & 0.650 & 0.000847 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.515 & 10.397 & 0.377 & 0.652 & 0.00193 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.598 & 7.790 & 0.385 & 0.811 & 0.00513 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.490 & 6.728 & 0.288 & 0.692 & 0.00763 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.388 & 5.838 & 0.203 & 0.572 & 0.0107 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.404 & 5.405 & 0.196 & 0.612 & 0.0113 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.559 & 5.047 & 0.252 & 0.867 & 0.0113 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.566 & 4.778 & 0.237 & 0.896 & 0.0113 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.374 & 4.407 & 0.138 & 0.609 & 0.0113 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/freesolv_nb_compact_mae.tex b/plotting/statstable/freesolv_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..02d44a0bd8c5b8b9e74a1b30be573673545feaf6 --- /dev/null +++ b/plotting/statstable/freesolv_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{freesolv}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:freesolv_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gin\_smiles & 1.671 & 19.269 & 1.430 & 1.912 & 0.000256 \\ +polyatomic\_polyatomic vs gcn\_selfies & 1.690 & 16.561 & 1.406 & 1.973 & 0.000428 \\ +polyatomic\_polyatomic vs gin\_selfies & 1.697 & 15.350 & 1.390 & 2.004 & 0.000525 \\ +polyatomic\_polyatomic vs gcn\_smiles & 1.629 & 11.909 & 1.249 & 2.009 & 0.00128 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.467 & 7.425 & 0.292 & 0.641 & 0.00702 \\ +polyatomic\_polyatomic vs sage\_smiles & 1.173 & 6.812 & 0.695 & 1.651 & 0.0085 \\ +polyatomic\_polyatomic vs gat\_smiles & 1.213 & 6.224 & 0.672 & 1.754 & 0.00931 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.452 & 6.376 & 0.255 & 0.649 & 0.00931 \\ +polyatomic\_polyatomic vs gat\_selfies & 1.202 & 5.427 & 0.587 & 1.817 & 0.0112 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.428 & 4.617 & 0.171 & 0.686 & 0.0149 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.995 & 3.864 & 0.280 & 1.709 & 0.0181 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.323 & 2.856 & 0.009 & 0.637 & 0.0231 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/freesolv_nb_compact_rmse.tex b/plotting/statstable/freesolv_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..034f444498668783527e2c77f5ffd4063fc9895e --- /dev/null +++ b/plotting/statstable/freesolv_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{freesolv}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:freesolv_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gin\_selfies & 2.113 & 11.592 & 1.607 & 2.619 & 0.0019 \\ +polyatomic\_polyatomic vs gcn\_selfies & 2.172 & 11.171 & 1.632 & 2.712 & 0.00193 \\ +polyatomic\_polyatomic vs gin\_smiles & 2.141 & 11.296 & 1.615 & 2.667 & 0.00193 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.581 & 10.341 & 0.425 & 0.737 & 0.00222 \\ +polyatomic\_polyatomic vs gcn\_smiles & 2.067 & 9.301 & 1.450 & 2.684 & 0.00297 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.667 & 4.538 & 0.259 & 1.075 & 0.0146 \\ +polyatomic\_polyatomic vs gat\_selfies & 1.474 & 5.882 & 0.778 & 2.169 & 0.0146 \\ +polyatomic\_polyatomic vs gat\_smiles & 1.463 & 5.799 & 0.763 & 2.164 & 0.0146 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.691 & 5.112 & 0.316 & 1.067 & 0.0146 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.424 & 5.376 & 0.205 & 0.643 & 0.0146 \\ +polyatomic\_polyatomic vs sage\_selfies & 1.185 & 4.426 & 0.442 & 1.928 & 0.0146 \\ +polyatomic\_polyatomic vs sage\_smiles & 1.390 & 5.690 & 0.712 & 2.068 & 0.0146 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/ic50_nb_compact_mae.tex b/plotting/statstable/ic50_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..9ab6eb324bfcb1e0d7ba7c50f9992c1ec352b3d9 --- /dev/null +++ b/plotting/statstable/ic50_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{ic50}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:ic50_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gat\_ecfp & -0.000 & -0.023 & -0.037 & 0.036 & 1 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.013 & 1.179 & -0.017 & 0.043 & 1 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.012 & 1.159 & -0.017 & 0.041 & 1 \\ +polyatomic\_polyatomic vs gcn\_ecfp & -0.000 & -0.008 & -0.023 & 0.023 & 1 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.011 & 0.840 & -0.024 & 0.046 & 1 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.011 & 1.028 & -0.019 & 0.041 & 1 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.009 & 0.825 & -0.021 & 0.038 & 1 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.014 & 1.507 & -0.012 & 0.039 & 1 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.013 & 1.296 & -0.014 & 0.040 & 1 \\ +polyatomic\_polyatomic vs sage\_ecfp & -0.004 & -0.463 & -0.030 & 0.021 & 1 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.014 & 1.206 & -0.018 & 0.045 & 1 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.012 & 1.050 & -0.020 & 0.043 & 1 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/ic50_nb_compact_rmse.tex b/plotting/statstable/ic50_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..1d07269e34567894e23c3dc350f2cd858146e88a --- /dev/null +++ b/plotting/statstable/ic50_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{ic50}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:ic50_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gin\_ecfp & 0.026 & 5.608 & 0.013 & 0.039 & 0.0298 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.012 & 1.099 & -0.018 & 0.042 & 1 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.025 & 1.203 & -0.032 & 0.081 & 1 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.025 & 1.238 & -0.031 & 0.082 & 1 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.007 & 0.693 & -0.022 & 0.037 & 1 \\ +polyatomic\_polyatomic vs gcn\_selfies & 0.026 & 1.277 & -0.031 & 0.083 & 1 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.026 & 1.282 & -0.030 & 0.082 & 1 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.027 & 1.374 & -0.027 & 0.081 & 1 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.027 & 1.338 & -0.029 & 0.082 & 1 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.007 & 0.789 & -0.019 & 0.034 & 1 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.026 & 1.239 & -0.032 & 0.085 & 1 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.026 & 1.244 & -0.031 & 0.082 & 1 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/lipophil_nb_compact_mae.tex b/plotting/statstable/lipophil_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..354bf4a1ef9894f4260b5f5e780b6684d7d1c6b3 --- /dev/null +++ b/plotting/statstable/lipophil_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{lipophil}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:lipophil_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_selfies & 0.332 & 35.043 & 0.305 & 0.358 & 2.4e-05 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.338 & 32.601 & 0.309 & 0.366 & 2.9e-05 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.219 & 15.687 & 0.180 & 0.257 & 0.000482 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.331 & 15.062 & 0.270 & 0.392 & 0.00051 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.301 & 14.563 & 0.244 & 0.359 & 0.000517 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.232 & 13.138 & 0.183 & 0.281 & 0.000678 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.293 & 11.414 & 0.222 & 0.365 & 0.00101 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.132 & 10.909 & 0.098 & 0.165 & 0.00101 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.132 & 10.861 & 0.098 & 0.166 & 0.00101 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.134 & 9.321 & 0.094 & 0.174 & 0.00111 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.317 & 7.518 & 0.200 & 0.434 & 0.00168 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.089 & 3.640 & 0.021 & 0.157 & 0.011 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/lipophil_nb_compact_rmse.tex b/plotting/statstable/lipophil_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..1e070ed26b0b1713fd1440d27f02cbd021a9bb6f --- /dev/null +++ b/plotting/statstable/lipophil_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{lipophil}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:lipophil_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_selfies & 0.353 & 20.048 & 0.304 & 0.402 & 0.000219 \\ +polyatomic\_polyatomic vs gcn\_smiles & 0.358 & 17.665 & 0.302 & 0.415 & 0.000332 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.355 & 13.628 & 0.283 & 0.427 & 0.000839 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.320 & 11.120 & 0.240 & 0.400 & 0.00167 \\ +polyatomic\_polyatomic vs gat\_ecfp & 0.158 & 8.365 & 0.106 & 0.210 & 0.00259 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.314 & 8.565 & 0.212 & 0.416 & 0.00259 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 0.149 & 8.517 & 0.100 & 0.197 & 0.00259 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.345 & 6.855 & 0.205 & 0.485 & 0.00259 \\ +polyatomic\_polyatomic vs sage\_ecfp & 0.148 & 9.091 & 0.103 & 0.193 & 0.00259 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.230 & 9.643 & 0.164 & 0.296 & 0.00259 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.238 & 9.620 & 0.170 & 0.307 & 0.00259 \\ +polyatomic\_polyatomic vs gin\_ecfp & 0.112 & 4.077 & 0.036 & 0.189 & 0.00757 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/qm9_nb_compact_mae.tex b/plotting/statstable/qm9_nb_compact_mae.tex new file mode 100644 index 0000000000000000000000000000000000000000..6523543a61748c523d9cbcf69a29ee3ae5293fea --- /dev/null +++ b/plotting/statstable/qm9_nb_compact_mae.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{MAE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{qm9}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:qm9_nb_compact_mae} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)MAE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_selfies & 1.212 & 48.842 & 1.143 & 1.281 & 6e-06 \\ +polyatomic\_polyatomic vs gcn\_smiles & 1.267 & 25.966 & 1.132 & 1.403 & 7.2e-05 \\ +polyatomic\_polyatomic vs gin\_ecfp & 1.254 & 22.974 & 1.103 & 1.406 & 0.000106 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.829 & 22.089 & 0.725 & 0.934 & 0.000112 \\ +polyatomic\_polyatomic vs gat\_ecfp & 1.167 & 20.716 & 1.011 & 1.324 & 0.000125 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.831 & 20.866 & 0.720 & 0.941 & 0.000125 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.834 & 19.948 & 0.718 & 0.950 & 0.000125 \\ +polyatomic\_polyatomic vs sage\_ecfp & 1.177 & 17.804 & 0.993 & 1.361 & 0.000146 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 1.153 & 15.862 & 0.951 & 1.354 & 0.000185 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.835 & 13.358 & 0.661 & 1.008 & 0.000272 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.548 & 9.634 & 0.390 & 0.706 & 0.000649 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.551 & 7.743 & 0.353 & 0.748 & 0.000749 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/plotting/statstable/qm9_nb_compact_rmse.tex b/plotting/statstable/qm9_nb_compact_rmse.tex new file mode 100644 index 0000000000000000000000000000000000000000..621db74a1a0f61a3f67a88ed4c643b115d0be6e9 --- /dev/null +++ b/plotting/statstable/qm9_nb_compact_rmse.tex @@ -0,0 +1,31 @@ + +% Auto-generated compact NB tables +% Requires in preamble: \usepackage{booktabs,tabularx,siunitx} +% \sisetup{round-mode=places,round-precision=3,scientific-notation=true} + +\begin{table}[t] +\centering +\small +\setlength{\tabcolsep}{4pt} +\caption{RMSE: NB-corrected one-sided tests (outer folds, $K=5$) on dataset \texttt{qm9}; control \texttt{polyatomic\_polyatomic}. +Positive $\Delta$ (competitor $-$ control) favors control. Holm controls FWER.} +\label{tab:qm9_nb_compact_rmse} +\begin{tabularx}{\linewidth}{@{}l S S S S S@{}} +\toprule +Comparison & {\(\Delta\)RMSE} & {$t_{\text{NB}}$} & {CI\(_{\text{low}}\)} & {CI\(_{\text{high}}\)} & {p\(_{\text{Holm}}\)}\\ +\midrule +polyatomic\_polyatomic vs gcn\_smiles & 1.424 & 30.029 & 1.292 & 1.556 & 4.4e-05 \\ +polyatomic\_polyatomic vs gcn\_selfies & 1.359 & 19.070 & 1.161 & 1.556 & 0.000245 \\ +polyatomic\_polyatomic vs gin\_ecfp & 1.584 & 16.790 & 1.322 & 1.846 & 0.000369 \\ +polyatomic\_polyatomic vs gat\_ecfp & 1.491 & 16.167 & 1.235 & 1.747 & 0.000385 \\ +polyatomic\_polyatomic vs sage\_ecfp & 1.516 & 14.189 & 1.220 & 1.813 & 0.000573 \\ +polyatomic\_polyatomic vs gcn\_ecfp & 1.484 & 12.955 & 1.166 & 1.802 & 0.000717 \\ +polyatomic\_polyatomic vs gat\_smiles & 0.897 & 12.286 & 0.694 & 1.100 & 0.000756 \\ +polyatomic\_polyatomic vs gin\_selfies & 0.884 & 11.020 & 0.661 & 1.107 & 0.000964 \\ +polyatomic\_polyatomic vs gin\_smiles & 0.877 & 10.341 & 0.641 & 1.112 & 0.000987 \\ +polyatomic\_polyatomic vs gat\_selfies & 0.899 & 8.979 & 0.621 & 1.177 & 0.00128 \\ +polyatomic\_polyatomic vs sage\_selfies & 0.562 & 6.329 & 0.315 & 0.808 & 0.00319 \\ +polyatomic\_polyatomic vs sage\_smiles & 0.553 & 6.171 & 0.304 & 0.802 & 0.00319 \\ +\bottomrule +\end{tabularx} +\end{table} diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..df87d6f5577d98ce710443397952e8055c5672fb --- /dev/null +++ b/requirements.txt @@ -0,0 +1,222 @@ +aiohappyeyeballs==2.6.1 +aiohttp==3.12.14 +aiosignal==1.4.0 +alembic==1.16.4 +annotated-types==0.7.0 +anyio==4.9.0 +appdirs==1.4.4 +appnope==0.1.4 +argon2-cffi==25.1.0 +argon2-cffi-bindings==21.2.0 +arrow==1.3.0 +ase==3.25.0 +asttokens==3.0.0 +async-lru==2.0.5 +attrs==25.3.0 +babel==2.17.0 +beautifulsoup4==4.13.4 +bibtexparser==1.4.3 +biopandas==0.5.1 +biopython==1.85 +bioservices==1.12.1 +bleach==6.2.0 +botorch==0.14.0 +cattrs==25.1.1 +certifi==2025.7.14 +cffi==1.17.1 +charset-normalizer==3.4.2 +click==8.2.1 +colorama==0.4.6 +colorlog==6.9.0 +comm==0.2.2 +contourpy==1.3.2 +cpdb-protein==0.2.0 +cycler==0.12.1 +Cython==3.1.2 +debugpy==1.8.15 +decorator==5.2.1 +deepdiff==8.5.0 +defusedxml==0.7.1 +dftd3==1.2.1 +dill==0.4.0 +easydev==0.13.3 +executing==2.2.0 +fastjsonschema==2.21.1 +filelock==3.18.0 +fonttools==4.59.0 +fqdn==1.5.1 +frozenlist==1.7.0 +fsspec==2025.7.0 +future==1.0.0 +gauche==0.1.6 +geometric==1.1 +gevent==25.5.1 +git-lfs==1.6 +gitdb==4.0.12 +GitPython==3.1.45 +gpytorch==1.14 +GraKeL==0.1.10 +graphein==1.7.7 +greenlet==3.2.3 +grequests==0.7.0 +gudhi==3.11.0 +h11==0.16.0 +h5py==3.14.0 +httpcore==1.0.9 +httpx==0.28.1 +idna==3.10 +ipykernel==6.30.0 +ipython==9.4.0 +ipython_pygments_lexers==1.1.1 +isoduration==20.11.0 +jax==0.7.0 +jaxlib==0.7.0 +jaxtyping==0.3.2 +jedi==0.19.2 +Jinja2==3.1.6 +joblib==1.5.1 +json5==0.12.0 +jsonpointer==3.0.0 +jsonschema==4.25.0 +jsonschema-specifications==2025.4.1 +jupyter-events==0.12.0 +jupyter-lsp==2.2.6 +jupyter_client==8.6.3 +jupyter_core==5.8.1 +jupyter_server==2.16.0 +jupyter_server_terminals==0.5.3 +jupyterlab==4.4.5 +jupyterlab_pygments==0.3.0 +jupyterlab_server==2.27.3 +kiwisolver==1.4.8 +lark==1.2.2 +line_profiler==4.2.0 +linear-operator==0.6 +loguru==0.7.3 +looseversion==1.1.2 +lxml==5.4.0 +Mako==1.3.10 +markdown-it-py==3.0.0 +MarkupSafe==3.0.2 +matplotlib==3.10.3 +matplotlib-inline==0.1.7 +mdurl==0.1.2 +mistune==3.1.3 +ml_dtypes==0.5.1 +mmtf-python==1.1.3 +monty==2025.3.3 +mpmath==1.3.0 +msgpack==1.1.1 +multidict==6.6.3 +multipledispatch==1.0.0 +mypy_extensions==1.1.0 +narwhals==1.48.0 +nbclient==0.10.2 +nbconvert==7.16.6 +nbformat==5.10.4 +nest-asyncio==1.6.0 +networkx==3.5 +notebook_shim==0.2.4 +numpy==1.26.4 +opt_einsum==3.4.0 +optuna==4.4.0 +orderly-set==5.5.0 +orjson==3.11.0 +overrides==7.7.0 +packaging==25.0 +palettable==3.3.3 +pandas==2.3.1 +pandocfilters==1.5.1 +parso==0.8.4 +patsy==1.0.1 +periodictable==2.0.2 +pexpect==4.9.0 +pillow==11.3.0 +platformdirs==4.3.8 +plotly==6.2.0 +polyatomic_complexes==1.0.8 +prometheus_client==0.22.1 +prompt_toolkit==3.0.51 +propcache==0.3.2 +protobuf==6.31.1 +psutil==7.0.0 +ptyprocess==0.7.0 +pure_eval==0.2.3 +pyarrow==21.0.0 +pycparser==2.22 +pydantic==2.11.7 +pydantic_core==2.33.2 +Pygments==2.19.2 +pymatgen==2025.6.14 +pyparsing==3.2.3 +pyre-extensions==0.0.32 +pyro-api==0.1.2 +pyro-ppl==1.9.1 +pyscf==2.10.0 +python-dateutil==2.9.0.post0 +python-json-logger==3.3.0 +pytz==2025.2 +PyYAML==6.0.2 +pyzmq==27.0.0 +rdkit==2025.3.3 +referencing==0.36.2 +requests==2.32.4 +requests-cache==1.2.1 +rfc3339-validator==0.1.4 +rfc3986-validator==0.1.1 +rfc3987-syntax==1.1.0 +rich==14.0.0 +rich-click==1.8.9 +rpds-py==0.26.0 +ruamel.yaml==0.18.14 +ruamel.yaml.clib==0.2.12 +scikit-learn==1.7.1 +scipy==1.16.0 +seaborn==0.13.2 +selfies==2.2.0 +Send2Trash==1.8.3 +sentry-sdk==2.33.2 +setuptools==80.9.0 +six==1.17.0 +smmap==5.0.2 +sniffio==1.3.1 +soupsieve==2.7 +spglib==2.6.0 +SQLAlchemy==2.0.42 +stack-data==0.6.3 +statsmodels==0.14.5 +suds-community==1.2.0 +sympy==1.14.0 +tabulate==0.9.0 +terminado==0.18.1 +threadpoolctl==3.6.0 +tinycss2==1.4.0 +TopoNetX==0.2.0 +torch==2.7.1 +torch-geometric==2.6.1 +tornado==6.5.1 +tqdm==4.67.1 +traitlets==5.14.3 +trimesh==4.7.1 +types-python-dateutil==2.9.0.20250708 +typing-inspect==0.9.0 +typing-inspection==0.4.1 +typing_extensions==4.14.1 +tzdata==2025.2 +uncertainties==3.2.3 +uri-template==1.3.0 +url-normalize==2.2.1 +urllib3==2.5.0 +wadler_lindig==0.1.7 +wandb==0.21.0 +wcwidth==0.2.13 +webcolors==24.11.1 +webencodings==0.5.1 +websocket-client==1.8.0 +wget==3.2 +wrapt==1.17.2 +xarray==2025.7.1 +xmltodict==0.14.2 +yarl==1.20.1 +zope.event==5.1.1 +zope.interface==7.2 diff --git a/run_all.sh b/run_all.sh new file mode 100644 index 0000000000000000000000000000000000000000..e1d06838efa2677411563e4323c7e703c14b6eaa --- /dev/null +++ b/run_all.sh @@ -0,0 +1,38 @@ +#!/bin/bash + +# --- 1. Define your parameters here --- +# Special case for your model +PACTNET_MODEL="polyatomic" +PACTNET_REP="polyatomic" + +# Baseline models and representations +BASELINE_MODELS=("gcn" "gin" "gat" "sage") +BASELINE_REPS=("smiles" "selfies" "ecfp") + +# Datasets for all experiments +DATASETS=("esol" "freesolv" "lipophil" "boilingpoint" "qm9" "ic50" "bindingdb") + +# --- 2. Generate all valid commands --- +# We use a subshell `( ... )` to group the output of two separate loops. +# This combined output is then piped to GNU Parallel. + +( + # Loop 1: Generate commands for your PACTNet model + echo "--- Generating PACTNet Jobs ---" >&2 + for dataset in "${DATASETS[@]}"; do + echo "python3 main.py --model $PACTNET_MODEL --rep $PACTNET_REP --dataset $dataset" + done + + # Loop 2: Generate commands for all baseline combinations + echo "--- Generating Baseline GNN Jobs ---" >&2 + for model in "${BASELINE_MODELS[@]}"; do + for rep in "${BASELINE_REPS[@]}"; do + for dataset in "${DATASETS[@]}"; do + echo "python3 main.py --model $model --rep $rep --dataset $dataset" + done + done + done +) | \ +caffeinate -s parallel -j 10 --bar --eta + +echo "All jobs complete." \ No newline at end of file diff --git a/runners.py b/runners.py new file mode 100644 index 0000000000000000000000000000000000000000..cc62ba93d8e648ca598fbc7b4b48bd61ee0f3acc --- /dev/null +++ b/runners.py @@ -0,0 +1,65 @@ +import numpy as np +import pandas as pd +from pathlib import Path + +# Import your project's modules +from data.data_handling import prepare_and_load_data, GP_FEATURIZERS +from training.training_pipeline import k_fold_tuned_eval +from models.gp import TanimotoGP as GPModel +from data.loaders import load_dataset + +from training.train_eval import ( + k_fold_eval as gp_k_fold_eval, + train_gp_model, + eval_gp_model, +) + + +def run_gnn_experiment(args): + """ + Orchestrates a full, tuned GNN experiment using the EFFICIENT pipeline. + """ + print( + f"--- Starting GNN Experiment: {args.model} | {args.rep} | {args.dataset} ---" + ) + + # 1. Prepare data ONCE. This function handles caching. + train_graphs, test_graphs = prepare_and_load_data(args) + + # 2. Run the rigorous evaluation pipeline with the pre-featurized data. + k_fold_tuned_eval(args, train_graphs, test_graphs) + + print(f"---GNN Experiment Finished. Results saved---") + + +def run_gp_experiment(args): + """Orchestrates a GP experiment, preserving the original logic.""" + print(f"--- Starting GP Experiment: {args.rep} | {args.dataset} ---") + + X_train, X_test, y_train, y_test = load_dataset(args.dataset) + gp_feat = GP_FEATURIZERS[args.rep] + + X_train_feat = np.stack([gp_feat(x) for x in X_train]).astype(np.float32) + X_test_feat = np.stack([gp_feat(x) for x in X_test]).astype(np.float32) + + def train_fn(X_tr, y_tr, log_file): + model = GPModel() + return train_gp_model(model, X_tr, y_tr, log_file) + + def eval_fn(model, X_te, y_te, log_file, scaler, return_preds=False): + return eval_gp_model( + model, X_te, y_te, log_file, scaler, return_preds=return_preds + ) + + _, test_metrics = gp_k_fold_eval( + train_fn=train_fn, + eval_fn=eval_fn, + X_train=X_train_feat, + y_train=y_train, + model_name="gp", + rep_name=args.rep, + dataset_name=args.dataset, + X_test=X_test_feat, + y_test=y_test, + ) + print(f"--- GP Experiment Finished. Final Test Metrics: {test_metrics} ---") diff --git a/training/train_eval.py b/training/train_eval.py new file mode 100644 index 0000000000000000000000000000000000000000..b2b0eb4c1d57ecc992a56649cf46be89e37cd98c --- /dev/null +++ b/training/train_eval.py @@ -0,0 +1,277 @@ +import torch +from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score +from sklearn.model_selection import KFold +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm +import numpy as np +import os +from datetime import datetime +from pathlib import Path + +# polyatomic +from torch.amp.autocast_mode import autocast + +ROOT = Path(__file__).parent.parent.resolve().__str__() +LOG_ROOT = Path(ROOT + "/" + "logs_hyperparameter") +if not os.path.exists(LOG_ROOT): + os.makedirs(LOG_ROOT, exist_ok=False) + + +def setup_log_file(model_name, rep_name, dataset_name): + from pathlib import Path + from datetime import datetime + + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + fname = f"{model_name}_{rep_name}_{dataset_name}_{timestamp}.txt" + parent = Path(__file__).parent.parent.resolve().__str__() + log_dir = Path(parent + "/" + "logs_hyperparameter") + if not os.path.exists(log_dir): + os.makedirs(LOG_ROOT, exist_ok=False) + + log_path = log_dir / fname + print(f"[Logging] Writing to: {log_path}") + return open(log_path, "w") + + +def write_log(log_file, text): + print(text) + log_file.write(text + "\n") + log_file.flush() + + +def train_gnn_model(model, loader, optimizer, log_file, loss_fn=torch.nn.MSELoss()): + total_loss = 0 + for _ in range(20): + model.train() + total_loss = 0 + for batch in loader: + batch = batch.to(next(model.parameters()).device) + optimizer.zero_grad() + out = model(batch).squeeze() + loss = loss_fn(out, batch.y) + loss.backward() + optimizer.step() + total_loss += loss.item() + avg_loss = total_loss / len(loader) + write_log(log_file, f"GNN Train Loss: {avg_loss:.4f}") + return avg_loss + + +def eval_gnn_model(model, loader, log_file, scaler, return_preds=False): + model.eval() + y_true, y_pred = [], [] + with torch.no_grad(): + for batch in tqdm(loader, desc="Evaluating GNN"): + batch = batch.to(next(model.parameters()).device) + out = model(batch).view(-1) + y_true.append(batch.y.cpu()) + y_pred.append(out.cpu()) + y_true = scaler.inverse_transform(torch.cat(y_true).numpy().reshape(-1, 1)).ravel() + y_pred = scaler.inverse_transform(torch.cat(y_pred).numpy().reshape(-1, 1)).ravel() + metrics = report_metrics(y_true, y_pred, log_file) + if return_preds: + return metrics, y_true, y_pred + return metrics + + +def train_gp_model(gp_model, X_train, y_train, log_file): + write_log(log_file, "Training GP model...") + gp_model.fit(X_train, y_train) + return gp_model + + +def eval_gp_model(gp_model, X_test, y_test, log_file, scaler, return_preds=False): + write_log(log_file, "Evaluating GP model...") + y_pred, _ = gp_model.predict(X_test) + y_test = scaler.inverse_transform(y_test.reshape(-1, 1)).ravel() + y_pred = scaler.inverse_transform(y_pred.reshape(-1, 1)).ravel() + metrics = report_metrics(y_test, y_pred, log_file) + if return_preds: + return metrics, y_test, y_pred + return metrics + + +def report_metrics(y_true, y_pred, log_file): + rmse = np.sqrt(mean_squared_error(y_true, y_pred)) + mae = mean_absolute_error(y_true, y_pred) + r2 = r2_score(y_true, y_pred) + write_log(log_file, f"RMSE: {rmse:.4f}, MAE: {mae:.4f}, R2: {r2:.4f}") + return {"rmse": rmse, "mae": mae, "r2": r2} + + +def bootstrap_ci(arr, n_boot=1000, ci=95): + boot_means = [ + np.mean(np.random.choice(arr, size=len(arr), replace=True)) + for _ in range(n_boot) + ] + lower = np.percentile(boot_means, (100 - ci) / 2) + upper = np.percentile(boot_means, 100 - (100 - ci) / 2) + return np.mean(boot_means), (lower, upper) + + +def bootstrap_metric_ci(metric_fn, y_true, y_pred, n_boot=1000, ci=95, rng=None): + rng = np.random.default_rng(rng) + y_true = np.asarray(y_true) + y_pred = np.asarray(y_pred) + n = len(y_true) + boot_vals = [] + for _ in range(n_boot): + idx = rng.choice(n, n, replace=True) + boot_vals.append(metric_fn(y_true[idx], y_pred[idx])) + mean_val = np.mean(boot_vals) + lo, hi = np.percentile(boot_vals, [(100 - ci) / 2, 100 - (100 - ci) / 2]) + return mean_val, (lo, hi) + + +def train_polyatomic( + model, loader, optimizer, loss_fn, scaler_grad, device, scheduler, accum_steps=1 +): + """ + custom training loop for polyatomic GNNs + uses mixed precision training with autocast + accum_steps allows gradient accumulation for larger effective batch size + this was designed for GPU training, but here is in CPU mode + """ + use_amp = torch.cuda.is_available() + for _ in range(20): + model.train() + total_loss = 0.0 + optimizer.zero_grad() + + for i, batch in enumerate(loader): + batch = batch.to(device) + batch.x = batch.x.float() + batch.edge_attr = batch.edge_attr.float() + batch.graph_feats = batch.graph_feats.float() + batch.y = batch.y.float() + + if use_amp: + with autocast(device_type="cuda", dtype=torch.float16): + output = model(batch) + loss = loss_fn(output, batch.y.view(-1)) / accum_steps + else: + output = model(batch) + loss = loss_fn(output, batch.y.view(-1)) / accum_steps + + if use_amp: + scaler_grad.scale(loss).backward() + else: + loss.backward() + + torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0) + + if (i + 1) % accum_steps == 0 or (i + 1 == len(loader)): + if use_amp: + scaler_grad.step(optimizer) + scaler_grad.update() + else: + optimizer.step() + + optimizer.zero_grad() + + total_loss += loss.item() * batch.num_graphs * accum_steps + + avg_loss = total_loss / len(loader.dataset) + if scheduler is not None: + scheduler.step(avg_loss) + + return model + + +def evaluate_polyatomic(model, loader, device, log_file, scaler, return_preds=False): + """ + uses autocast for mixed precision evaluation + this was designed for GPU training, but here is in CPU mode + """ + model.eval() + preds, trues = [], [] + with torch.no_grad(), autocast( + device_type="cpu", dtype=torch.float16 + ): # change to 'cuda' if using GPU + for batch in loader: + batch = batch.to(device) + out = model(batch) + preds.append(out.view(-1)) + trues.append(batch.y.view(-1)) + y_pred = torch.cat(preds) + y_test = torch.cat(trues) + y_pred = scaler.inverse_transform(y_pred.numpy().reshape(-1, 1)).ravel() + y_test = scaler.inverse_transform(y_test.numpy().reshape(-1, 1)).ravel() + metrics = report_metrics(y_test, y_pred, log_file) + if return_preds: + return metrics, y_test, y_pred + return metrics + + +def k_fold_eval( + train_fn, + eval_fn, + X_train, + y_train, + model_name, + rep_name, + dataset_name, + X_test, + y_test, + k=5, + seed=42, + log_file=None, +): + log_file = setup_log_file(model_name, rep_name, dataset_name) + write_log(log_file, f"Experiment: {model_name}+{rep_name} on {dataset_name}") + + kf = KFold(n_splits=k, shuffle=True, random_state=seed) + fold_metrics, fold_models = [], [] + + for fold, (tr_idx, val_idx) in enumerate(kf.split(X_train)): + write_log(log_file, f"\nFOLD {fold+1}/{k}") + X_tr, X_val = X_train[tr_idx], X_train[val_idx] + y_tr, y_val = y_train[tr_idx], y_train[val_idx] + + scaler = StandardScaler() + y_tr_s = scaler.fit_transform(y_tr.reshape(-1, 1)).ravel() + y_val_s = scaler.transform(y_val.reshape(-1, 1)).ravel() + + model = train_fn(X_tr, y_tr_s, log_file) + m = eval_fn(model, X_val, y_val_s, log_file, scaler) + fold_metrics.append(m) + fold_models.append((model, m["rmse"])) + + write_log(log_file, "\n====== K-FOLD SUMMARY ======") + for key in fold_metrics[0]: + vals = [m[key] for m in fold_metrics] + mean, (lo, hi) = bootstrap_ci(vals) + write_log(log_file, f"{key.upper()}: {mean:.4f} [{lo:.4f}, {hi:.4f}]") + + best_idx = np.argmin([rm for (_, rm) in fold_models]) + best_model = fold_models[best_idx][0] + write_log(log_file, f"\n★ Using fold {best_idx+1} model for test inference") + + test_scaler = StandardScaler().fit(y_train.reshape(-1, 1)) + y_test_s = test_scaler.transform(y_test.reshape(-1, 1)).ravel() + test_metrics, y_true_test, y_pred_test = eval_fn( + best_model, X_test, y_test_s, log_file, test_scaler, return_preds=True + ) + + write_log(log_file, f"\n====== HELD-OUT TEST METRICS ======\n{test_metrics}") + rmse_mean, (rmse_lo, rmse_hi) = bootstrap_metric_ci( + lambda a, b: np.sqrt(mean_squared_error(a, b)), y_true_test, y_pred_test + ) + mae_mean, (mae_lo, mae_hi) = bootstrap_metric_ci( + mean_absolute_error, y_true_test, y_pred_test + ) + r2_mean, (r2_lo, r2_hi) = bootstrap_metric_ci(r2_score, y_true_test, y_pred_test) + write_log( + log_file, + f"Test RMSE: {rmse_mean:.4f} (95 % CI: {rmse_lo:.4f}–{rmse_hi:.4f})\n", + ) + write_log( + log_file, + f"Test MAE : {mae_mean :.4f} (95 % CI: {mae_lo :.4f}–{mae_hi :.4f})\n", + ) + write_log( + log_file, + f"Test R² : {r2_mean :.4f} (95 % CI: {r2_lo :.4f}–{r2_hi :.4f})\n", + ) + log_file.close() + return fold_metrics, test_metrics diff --git a/training/training_pipeline.py b/training/training_pipeline.py new file mode 100644 index 0000000000000000000000000000000000000000..fccf7ad661948a35a990ea69dd2f2ab8a3d82a61 --- /dev/null +++ b/training/training_pipeline.py @@ -0,0 +1,396 @@ +import torch +import torch.nn as nn +from sklearn.model_selection import KFold, train_test_split +from sklearn.preprocessing import StandardScaler +import numpy as np +import os +import tempfile +from pathlib import Path +from datetime import datetime +import optuna +import pandas as pd +from torch_geometric.loader import DataLoader +import copy + +from data.data_handling import get_model_instance + +ROOT = Path(__file__).parent.parent.resolve().__str__() +LOG_ROOT = Path(ROOT + "/" + "logs_hyperparameter") +if not os.path.exists(LOG_ROOT): + os.makedirs(LOG_ROOT, exist_ok=False) + + +def setup_log_file(args): + from pathlib import Path + from datetime import datetime + + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + model_name, rep_name, dataset_name = args.model, args.rep, args.dataset + fname = f"{model_name}_{rep_name}_{dataset_name}_{timestamp}.txt" + parent = Path(__file__).parent.parent.resolve().__str__() + log_dir = Path(parent + "/" + "logs_hyperparameter" + "/" + f"{args.dataset}") + if not os.path.exists(log_dir): + os.makedirs(log_dir, exist_ok=False) + + log_path = log_dir / fname + print(f"[Logging] Writing to: {log_path}") + return log_path + + +def write_log(log_file_path, text): + """Writes a message to both console and the log file.""" + print(text) + with open(log_file_path, "a") as f: + f.write(text + "\n") + + +def train_gnn_model( + model, + train_loader, + val_loader, + optimizer, + device, + loss_fn, + max_epochs=200, + patience=20, +): + """Trains a GNN with early stopping based on a validation set.""" + best_val_loss = float("inf") + epochs_no_improve = 0 + temp_dir = tempfile.gettempdir() + best_model_path = os.path.join(temp_dir, f"best_model_{os.getpid()}.pt") + + for _ in range(max_epochs): + model.train() + for batch in train_loader: + batch = batch.to(device) + if batch.num_edges == 0: + continue + optimizer.zero_grad() + out = model(batch).view(-1) + loss = loss_fn(out, batch.y.view(-1)) + loss.backward() + optimizer.step() + + model.eval() + val_loss = 0 + with torch.no_grad(): + for batch in val_loader: + batch = batch.to(device) + val_loss += loss_fn(model(batch).view(-1), batch.y.view(-1)).item() + + if len(val_loader) > 0: + avg_val_loss = val_loss / len(val_loader) + else: + avg_val_loss = float("inf") + + if avg_val_loss < best_val_loss: + best_val_loss = avg_val_loss + torch.save(model.state_dict(), best_model_path) + epochs_no_improve = 0 + else: + epochs_no_improve += 1 + if epochs_no_improve >= patience: + break + + if os.path.exists(best_model_path): + model.load_state_dict(torch.load(best_model_path)) + os.remove(best_model_path) + + return model + + +def objective(trial, args, train_graphs, val_graphs, device, scaler): + """Optuna objective function. Uses a pre-fitted scaler for consistency.""" + + train_graphs = copy.deepcopy(train_graphs) + val_graphs = copy.deepcopy(val_graphs) + + params = { + "lr": trial.suggest_float("lr", 5e-4, 1e-3, log=True), + "hidden_dim": trial.suggest_categorical("hidden_dim", [64, 128, 256]), + "batch_size": trial.suggest_categorical("batch_size", [32, 64]), + } + + # Use the provided scaler, do not re-fit + for g in train_graphs: + g.y = torch.tensor(scaler.transform(g.y.reshape(1, -1)), dtype=torch.float) + for g in val_graphs: + g.y = torch.tensor(scaler.transform(g.y.reshape(1, -1)), dtype=torch.float) + + train_loader = DataLoader( + train_graphs, batch_size=params["batch_size"], shuffle=True + ) + val_loader = DataLoader(val_graphs, batch_size=params["batch_size"]) + + model = get_model_instance(args, params, train_graphs).to(device) + optimizer = torch.optim.Adam(model.parameters(), lr=params["lr"]) + train_gnn_model( + model, train_loader, val_loader, optimizer, device, loss_fn=nn.MSELoss() + ) + + model.eval() + val_loss = 0 + with torch.no_grad(): + for batch in val_loader: + batch = batch.to(device) + val_loss += nn.MSELoss()(model(batch).view(-1), batch.y.view(-1)).item() + + return val_loss / len(val_loader) if len(val_loader) > 0 else float("inf") + + +def find_best_hyperparameters(args, train_val_graphs, device, scaler): + """ + Runs an Optuna study. + """ + train_graphs, val_graphs = train_test_split( + train_val_graphs, test_size=0.2, random_state=42 + ) + + study = optuna.create_study( + direction="minimize", sampler=optuna.samplers.TPESampler(seed=42) + ) + + study.optimize( + lambda trial: objective(trial, args, train_graphs, val_graphs, device, scaler), + n_trials=args.n_trials, + show_progress_bar=True, + ) + return study.best_params + + +def bootstrap_metric(y_true, y_pred, metric_func, n_bootstraps=1000): + """Performs bootstrapping to estimate the confidence interval of a metric.""" + n_samples = len(y_true) + bootstrapped_scores = [] + for _ in range(n_bootstraps): + indices = np.random.choice(n_samples, n_samples, replace=True) + score = metric_func(y_true[indices], y_pred[indices]) + bootstrapped_scores.append(score) + + lower_bound = np.percentile(bootstrapped_scores, 2.5) + upper_bound = np.percentile(bootstrapped_scores, 97.5) + mean_score = np.mean(bootstrapped_scores) + + return mean_score, lower_bound, upper_bound + + +def rmse_func(y_true, y_pred): + return np.sqrt(np.mean((y_true - y_pred) ** 2)) + + +def mae_func(y_true, y_pred): + return np.mean(np.abs(y_true - y_pred)) + + +def k_fold_tuned_eval(args, train_graphs_full, test_graphs): + """ + Orchestrates a rigorous NESTED cross-validation workflow. + """ + log_file_path = setup_log_file(args) + device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + + outer_kf = KFold(n_splits=5, shuffle=True, random_state=42) + val_fold_rmses = [] + val_fold_maes = [] + + train_indices = np.arange(len(train_graphs_full)) + + for fold, (train_idx, val_idx) in enumerate(outer_kf.split(train_indices)): + write_log(log_file_path, f"\n--- OUTER FOLD {fold + 1}/5 ---") + + train_fold_graphs = [train_graphs_full[i] for i in train_idx] + val_fold_graphs = [train_graphs_full[i] for i in val_idx] + + y_train_fold_raw = np.array([g.y.item() for g in train_fold_graphs]).reshape( + -1, 1 + ) + scaler = StandardScaler().fit(y_train_fold_raw) + + best_params_for_fold = find_best_hyperparameters( + args, train_fold_graphs, device, scaler + ) + write_log( + log_file_path, + f"INFO: Best params for fold {fold + 1}: {best_params_for_fold}", + ) + + train_fold_graphs_scaled = [g.clone() for g in train_fold_graphs] + val_fold_graphs_scaled = [g.clone() for g in val_fold_graphs] + for g in train_fold_graphs_scaled: + g.y = torch.tensor(scaler.transform(g.y.reshape(1, -1)), dtype=torch.float) + for g in val_fold_graphs_scaled: + g.y = torch.tensor(scaler.transform(g.y.reshape(1, -1)), dtype=torch.float) + + train_loader = DataLoader( + train_fold_graphs_scaled, + batch_size=best_params_for_fold["batch_size"], + shuffle=True, + ) + val_loader = DataLoader( + val_fold_graphs_scaled, batch_size=best_params_for_fold["batch_size"] + ) + + model = get_model_instance(args, best_params_for_fold, train_fold_graphs).to( + device + ) + optimizer = torch.optim.Adam(model.parameters(), lr=best_params_for_fold["lr"]) + train_gnn_model( + model, train_loader, val_loader, optimizer, device, loss_fn=nn.MSELoss() + ) + + y_true_val, y_pred_val = [], [] + model.eval() + with torch.no_grad(): + for batch in val_loader: + batch = batch.to(device) + out = model(batch).view(-1) + y_true_val.extend( + scaler.inverse_transform( + batch.y.cpu().numpy().reshape(-1, 1) + ).ravel() + ) + y_pred_val.extend( + scaler.inverse_transform(out.cpu().numpy().reshape(-1, 1)).ravel() + ) + + fold_rmse = rmse_func(np.array(y_true_val), np.array(y_pred_val)) + fold_mae = mae_func(np.array(y_true_val), np.array(y_pred_val)) + val_fold_rmses.append(fold_rmse) + val_fold_maes.append(fold_mae) + write_log( + log_file_path, + f"INFO: Fold {fold + 1} Val RMSE: {fold_rmse:.4f}, MAE: {fold_mae:.4f}", + ) + + mean_val_rmse = np.mean(val_fold_rmses) + std_val_rmse = np.std(val_fold_rmses) + mean_val_mae = np.mean(val_fold_maes) + std_val_mae = np.std(val_fold_maes) + write_log(log_file_path, "\n------ Nested Cross-Validation Summary ------") + write_log( + log_file_path, + f"Unbiased Validation RMSE: {mean_val_rmse:.4f} ± {std_val_rmse:.4f}", + ) + write_log( + log_file_path, + f"Unbiased Validation MAE: {mean_val_mae:.4f} ± {std_val_mae:.4f}", + ) + write_log(log_file_path, f"VAL FOLD RMSEs: {val_fold_rmses}") + write_log(log_file_path, f"VAL FOLD MAEs: {val_fold_maes}") + + write_log(log_file_path, "\n===== STEP 2: Final Model Training & Testing =====") + write_log( + log_file_path, + "INFO: Finding best hyperparameters on the FULL train/val set for final model...", + ) + + final_y_train_full_raw = np.array([g.y.item() for g in train_graphs_full]).reshape( + -1, 1 + ) + final_hpo_scaler = StandardScaler().fit(final_y_train_full_raw) + final_best_params = find_best_hyperparameters( + args, train_graphs_full, device, final_hpo_scaler + ) + + write_log( + log_file_path, + f"INFO: Optimal hyperparameters for final model: {final_best_params}", + ) + + write_log(log_file_path, "INFO: Training final model...") + y_train_full_raw = np.array([g.y.item() for g in train_graphs_full]).reshape(-1, 1) + final_scaler = StandardScaler().fit(y_train_full_raw) + + final_train_graphs = [g.clone() for g in train_graphs_full] + for g in final_train_graphs: + g.y = torch.tensor( + final_scaler.transform(g.y.reshape(1, -1)), dtype=torch.float + ) + + train_subset, val_subset = train_test_split( + final_train_graphs, test_size=0.1, random_state=42 + ) + final_train_loader = DataLoader( + train_subset, batch_size=final_best_params["batch_size"], shuffle=True + ) + final_val_loader = DataLoader( + val_subset, batch_size=final_best_params["batch_size"] + ) + + final_model = get_model_instance(args, final_best_params, final_train_graphs).to( + device + ) + final_optimizer = torch.optim.Adam( + final_model.parameters(), lr=final_best_params["lr"] + ) + train_gnn_model( + final_model, + final_train_loader, + final_val_loader, + final_optimizer, + device, + loss_fn=nn.MSELoss(), + ) + + write_log(log_file_path, "\n===== STEP 3: Final Held-Out Test Evaluation =====") + final_test_graphs = [g.clone() for g in test_graphs] + for g in final_test_graphs: + g.y = torch.tensor( + final_scaler.transform(g.y.reshape(1, -1)), dtype=torch.float + ) + test_loader = DataLoader( + final_test_graphs, batch_size=final_best_params["batch_size"] + ) + + y_true_test, y_pred_test = [], [] + final_model.eval() + with torch.no_grad(): + for batch in test_loader: + batch = batch.to(device) + out = final_model(batch).view(-1) + y_true_test.extend( + final_scaler.inverse_transform( + batch.y.cpu().numpy().reshape(-1, 1) + ).ravel() + ) + y_pred_test.extend( + final_scaler.inverse_transform(out.cpu().numpy().reshape(-1, 1)).ravel() + ) + + y_true_test, y_pred_test = np.array(y_true_test), np.array(y_pred_test) + + rmse_mean, rmse_low, rmse_high = bootstrap_metric( + y_true_test, y_pred_test, rmse_func + ) + mae_mean, mae_low, mae_high = bootstrap_metric(y_true_test, y_pred_test, mae_func) + + write_log( + log_file_path, + f"Test RMSE: {rmse_mean:.4f} (95% CI: [{rmse_low:.4f}, {rmse_high:.4f}])", + ) + write_log( + log_file_path, + f"Test MAE: {mae_mean:.4f} (95% CI: [{mae_low:.4f}, {mae_high:.4f}])", + ) + + results_data = { + "val_rmse_mean": [mean_val_rmse], + "val_rmse_std": [std_val_rmse], + "val_mae_mean": [mean_val_mae], + "val_mae_std": [std_val_mae], + "test_rmse_mean": [rmse_mean], + "test_rmse_ci_low": [rmse_low], + "test_rmse_ci_high": [rmse_high], + "test_mae_mean": [mae_mean], + "test_mae_ci_low": [mae_low], + "test_mae_ci_high": [mae_high], + } + parent = Path(__file__).parent.parent.resolve().__str__() + log_dir = Path( + parent + "/" + "logs_hyperparameter" + "/" + f"{args.dataset}" + ).__str__() + data_res_path = ( + log_dir + "/" + f"{args.model}_{args.rep}_{args.dataset}_final_results.csv" + ) + pd.DataFrame(results_data).to_csv(data_res_path, index=False)