{'fraction_non_alphanumeric': 0.031031807602792862, 'fraction_numerical': 0.021722265321955005, 'mean_word_length': 5.515151515151516, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Computer-Assisted Improvement of Sulfonylureas with Antifungal Properties and Limited Herbicidal Activity: Potential Application in Forage Conservation.

This work reports studies at the molecular level of a series of modified sulfonylureas to determine the chemophoric sites responsible for their antifungal and herbicidal activities. For forage conservation, high antifungal potency and low phytotoxicity are required. A molecular modeling study based on multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) was performed to model these properties, as well as to guide the design of new agrochemical candidates. As a result, the MIA-QSAR models were reliable, robust, and predictive; for antifungal activity, the averages of the main validation parameters were r2 = 0.936, q2 = 0.741, and r2pred = 0.720, and for herbicidal activity, the model was very predictive (r2pred = 0.981 and r2m = 0.944). From the interpretation of the MIA-plots, 46 novel sulfonylureas with likely improved performance were proposed, from which 9 presented promising calculated selectivity indexes. Docking studies were performed to validate the QSAR predictions and to understand the interaction mode of the proposed ligands with the acetohydroxyacid synthase enzyme.