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Proteomic data mining using predicted peptide chromatographic retention times

Correct identification of proteins from peptide fragments is important for proteomic analyses. Peptides are initially separated by Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) before Mass Spectrometry (MS) identification. At the present time, peptide fragment retention (separation) time is not used as a useful scoring filter for identification of the peptide fragments and their parent proteins. In the present paper, we present a new web-based tool for the prediction of peptide fragment retention times and its use in compiling a database of approximately 133,000 peptide fragments computationally obtained by digestion with trypsin of 4,265 E. coli - K12 proteins. The retention calculation is based on the described formulae and the fragments/protein identification was carried out using a simple search-scoring algorithm.