Integrated modeling of peptide digestion and detection for the prediction of proteotypic peptides in targeted proteomics

Abstract

ABSTRACTMotivationThe selection of proteotypic peptides, i.e., detectable unique representatives of proteins of interest, is a key step in targeted shotgun proteomics. To date, much effort has been made to predict proteotypic peptides in the absence of mass spectrometry data. However, the performance of existing tools is still unsatisfactory. One crucial reason is their neglect of the close relationship between protein proteolytic digestion and peptide detection.ResultsWe present an algorithm (named AP3) that firstly considers peptide digestion probability as a feature for proteotypic peptide prediction and demonstrated peptide digestion probability is the most important feature for accurate prediction of proteotypic peptides. AP3 showed higher accuracy than existing tools and accurately predicted the proteotypic peptides for a targeted proteomics assay, showing its great potential for assisting the design of targeted proteomics experiments.Availability and ImplementationFreely available at http://fugroup.amss.ac.cn/software/AP3/AP3.html.Contactyfu@amss.ac.cn or zhuyunping@gmail.comSupplementary InformationSupplementary data are available at Bioinformatics online.