AP3: An Advanced Proteotypic Peptide Predictor for Targeted Proteomics by Incorporating Peptide Digestibility

The selection of
proteotypic peptides, that is, detectable unique
representatives of proteins of interest, is a key step in targeted
proteomics. To date, much effort has been made to understand the mechanisms
underlying peptide detection in liquid chromatography–tandem
mass spectrometry (LC-MS/MS) based shotgun proteomics and to predict
proteotypic peptides in the absence of experimental LC-MS/MS data.
However, the prediction accuracy of existing tools is still unsatisfactory.
We find that one crucial reason is their neglect of the significant
influence of protein proteolytic digestion on peptide detectability
in shotgun proteomics. Here, we present an Advanced Proteotypic Peptide
Predictor (AP3), which explicitly takes peptide digestibility into
account for the prediction of proteotypic peptides. Specifically,
peptide digestibility is first predicted for each peptide and then
incorporated as a feature into the peptide detectability prediction
model. Our results demonstrated that peptide digestibility is the
most important feature for the accurate prediction of proteotypic
peptides in our model. Compared with the existing available algorithms,
AP3 showed 10.3–34.7% higher prediction accuracy. On a targeted
proteomics data set, AP3 accurately predicted the proteotypic peptides
for proteins of interest, showing great potential for assisting the
design of targeted proteomics experiments.