Rapid identification of multi-PTMs peptide sequence tags with a graph search approach

Abstract

Identifying post-translational modifications (PTMs) is a big challenge for proteomics. Mass spectrometry is a popular tool for the identification of peptide sequence. Here we present a method for rapid identification of PTMs by mass spectrometry based on graph theory. The approach takes advantage of several possibility pair's values of corresponding Tandem Mass Spectrometry (MS/MS), and uses score function to screen candidate peptide sequences. We proposed the Pair Peak of Set (PPS) and used the most possibility mass of PPS as the root of graph tree, the rest ones are viewed as the reference node of graph. Our experiment on 2620 experimental MS/MS with two PTMs shows that our approach achieves better accuracy than PepNovo approaches with higher efficiency and it could deal with low quality PTMs data.