A multi-edge graph based de novo peptide sequencing method for HCD spectra

Abstract

In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra (MS/MS spectra). Here, we present a new spectrum graph model with multiple types of edges (called a multi-edge graph), and integrate amino acid combination (AAC) information and peptide tags into it for peptide sequencing. In addition, the information about immoniun ions observed particularly in higher-energy collisional dissociation (HCD) spectra are incorporated. Comparisons between the proposed method and another successful de novo peptide sequencing method for HCD spectra, pNovo, were performed. Experiments were conducted on four HCD spectral datasets. Results show that the proposed method outperforms pNovo in terms of full length peptide identification accuracy; specifically, the accuracy increases 7%-13% over all four datasets.