N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search

• Main Authors: Zhiwu An, Qingbo Shu, Hao Lv, Lian Shu, Jifeng Wang, Fuquan Yang, Yan Fu
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2018/1564136

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.