Program

Oral Sessions

Day 4, May 18（Fri.）　12:20-12:40　Room A (OrBit Hall)

4A-L-P-1220　　PDF

High Efficient and Precise Glycoproteomic Analysis with Intelligent Technology

(¹Fudan IBS, ²CAS Computing Tech)
^oPengyuan Yang¹, Weiqian Cao¹, Mingqi Liu¹, Wenfeng Zeng², Chao Liu², Pan Fang¹, Huali Shen¹, Simin He²

Protein glycosylation is a heterogeneous post-translational modification that generates great proteomic diversity and gives rise to functional variance. High efficient and precise characterization of protein glycosylation at site-specific level and the proteome scale is critical for understanding the biological functions. To achieve this goal, we propose a series of identification strategies and searching engines: pGlyco1.0, pGlcyo2.0 and pGlyco3.0. pGlyco1.0 is a pipeline for the identification of intact glycopeptides by integrating HCD-MS/MS, CID-MS/MS and MS3, and using a novel target-decoy method to estimate the false discovery rate of the glycan identification. pGlyco2.0 is a one-step tandem MS strategy for intact glycopeptide identification with optimized stepped-energy fragmentation and a dedicated search engine. With pGlyco2.0, intact glycopeptides could be identified at proteome scale and with comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides. In pGlyco3.0, a database-free algorithm was developed for universal glycoproteome analysis without user-defined glycan composition list or glycan structure database. A large-scale N-glycoproteome dataset containing more than 50,000 unique N-glycopeptides was established with these strategies. We are moving towards to universal O-glycoproteome analysis.