GPMAW Glyco-Search: An Integrated Workflow for Identification and Validation of Intact Sialylated N-Glycopeptides

Comprehensive analysis of intact sialylated N-glycopeptides remains challenging because of their low abundance, extensive structural heterogeneity, and limited peptide backbone fragmentation during tandem mass spectrometry. Here, we present an integrated workflow for high-confidence identification of intact sialylated N-glycopeptides that combines selective TiO₂ enrichment, dual LC-MS/MS analysis of intact and deglycosylated glycopeptides, and the GPMAW glyco-search platform based on high-accuracy mass mapping. Unlike most conventional glycoproteomics search engines, GPMAW uses experimentally identified deglycopeptides to constrain glycan assignment before matching intact glycopeptide precursor masses to candidate glycan compositions. Identifications were validated using diagnostic oxonium ions, glycopeptide-associated Y-ion fragments, and an experimentally derived glycopeptide score. In addition, GPMAW integrates an interactive spectrum annotation interface that enables rapid manual validation of candidate identifications through visualization of annotated Y-ion series, oxonium ions, and peptide fragments, allowing individual assignments to be readily accepted or rejected.

The workflow was optimized using bovine fetuin, validated on standard glycoproteins, and applied to depleted human plasma, where more than 2800 unique intact sialylated N-glycopeptides were identified across hundreds of glycosites and glycoproteins. Moreover, more than 1000 unique N-glycopeptides were identified from only 1 μL of plasma. Comparative analysis demonstrated that GPMAW glyco-search identified more confidently assigned intact sialylated N-glycopeptides than three widely used N-glycoproteomics search engines while maintaining high reproducibility and low false-positive rates following manual validation. Together, this workflow provides a robust, flexible, and accessible platform for large-scale, high-confidence characterization of intact N-glycopeptides and establishes experimentally constrained glycan composition assignment combined with interactive spectrum validation as an effective strategy for reducing ambiguity in N-glycoproteomics.