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Data from: GlypPRM: An automated analyzer and quantification tool for glycopeptides parallel reaction monitoring

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Apr 28, 2026 version files 4.38 GB

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Abstract

Glycosylation is a prevalent and structurally complex post-translational modification implicated in diverse biological processes and diseases. Mass spectrometry (MS)-based glycoproteomics, especially Parallel Reaction Monitoring (PRM), offers high specificity and quantitative power for glycopeptide analysis. PRM enables full MS/MS acquisition for targeted precursors, enhancing signal-to-noise ratios and structural confidence, key advantages over conventional targeted methods. However, the identification and quantification of glycopeptides from PRM data remain challenging due to extensive glycan heterogeneity, site multiplicity, and complex fragmentation patterns. Existing software platforms often lack tailored support for glycopeptide-specific fragmentation logic, glycan structure modeling, or automated spectral interpretation, leaving much of PRM-based glycoproteomics reliant on manual workflows. To address these limitations, we developed GlypPRM, a Python-based, fully integrated platform for automated glycopeptide PRM data analysis. GlypPRM features theoretical fragment ion simulation, glycan structure prediction, spectral matching, chromatographic integration, and quantitative analysis for both N- and O-glycopeptides. We validated its performance using glycopeptides derived from bovine fetuin and complex human serum samples, demonstrating high structural accuracy, reproducibility, and interpretability. GlypPRM also includes advanced visualization, flexible input handling, diagnostic ion filtering, and publication-ready export formats. This scalable, glycan- and peptide-aware platform establishes a robust foundation for high-confidence PRM-based glycoproteomics in biomarker discovery and disease research.