GlypPRM: An Automated Analyzer and Quantification Tool for Glycopeptides Parallel Reaction Monitoring

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 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 supports compositional glycan structure modeling for theoretical fragment ion generation, spectral matching, chromatographic integration, and quantitative analysis for both N- and O-glycopeptides. We validated its performance using glycopeptides derived from bovine fetuin and human serum samples, demonstrating high structural accuracy, reproducibility, and interpretability. GlypPRM also includes advanced visualization, flexible input handling, ion filtering, and publication-ready export formats. This scalable, glycan- and peptide-aware platform establishes a strong foundation for high-confidence PRM-based glycoproteomics in biomarker discovery and disease research.