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.