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Protein Glycosylation

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Bioinformatics Resources for the Study of Glycan-Mediated Protein Interactions

Bioinformatics Resources for the Study of Glycan-Mediated Protein Interactions

Published on: January 20, 2022

Comparative analysis of glycoproteomic software using a tailored glycan database.

Reuben A Hogan¹, Lauren E Pepi², Nicholas M Riley³

¹University of California, San Francisco, San Francisco, CA, USA. reuben.hogan@ucsf.edu.

Analytical and Bioanalytical Chemistry

|March 18, 2025

Summary

Comparing glycoproteomics software is crucial for accurate analysis. No single tool excelled, but using multiple software, excluding Byonic, provides reliable results through consensus.

Keywords:

Comparison Glycoproteomic software Glycoproteomics

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Area of Science:

Glycoscience
Proteomics
Bioinformatics

Background:

Glycoproteomics is rapidly advancing, driven by technological innovations.
Numerous software tools exist for glycoproteomic data analysis, making comparison challenging.
Standardized comparison of these tools is needed to guide researchers.

Purpose of the Study:

To conduct a head-to-head comparison of five modern glycoproteomic analysis software packages.
To evaluate software performance using matched glycan databases derived from sample glycomic profiling.
To identify the most reliable software for glycopeptide spectrum identification and analysis.

Main Methods:

Compared Byonic, Protein Prospector, MSFraggerGlyco, pGlyco3, and GlycoDecipher.
Minimized parameter variables and constructed matched glycan databases for each software.
Analyzed glycopeptide spectra from three replicates of wild-type SH-SY5Y cells, identifying up to 17,000 spectra per software.

Main Results:

Significant overlap was observed across software for identified glycoproteins, glycosite locations, and glycans.
No single software demonstrated superior performance across all criteria.
Evidence suggests Byonic may report spurious results at glycoprotein and glycosite levels.

Conclusions:

Assessing glycoproteomic software requires multiple comparative criteria beyond just the number of spectra identified.
Glycoproteomic data analysis should involve consensus from multiple software tools, excluding the current version of Byonic, for increased confidence.
Future research could explore combining peptide-first and glycan-first analytical approaches.