Title : Automated assignments of N- and O-site specific glycosylation with
extensive glycan heterogeneity of
glycoprotein mixtures
Abstract :
- Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics
- Effective methods require new approaches in sample preparation, detection, and data analysis
- While the field has advanced in sample preparation and detection, automated data analysis remains an important goal
- A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides , including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS)
- SSG for multiple N- and O-glycosylation sites , including extensive glycan heterogeneity , was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA)
- The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles