Format

Send to

Choose Destination

See 1 citation found by title matching your search:

Anal Chem. 2013 Jun 18;85(12):5666-75. doi: 10.1021/ac4006556. Epub 2013 May 24.

Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures.

Author information

1
Department of Chemistry, University of California, Davis, California 95616, USA.

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.

PMID:
23662732
PMCID:
PMC3692395
DOI:
10.1021/ac4006556
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for American Chemical Society Icon for PubMed Central
Loading ...
Support Center