Format

Send to

Choose Destination
See comment in PubMed Commons below
Brief Bioinform. 2013 May;14(3):361-74. doi: 10.1093/bib/bbs045. Epub 2012 Jul 27.

Automated glycopeptide analysis--review of current state and future directions.

Author information

1
University of California, Davis, Davis, CA 95616, USA.

Abstract

Glycosylation of proteins is involved in immune defense, cell-cell adhesion, cellular recognition and pathogen binding and is one of the most common and complex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins-glycoproteomics-remains in its infancy due to the scarcity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for complex biological mixtures. Glycopeptide composition and structure can be determined with high mass-accuracy mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review discusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoproteomics. However, there is currently no freely available software that can analyze spectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoproteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpret mass spectral data from a variety of sources and (iv) are open source and freely available.

KEYWORDS:

N-linked; O-linked; bioinformatics; glycopeptide; glycopeptidomics; glycoproteomics

PMID:
22843980
PMCID:
PMC3659302
DOI:
10.1093/bib/bbs045
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Silverchair Information Systems Icon for PubMed Central
    Loading ...
    Support Center