Literature DB >> 17727280

Automated N-glycopeptide identification using a combination of single- and tandem-MS.

David Goldberg1, Marshall Bern, Simon Parry, Mark Sutton-Smith, Maria Panico, Howard R Morris, Anne Dell.   

Abstract

We describe Peptoonist, a program that can automatically identify the glycans (sugars) present at each N-glycosylation site of a protein. The input to Peptoonist is a series of mass spectra, both MS and MS/MS, obtained from a liquid chromatography (LC) run of proteolytically digested purified glycoproteins. The program uses MS/MS to identify glycosylated peptides and single-MS to identify the N-glycans present on each of these peptides, at least to the level of monosaccharide composition. We validate the program on an LC run of mouse zona pellucida proteins that had been intensively hand annotated by a human expert. Our program doubled the number of glycopeptide identifications, and also found several possible errors in the hand annotation. In addition, it automatically made most of the same glycan isomer identifications as the expert annotator.

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Year:  2007        PMID: 17727280     DOI: 10.1021/pr070239f

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  35 in total

1.  Photo-lysine captures proteins that bind lysine post-translational modifications.

Authors:  Tangpo Yang; Xiao-Meng Li; Xiucong Bao; Yi Man Eva Fung; Xiang David Li
Journal:  Nat Chem Biol       Date:  2015-12-21       Impact factor: 15.040

Review 2.  Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data.

Authors:  Gang Liu; Sriram Neelamegham
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2015-04-13

3.  Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages.

Authors:  R Zhu; L Zacharias; K M Wooding; W Peng; Y Mechref
Journal:  Methods Enzymol       Date:  2017-01-16       Impact factor: 1.600

Review 4.  Automated glycopeptide analysis--review of current state and future directions.

Authors:  David C Dallas; William F Martin; Serenus Hua; J Bruce German
Journal:  Brief Bioinform       Date:  2012-07-27       Impact factor: 11.622

Review 5.  High-sensitivity analytical approaches for the structural characterization of glycoproteins.

Authors:  William R Alley; Benjamin F Mann; Milos V Novotny
Journal:  Chem Rev       Date:  2013-03-27       Impact factor: 60.622

6.  A classifier based on accurate mass measurements to aid large scale, unbiased glycoproteomics.

Authors:  John W Froehlich; Eric D Dodds; Mathias Wilhelm; Oliver Serang; Judith A Steen; Richard S Lee
Journal:  Mol Cell Proteomics       Date:  2013-02-25       Impact factor: 5.911

Review 7.  Global and site-specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry.

Authors:  Haopeng Xiao; Fangxu Sun; Suttipong Suttapitugsakul; Ronghu Wu
Journal:  Mass Spectrom Rev       Date:  2019-01-03       Impact factor: 10.946

Review 8.  Sweetening the pot: adding glycosylation to the biomarker discovery equation.

Authors:  Penelope M Drake; Wonryeon Cho; Bensheng Li; Akraporn Prakobphol; Eric Johansen; N Leigh Anderson; Fred E Regnier; Bradford W Gibson; Susan J Fisher
Journal:  Clin Chem       Date:  2009-12-03       Impact factor: 8.327

Review 9.  A review of methods for interpretation of glycopeptide tandem mass spectral data.

Authors:  Han Hu; Kshitij Khatri; Joshua Klein; Nancy Leymarie; Joseph Zaia
Journal:  Glycoconj J       Date:  2015-11-26       Impact factor: 2.916

Review 10.  Bioinformatics and molecular modeling in glycobiology.

Authors:  Martin Frank; Siegfried Schloissnig
Journal:  Cell Mol Life Sci       Date:  2010-04-04       Impact factor: 9.261

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