Introduction

Glycosylation is one of the most common post-translational modifications in proteins, existing in ~50% of mammalian proteins. Several research groups have demonstrated that mass spectrometry is an efficient technique for glycopeptide identification; however, this problem is still challenging because of the enormous diversity of glycan structures and the microheterogeneity of glycans. In addition, a glycopeptide may contain multiple glycosylation sites, making the problem complex. Current software tools often fail to identify glycopeptides with multiple glycosylation sites, and hence we present GlycoMID, a graph-based spectral alignment algorithm that can identify glycopeptides with multiple hydroxylysine O-glycosylation sites by tandem mass spectra. GlycoMID was tested on mass spectrometry data sets of the bovine collagen α-(II) chain protein, and experimental results showed that it identified more glycopeptide-spectrum matches than other existing tools, including many glycopeptides with two glycosylation sites.

Publications

  1. Identification of Glycopeptides with Multiple Hydroxylysine O-Glycosylation Sites by Tandem Mass Spectrometry.
    Cite this
    Zhang Y, Yu CY, Song E, Li SC, Mechref Y, Tang H, Liu X, 2015-12-01 - Journal of proteome research

Credits

  1. Yanlin Zhang
    Developer

    Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, United States of America

  2. Chuan-Yih Yu
    Developer

    School of Informatics and Computing, Indiana University Bloomington, United States of America

  3. Ehwang Song
    Developer

    Department of Chemistry and Biochemistry, Texas Tech University, United States of America

  4. Shuai Cheng Li
    Developer

    Department of Computer Science, City University of Hong Kong, Hong Kong

  5. Yehia Mechref
    Developer

    Department of Chemistry and Biochemistry, Texas Tech University, United States of America

  6. Haixu Tang
    Developer

    School of Informatics and Computing, Indiana University Bloomington, United States of America

  7. Xiaowen Liu
    Investigator

    Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, United States of America

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Summary
AccessionBT000184
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByXiaowen Liu