A computational approach for the identification of site-specific protein glycosylations through ion-trap mass spectrometry

  • Authors:

  • Yin Wu;Yehia Mechref;Iveta Klouckova;Milos V. Novotny;Haixu Tang

  • Affiliations:

  • Department of Computer Science and National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, IN;Department of Chemistry and National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, IN;Department of Chemistry, Indiana University, Bloomington, IN;Department of Chemistry and National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, IN;School of Informatics and Center for Genomics and Bioinformatics and National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, IN

  • Venue:
  • RECOMB'06 Proceedings of the joint 2006 satellite conference on Systems biology and computational proteomics
  • Year:
  • 2006

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Abstract

Glycosylation is one of the most common post-translational modifications (PTMs) of proteins, the characterization of which is commonly achieved utilizing mass spectrometry (MS). However, its applicability is currently limited by the lack of computational tools capable of autmoated interpretation of high throughput MS experiments which would allow the characterization of glycosylation sites and their microheterogeneities. We present here a computational approach which overcomes this problem and allows the identification and assignment of the microheterogeneities of glycosylation sites of glycoproteins from liquid chromatography ion-trap-based mass spectrometry (LC/MS) data. This method was implemented in a software tool and tested on several model glycoproteins. The results demonstrate the potential of our computational approach in automating the high throughput identification of glycoproteins.