Affordable Access

deepdyve-link
Publisher Website

ISOGlyP: de novo prediction of isoform-specific mucin-type O-glycosylation.

Authors
  • Mohl, Jonathon E1
  • Gerken, Thomas A2
  • Leung, Ming-Ying1
  • 1 Department of Mathematical Sciences and Border Biomedical Research Center, The University of Texas at El Paso, W University, El Paso, TX 79968, USA.
  • 2 Departments of Biochemistry and Chemistry, Case Western Reserve University, Cleveland, OH 44106, USA.
Type
Published Article
Journal
Glycobiology
Publisher
Oxford University Press
Publication Date
Apr 01, 2021
Volume
31
Issue
3
Pages
168–172
Identifiers
DOI: 10.1093/glycob/cwaa067
PMID: 32681163
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Mucin-type O-glycosylation is one of the most common posttranslational modifications of proteins. The abnormal expression of various polypeptide GalNAc-transferases (GalNAc-Ts) which initiate and define sites of O-glycosylation are linked to many cancers and other diseases. Current O-glycosyation prediction programs utilize O-glycoproteomics data obtained without regard to the transferase isoform (s) responsible for the glycosylation. With 20 different GalNAc-Ts in humans, having an ability to predict and interpret O-glycosylation sites in terms of specific GalNAc-T isoforms is invaluable. To fill this gap, ISOGlyP (Isoform-Specific O-Glycosylation Prediction) has been developed. Using position-specific enhancement values generated based on GalNAc-T isoform-specific amino acid preferences, ISOGlyP predicts the propensity that a site would be glycosylated by a specific transferase. ISOGlyP gave an overall prediction accuracy of 70% against in vivo data, which is comparable to that of the NetOGlyc4.0 predictor. Additionally, ISOGlyP can identify the known effects of long- and short-range prior glycosylation and can generate potential peptide sequences selectively glycosylated by specific isoforms. ISOGlyP is freely available for use at ISOGlyP.utep.edu. The code is also available on GitHub (https://github.com/jonmohl/ISOGlyP). © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]

Report this publication

Statistics

Seen <100 times