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

Author:

Mohl Jonathon E1ORCID,Gerken Thomas A2,Leung Ming-Ying1

Affiliation:

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

Abstract

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).

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Biochemistry

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