Computational Prediction of Protein O-GlcNAc Modification

Methods Mol Biol. 2018:1754:235-246. doi: 10.1007/978-1-4939-7717-8_14.

Abstract

Protein O-GlcNAcylation on serine and threonine residues is a significant posttranslational modification. Experimental techniques can uncover only a small portion of O-GlcNAcylation sites. Several computational algorithms have been proposed as necessary auxiliary tools to identify potential O-GlcNAcylation sites. This chapter discusses the metrics and procedures used to assess prediction tools and surveys six computational tools for the prediction of protein O-GlcNAcylation sites. Analyses of these tools using an independent test dataset indicated the advantages and disadvantages of the six existing prediction methods. We also discuss the challenges that may be faced while developing novel predictors in the future.

Keywords: Features; O-GlcNAcylation; Prediction; Sequence information.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acetylglucosamine / metabolism*
  • Algorithms*
  • Animals
  • Computational Biology / instrumentation
  • Computational Biology / methods*
  • Datasets as Topic
  • Glycosylation
  • Humans
  • N-Acetylglucosaminyltransferases / metabolism*
  • Protein Processing, Post-Translational*
  • Protein Structure, Secondary
  • Serine / metabolism
  • Threonine / metabolism

Substances

  • Threonine
  • Serine
  • N-Acetylglucosaminyltransferases
  • Acetylglucosamine