Computational prediction of intrinsic disorder in protein sequences with the disCoP meta-predictor

Christopher J. Oldfield, Xiao Fan, Chen Wang, A. Keith Dunker, Lukasz Kurgan

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Intrinsically disordered proteins are either entirely disordered or contain disordered regions in their native state. These proteins and regions function without the prerequisite of a stable structure and were found to be abundant across all kingdoms of life. Experimental annotation of disorder lags behind the rapidly growing number of sequenced proteins, motivating the development of computational methods that predict disorder in protein sequences. DisCoP is a user-friendly webserver that provides accurate sequence-based prediction of protein disorder. It relies on meta-architecture in which the outputs generated by multiple disorder predictors are combined together to improve predictive performance. The architecture of disCoP is presented, and its accuracy relative to several other disorder predictors is briefly discussed. We describe usage of the web interface and explain how to access and read results generated by this computational tool. We also provide an example of prediction results and interpretation. The disCoP’s webserver is publicly available at http://biomine.cs.vcu.edu/servers/disCoP/.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages21-35
Number of pages15
DOIs
StatePublished - 2020

Publication series

NameMethods in Molecular Biology
Volume2141
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Bioinformatics
  • IDP
  • Intrinsically disordered proteins
  • Meta-architecture
  • Webserver

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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