Prediction of protein disorder based on IUPred

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30 Citations (Scopus)


Many proteins contain intrinsically disordered regions (IDRs), functional polypeptide segments that in isolation adopt a highly flexible conformational ensemble instead of a single, well-defined structure. Disorder prediction methods, which can discriminate ordered and disordered regions from the amino acid sequence, have contributed significantly to our current understanding of the distinct properties of intrinsically disordered proteins by enabling the characterization of individual examples as well as large-scale analyses of these protein regions. One popular method, IUPred provides a robust prediction of protein disorder based on an energy estimation approach that captures the fundamental difference between the biophysical properties of ordered and disordered regions. This paper reviews the energy estimation method underlying IUPred and the basic properties of the web server. Through an example, it also illustrates how the prediction output can be interpreted in a more complex case by taking into account the heterogeneous nature of IDRs. Various applications that benefited from IUPred to provide improved disorder predictions, complementing domain annotations and aiding the identification of functional short linear motifs are also described here. IUPred is freely available for noncommercial users through the web server ( and The program can also be downloaded and installed locally for large-scale analyses.

Original languageEnglish
Pages (from-to)331-340
Number of pages10
JournalProtein Science
Issue number1
Publication statusPublished - Jan 2018


  • globular domains
  • intrinsically disordered proteins
  • sequence-based prediction methods
  • short linear motifs
  • statistical potential

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

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