期刊
BRIEFINGS IN BIOINFORMATICS
卷 11, 期 2, 页码 225-243出版社
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbp061
关键词
protein disorder; coupled folding and binding; machine-learning algorithm; prediction method; binary classification
资金
- Hungarian Scientific Research Fund (OTKA) [K 72569]
- National Office for Research and Technology (NKTH) [NKTH07a-TB-INTER]
Intrinsically disordered/unstructured proteins exist without a stable three-dimensional (3D) structure as highly flexible conformational ensembles. The available genome sequences revealed that these proteins are surprisingly common and their frequency reaches high proportions in eukaryotes. Due to their vital role in various biological processes including signaling and regulation and their involvement in various diseases, disordered proteins and protein segments are the focus of many biochemical, molecular biological, pathological and pharmaceutical studies. These proteins are difficult to study experimentally because of the lack of unique structure in the isolated form. Their amino acid sequence, however, is available, and can be used for their identification and characterization by bioinformatic tools, analogously to globular proteins. In this review, we first present a small survey of current methods to identify disordered proteins or protein segments, focusing on those that are publicly available as web servers. In more detail we also discuss approaches that predict disordered regions and specific regions involved in protein binding by modeling the physical background of protein disorder. In our review we argue that the heterogeneity of disordered segments needs to be taken into account for a better understanding of protein disorder.
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