Predicting Protein-Protein Interfaces that Bind Intrinsically Disordered Protein Regions.

Autor: Wong ETC; Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada., Gsponer J; Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada. Electronic address: gsponer@msl.ubc.ca.
Jazyk: angličtina
Zdroj: Journal of molecular biology [J Mol Biol] 2019 Aug 09; Vol. 431 (17), pp. 3157-3178. Date of Electronic Publication: 2019 Jun 15.
DOI: 10.1016/j.jmb.2019.06.010
Abstrakt: A long-standing goal in biology is the complete annotation of function and structure on all protein-protein interactions, a large fraction of which is mediated by intrinsically disordered protein regions (IDRs). However, knowledge derived from experimental structures of such protein complexes is disproportionately small due, in part, to challenges in studying interactions of IDRs. Here, we introduce IDRBind, a computational method that by combining gradient boosted trees and conditional random field models predicts binding sites of IDRs with performance approaching state-of-the-art globular interface predictions, making it suitable for proteome-wide applications. Although designed and trained with a focus on molecular recognition features, which are long interaction-mediating-elements in IDRs, IDRBind also predicts the binding sites of short peptides more accurately than existing specialized predictors. Consistent with IDRBind's specificity, a comparison of protein interface categories uncovered uniform trends in multiple physicochemical properties, positioning molecular recognition feature interfaces between peptide and globular interfaces.
(Copyright © 2019 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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