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Prediction of allosteric sites and signalling: insights from benchmarking datasets

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Title: Prediction of allosteric sites and signalling: insights from benchmarking datasets
Authors: Wu, N
Stromich, L
Yaliraki, SN
Item Type: Journal Article
Abstract: Allostery is a pervasive mechanism that regulates protein activity through ligand binding at a site different from the orthosteric site. The universality of allosteric regulation complemented by the benefits of highly specific and potentially non-toxic allosteric drugs makes uncovering allosteric sites invaluable. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis has successfully predicted allosteric sites in 19 of 20 cases using an energy-weighted atomistic graph. We here extended the analysis onto 432 structures of 146 proteins from two benchmarking datasets for allosteric proteins: ASBench and CASBench. We further introduced two statistical measures to account for the cumulative effect of high-propensity residues and the crucial residues in a given site. The allosteric site is recovered for 127 of 146 proteins (407 of 432 structures) knowing only the orthosteric sites or ligands. The quantitative analysis using a range of statistical measures enables better characterization of potential allosteric sites and mechanisms involved.
Issue Date: 14-Jan-2022
Date of Acceptance: 15-Nov-2021
URI: http://hdl.handle.net/10044/1/93103
DOI: 10.1016/j.patter.2021.100408
ISSN: 2666-3899
Publisher: Cell Press
Start Page: 1
End Page: 12
Journal / Book Title: Patterns
Volume: 3
Issue: 1
Copyright Statement: © 2021 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/N014529/1
Publication Status: Published
Online Publication Date: 2021-12-09
Appears in Collections:Chemistry
Biological and Biophysical Chemistry
Faculty of Natural Sciences

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