Imperial College London
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ProfessorSophiaYaliraki

Faculty of Natural Sciences, Department of Chemistry

Professor of Theoretical Chemistry
 
 
 
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Contact

 

s.yaliraki

 
 
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Location

 

Molecular Sciences Research HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Wu:2022:10.1016/j.patter.2021.100408,
author = {Wu, N and Stromich, L and Yaliraki, SN},
doi = {10.1016/j.patter.2021.100408},
journal = {Patterns},
pages = {1--12},
title = {Prediction of allosteric sites and signalling: insights from benchmarking datasets},
url = {http://dx.doi.org/10.1016/j.patter.2021.100408},
volume = {3},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Wu,N
AU  - Stromich,L
AU  - Yaliraki,SN
DO  - 10.1016/j.patter.2021.100408
EP  - 12
PY  - 2022///
SN  - 2666-3899
SP  - 1
TI  - Prediction of allosteric sites and signalling: insights from benchmarking datasets
T2  - Patterns
UR  - http://dx.doi.org/10.1016/j.patter.2021.100408
UR  - https://www.sciencedirect.com/science/article/pii/S2666389921002828
UR  - http://hdl.handle.net/10044/1/93103
VL  - 3
ER  -
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