Issue 25, 2023

Combining structural and coevolution information to unveil allosteric sites

Abstract

Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.

Graphical abstract: Combining structural and coevolution information to unveil allosteric sites

Supplementary files

Article information

Article type
Edge Article
Submitted
14 Nov 2022
Accepted
02 Jun 2023
First published
08 Jun 2023
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2023,14, 7057-7067

Combining structural and coevolution information to unveil allosteric sites

G. La Sala, C. Pfleger, H. Käck, L. Wissler, P. Nevin, K. Böhm, J. P. Janet, M. Schimpl, C. J. Stubbs, M. De Vivo, C. Tyrchan, A. Hogner, H. Gohlke and A. I. Frolov, Chem. Sci., 2023, 14, 7057 DOI: 10.1039/D2SC06272K

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