TY  - JOUR
AU  - La Sala, Giuseppina
AU  - Pfleger, Christopher
AU  - Käck, Helena
AU  - Wissler, Lisa
AU  - Nevin, Philip
AU  - Böhm, Kerstin
AU  - Janet, Jon Paul
AU  - Schimpl, Marianne
AU  - Stubbs, Christopher J.
AU  - De Vivo, Marco
AU  - Tyrchan, Christian
AU  - Hogner, Anders
AU  - Gohlke, Holger
AU  - Frolov, Andrey I.
TI  - Combining structural and coevolution information to unveil allosteric sites
JO  - Chemical science
VL  - 14
IS  - 25
SN  - 2041-6520
CY  - Cambridge
PB  - RSC
M1  - FZJ-2023-02416
SP  - 7057-7067 
PY  - 2023
N1  - This is an open access publication.
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - 37389247
UR  - <Go to ISI:>//WOS:001004486700001
DO  - DOI:10.1039/D2SC06272K
UR  - https://juser.fz-juelich.de/record/1008583
ER  -