This title appears in the Scientific Report :
2023
Please use the identifier:
http://dx.doi.org/10.34734/FZJ-2023-02416 in citations.
Please use the identifier: http://dx.doi.org/10.1039/D2SC06272K in citations.
Combining structural and coevolution information to unveil allosteric sites
Combining structural and coevolution information to unveil allosteric sites
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 i...
Saved in:
Personal Name(s): | La Sala, Giuseppina (Corresponding author) |
---|---|
Pfleger, Christopher / Käck, Helena / Wissler, Lisa / Nevin, Philip / Böhm, Kerstin / Janet, Jon Paul / Schimpl, Marianne / Stubbs, Christopher J. / De Vivo, Marco / Tyrchan, Christian / Hogner, Anders / Gohlke, Holger (Corresponding author) / Frolov, Andrey I. (Corresponding author) | |
Contributing Institute: |
Bioinformatik; IBG-4 Strukturbiochemie; IBI-7 Jülich Supercomputing Center; JSC John von Neumann - Institut für Computing; NIC |
Published in: | Chemical science, 14 (2023) 25, S. 7057-7067 |
Imprint: |
Cambridge
RSC
2023
|
DOI: |
10.34734/FZJ-2023-02416 |
DOI: |
10.1039/D2SC06272K |
Document Type: |
Journal Article |
Research Program: |
Forschergruppe Gohlke Biological and environmental resources for sustainable use Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1039/D2SC06272K in citations.
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. |