| Autor: |
Tee WV; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore., Lim SJM; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore., Berezovsky IN; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore.; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117579, Singapore. |
| Abstrakt: |
While the therapeutic potential of allosteric drugs is increasingly realized, the discovery of effectors is largely incidental. The rational design of allosteric effectors requires new state-of-the-art approaches to account for the distinct characteristics of allosteric ligands and their modes of action. We present a broadly applicable computational framework for obtaining allosteric site-effector pairs, providing targeted, highly specific, and tunable regulation to any functional site. We validated the framework using the main protease from SARS-CoV-2 and the K-Ras G12D oncoprotein. High-throughput per-residue quantification of the energetics of allosteric signaling and effector binding revealed known drugs capable of inducing the required modulation upon binding. Starting from fragments of known well-characterized drugs, allosteric effectors and binding sites were designed and optimized simultaneously to achieve targeted and specific signaling to distinct functional sites, such as, for example, the switch regions of K-Ras G12D . The generic framework proposed in this work will be instrumental in developing allosteric therapies aligned with a precision medicine approach. |
