Accelerating the Hit-To-Lead Optimization of a SARS-CoV-2 Mpro Inhibitor Series by Combining High-Throughput Medicinal Chemistry and Computational Simulations.

ABSTRACT: In this study, we performed the hit-to-lead optimization of a SARS-CoV-2 Mpro diazepane hit (identified by computational methods in a previous work) by combining computational simulations with high-throughput medicinal chemistry (HTMC). Leveraging the 3D structural information of Mpro, we refined the original hit by targeting the S1 and S2 binding pockets of the protein. Additionally, we identified a novel exit vector pointing toward the S1' pocket, which significantly enhanced the binding affinity. This strategy enabled us to transform, rapidly with a limited number of compounds synthesized, a 14 μM hit into a potent 16 nM lead compound, for which key pharmacological properties were subsequently evaluated. This result demonstrated that combining computational technologies such as machine

SUBMITTER: Hazemann J 

PROVIDER: S-EPMC12035803 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature