9HJH

Structure of compound 1 bound to SARS-CoV-2 main protease

これはPDB形式変換不可エントリーです。

9HJH の概要

• エントリーDOI: 10.2210/pdb9hjh/pdb
• 分子名称: 3C-like proteinase nsp5, (2~{R})-4-[(4-bromanyl-2-ethyl-phenyl)methyl]-1-(5-chloranylpyridin-3-yl)carbonyl-~{N}-ethyl-1,4-diazepane-2-carboxamide, 1,2-ETHANEDIOL, ... (6 entities in total)
• 機能のキーワード: inhibitor, docking, hydrolase
• 由来する生物種: Severe acute respiratory syndrome coronavirus 2
• タンパク質・核酸の鎖数: 2
• 化学式量合計: 69177.77

構造登録者

Mac Sweeney, A.,Hazemann, J. (登録日: 2024-11-29, 公開日: 2024-12-11, 最終更新日: 2025-05-07)

主引用文献

Hazemann, J.,Kimmerlin, T.,Mac Sweeney, A.,Bourquin, G.,Lange, R.,Ritz, D.,Richard-Bildstein, S.,Regeon, S.,Czodrowski, P.
Accelerating the Hit-To-Lead Optimization of a SARS-CoV-2 Mpro Inhibitor Series by Combining High-Throughput Medicinal Chemistry and Computational Simulations.
J.Med.Chem., 68:8269-8294, 2025

PubMed 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 learning, molecular docking, and molecular dynamics simulation with HTMC can efficiently accelerate hit identification and subsequent lead generation.

PubMed: 40186586
DOI: 10.1021/acs.jmedchem.4c02941

実験手法

X-RAY DIFFRACTION (1.2 Å)