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靶向严重急性呼吸综合征冠状病毒2主蛋白酶:一种药效团和分子建模方法。

Targeting SARS-CoV-2 main protease: a pharmacophore and molecular modeling approach.

作者信息

Darai Nitchakan, Pojtanadithee Piyatida, Sanachai Kamonpan, Langer Thierry, Wolschann Peter, Rungrotmongkol Thanyada

机构信息

Center of Excellence in Biocatalyst and Sustainable Biotechnology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.

Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.

出版信息

J Mol Model. 2025 Jul 29;31(8):222. doi: 10.1007/s00894-025-06441-5.

Abstract

CONTEXT

The COVID-19 pandemic, driven by SARS-CoV-2, has had a profound impact on global health, with severe respiratory complications being a primary concern. The main protease (Mpro) of SARS-CoV-2 plays a critical role in viral replication, making it an attractive target for therapeutic intervention. This study aimed to identify potential Mpro inhibitors using an integrated computational approach. From an initial pool of 89,200 compounds in the ChemDiv database, a systematic screening process reduced the candidates to 735 through drug-like property predictions and pharmacophore-based virtual screening. Molecular docking against four co-crystal structures of the inhibitor/Mpro complex, followed by molecular dynamics (MD) simulations and binding free energy calculations, identified E912-0363 and G740-1003 as promising candidates with binding affinities comparable to nirmatrelvir. Extended 500-ns MD simulations further established E912-0363 as a highly promising Mpro inhibitor, supporting its potential for therapeutic development as a complementary or alternative treatment to nirmatrelvir.

METHODS

Pharmacophore modeling and virtual screening were conducted using the ChemDiv database, reducing 89,200 compounds to 735 candidates based on drug-like property predictions. Molecular docking was performed against four SARS-CoV-2 Mpro co-crystal structures using AutoDock VinaXB and GOLD docking programs. The top five candidates (E912-0363, P635-0261, G740-1003, G069-0804, and 8602-0428) were subjected to 100-ns molecular dynamics (MD) simulations using the AMBER force field. Binding free energy calculations were performed using the MM/GBSA method. Extended 500-ns MD simulations were carried out for the most promising candidate, E912-0363, to evaluate its long-term stability and interaction with the Mpro binding site.

摘要

背景

由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引发的2019冠状病毒病疫情对全球健康产生了深远影响,严重的呼吸道并发症是主要关注点。SARS-CoV-2的主要蛋白酶(Mpro)在病毒复制中起关键作用,使其成为治疗干预的一个有吸引力的靶点。本研究旨在使用综合计算方法鉴定潜在的Mpro抑制剂。从ChemDiv数据库中的89200种化合物初始库开始,通过类药性质预测和基于药效团的虚拟筛选,系统筛选过程将候选物减少到735种。针对抑制剂/Mpro复合物的四种共晶体结构进行分子对接,随后进行分子动力学(MD)模拟和结合自由能计算,确定E912-0363和G740-1003为有前景的候选物,其结合亲和力与奈玛特韦相当。延长至500纳秒的MD模拟进一步确定E912-0363为极具前景的Mpro抑制剂,支持其作为奈玛特韦的补充或替代治疗进行治疗开发的潜力。

方法

使用ChemDiv数据库进行药效团建模和虚拟筛选,基于类药性质预测将89200种化合物减少到735种候选物。使用AutoDock VinaXB和GOLD对接程序针对四种SARS-CoV-2 Mpro共晶体结构进行分子对接。前五个候选物(E912-0363、P635-0261、G740-1003、G069-0804和8602-0428)使用AMBER力场进行100纳秒的分子动力学(MD)模拟。使用MM/GBSA方法进行结合自由能计算。对最有前景的候选物E912-0363进行延长至500纳秒的MD模拟,以评估其长期稳定性及其与Mpro结合位点的相互作用。

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