Structure-based virtual screening and molecular dynamics simulation studies to discover new SARS-CoV-2 main protease inhibitors

基于结构的虚拟筛选和分子动力学模拟研究,旨在发现新的SARS-CoV-2主蛋白酶抑制剂

阅读:2

Abstract

Computational methods were used to filter two datasets (> 8,000 compounds) based on two criteria: higher binding affinity for M(PRO) than cocrystallized inhibitor and binding interactions with M(PRO) catalytic dyad (Cys145 and His41). After virtual screening involving ranking and reranking, eleven compounds were identified to satisfy these criteria and analysis of their structures revealed an unparallel common features among them which could be critical for their interactions with M(PRO). However, only the topmost scoring compound (AV-203: K (i) = 0.31 µM) exhibited relatively stable binding interaction during the period of 50 ns MD simulation and thus is a suitable template for drug development.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。