Ensemble docking based virtual screening of SARS-CoV-2 main protease inhibitors.

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL Molecular Informatics Pub Date : 2024-08-01 Epub Date: 2024-07-08 DOI:10.1002/minf.202300279
Anastasia D Fomina, Victoria I Uvarova, Liubov I Kozlovskaya, Vladimir A Palyulin, Dmitry I Osolodkin, Aydar A Ishmukhametov
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Abstract

During the first years of COVID-19 pandemic, X-ray structures of the coronavirus drug targets were acquired at an unprecedented rate, giving hundreds of PDB depositions in less than a year. The main protease (Mpro) of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) is the primary validated target of direct-acting antivirals. The selection of the optimal ensemble of structures of Mpro for the docking-driven virtual screening campaign was thus non-trivial and required a systematic and automated approach. Here we report a semi-automated active site RMSD based procedure of ensemble selection from the SARS-CoV-2 Mpro crystallographic data and virtual screening of its inhibitors. The procedure was compared with other approaches to ensemble selection and validated with the help of hand-picked and peer-reviewed activity-annotated libraries. Prospective virtual screening of non-covalent Mpro inhibitors resulted in a new chemotype of thienopyrimidinone derivatives with experimentally confirmed enzyme inhibition.

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基于组合对接的 SARS-CoV-2 主要蛋白酶抑制剂虚拟筛选。
在 COVID-19 大流行的最初几年,冠状病毒药物靶点的 X 射线结构以前所未有的速度获得,在不到一年的时间里就有数百个 PDB 文件沉积。严重急性呼吸系统综合征相关冠状病毒 2(SARS-CoV-2)的主要蛋白酶(Mpro)是直接作用抗病毒药物的主要验证靶点。因此,为对接驱动的虚拟筛选活动选择最佳的 Mpro 结构组合并非易事,需要一种系统的自动化方法。在此,我们报告了一种基于活性位点 RMSD 的半自动程序,该程序从 SARS-CoV-2 Mpro 晶体数据中选择组合结构,并对其抑制剂进行虚拟筛选。我们将该程序与其他组合筛选方法进行了比较,并在人工挑选和同行评议的活性注释库的帮助下进行了验证。对非共价 Mpro 抑制剂的前瞻性虚拟筛选产生了一种新的噻吩嘧啶酮衍生物化学类型,其酶抑制作用已得到实验证实。
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来源期刊
Molecular Informatics
Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.30
自引率
2.80%
发文量
70
审稿时长
3 months
期刊介绍: Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.
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