Identification of amentoflavone as a potent SARS-CoV-2 Mpro inhibitor: a combination of computational studies and in vitro biological evaluation.

IF 2.7 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Prabuddha Bhattacharya, Anirban Mandal
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引用次数: 0

Abstract

Small-molecule inhibitors of SARS-CoV-2 Mpro that block the active site pocket of the viral main protease have been considered potential therapeutics for the development of drugs against SARS-CoV-2. Here, we report the identification of amentoflavone (a biflavonoid) through docking-based virtual screening of a library comprised of 231 compounds consisting of flavonoids and isoflavonoids. The docking results were further substantiated through extensive analysis of the data obtained from all-atom 150 ns MD simulation. End-state effective free energy calculations using MM-PBSA calculations further suggested that (Ra)-amentoflavone (C3'-C8''-atropisomer) may show a greater binding affinity towards the Mpro than (Sa)-amentoflavone. In vitro cytotoxicity assay established that amentoflavone showed a high CC50 value indicating much lower toxicity. Further, potent inhibition of the Mpro by amentoflavone was established by studying the effect on HEK293T cells treated with SARS-CoV-2 Mpro expressing plasmid.

鉴定作为 SARS-CoV-2 Mpro 有效抑制剂的门黄酮:计算研究与体外生物评估的结合。
阻断病毒主蛋白酶活性位点口袋的 SARS-CoV-2 Mpro 小分子抑制剂被认为是开发抗 SARS-CoV-2 药物的潜在疗法。在此,我们报告了通过对由 231 种黄酮类和异黄酮类化合物组成的化合物库进行基于对接的虚拟筛选,鉴定出了一种门黄酮(一种双黄酮类化合物)。通过对全原子 150 ns MD 模拟获得的数据进行广泛分析,进一步证实了对接结果。利用 MM-PBSA 计算方法进行的终态有效自由能计算进一步表明,(Ra)-金黄酮(C3'-C8''-异构体)可能比(Sa)-金黄酮对 Mpro 表现出更大的结合亲和力。体外细胞毒性试验表明,金刚烷黄酮的 CC50 值很高,表明其毒性更低。此外,通过研究对用 SARS-CoV-2 Mpro 表达质粒处理的 HEK293T 细胞的影响,确定了金门黄酮对 Mpro 的强效抑制作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biomolecular Structure & Dynamics
Journal of Biomolecular Structure & Dynamics 生物-生化与分子生物学
CiteScore
8.90
自引率
9.10%
发文量
597
审稿时长
2 months
期刊介绍: The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.
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