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通过虚拟筛选和分子动力学模拟研究寻找严重急性呼吸综合征冠状病毒2(SARS-CoV-2)主蛋白酶(Mpro)的潜在抑制剂。

Finding potential inhibitors for Main protease (Mpro) of SARS-CoV-2 through virtual screening and MD simulation studies.

作者信息

Ahamed N Anis, Arif Ibrahim A

机构信息

Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.

出版信息

Saudi J Biol Sci. 2023 Dec;30(12):103845. doi: 10.1016/j.sjbs.2023.103845. Epub 2023 Oct 20.

Abstract

SARS-CoV-2 is a highly hazardous species that can infect people with Covid-19 disease, dramatically increasing mortality rates worldwide. Plenty of researches have been done to find drugs or inhibitors, with this study aiming to identify an inhibitor within the ChEMBL database using computational approaches. From the ChEMBL library, 19,43,048 compounds which are known type of small compounds and proteins were downloaded and docked with the Main protease (M). After performing compound screening using Lipinski's rule, Qikprop analysis following with virtual Screening, Induced Fit Docking (IFD) and MM-GBSA analysis with the Glide and Prime modules of Schrödinger, the best complex was subjected to MD simulation with Desmond. According to the docking results, small protein 2,371,668 and compound 1,090,395 were docked with Main protease with -12.6, -12.0 kcal/mol dock score and interacted with the functional site residues His 41 and Cys 145, as well as the binding site residues Thr 26, Phe 140, Asn 142, Gly 143, Glu 166, and Gln 189. Complex structures were shown to be steadier by the MD simulation study because both the ligands heavy atoms and the protein Cα atoms' RMSD values fell within acceptable ranges. As a result, this research suggests that the molecule CHEMBL2371668 and the compound CHEMBL1090395 may inhibit the activity of Main protease, and the usefulness of these molecules will be examined further through experimental research.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)是一种极具危险性的病毒,可导致新冠肺炎,极大地提高了全球死亡率。为寻找药物或抑制剂已开展了大量研究,本研究旨在通过计算方法在ChEMBL数据库中识别一种抑制剂。从ChEMBL库中下载了1943048种已知类型的小分子化合物和蛋白质,并与主要蛋白酶(M)进行对接。使用Lipinski规则进行化合物筛选,随后进行Qikprop分析以及虚拟筛选、诱导契合对接(IFD),并使用薛定谔的Glide和Prime模块进行MM-GBSA分析,对最佳复合物进行Desmond分子动力学(MD)模拟。根据对接结果,小分子2371668和化合物1090395与主要蛋白酶对接,对接分数分别为-12.6、-12.0千卡/摩尔,并与功能位点残基组氨酸41和半胱氨酸145以及结合位点残基苏氨酸26、苯丙氨酸140、天冬酰胺142、甘氨酸143、谷氨酸166和谷氨酰胺189相互作用。MD模拟研究表明复合物结构更稳定,因为配体重原子和蛋白质Cα原子的均方根偏差(RMSD)值均在可接受范围内。因此,本研究表明分子CHEMBL2371668和化合物CHEMBL1090395可能抑制主要蛋白酶的活性,这些分子的有效性将通过实验研究进一步检验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70c2/10663854/cf6418b50be1/gr1.jpg

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