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针对 COVID-19 的合成蛋白酶抑制剂的分子对接和模拟研究:一项计算研究。

Molecular docking and simulation studies of synthetic protease inhibitors against COVID-19: a computational study.

机构信息

Medical Biochemistry Department, Medical Research Division, National Research Centre, Cairo, Egypt.

Chemistry of Natural and Microbial Products, Pharmaceutical Industry Research Division, National Research Center, Cairo, Egypt.

出版信息

J Biomol Struct Dyn. 2022;40(24):13976-13996. doi: 10.1080/07391102.2021.1997822. Epub 2021 Nov 5.

DOI:10.1080/07391102.2021.1997822
PMID:34738871
Abstract

COVID-19 is the most recent threat to global health. Many people preferred treatment in case of infection instead of vaccination. The inhibition of viral replication is a good strategy for the treatment of COVID-19 infection. 3CLpro and PLpro are two important viral proteases responsible for proteolysis, infection, and replication of the virus. Therefore, targeting of these two enzymes is an attractive way to deal with COVID-19. The aim of this study was to screen some synthetic protease inhibitors to determine an appropriate hit molecule against COVID-19 using molecular docking and molecular dynamic simulations. The strategy depends on docking existing synthetic compounds mostly HIV protease inhibitors against two COVID-19 proteases to identify promising drugs for the treatment of COVID-19. We used protein data bank to obtain the X-ray crystal structure of the most important COVID-19 proteases 3CL pro (PDB ID: 6M2N) and PL pro (PDB ID: 6WX4). In this conceptual context, an attempt has been made to suggest an in silico computational relationship between 50 synthetic protease inhibitors and COVID-19 proteases. Out of 50 screened compounds, the best docking scores were found for these five protease inhibitors BDBM7021, BDBM698, BDBM694, BDBM93239, BDBM700. A 100-ns MD simulation was carried out to assess the stability of COVID-19 proteases and inhibitors, revealing an average RMSD value of 0.7 and favorable binding free energy (MM-GBSA) for all complexes confirming their potency as powerful binders in the COVID-19 proteases' binding pocket. Furthermore, the current results must be confirmed using in- and in- antiviral methods.Communicated by Ramaswamy H. Sarma.

摘要

COVID-19 是对全球健康的最新威胁。许多人更倾向于在感染时接受治疗,而不是接种疫苗。抑制病毒复制是治疗 COVID-19 感染的一种好策略。3CLpro 和 PLpro 是两种重要的病毒蛋白酶,负责病毒的蛋白水解、感染和复制。因此,针对这两种酶是应对 COVID-19 的一种有吸引力的方法。本研究的目的是筛选一些合成蛋白酶抑制剂,通过分子对接和分子动力学模拟确定针对 COVID-19 的合适命中分子。该策略依赖于对接现有的合成化合物,主要是 HIV 蛋白酶抑制剂,以针对两种 COVID-19 蛋白酶识别有前途的 COVID-19 治疗药物。我们使用蛋白质数据库获取最重要的 COVID-19 蛋白酶 3CL pro(PDB ID:6M2N)和 PL pro(PDB ID:6WX4)的 X 射线晶体结构。在这个概念框架中,我们试图提出 50 种合成蛋白酶抑制剂与 COVID-19 蛋白酶之间的计算关系。在筛选出的 50 种化合物中,发现这五种蛋白酶抑制剂 BDBM7021、BDBM698、BDBM694、BDBM93239、BDBM700 的对接得分最好。进行了 100-ns MD 模拟,以评估 COVID-19 蛋白酶和抑制剂的稳定性,结果显示所有复合物的平均 RMSD 值为 0.7,结合自由能(MM-GBSA)有利,证实它们作为 COVID-19 蛋白酶结合口袋中的强力配体的效力。此外,必须使用体内和体内抗病毒方法进一步确认当前结果。由 Ramaswamy H. Sarma 传达。

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