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了解冠状病毒并探索分子动力学模拟,以寻找针对 nCoV Mpro 的有前途的候选药物来对抗 COVID-19:系统评价。

An understanding of coronavirus and exploring the molecular dynamics simulations to find promising candidates against the Mpro of nCoV to combat the COVID-19: A systematic review.

机构信息

Department of Chemistry, Atma Ram Sanatan Dharma College, University of Delhi, New Delhi, India.

Department of Biochemistry, University of Delhi, New Delhi, India.

出版信息

J Infect Public Health. 2022 Nov;15(11):1326-1349. doi: 10.1016/j.jiph.2022.10.013. Epub 2022 Oct 19.

DOI:10.1016/j.jiph.2022.10.013
PMID:36288640
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9579205/
Abstract

The first infection case of new coronavirus was reported at the end of 2019 and after then, the cases are reported in all nations across the world in a very short period. Further, the regular news of mutations in the virus has made life restricted with appropriate behavior. To date, a new strain (Omicron and its new subvariant Omicron XE) has brought fear amongst us due to a higher trajectory of increase in the number of cases. The researchers thus started giving attention to this viral infection and discovering drug-like candidates to cure the infections. Finding a drug for any viral infection is not an easy task and takes plenty of time. Therefore, computational chemistry/bioinformatics is followed to get promising molecules against viral infection. Molecular dynamics (MD) simulations are being explored to get drug candidates in a short period. The molecules are screened via molecular docking, which provides preliminary information which can be further verified by molecular dynamics (MD) simulations. To understand the change in structure, MD simulations generated several trajectories such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, and radius of gyration for the main protease (Mpro) of the new coronavirus (nCoV) in the presence of small molecules. Additionally, change in free energy for the formation of complex of Mpro of nCoV with the small molecule can be determined by applying molecular mechanics with generalized born and surface area solvation (MM-GBSA). Thus, the promising molecules can be further explored for clinical trials to combat coronavirus disease-19 (COVID-19).

摘要

2019 年末报告了首例新型冠状病毒感染病例,此后,世界各国在很短的时间内都报告了病例。此外,病毒不断出现变异的消息,使人们不得不采取适当的行为来限制生活。迄今为止,由于病例数量呈更高的增长轨迹,一种新的毒株(奥密克戎及其新的子变体奥密克戎 XE)给我们带来了恐惧。因此,研究人员开始关注这种病毒感染,并发现类似药物的候选药物来治疗感染。寻找任何病毒感染的药物都不是一件容易的事,需要大量的时间。因此,人们采用计算化学/生物信息学来寻找针对病毒感染的有希望的分子。分子动力学(MD)模拟正在被探索用于在短时间内获得候选药物。通过分子对接对分子进行筛选,提供初步信息,然后可以通过分子动力学(MD)模拟进一步验证。为了了解结构的变化,对新型冠状病毒(nCoV)的主要蛋白酶(Mpro)进行了 MD 模拟,生成了几个轨迹,如均方根偏差(RMSD)、均方根波动(RMSF)、氢键和旋转半径,同时小分子存在于其中。此外,还可以通过应用分子力学与广义 Born 和表面积溶剂化(MM-GBSA)来确定 Mpro 与小分子形成复合物的自由能变化。因此,有希望的分子可以进一步探索用于临床试验,以对抗冠状病毒病-19(COVID-19)。

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