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基于分子动力学模拟研究的 SARS-CoV-2 主蛋白酶抑制的计算基础。

Computational basis of SARS-CoV 2 main protease inhibition: an insight from molecular dynamics simulation based findings.

机构信息

Department of Biophysics, Postgraduate Institute of Medical Education and Research, Chandigarh, India.

Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.

出版信息

J Biomol Struct Dyn. 2022;40(19):8894-8904. doi: 10.1080/07391102.2021.1922310. Epub 2021 May 13.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic is caused by newly discovered severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). One of the striking targets amongst all the proteins in coronavirus is the main protease (M), as it plays vital biological roles in replication and maturation of the virus, and hence the potential target. The aim of this study is to repurpose the Food and Drug Administration (FDA) approved molecules via computer-aided drug designing against M (PDB ID: 6Y2F) of SARS CoV-2 due to its high x-ray resolution of 1.95Å as compared to other published Mstructures. High Through Virtual Screening (HTVS) of 2456 FDA approved drugs using structure-based docking were analyzed. Molecular Dynamics simulations were performed to check the overall structural stability (RMSD), Cα fluctuations (RMSF) and protein-ligand interactions. Further, trajectory analysis was performed to assess the binding quality by exploiting the protein-residue motion cross correlation (DCCM) and binding free energy (MM/GBSA). Tenofovir, an antiretroviral for HIV-proteases and Terlipressin, a vasoconstrictor show stable RMSD, RMSF, better MM/GBSA with good cross correlation as compared to the Apo and O6K. Moreover, the results show concurrence with Nelfinavir, Lopinavir and Ritonavir which have shown significant inhibition in studies. Therefore, we conclude that Tenofovir and Terlipresssin might also show protease inhibition but are still open to clinical validation in case of SARS-CoV 2 treatment.Communicated by Ramaswamy H. Sarma.

摘要

新型冠状病毒疾病(COVID-19)大流行是由新发现的严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的。冠状病毒所有蛋白中,有一个引人注目的靶标是主蛋白酶(M),因为它在病毒的复制和成熟中起着至关重要的生物学作用,因此是潜在的靶标。本研究旨在通过计算机辅助药物设计,重新利用食品和药物管理局(FDA)批准的分子,针对 SARS CoV-2 的 M(PDB ID:6Y2F),因为与其他已发表的 M 结构相比,其 X 射线分辨率高达 1.95Å。使用基于结构的对接对 2456 种 FDA 批准的药物进行高通量虚拟筛选(HTVS),并进行分子动力学模拟以检查整体结构稳定性(RMSD)、Cα波动(RMSF)和蛋白-配体相互作用。进一步通过蛋白残基运动交叉相关(DCCM)和结合自由能(MM/GBSA)评估轨迹分析来评估结合质量。与 Apo 和 O6K 相比,抗病毒药物替诺福韦(Tenofovir)和血管收缩剂特利加压素(Terlipressin)显示出稳定的 RMSD、RMSF、更好的 MM/GBSA 和良好的交叉相关性。此外,这些结果与奈非那韦、洛匹那韦和利托那韦的研究结果一致,这些研究表明它们具有显著的抑制作用。因此,我们得出结论,替诺福韦和特利加压素也可能显示出蛋白酶抑制作用,但仍有待 SARS-CoV-2 治疗的临床验证。

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