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通过分子动力学模拟和网络拓扑分析对 SARS-CoV2 主蛋白酶的进化后果进行生物物理解释。

Biophysical Interpretation of Evolutionary Consequences on the SARS-CoV2 Main Protease through Molecular Dynamics Simulations and Network Topology Analysis.

机构信息

Theoretical and Computational Physics Group, Department of Physics, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok 10140, Thailand.

Center of Excellence in Theoretical and Computational Science (TaCS-CoE), Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok 10140, Thailand.

出版信息

J Phys Chem B. 2023 Mar 23;127(11):2331-2343. doi: 10.1021/acs.jpcb.2c08312. Epub 2023 Mar 13.

Abstract

In this study, we present a combined analysis procedure between atomistic molecular dynamics (MD) simulations and network topology to obtain more understanding on the evolutionary consequences on protein stability and substrate binding of the main protease enzyme of SARS-CoV2. Communicability matrices of the protein residue networks (PRNs) were extracted from MD trajectories of both Mpro enzymes in complex with the nsp8/9 peptide substrate to compare the local communicability within both proteases that would affect the enzyme function, along with biophysical details on global protein conformation, flexibility, and contribution of amino acid side chains to both intramolecular and intermolecular interactions. The analysis displayed the significance of the mutated residue 46 with the highest communicability gain to the binding pocket closure. Interestingly, the mutated residue 134 with the highest communicability loss corresponded to a local structural disruption of the adjacent peptide loop. The enhanced flexibility of the disrupted loop connecting to the catalytic residue Cys145 introduced an extra binding mode that brought the substrate in proximity and could facilitate the reaction. This understanding might provide further help in the drug development strategy against SARS-CoV2 and prove the capability of the combined techniques of MD simulations and network topology analysis as a "reverse" protein engineering tool.

摘要

在这项研究中,我们提出了一种原子分子动力学(MD)模拟和网络拓扑相结合的分析程序,以更深入地了解 SARS-CoV2 的主要蛋白酶稳定性和底物结合的进化后果。从与 nsp8/9 肽底物复合的 Mpro 酶的 MD 轨迹中提取了蛋白质残基网络(PRN)的可传递性矩阵,以比较两种蛋白酶内的局部可传递性,这将影响酶的功能,以及有关全局蛋白质构象、灵活性以及氨基酸侧链对分子内和分子间相互作用的贡献的生物物理细节。分析显示了突变残基 46 的重要性,它与结合口袋的闭合有关,具有最高的可传递性增益。有趣的是,突变残基 134 的可传递性损失最高,对应于相邻肽环的局部结构破坏。与催化残基 Cys145 连接的破坏环的增强灵活性引入了额外的结合模式,使底物靠近,并可能促进反应。这种理解可能会在针对 SARS-CoV2 的药物开发策略中提供进一步的帮助,并证明 MD 模拟和网络拓扑分析相结合的技术作为“反向”蛋白质工程工具的能力。

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