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基于相对自由能计算的 SARS-CoV-2 结合突变效应的计算预测。

Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations.

机构信息

Shenzhen Jingtai Technology Co., Ltd. (XtalPi), 4F, No. 9 Hualian Industrial Zone, Dalang Street, Longhua District, Shenzhen, China, 518000.

XtalPi-AI Research Center (XARC), 9F, Tower A, Dongsheng Building, No.8, Zhongguancun East Road, Haidian District, Beijing, China, 100083.

出版信息

J Chem Inf Model. 2020 Dec 28;60(12):5794-5802. doi: 10.1021/acs.jcim.0c00679. Epub 2020 Aug 31.

DOI:10.1021/acs.jcim.0c00679
PMID:32786709
Abstract

The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the "hotspot" residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis and also provide useful information for the design of antiviral drugs.

摘要

冠状病毒感染人类的能力通常与其与人类受体蛋白的结合强度有关。SARS-CoV-2(最初命名为 2019-nCoV)和 SARS-CoV 均被报道利用血管紧张素转化酶 2(ACE2)作为人类细胞的进入受体。为了更好地理解 SARS-CoV-2 和 ACE2 之间的相互作用,我们使用相对自由能计算对蛋白质-蛋白质界面上的“热点”残基进行了计算性丙氨酸扫描突变。我们的数据表明,SARS-CoV-2 的突变导致与 SARS-CoV 相比具有更高的结合亲和力。此外,我们的自由能计算从物理基础上提供了对病毒感染能力的深入了解,并且还为抗病毒药物的设计提供了有用的信息。

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