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SARS-CoV-2 主蛋白酶中动态变构和控制的计算分析。

Computational analysis of dynamic allostery and control in the SARS-CoV-2 main protease.

机构信息

School of Natural Sciences, University of York, York, UK.

Department of Physics, University of York, York, UK.

出版信息

J R Soc Interface. 2021 Jan;18(174):20200591. doi: 10.1098/rsif.2020.0591. Epub 2021 Jan 6.

Abstract

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has no publicly available vaccine or antiviral drugs at the time of writing. An attractive coronavirus drug target is the main protease (M, also known as 3CL) because of its vital role in the viral cycle. A significant body of work has been focused on finding inhibitors which bind and block the active site of the main protease, but little has been done to address potential non-competitive inhibition, targeting regions other than the active site, partly because the fundamental biophysics of such allosteric control is still poorly understood. In this work, we construct an elastic network model (ENM) of the SARS-CoV-2 M homodimer protein and analyse its dynamics and thermodynamics. We found a rich and heterogeneous dynamical structure, including allosterically correlated motions between the homodimeric protease's active sites. Exhaustive 1-point and 2-point mutation scans of the ENM and their effect on fluctuation free energies confirm previously experimentally identified bioactive residues, but also suggest several new candidate regions that are distant from the active site, yet control the protease function. Our results suggest new dynamically driven control regions as possible candidates for non-competitive inhibiting binding sites in the protease, which may assist the development of current fragment-based binding screens. The results also provide new insights into the active biophysical research field of protein fluctuation allostery and its underpinning dynamical structure.

摘要

在撰写本文时,由新型冠状病毒 SARS-CoV-2 引起的 COVID-19 大流行尚无公开可用的疫苗或抗病毒药物。由于其在病毒周期中的重要作用,冠状病毒的主要蛋白酶(M,也称为 3CL)是一个很有吸引力的药物靶标。已经有大量工作致力于寻找结合并阻断主蛋白酶活性位点的抑制剂,但很少有针对潜在非竞争性抑制的研究,也很少有针对活性位点以外的其他区域的研究,部分原因是这种变构控制的基本生物物理学仍然知之甚少。在这项工作中,我们构建了 SARS-CoV-2 M 同源二聚体蛋白的弹性网络模型(ENM),并分析了其动力学和热力学性质。我们发现了一种丰富且异构的动力学结构,包括同源二聚体蛋白酶活性位点之间的变构相关运动。对 ENM 的 1 点和 2 点突变扫描及其对波动自由能的影响证实了先前实验鉴定的生物活性残基,但也表明了几个远离活性位点但控制蛋白酶功能的新候选区域。我们的研究结果表明,新的动态驱动控制区域可能是蛋白酶中非竞争性抑制结合位点的候选区域,这可能有助于当前基于片段的结合筛选的发展。该结果还为蛋白质波动变构及其基础动力学结构的活跃生物物理研究领域提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ff7/7879766/7b3926b70d16/rsif20200591-g1.jpg

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