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Computational Analysis of Dynamic Allostery and Control in the SARS-CoV-2 Main Protease
bioRxiv - Biophysics Pub Date : 2020-07-20 , DOI: 10.1101/2020.05.21.105965
Igors Dubanevics , Tom C.B. McLeish

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has generated a global pandemic and no vaccine or antiviral drugs exist at the moment of writing. An attractive coronavirus drug target is the main protease (Mpro, also known as 3CLpro) 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 which targets regions beyond 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 theSARS-CoV-2 Mpro homodimer protein and analyse the dynamics and thermodynamics of the main protease's ENM. We found a rich and heterogeneous dynamical structure in the correlated motions, 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 for control of 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. They also provide new insight into the protein physics of fluctuation allostery and its underpinning dynamical structure.

中文翻译:

SARS-CoV-2主蛋白酶动态构象与调控的计算分析

由新型冠状病毒SARS-CoV-2引起的COVID-19大流行已引起全球大流行,在撰写本文时不存在疫苗或抗病毒药物。冠状病毒药物的有吸引力的靶标是主要蛋白酶(M pro,也称为3CL pro),因为它在病毒周期中起着至关重要的作用。一项重要的工作集中在寻找结合和阻断主要蛋白酶活性位点的抑制剂上,但是对于解决靶向该活性位点以外区域的潜在非竞争性抑制作用却做得很少,部分原因是这种酶的基本生物物理学变构控制仍然知之甚少。在这项工作中,我们构建了SARS-CoV-2 M pro的弹性网络模型(ENM)同源二聚体蛋白,并分析主要蛋白酶的ENM的动力学和热力学。我们在相关运动中发现了丰富而异质的动力学结构,包括同二聚体蛋白酶活性位点之间的变构相关运动。ENM的详尽的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确定的生物活性残基,但也暗示了一些远离活性位点的新候选区域,可控制蛋白酶的功能。我们的结果表明,新的动态驱动控制区可能是蛋白酶中非竞争性抑制结合位点的可能候选者,这可能有助于当前基于片段的结合筛选的发展。
更新日期:2020-07-21
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