6lu7-croscor-25-0.xlsx from Computational analysis of dynamic allostery and control in the SARS-CoV-2 main protease

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^pro, also known as 3CL^pro) 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^pro 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.

由新型冠状病毒SARS-CoV-2引发的COVID-19大流行，在本文撰写之际仍无公开可用的疫苗或抗病毒治疗药物。冠状病毒的一个极具研究价值的药物靶点是主蛋白酶（main protease，Mpro，亦称3CLpro），因其在病毒复制周期中发挥着至关重要的作用。此前已有大量研究致力于寻找可结合并阻断该主蛋白酶活性位点的抑制剂，但针对非竞争性抑制、靶向活性位点以外区域的相关研究却寥寥无几，部分原因在于这类变构调控的基础生物物理机制仍未被充分阐明。本研究构建了SARS-CoV-2 Mpro同源二聚体蛋白的弹性网络模型（Elastic Network Model，ENM），并对其动力学与热力学特性进行了系统性分析。研究发现该蛋白存在丰富且具有异质性的动力学结构，其中包括同源二聚体蛋白酶活性位点之间的变构关联运动。对该弹性网络模型进行全面的单点及两点突变扫描，并分析其对涨落自由能的影响，结果不仅验证了过往实验中已确认的生物活性残基，还发现了数个远离活性位点却可调控蛋白酶功能的全新候选区域。本研究结果表明，这些受动力学调控的区域可作为该蛋白酶中非竞争性抑制结合位点的潜在候选靶点，有望助力当前基于片段的结合筛选工作的开展。本研究成果还为蛋白质涨落变构这一前沿生物物理研究领域及其背后的动力学结构提供了全新的见解。