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高通量虚拟筛选和 SARS-CoV-2 主蛋白酶非共价抑制剂的验证。

High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor.

机构信息

Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois 60439, United States.

Department of Computer Science, University of Chicago, Chicago, Illinois 60615, United States.

出版信息

J Chem Inf Model. 2022 Jan 10;62(1):116-128. doi: 10.1021/acs.jcim.1c00851. Epub 2021 Nov 18.

Abstract

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel noncovalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (M) by employing a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this M inhibitor with an inhibition constant () of 2.9 μM (95% CI 2.2, 4.0). Furthermore, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of M forming stable hydrogen bond and hydrophobic interactions. We then used multiple μs-time scale molecular dynamics (MD) simulations and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by M, involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits M and offers a springboard for further therapeutic design.

摘要

尽管最近已经有了针对急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 的疫苗,但寻找抑制性治疗药物尤其重要,尤其是在新的病毒变体不断出现的情况下。在本文中,我们描述了一种新型非共价小分子抑制剂 MCULE-5948770040 的发现,该抑制剂通过采用可扩展的高通量虚拟筛选 (HTVS) 框架和一个超过 650 万个可轻松订购和购买的靶向化合物库,与 SARS-CoV-2 主蛋白酶 (M) 结合并抑制其活性。我们的 HTVS 框架利用美国超级计算基础设施,实现了近 91%的资源利用率和近 1.26 亿次每小时的对接计算。下游生化测定验证了这种 M 抑制剂的抑制常数 () 为 2.9 μM(95%CI 2.2, 4.0)。此外,我们使用室温 X 射线晶体学表明,MCULE-5948770040 结合到 M 的主要结合位点的裂隙中,形成稳定的氢键和疏水相互作用。然后,我们使用多种 μs 时间尺度的分子动力学 (MD) 模拟和机器学习 (ML) 技术来阐明结合配体如何改变 M 可访问的构象状态,涉及到结合位点近端和远端的运动。总之,我们的结果表明 MCULE-5948770040 如何抑制 M,并为进一步的治疗设计提供了一个跳板。

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