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利用分子动力学模拟加速 COVID-19 研究。

Accelerating COVID-19 Research Using Molecular Dynamics Simulation.

机构信息

Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.

Department of Biotechnology, National Institute of Technology, Warangal, Telangana 506004, India.

出版信息

J Phys Chem B. 2021 Aug 19;125(32):9078-9091. doi: 10.1021/acs.jpcb.1c04556. Epub 2021 Jul 28.

Abstract

The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.

摘要

新冠疫情已成为一场全球性的医学、社会和经济灾难。由于缺乏针对 SARS-CoV-2 的有效疗法,科学家们正在竞相提出可快速部署的治疗选择建议,包括药物重定位和重新定位策略。分子动力学(MD)模拟为在危机时刻做出合理的科学突破提供了机会。近年来,这些技术的进步已成为研究蛋白质结构、功能、动力学、相互作用和药物发现的科学家不可或缺的工具。将高分辨率方法获得的结构数据与 MD 模拟相结合,有助于在短时间内理解感染和发病机制,以及 SARS-CoV-2 在宿主细胞中的成熟过程。它还指导我们识别和优先考虑药物靶点和新的化学实体,并重新定位药物。在这里,我们讨论了科学界如何利用 MD 模拟来加速和指导过去一年中对 SARS-CoV-2 的转化研究。我们还考虑了未来研究的方向,在那里 MD 模拟可以帮助填补 COVID-19 研究中的现有空白。

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