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基于天然产物的 SARS-CoV-2 宏结构域 1 抑制剂筛选

-based screening of natural products as potential inhibitors of SARS-CoV-2 macrodomain 1.

机构信息

College of Chemistry, Fuzhou University, Fuzhou, China.

Xiamen ITG-SUIS High School, Xiamen, China.

出版信息

J Biomol Struct Dyn. 2024 Jul;42(10):5229-5237. doi: 10.1080/07391102.2023.2226745. Epub 2023 Jun 22.

Abstract

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has led to over 600 million cases of coronavirus disease 2019 (COVID-19). Identifying effective molecules that can counteract the virus is imperative. SARS-CoV-2 macrodomain 1 (Mac1) represents a promising antiviral drug target. In this study, we predicted potential inhibitors of SARS-CoV-2 Mac1 from natural products using -based screening. Based on the high-resolution crystal structure of Mac1 bound to its endogenous ligand ADP-ribose (ADPr), we first performed a docking-based virtual screening of Mac1 inhibitors against a natural product library and obtained five representative compounds (MC1-MC5) by clustering analysis. All five compounds were stably bound to Mac1 during 500 ns long molecular dynamics simulations. The binding free energy of these compounds to Mac1 was calculated using molecular mechanics generalized Born surface area and further refined with localized volume-based metadynamics. The results demonstrated that both MC1 (-9.8 ± 0.3 kcal/mol) and MC5 (-9.6 ± 0.3 kcal/mol) displayed more favorable affinities to Mac1 with respect to ADPr (-8.9 ± 0.3 kcal/mol), highlighting their potential as potent SARS-CoV-2 Mac1 inhibitors. Overall, this study provides potential SARS-CoV-2 Mac1 inhibitors, which may pave the way for developing effective therapeutics for COVID-19.Communicated by Ramaswamy H. Sarma.

摘要

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)在全球范围内的迅速传播导致了超过 6 亿例 2019 年冠状病毒病(COVID-19)。确定能够对抗病毒的有效分子是当务之急。SARS-CoV-2 宏结构域 1(Mac1)是一个很有前途的抗病毒药物靶点。在这项研究中,我们使用基于结构的筛选方法从天然产物中预测了 SARS-CoV-2 Mac1 的潜在抑制剂。基于 Mac1 与其内源性配体 ADP-核糖(ADPr)结合的高分辨率晶体结构,我们首先对 Mac1 抑制剂进行了基于对接的虚拟筛选,通过聚类分析得到了五个代表性化合物(MC1-MC5)。在 500 ns 长的分子动力学模拟中,这五种化合物都能稳定地结合到 Mac1 上。使用分子力学广义 Born 表面面积计算了这些化合物与 Mac1 的结合自由能,并使用基于局部体积的元动力学进一步进行了细化。结果表明,与 ADPr(-8.9 ± 0.3 kcal/mol)相比,MC1(-9.8 ± 0.3 kcal/mol)和 MC5(-9.6 ± 0.3 kcal/mol)与 Mac1 的亲和力更强,这表明它们具有成为强效 SARS-CoV-2 Mac1 抑制剂的潜力。总体而言,这项研究提供了潜在的 SARS-CoV-2 Mac1 抑制剂,为开发 COVID-19 的有效疗法铺平了道路。由 Ramaswamy H. Sarma 交流。

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