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利用功能位点相互作用指纹法研究病毒 RNA 依赖性 RNA 聚合酶的结合模式,为 RNA 病毒药物发现提供结构见解。

Structural Insights into the Binding Modes of Viral RNA-Dependent RNA Polymerases Using a Function-Site Interaction Fingerprint Method for RNA Virus Drug Discovery.

机构信息

School of Data Science, University of Virginia, Charlottesville, Virginia 22904, United States of America.

Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia 22904, United States of America.

出版信息

J Proteome Res. 2020 Nov 6;19(11):4698-4705. doi: 10.1021/acs.jproteome.0c00623. Epub 2020 Sep 29.

Abstract

The coronavirus disease of 2019 (COVID-19) pandemic speaks to the need for drugs that not only are effective but also remain effective given the mutation rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To this end, we describe structural binding-site insights for facilitating COVID-19 drug design when targeting RNA-dependent RNA polymerase (RDRP), a common conserved component of RNA viruses. We combined an RDRP structure data set, including 384 RDRP PDB structures and all corresponding RDRP-ligand interaction fingerprints, thereby revealing the structural characteristics of the active sites for application to RDRP-targeted drug discovery. Specifically, we revealed the intrinsic ligand-binding modes and associated RDRP structural characteristics. Four types of binding modes with corresponding binding pockets were determined, suggesting two major subpockets available for drug discovery. We screened a drug data set of 7894 compounds against these binding pockets and presented the top-10 small molecules as a starting point in further exploring the prevention of virus replication. In summary, the binding characteristics determined here help rationalize RDRP-targeted drug discovery and provide insights into the specific binding mechanisms important for containing the SARS-CoV-2 virus.

摘要

2019 年冠状病毒病(COVID-19)大流行表明,我们不仅需要有效的药物,还需要在严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的突变率下保持有效的药物。为此,我们描述了针对 RNA 依赖性 RNA 聚合酶(RDRP)的结构结合位点见解,这是 RNA 病毒的常见保守成分,以促进 COVID-19 药物设计。我们结合了 RDRP 结构数据集,包括 384 个 RDRP PDB 结构和所有对应的 RDRP-配体相互作用指纹,从而揭示了活性位点的结构特征,以应用于针对 RDRP 的药物发现。具体来说,我们揭示了内在的配体结合模式和相关的 RDRP 结构特征。确定了四种具有相应结合口袋的结合模式,表明有两个主要的亚口袋可供药物发现。我们针对这些结合口袋筛选了 7894 种化合物的药物数据集,并提出了前 10 种小分子作为进一步探索预防病毒复制的起点。总之,这里确定的结合特征有助于合理化针对 RDRP 的药物发现,并深入了解包含 SARS-CoV-2 病毒的特定结合机制。

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