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通过虚拟筛选 ChEMBL 数据库中针对主要冠状病毒蛋白酶的化合物,鉴定出具有抗 SARS-CoV-2 潜力的候选药物。

Potential anti-SARS-CoV-2 drug candidates identified through virtual screening of the ChEMBL database for compounds that target the main coronavirus protease.

机构信息

Institute of Molecular Function, Misato-shi, Saitama, Japan.

出版信息

FEBS Open Bio. 2020 Jun;10(6):995-1004. doi: 10.1002/2211-5463.12875. Epub 2020 May 29.

Abstract

A novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or 2019 novel coronavirus] has been identified as the pathogen of coronavirus disease 2019. The main protease (M , also called 3-chymotrypsin-like protease) of SARS-CoV-2 is a potential target for treatment of COVID-19. A M homodimer structure suitable for docking simulations was prepared using a crystal structure (PDB ID: 6Y2G; resolution 2.20 Å). Structural refinement was performed in the presence of peptidomimetic α-ketoamide inhibitors, which were previously disconnected from each Cys145 of the M homodimer, and energy calculations were performed. Structure-based virtual screenings were performed using the ChEMBL database. Through a total of 1 485 144 screenings, 64 potential drugs (11 approved, 14 clinical, and 39 preclinical drugs) were predicted to show high binding affinity with M . Additional docking simulations for predicted compounds with high binding affinity with M suggested that 28 bioactive compounds may have potential as effective anti-SARS-CoV-2 drug candidates. The procedure used in this study is a possible strategy for discovering anti-SARS-CoV-2 drugs from drug libraries that may significantly shorten the clinical development period with regard to drug repositioning.

摘要

一种新型冠状病毒(严重急性呼吸综合征冠状病毒 2 型,或 2019 年新型冠状病毒)已被确定为 2019 年冠状病毒病的病原体。SARS-CoV-2 的主要蛋白酶(M,也称为 3-糜蛋白酶样蛋白酶)是治疗 COVID-19 的潜在靶点。使用晶体结构(PDB ID:6Y2G;分辨率 2.20 Å)制备了适合对接模拟的 M 同源二聚体结构。在存在先前与 M 同源二聚体的每个 Cys145 断开的肽拟似α-酮酰胺抑制剂的情况下进行结构细化,并进行能量计算。使用 ChEMBL 数据库进行基于结构的虚拟筛选。通过总共 1485144 次筛选,预测 64 种潜在药物(11 种已批准、14 种临床和 39 种临床前药物)与 M 具有高结合亲和力。对与 M 具有高结合亲和力的预测化合物进行额外的对接模拟表明,28 种生物活性化合物可能具有作为有效抗 SARS-CoV-2 药物候选物的潜力。本研究中使用的程序是一种从药物库中发现抗 SARS-CoV-2 药物的可能策略,可能会显著缩短药物重新定位的临床开发周期。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d883/7262888/0a30cec96a9a/FEB4-10-995-g001.jpg

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