Discovery of Natural Compounds as SARS-CoV-2’s Main Protease Inhibitors by Docking-based Virtual Screening

虚拟筛选 对接(动物) 化学 蛋白酶 蛋白质数据库 体外 IC50型 冠状病毒 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 计算生物学 药物发现 2019年冠状病毒病(COVID-19) 药理学 生物化学 传染病(医学专业) 生物 疾病 医学 病理 护理部
作者
Jing Wang,Yu Jiang,Yingnan Wu,Yuheng Ma,Hui Yu,Zhanli Wang
出处
期刊:Letters in Drug Design & Discovery [Bentham Science Publishers]
卷期号:21 (10): 1604-1610
标识
DOI:10.2174/1570180820666230502152058
摘要

Introduction: The novel coronavirus disease (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SAR-CoV-2). The development of antiviral drugs has enhaced treatment of COVID-19. SARS-CoV-2 main protease (Mpro) is a key enzyme responsible for viral replication and transcription. This study aimed to identify new natural structures for the design of SARS-CoV-2 Mpro inhibitors. Methods: In this present work, The CDOCKER protocol and scoring functions were validated. The validated docking-based virtual screening approach was then employed to search the in-house database of natural compounds for potential lead compounds as SARS-CoV-2 Mpro inhibitors. The top 3 compounds were further biologically evaluated in vitro. Results and Discussion: Docking studies of the known ligand GC-376 led to results consistent with cocrystallized data (PDB ID: 7D1M). Additionally, the effectiveness of docking scoring functions was validated by using the training set consisting of 15 active compounds and 15 inactive compounds. Then, the in-house database of natural compounds (overall 34,439 natural compounds) was subjected to dockingbased virtual screening resulting in the identification of the top 100 compounds having relatively better docking scores. Among them, the highest ranking 3 compounds (W-1, W-2, and W-3) were biologically evaluated in vitro for their inhibitory activity against SARS-CoV-2 Mpro, and compound W-1 was identified as the most potent SARS-CoV-2 Mpro inhibitor with an IC50 value of 63 ± 3 μM. Interestingly, it appeared that the in vitro activities of compounds W-1, W-2, and W-3 were in agreement with their molecular modeling data. Conclusion: Our results provided a useful reference for the discovery of novel natural SARS-CoV-2 Mpro inhibitors by virtual screening.
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