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基于结构的沙特药用植物来源植物化学物质虚拟筛选及分子动力学研究以鉴定潜在的COVID-19治疗药物。

Structure-based virtual screening and molecular dynamics of phytochemicals derived from Saudi medicinal plants to identify potential COVID-19 therapeutics.

作者信息

Alamri Mubarak A, Altharawi Ali, Alabbas Alhumaidi B, Alossaimi Manal A, Alqahtani Safar M

机构信息

Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj 11942, Saudi Arabia.

出版信息

Arab J Chem. 2020 Sep;13(9):7224-7234. doi: 10.1016/j.arabjc.2020.08.004. Epub 2020 Aug 9.

Abstract

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNA-dependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CL) and papain like protease (PL) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from -9.9 to -6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6″-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6-galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CL, and withanolide A, isocodonocarpine and calonysterone bound tightly to PL. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

摘要

2019年冠状病毒病(COVID-19)通过引发全球大流行且死亡率高,影响了世界上几乎每个国家。缺乏针对病原体严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的有效疫苗和/或抗病毒药物,严重阻碍了对这种新型冠状病毒的应对。天然产物长期以来一直用于传统药物治疗各种疾病,从药用植物中纯化的植物化学物质为发现新的药物先导物提供了有价值的框架。在本研究中,我们对一个内部数据库进行了计算筛选,该数据库由约1000种源自沙特传统药用植物且具有公认抗病毒活性的植物化学物质组成。针对三个可成药的SARS-CoV-2靶点,即病毒RNA依赖性RNA聚合酶(RdRp)、3-胰凝乳蛋白酶样半胱氨酸蛋白酶(3CL)和木瓜蛋白酶样蛋白酶(PL)进行基于结构的虚拟筛选,以鉴定可能促进潜在抗COVID-19候选药物开发的假定抑制剂。计算分析确定了三种抑制每个靶点的化合物,其结合亲和力得分在-9.9至-6.5千卡/摩尔之间。其中,木犀草素7-芸香糖苷、大黄酚8-(6-没食子酰葡萄糖苷)和山奈酚7-(6″-没食子酰葡萄糖苷)与RdRp有效结合,而大黄酚8-(6-没食子酰葡萄糖苷)、3,4,5-三-O-没食子酰奎尼酸和桑呋喃G与3CL强烈相互作用,而醉茄内酯A、异党参碱和卡诺甾酮与PL紧密结合。这些潜在的候选药物将接受进一步的体外和体内研究,并可能有助于开发有效的抗COVID-19药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50f6/7415226/e4a12b26c94d/gr1_lrg.jpg

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