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针对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)跨膜丝氨酸蛋白酶2(TMPRSS2)靶点的虚拟药物重新利用研究。

Virtual drug repurposing study against SARS-CoV-2 TMPRSS2 target.

作者信息

DurdaĞi Serdar

机构信息

Department of Biophysics, Computational Biology and Molecular Simulations Laboratory, School of Medicine, Bahçeşehir University, İstanbul Turkey.

出版信息

Turk J Biol. 2020 Jun 21;44(3):185-191. doi: 10.3906/biy-2005-112. eCollection 2020.

DOI:10.3906/biy-2005-112
PMID:32595355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7314512/
Abstract

Currently, the world suffers from a new coronavirus SARS-CoV-2 that causes COVID-19. Therefore, there is a need for the urgent development of novel drugs and vaccines for COVID-19. Since it can take years to develop new drugs against this disease, here we used a hybrid combined molecular modeling approach in virtual drug screening repurposing study to identify new compounds against this disease. One of the important SARS-CoV-2 targets namely type 2 transmembrane serine protease (TMPRSS2) was screened with NPC's NIH small molecule library which includes approved drugs by FDA and compounds in clinical investigation. We used 6654 small molecules in molecular docking and top-50 docking scored compounds were initially used in short (10-ns) molecular dynamics (MD) simulations. Based on average MM/GBSA binding free energy results, long (100-ns) MD simulations were employed for the identified hits. Both binding energy results as well as crucial residues in ligand binding were also compared with a positive control TMPRSS2 inhibitor, Camostat mesylate. Based on these numerical calculations we proposed a compound (benzquercin) as strong TMPRSS2 inhibitor. If these results can be validated by in vitro and in vivo studies, benzquercin can be considered to be used as inhibitor of TMPRSS2 at the clinical studies.

摘要

目前,全球正遭受由新型冠状病毒SARS-CoV-2引发的COVID-19疫情。因此,迫切需要研发针对COVID-19的新型药物和疫苗。鉴于研发针对该疾病的新药可能需要数年时间,在此我们采用混合组合分子建模方法,在虚拟药物筛选再利用研究中,以识别针对该疾病的新化合物。对SARS-CoV-2的一个重要靶点即2型跨膜丝氨酸蛋白酶(TMPRSS2),使用了美国国立癌症研究所(NPC)的美国国立卫生研究院小分子库进行筛选,该库包含美国食品药品监督管理局(FDA)批准的药物以及处于临床研究阶段的化合物。我们在分子对接中使用了6654个小分子,最初对对接评分最高的前50种化合物进行了短时间(10纳秒)的分子动力学(MD)模拟。基于平均的MM/GBSA结合自由能结果,对筛选出的命中化合物进行了长时间(100纳秒)的MD模拟。还将结合能结果以及配体结合中的关键残基与阳性对照TMPRSS2抑制剂甲磺酸卡莫司他进行了比较。基于这些数值计算,我们提出了一种化合物(苯槲皮素)作为强效的TMPRSS2抑制剂。如果这些结果能通过体外和体内研究得到验证,苯槲皮素可被考虑在临床研究中用作TMPRSS2的抑制剂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b6/7314512/0b28da7a993b/turkjbio-44-185-fig002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b6/7314512/0b83283f42ab/turkjbio-44-185-fig001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b6/7314512/0b28da7a993b/turkjbio-44-185-fig002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b6/7314512/0b83283f42ab/turkjbio-44-185-fig001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b6/7314512/0b28da7a993b/turkjbio-44-185-fig002.jpg

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