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应用多药理学方法进行针对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的药物重新利用。

Applying polypharmacology approach for drug repurposing for SARS-CoV2.

作者信息

Jamir Esther, Sarma Himakshi, Priyadarsinee Lipsa, Nagamani Selvaraman, Kiewhuo Kikrusenuo, Gaur Anamika Singh, Rawal Ravindra K, Murugan Natarajan Arul, Subramanian Venkatesan, Sastry G Narahari

机构信息

Advanced Computation and Data Sciences Division, CSIR - North East Institute of Science and Technology, Jorhat, Assam 785006 India.

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

出版信息

J Chem Sci (Bangalore). 2022;134(2):57. doi: 10.1007/s12039-022-02046-0. Epub 2022 Apr 22.

DOI:10.1007/s12039-022-02046-0
PMID:35498548
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9028909/
Abstract

UNLABELLED

Exploring the new therapeutic indications of known drugs for treating COVID-19, popularly known as drug repurposing, is emerging as a pragmatic approach especially owing to the mounting pressure to control the pandemic. Targeting multiple targets with a single drug by employing drug repurposing known as the polypharmacology approach may be an optimised strategy for the development of effective therapeutics. In this study, virtual screening has been carried out on seven popular SARS-CoV-2 targets (3CL, PL, RdRp (NSP12), NSP13, NSP14, NSP15, and NSP16). A total of 4015 approved drugs were screened against these targets. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected based on the docking score, ability to interact with four or more targets and having a reasonably good number of interactions with key residues in the targets. The MD simulations and MM-PBSA studies showed reasonable stability of protein-drug complexes and sustainability of key interactions between the drugs with their respective targets throughout the course of MD simulations. The identified four drug molecules were also compared with the known drugs namely elbasvir and nafamostat. While the study has provided a detailed account of the chosen protein-drug complexes, it has explored the nature of seven important targets of SARS-CoV-2 by evaluating the protein-drug complexation process in great detail.

GRAPHICAL ABSTRACT

Drug repurposing strategy against SARS-CoV2 drug targets. Computational analysis was performed to identify repurposable approved drug candidates against SARS-CoV2 using approaches such as virtual screening, molecular dynamics simulation and MM-PBSA calculations. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected as potential candidates.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12039-022-02046-0.

摘要

未标注

探索已知药物治疗新冠病毒病的新治疗适应症,即通常所说的药物重新利用,正成为一种务实的方法,特别是由于控制疫情的压力不断增加。通过采用被称为多药理学方法的药物重新利用来用单一药物靶向多个靶点,可能是开发有效治疗方法的优化策略。在本研究中,对七个常见的严重急性呼吸综合征冠状病毒2(SARS-CoV-2)靶点(3CL、PL、RNA依赖性RNA聚合酶(RdRp,NSP12)、NSP13、NSP14、NSP15和NSP16)进行了虚拟筛选。针对这些靶点共筛选了4015种已批准药物。根据对接分数、与四个或更多靶点相互作用的能力以及与靶点中关键残基有相当数量的相互作用,选择了四种药物,即维奈托克、替拉扎德、乙酰毛花苷和雷迪帕韦。分子动力学(MD)模拟和MM-PBSA研究表明,在MD模拟过程中,蛋白质-药物复合物具有合理的稳定性,药物与其各自靶点之间的关键相互作用具有可持续性。还将鉴定出的四种药物分子与已知药物埃尔巴韦和那法莫司他进行了比较。虽然该研究详细描述了所选的蛋白质-药物复合物,但它通过非常详细地评估蛋白质-药物络合过程,探索了SARS-CoV-2七个重要靶点的性质。

图形摘要

针对SARS-CoV-2药物靶点的药物重新利用策略。使用虚拟筛选、分子动力学模拟和MM-PBSA计算等方法进行了计算分析,以确定针对SARS-CoV-2的可重新利用的已批准药物候选物。选择了维奈托克、替拉扎德、乙酰毛花苷和雷迪帕韦四种药物作为潜在候选物。

补充信息

在线版本包含可在10.1007/s12039-022-02046-0获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/44e22e5f0106/12039_2022_2046_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/0aa85000f2c9/12039_2022_2046_Fig1a_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/0856880ddf4c/12039_2022_2046_Fig5a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/1f7bca0b95d5/12039_2022_2046_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/278817a7e8af/12039_2022_2046_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/199819c5b87b/12039_2022_2046_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/3f9a91606a49/12039_2022_2046_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/2cb621f3111f/12039_2022_2046_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/beba9e33686a/12039_2022_2046_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4137/9028909/44e22e5f0106/12039_2022_2046_Fig12_HTML.jpg

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