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通过计算方法对血管紧张素转换酶相关羧肽酶(ACE2)进行药物重新利用

Drug Repurposing Against Angiotensin-Converting Enzyme-Related Carboxypeptidase (ACE2) Through Computational Approach.

作者信息

Vaseghi Golnaz, Golestaneh Ali, Jafari Leila, Ghasemi Fahimeh

机构信息

Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran.

Applied Physiology Research Center, Cardiovascular Research Institute, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran.

出版信息

J Med Signals Sens. 2022 Nov 10;12(4):341-346. doi: 10.4103/jmss.JMSS_66_20. eCollection 2022 Oct-Dec.

DOI:10.4103/jmss.JMSS_66_20
PMID:36726422
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9885507/
Abstract

Ongoing novel coronavirus (COVID-19) with high mortality is an infectious disease in the world which epidemic in 2019 with human-human transmission. According to the literature, S-protein is one of the main proteins of COVID-19 that bind to the human cell receptor angiotensin-converting enzyme 2 (ACE2). In this study, it was attempted to identify the main effective drugs approved that may be repurposed to the binding site of ACE2. High throughput virtual screening based on the docking study was performed to know which one of the small-molecules had a potential interaction with ACE2 structure. Forasmuch as investigating and identifying the best ACE2 inhibitors among more than 3,500 small-molecules is time-consuming, supercomputer was utilized to apply docking-based virtual screening. Outputs of the proposed computational model revealed that vincristine, vinbelastin and bisoctrizole can significantly bind to ACE2 and may interface with its normal activity.

摘要

持续存在且死亡率高的新型冠状病毒(COVID-19)是一种2019年在全球流行且可人际传播的传染病。根据文献,S蛋白是COVID-19的主要蛋白之一,可与人类细胞受体血管紧张素转换酶2(ACE2)结合。在本研究中,试图鉴定已获批的可能重新用于ACE2结合位点的主要有效药物。基于对接研究进行了高通量虚拟筛选,以了解哪些小分子与ACE2结构有潜在相互作用。由于在3500多种小分子中研究和鉴定最佳ACE2抑制剂耗时较长,因此利用超级计算机进行基于对接的虚拟筛选。所提出的计算模型的结果表明,长春新碱、长春贝司汀和二苯甲酰甲烷可与ACE2显著结合,并可能影响其正常活性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/9885507/70ee7208c8c7/JMSS-12-341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/9885507/c5377da3d078/JMSS-12-341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/9885507/70ee7208c8c7/JMSS-12-341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/9885507/c5377da3d078/JMSS-12-341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/9885507/70ee7208c8c7/JMSS-12-341-g002.jpg

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本文引用的文献

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基于分子对接和虚拟筛选的 COVID-19 药物预测。
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Clinical and computed tomographic imaging features of novel coronavirus pneumonia caused by SARS-CoV-2.SARS-CoV-2 引起的新型冠状病毒肺炎的临床和计算机断层扫描影像学特征。
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