Computational guided approach for drug repurposing against SARS-CoV-2

被引：5

作者：

Anand, Jigisha ^{[1
]}

Ghildiyal, Tanmay ^{[2
]}

Madhwal, Aakanksha ^{[2
]}

Bhatt, Rishabh ^{[2
]}

Verma, Devvret ^{[1
]}

Rai, Nishant ^{[1
]}

机构：

[1] Graph Era Deemed Univ, Dept Biotechnol, Dehra Dun 248001, Uttarakhand, India

[2] Graph Era Deemed Univ, Dept Life Sci, Dehra Dun 248001, Uttarakhand, India

来源：

FUTURE VIROLOGY | 2021年 / 16卷 / 03期

关键词：

ADMET; in silico; nsp3; nsp5; protein modeling; SARS-CoV-2; MOUSE HEPATITIS-VIRUS; SARS-CORONAVIRUS; PROTEIN; REPLICATION; BINDING;

D O I：

10.2217/fvl-2020-0403

中图分类号：

Q93 [微生物学];

学科分类号：

071005 ; 100705 ;

摘要：

Background: In the current SARS-CoV-2 outbreak, drug repositioning emerges as a promising approach to develop efficient therapeutics in comparison to de novo drug development. The present investigation screened 130 US FDA-approved drugs including hypertension, cardiovascular diseases, respiratory tract infections (RTI), antibiotics and antiviral drugs for their inhibitory potential against SARS-CoV-2. Materials & methods: The molecular drug targets against SARS-CoV-2 proteins were determined by the iGEMDOCK computational docking tool. The protein homology models were generated through SWISS Model workspace. The pharmacokinetics of all the ligands was determined by ADMET analysis. Results: The study identified 15 potent drugs exhibiting significant inhibitory potential against SARS-CoV-2. Conclusion: Our investigation has identified possible repurposed drug candidates to improve the current modus operandi of the treatment given to COVID-19 patients.

引用

页码：211 / 243

页数：33

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