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

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 tr...

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Autores principales: Anand, Jigisha, Ghildiyal, Tanmay, Madhwal, Aakanksha, Bhatt, Rishabh, Verma, Devvret, Rai, Nishant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Medicine Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923689/
http://dx.doi.org/10.2217/fvl-2020-0403
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author Anand, Jigisha
Ghildiyal, Tanmay
Madhwal, Aakanksha
Bhatt, Rishabh
Verma, Devvret
Rai, Nishant
author_facet Anand, Jigisha
Ghildiyal, Tanmay
Madhwal, Aakanksha
Bhatt, Rishabh
Verma, Devvret
Rai, Nishant
author_sort Anand, Jigisha
collection PubMed
description 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.
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spelling pubmed-79236892021-03-02 Computational guided approach for drug repurposing against SARS-CoV-2 Anand, Jigisha Ghildiyal, Tanmay Madhwal, Aakanksha Bhatt, Rishabh Verma, Devvret Rai, Nishant Future Virol Research Article 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. Future Medicine Ltd 2021-03-02 2021-03 /pmc/articles/PMC7923689/ http://dx.doi.org/10.2217/fvl-2020-0403 Text en © 2021 Future Medicine Ltd This work is licensed under the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/)
spellingShingle Research Article
Anand, Jigisha
Ghildiyal, Tanmay
Madhwal, Aakanksha
Bhatt, Rishabh
Verma, Devvret
Rai, Nishant
Computational guided approach for drug repurposing against SARS-CoV-2
title Computational guided approach for drug repurposing against SARS-CoV-2
title_full Computational guided approach for drug repurposing against SARS-CoV-2
title_fullStr Computational guided approach for drug repurposing against SARS-CoV-2
title_full_unstemmed Computational guided approach for drug repurposing against SARS-CoV-2
title_short Computational guided approach for drug repurposing against SARS-CoV-2
title_sort computational guided approach for drug repurposing against sars-cov-2
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923689/
http://dx.doi.org/10.2217/fvl-2020-0403
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