Issue 57, 2021

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations

Abstract

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent for COVID-19, it continues to transmit and newer variants of concern have been consistently emerging world-wide. Computational strategies involving drug repurposing offer a viable opportunity to choose a medication from a rundown of affirmed drugs against distinct diseases including COVID-19. While pandemics impede the healthcare systems, drug repurposing or repositioning represents a hopeful approach in which existing drugs can be remodeled and employed to treat newer diseases. In this review, we summarize the diverse computational approaches attempted for developing drugs through drug repurposing or repositioning against COVID-19 and discuss their advantages and limitations. To this end, we have outlined studies that utilized computational techniques such as molecular docking, molecular dynamic simulation, disease–disease association, drug–drug interaction, integrated biological network, artificial intelligence, machine learning and network medicine to accelerate creation of smart and safe drugs against COVID-19.

Graphical abstract: Computational methods directed towards drug repurposing for COVID-19: advantages and limitations

Supplementary files

Article information

Article type
Review Article
Submitted
10 jul 2021
Accepted
07 okt 2021
First published
10 nov 2021
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2021,11, 36181-36198

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations

P. P. Sharma, M. Bansal, A. Sethi, Poonam, L. Pena, V. K. Goel, M. Grishina, S. Chaturvedi, D. Kumar and B. Rathi, RSC Adv., 2021, 11, 36181 DOI: 10.1039/D1RA05320E

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