Issue 46, 2021

Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow

Abstract

The devastating effect of SARS-CoV2 continues and the scientific community is pursuing to find the strategy to combat the spread of the virus. The approach is adapted to target this virus with medicine in combination with existing vaccines. For this, the medications that can specifically inhibit an enzyme essential for viral replication ‘RNA-dependant-RNA polymerase (RdRp)’ of SARS-CoV2 are being developed. RdRp is the enzyme commonly found in all RNA viruses but is absent in humans. There are in total 60 different RdRp inhibitors already under clinical trials for combating other RNA viruses, which are sought to even work for SARS-CoV2. These inhibitors are classified as nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. In this study, all the known RdRp inhibitors were computationally targeted in the native form and their active form making the use of molecular docking, MM-GBSA and molecular dynamics (MD) simulations to find the top two of each nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. The results showed ribavirin 5′-triphosphate and favipiravir ribonucleoside triphosphate (favipiravir-RTP) to be the top two nucleotide analogues while pimodivir and dihydropyrazolopyridinone analogue 8d were the top two nonnucleosides/non-nucleotide analogues.

Graphical abstract: Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow

Supplementary files

Article information

Article type
Paper
Submitted
09 Jun 2021
Accepted
06 Aug 2021
First published
02 Sep 2021
This article is Open Access
Creative Commons BY license

RSC Adv., 2021,11, 29015-29028

Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow

D. Goswami, RSC Adv., 2021, 11, 29015 DOI: 10.1039/D1RA04460E

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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