Whole genome analysis and homology modeling of SARS-CoV-2 Indian isolate reveals potent FDA approved drug choice for treating COVID-19.

Velu P, Rathinavel T, Kumarasamy S, Iqbal MN, Noor H, Ikram A, Rajamanickam K, Shanmugam G

J Biomol Struct Dyn - (-) 1-17 [2022-02-09; online 2022-02-09]

Coronaviruses have caused enough devastation in the last two decades. These viruses have some rare features while sharing some common features. Novel coronavirus disease (nCoV-19) caused an outbreak with a fatality rate of 5%. It emerged from China and spread into many countries. The present research focused on genome analysis of Indian nCoV-19 Isolate and its translational product subjected to homology modeling and its subsequent molecular simulations to find out potent FDA approved drug for treating COVID-19. Phylogenetic analysis of SARS-CoV-2 Indian isolate shows close resemblance with 17 countries SARS-CoV-2 isolates. Homology modeling of four non-structural proteins translational product of Indian SARS-CoV-2 genome shows high similarity and allowed regions with the existing PDB deposited SARS-CoV-2 target proteins. Finally, these four generated proteins show more affinity with cobicistat, remdesivir and indinavir out of 14 screened FDA approved drugs in molecular docking which is further proven by molecular dynamics simulation and MMGBSA analysis of target ligand complex with best simulation trajectories. Overall our present research findings is that three proposed drugs namely cobicistat, remdesivir and indinavir showed higher interaction with the model SARS-CoV-2 viral target proteins from the Indian nCoV-19 isolate. These compounds could be used as a starting point for the creation of active antiviral drugs to combat the deadly COVID-19 virus during global pandemic and its subsequent viral infection waves across the globe.Communicated by Ramaswamy H. Sarma.

Category: Genomics & transcriptomics

Category: Health

Category: Public Health

Type: Journal article

PubMed 35139758

DOI 10.1080/07391102.2022.2038272

Crossref 10.1080/07391102.2022.2038272


Publications 7.1.2