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Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach.

Authors :
Hossain, Mohammad Uzzal
Bhattacharjee, Arittra
Emon, Md. Tabassum Hossain
Chowdhury, Zeshan Mahmud
Mosaib, Md. Golam
Mourin, Muntahi
Das, Keshob Chandra
Keya, Chaman Ara
Salimullah, Md.
Source :
Gene. Mar2021, Vol. 771, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• RNA-dependent RNA polymerase (RdRp), Spike (S) and glycoprotein (M) were selected. • Both S and M were chosen for the development of a chimeric vaccine. • siRNAs were also designed for S and M gene silencing. • Six new drug candidates were suggested that might inhibit the activity of RdRp. Coronavirus disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has become an immense threat to global public health. In this study, we performed complete genome sequencing of a SARS-CoV-2 isolate. More than 67,000 genome sequences were further inspected from Global Initiative on Sharing All Influenza Data (GISAID). Using several in silico techniques, we proposed prospective therapeutics against this virus. Through meticulous analysis, several conserved and therapeutically suitable regions of SARS-CoV-2 such as RNA-dependent RNA polymerase (RdRp), Spike (S) and Membrane glycoprotein (M) coding genes were selected. Both S and M were chosen for the development of a chimeric vaccine that can generate memory B and T cells. siRNAs were also designed for S and M gene silencing. Moreover, six new drug candidates were suggested that might inhibit the activity of RdRp. Since SARS-CoV-2 and SARS-CoV-1 have 82.30% sequence identity, a Gene Expression Omnibus (GEO) dataset of Severe Acute Respiratory Syndrome (SARS) patients were analyzed. In this analysis, 13 immunoregulatory genes were found that can be used to develop type 1 interferon (IFN) based therapy. The proposed vaccine, siRNAs, drugs and IFN based analysis of this study will accelerate the development of new treatments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03781119
Volume :
771
Database :
Academic Search Index
Journal :
Gene
Publication Type :
Academic Journal
Accession number :
148120398
Full Text :
https://doi.org/10.1016/j.gene.2020.145368