A Computational Approach to Design Potential siRNA Molecules as a Prospective Tool for Silencing Nucleocapsid Phosphoprotein and Surface Glycoprotein Gene of SARS-CoV-2

Abstract

A disease outbreak named COVID-19, caused by a RNA virus, SARS-CoV-2 has become 18 pandemic with a magnitude which is daunting to all public health institutions in the absence of 19 specific antiviral treatment. Surface glycoprotein and nucleocapsid phosphoprotein are two 20 important proteins of this virus facilitating its entry into host cell and genome replication. Small 21 interfering RNA (siRNA) is a prospective tool of the RNA interference (RNAi) pathway for the 22 control of human viral infections by suppressing viral gene expression through hybridization and 23 neutralization of target complementary mRNA. So, in this study, the power of RNA interference 24 technology was harnessed to develop siRNA molecules against specific target genes namely, 25 nucleocapsid phosphoprotein gene and surface glycoprotein gene. Conserved sequence from 139 26 SARS-CoV-2 strains from around the globe was collected to construct 78 siRNA that can inactivate 27 nucleocapsid phosphoprotein and surface glycoprotein genes. Finally, through a rigorous filtering 28 process 8 siRNA molecules were selected with exerts the best action. These predicted siRNAs 29 should effectively silence the genes of SARS-CoV-2 during siRNA mediated treatment assisting in 30 the response against SARS-CoV-2