Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains. (June 2022)

• Record Type: Journal Article
• Authors: Madanagopal, Premnath; Muthukumar, Harshini; Thiruvengadam, Kothai
• Is Part Of: Computational biology and chemistry. Volume 98(2022)
• Publication Date: 2022-06
• Subjects: COVID-19 COrona VIrus Disease 2019 -- SARS-CoV-2 Severe Acute Respiratory Syndrome-Corona Virus-2 -- siRNA Small interfering RNA -- PTGS Post-Transcriptional Gene Silencing -- RNAi RNA interference -- Tm Melting temperature; COVID-19 -- SiRNA -- RNA interference -- Gene silencing -- Docking; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2022.107687
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: SARS-CoV-2 is a highly transmissible and pathogenic coronavirus that first emerged in late 2019 and has since triggered a pandemic of acute respiratory disease named COVID-19 which poses a significant threat to all public health institutions in the absence of specific antiviral treatment. Since the outbreak began in March 2020, India has reported 4.77 lakh Coronavirus deaths, according to the World Health Organization (WHO). The innate RNA interference (RNAi) pathway, on the other hand, allows for the development of nucleic acid-based antiviral drugs in which complementary small interfering RNAs (siRNAs) mediate the post-transcriptional gene silencing (PTGS) of target mRNA. Therefore, in this current study, the potential of RNAi was harnessed to construct siRNA molecules that target the consensus regions of specific structural proteins associated genes of SARS-CoV-2, such as the envelope protein gene (E), membrane protein gene (M), nucleocapsid phosphoprotein gene (N), and surface glycoprotein gene (S) which are important for the viral pathogenesis. Conserved sequences of 811 SARS-CoV-2 strains from around India were collected to design 21 nucleotides long siRNA duplex based on various computational algorithms and parameters targeting E, M, N and S genes. The proposed siRNA molecules possessed sufficient nucleotide-based and other features for effective gene silencing and BLAST results revealed that siRNAs' targets have no significant matches across the whole human genome. Hence, siRNAs were found to have no off-target effects on the genome, ruling out the possibility of off-target silencing. Finally, out of 157 computationally identified siRNAs, only 4 effective siRNA molecules were selected for each target gene which is proposed to exert the best action based on GC content, free energy of folding, free energy of binding, melting temperature, heat capacity and molecular docking analysis with Human AGO2 protein. Our engineered siRNA candidates could be used as a genome-level therapeutic treatment against various sequenced SARS-CoV-2 strains in India. However, future applications will necessitate additional validations in vitro and in vivo animal models. Graphical Abstract: ga1 Highlights: We designed and analyzed siRNAs from the wide array of 811 Indian SARS-CoV-2 strains that mediate PTGS of target mRNA. 4 siRNAs were sorted as potential therapeutic agents against E, M, N and S genes based on various algorithms and parameters. The goal of this computational study is to reduce the amount of time and effort required in wet lab methods.