Cargando…
Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains
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...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052778/ https://www.ncbi.nlm.nih.gov/pubmed/35537364 http://dx.doi.org/10.1016/j.compbiolchem.2022.107687 |
_version_ | 1784696855358078976 |
---|---|
author | Madanagopal, Premnath Muthukumar, Harshini Thiruvengadam, Kothai |
author_facet | Madanagopal, Premnath Muthukumar, Harshini Thiruvengadam, Kothai |
author_sort | Madanagopal, Premnath |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9052778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90527782022-05-02 Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains Madanagopal, Premnath Muthukumar, Harshini Thiruvengadam, Kothai Comput Biol Chem Article 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. Elsevier Ltd. 2022-06 2022-04-29 /pmc/articles/PMC9052778/ /pubmed/35537364 http://dx.doi.org/10.1016/j.compbiolchem.2022.107687 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Madanagopal, Premnath Muthukumar, Harshini Thiruvengadam, Kothai Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title | Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title_full | Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title_fullStr | Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title_full_unstemmed | Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title_short | Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains |
title_sort | computational study and design of effective sirnas to silence structural proteins associated genes of indian sars-cov-2 strains |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052778/ https://www.ncbi.nlm.nih.gov/pubmed/35537364 http://dx.doi.org/10.1016/j.compbiolchem.2022.107687 |
work_keys_str_mv | AT madanagopalpremnath computationalstudyanddesignofeffectivesirnastosilencestructuralproteinsassociatedgenesofindiansarscov2strains AT muthukumarharshini computationalstudyanddesignofeffectivesirnastosilencestructuralproteinsassociatedgenesofindiansarscov2strains AT thiruvengadamkothai computationalstudyanddesignofeffectivesirnastosilencestructuralproteinsassociatedgenesofindiansarscov2strains |