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Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach
Omicron, a variant of concern (VOC) of SARS-CoV-2, emerged in South Africa in November 2021. Omicron has been continuously acquiring a series of new mutations, especially in the spike (S) protein that led to high infectivity and transmissibility. Peptides targeting the receptor-binding domain (RBD)...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342843/ https://www.ncbi.nlm.nih.gov/pubmed/35923684 http://dx.doi.org/10.1007/s13205-022-03258-4 |
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author | Singh, Swati Banavath, Hemanth Naick Godara, Priya Naik, Biswajit Srivastava, Varshita Prusty, Dhaneswar |
author_facet | Singh, Swati Banavath, Hemanth Naick Godara, Priya Naik, Biswajit Srivastava, Varshita Prusty, Dhaneswar |
author_sort | Singh, Swati |
collection | PubMed |
description | Omicron, a variant of concern (VOC) of SARS-CoV-2, emerged in South Africa in November 2021. Omicron has been continuously acquiring a series of new mutations, especially in the spike (S) protein that led to high infectivity and transmissibility. Peptides targeting the receptor-binding domain (RBD) of the spike protein by which omicron and its variants attach to the host receptor, angiotensin-converting enzyme (ACE2) can block the viral infection at the first step. This study aims to identify antiviral peptides from the Antiviral peptide database (AVPdb) and HIV-inhibitory peptide database (HIPdb) against the RBD of omicron by using a molecular docking approach. The lead RBD binder peptides obtained through molecular docking were screened for allergenicity and physicochemical criteria (isoelectric point (pI) and net charge) required for peptide-based drugs. The binding affinity of the best five peptide inhibitors with the RBD of omicron was validated further by molecular dynamics (MD) simulation. Our result introduces five antiviral peptides, including AVP1056, AVP1059, AVP1225, AVP1801, and HIP755, that may effectively hinder omicron-host interactions. It is worth mentioning that all the three major sub-variants of omicron, BA.1 (B.1.1.529.1), BA.2 (B.1.1.529.2), and BA.3 (B.1.1.529.3), exhibits conserved ACE-2 interacting residues. Hence, the screened antiviral peptides with similar affinity can also interrupt the RBD-mediated invasion of different major sub-variants of omicron. Altogether, these peptides can be considered in the peptide-based therapeutics development for omicron treatment after further experimentation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-022-03258-4. |
format | Online Article Text |
id | pubmed-9342843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-93428432022-08-02 Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach Singh, Swati Banavath, Hemanth Naick Godara, Priya Naik, Biswajit Srivastava, Varshita Prusty, Dhaneswar 3 Biotech Original Article Omicron, a variant of concern (VOC) of SARS-CoV-2, emerged in South Africa in November 2021. Omicron has been continuously acquiring a series of new mutations, especially in the spike (S) protein that led to high infectivity and transmissibility. Peptides targeting the receptor-binding domain (RBD) of the spike protein by which omicron and its variants attach to the host receptor, angiotensin-converting enzyme (ACE2) can block the viral infection at the first step. This study aims to identify antiviral peptides from the Antiviral peptide database (AVPdb) and HIV-inhibitory peptide database (HIPdb) against the RBD of omicron by using a molecular docking approach. The lead RBD binder peptides obtained through molecular docking were screened for allergenicity and physicochemical criteria (isoelectric point (pI) and net charge) required for peptide-based drugs. The binding affinity of the best five peptide inhibitors with the RBD of omicron was validated further by molecular dynamics (MD) simulation. Our result introduces five antiviral peptides, including AVP1056, AVP1059, AVP1225, AVP1801, and HIP755, that may effectively hinder omicron-host interactions. It is worth mentioning that all the three major sub-variants of omicron, BA.1 (B.1.1.529.1), BA.2 (B.1.1.529.2), and BA.3 (B.1.1.529.3), exhibits conserved ACE-2 interacting residues. Hence, the screened antiviral peptides with similar affinity can also interrupt the RBD-mediated invasion of different major sub-variants of omicron. Altogether, these peptides can be considered in the peptide-based therapeutics development for omicron treatment after further experimentation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-022-03258-4. Springer International Publishing 2022-08-01 2022-09 /pmc/articles/PMC9342843/ /pubmed/35923684 http://dx.doi.org/10.1007/s13205-022-03258-4 Text en © King Abdulaziz City for Science and Technology 2022 |
spellingShingle | Original Article Singh, Swati Banavath, Hemanth Naick Godara, Priya Naik, Biswajit Srivastava, Varshita Prusty, Dhaneswar Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title | Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title_full | Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title_fullStr | Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title_full_unstemmed | Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title_short | Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach |
title_sort | identification of antiviral peptide inhibitors for receptor binding domain of sars-cov-2 omicron and its sub-variants: an in-silico approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342843/ https://www.ncbi.nlm.nih.gov/pubmed/35923684 http://dx.doi.org/10.1007/s13205-022-03258-4 |
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