In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes

Coronaviruses (2019-nCoV) are large single-stranded RNA viruses that usually cause respiratory infections with a crude lethality ratio of 3.8% and high levels of transmissibility. There is yet no applicable clinical evaluation to assess the efficacy of various therapeutic agents that have been sugge...

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Main Authors: B. Oso, I. Olaoye, C. Ogidi
Format: Article
Language:English
Published: Razi Vaccine and Serum Research Institute 2021-11-01
Series:Archives of Razi Institute
Subjects:
Online Access:https://archrazi.areeo.ac.ir/article_122865_04d05eea2c70940d6d34168784b44b35.pdf
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author B. Oso
I. Olaoye
C. Ogidi
author_facet B. Oso
I. Olaoye
C. Ogidi
author_sort B. Oso
collection DOAJ
description Coronaviruses (2019-nCoV) are large single-stranded RNA viruses that usually cause respiratory infections with a crude lethality ratio of 3.8% and high levels of transmissibility. There is yet no applicable clinical evaluation to assess the efficacy of various therapeutic agents that have been suggested as investigational drugs against the viruses despite their respective supposed hypothetical claims due to their antiviral potentials. Moreover, the development of a safe and effective vaccine has been suggested as an intervention to control the 2019-nCoV pandemic. However, a major concern in the development of a 2019-nCoV vaccine is the possibility of stimulating a corresponding immune response without enhancing the induction of the disease and associated side effects. The present investigation was carried out by predicting the antigenicity of the primary sequences of 2019-nCoV structural proteins and identification of B-cell and T-cell epitopes through the Bepipred and PEPVAC servers, respectively. The peptides of the vaccine construct include the selected epitopes based on the VaxiJen score with a threshold of 1.0 and β-defensinas an adjuvant. The putative binding of the vaccine constructs to intracellular toll-like receptors (TLRs) was assessed through molecular docking analysis and molecular dynamics simulations. The selected epitopes for the final vaccine construct are DPNFKD, SPLSLN, and LELQDHNE as B-cell epitopes and EPKLGSLVV, NFKDQVILL, and SSRSSSRSR as T-cell epitopes. The molecular docking analysis showed the vaccine construct could have favorable interactions with TLRs as indicated by the negative values of the computed binding energies. The constructed immunogen based on the immune informatics study could be employed in the strategy to develop potential vaccine candidates against 2019-nCoV.
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spelling doaj.art-09f67b237ebf4f8d861147e8642fb6412022-12-22T00:21:14ZengRazi Vaccine and Serum Research InstituteArchives of Razi Institute0365-34392008-98722021-11-017651191120210.22092/ari.2020.351605.1526122865In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell EpitopesB. Oso0I. Olaoye1C. Ogidi2Department of Biochemistry, McPherson University, Seriki Sotayo, Ogun State, NigeriaDepartment of Biochemistry, McPherson University, Seriki Sotayo, Ogun State, NigeriaSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, EnglandCoronaviruses (2019-nCoV) are large single-stranded RNA viruses that usually cause respiratory infections with a crude lethality ratio of 3.8% and high levels of transmissibility. There is yet no applicable clinical evaluation to assess the efficacy of various therapeutic agents that have been suggested as investigational drugs against the viruses despite their respective supposed hypothetical claims due to their antiviral potentials. Moreover, the development of a safe and effective vaccine has been suggested as an intervention to control the 2019-nCoV pandemic. However, a major concern in the development of a 2019-nCoV vaccine is the possibility of stimulating a corresponding immune response without enhancing the induction of the disease and associated side effects. The present investigation was carried out by predicting the antigenicity of the primary sequences of 2019-nCoV structural proteins and identification of B-cell and T-cell epitopes through the Bepipred and PEPVAC servers, respectively. The peptides of the vaccine construct include the selected epitopes based on the VaxiJen score with a threshold of 1.0 and β-defensinas an adjuvant. The putative binding of the vaccine constructs to intracellular toll-like receptors (TLRs) was assessed through molecular docking analysis and molecular dynamics simulations. The selected epitopes for the final vaccine construct are DPNFKD, SPLSLN, and LELQDHNE as B-cell epitopes and EPKLGSLVV, NFKDQVILL, and SSRSSSRSR as T-cell epitopes. The molecular docking analysis showed the vaccine construct could have favorable interactions with TLRs as indicated by the negative values of the computed binding energies. The constructed immunogen based on the immune informatics study could be employed in the strategy to develop potential vaccine candidates against 2019-nCoV.https://archrazi.areeo.ac.ir/article_122865_04d05eea2c70940d6d34168784b44b35.pdf2019-ncovepitopeimmunityimmunoinformaticsvaccine
spellingShingle B. Oso
I. Olaoye
C. Ogidi
In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
Archives of Razi Institute
2019-ncov
epitope
immunity
immunoinformatics
vaccine
title In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
title_full In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
title_fullStr In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
title_full_unstemmed In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
title_short In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
title_sort in silico design of a vaccine candidate for sar s cov 2 based on multiple t cell and b cell epitopes
topic 2019-ncov
epitope
immunity
immunoinformatics
vaccine
url https://archrazi.areeo.ac.ir/article_122865_04d05eea2c70940d6d34168784b44b35.pdf
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