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Research Article
Reverse vaccinology approach towards the in-silico multiepitope vaccine development against SARS-CoV-2
Manoj Jena
Lovely Professional University, Punjab, India
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
The novel severe acute respiratory syndrome related corona virus-2 (SARS-CoV-2) belongs to the “Coronaviridae” family and order “Nidovirales” cause coronavirus disease (COVID19). The SARS-CoV-2 has been spread in more than a hundred countries, and more than a million have lost their lives. Recently COVID-19 has been declared as pandemic worldwide. Vaccination and immunization could only be an effective strategy to combat this fatal COVID-19. For identification of the effective vaccine candidate against COVID-19, various immunoinformatics online tools and software were used to predict the epitopes. The cytotoxic T cell epitopes, Helper T cell epitopes, and B cell epitopes from three structural polyproteins ( Spike, Membrane, and Nucleocapsid (SMN) ) based on the binding affinity towards MHC , antigenicity, non-allergenicity, and non-toxicity were identified for vaccine development. The multiepitope based vaccine was constructed linking two additional adjuvants human betadefensin-3 and human beta-defensin-2 at N and C terminal, respectively. Constructed vaccine sequence was found to be a good antigen and non-allergen for the human body. The constructed vaccine was docked with the TLR-3 receptor. And the docked complex then further taken for Molecular dynamics simulations and RMSD was calculated, which showed stable binding of the complex. The codon adaptation index (CAI) of 0.92 and GC content of 55.5% for E.coli (k12) strain suggested the efficient expression of the predicted vaccine. The current study can be helpful in the reduction of time and cost for further experimental validations and could give a valuable contribution against this pandemic.
Keywords
SARS-CoV-2, COVID-19, Immunoinformatics, multi-epitope, docking, MD simulations
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This is a preprint. It has not completed peer review.
Research Article
Reverse vaccinology approach towards the in-silico multiepitope vaccine development against SARS-CoV-2
Manoj Jena
Lovely Professional University, Punjab, India
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 27 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The novel severe acute respiratory syndrome related corona virus-2 (SARS-CoV-2) belongs to the “Coronaviridae” family and order “Nidovirales” cause coronavirus disease (COVID19). The SARS-CoV-2 has been spread in more than a hundred countries, and more than a million have lost their lives. Recently COVID-19 has been declared as pandemic worldwide. Vaccination and immunization could only be an effective strategy to combat this fatal COVID-19. For identification of the effective vaccine candidate against COVID-19, various immunoinformatics online tools and software were used to predict the epitopes. The cytotoxic T cell epitopes, Helper T cell epitopes, and B cell epitopes from three structural polyproteins ( Spike, Membrane, and Nucleocapsid (SMN) ) based on the binding affinity towards MHC , antigenicity, non-allergenicity, and non-toxicity were identified for vaccine development. The multiepitope based vaccine was constructed linking two additional adjuvants human betadefensin-3 and human beta-defensin-2 at N and C terminal, respectively. Constructed vaccine sequence was found to be a good antigen and non-allergen for the human body. The constructed vaccine was docked with the TLR-3 receptor. And the docked complex then further taken for Molecular dynamics simulations and RMSD was calculated, which showed stable binding of the complex. The codon adaptation index (CAI) of 0.92 and GC content of 55.5% for E.coli (k12) strain suggested the efficient expression of the predicted vaccine. The current study can be helpful in the reduction of time and cost for further experimental validations and could give a valuable contribution against this pandemic.
Figure 1
Figure 2
Figure 3
Due to technical limitations the Tables are available as a download in the Supplementary Files.