tetano
Editor, Senior Moderator
F1000Res
. 2021 Jan 23;10:44.
doi: 10.12688/f1000research.36371.1. eCollection 2021.
Reverse vaccinology approach towards the in-silico multiepitope vaccine development against SARS-CoV-2
Vipul Kumar[SUP] 1 [/SUP], Sudhakar Kancharla[SUP] 2 [/SUP], Prachetha Kolli[SUP] 3 [/SUP], Manoj Jena[SUP] 1 [/SUP]
Affiliations
Abstract
Background: The novel severe acute respiratory syndrome related corona virus-2 (SARS-CoV-2) belongs to the "Coronaviridae" family and order "Nidovirales", which has caused the pandemic coronavirus disease 2019 (COVID-19). SARS-CoV-2 has been spread in more than a 100 countries, and more than a million have lost their lives. Vaccination and immunization could be an effective strategy to combat fatal COVID-19. Methods: For identification of effective vaccine candidate against COVID-19, various immunoinformatics online tools and softwares were used to predict epitopes. 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 beta-defensin-3 and human beta-defensin-2 at N and C terminal, respectively. Results: The 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. The docked complex was 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 efficient expression of the predicted vaccine. Conclusion: 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: COVID-19; Immunoinformatics; SARS-CoV-2; docking; multiepitope; simulations.
. 2021 Jan 23;10:44.
doi: 10.12688/f1000research.36371.1. eCollection 2021.
Reverse vaccinology approach towards the in-silico multiepitope vaccine development against SARS-CoV-2
Vipul Kumar[SUP] 1 [/SUP], Sudhakar Kancharla[SUP] 2 [/SUP], Prachetha Kolli[SUP] 3 [/SUP], Manoj Jena[SUP] 1 [/SUP]
Affiliations
- PMID: 33841800
- PMCID: PMC8009247
- DOI: 10.12688/f1000research.36371.1
Abstract
Background: The novel severe acute respiratory syndrome related corona virus-2 (SARS-CoV-2) belongs to the "Coronaviridae" family and order "Nidovirales", which has caused the pandemic coronavirus disease 2019 (COVID-19). SARS-CoV-2 has been spread in more than a 100 countries, and more than a million have lost their lives. Vaccination and immunization could be an effective strategy to combat fatal COVID-19. Methods: For identification of effective vaccine candidate against COVID-19, various immunoinformatics online tools and softwares were used to predict epitopes. 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 beta-defensin-3 and human beta-defensin-2 at N and C terminal, respectively. Results: The 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. The docked complex was 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 efficient expression of the predicted vaccine. Conclusion: 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: COVID-19; Immunoinformatics; SARS-CoV-2; docking; multiepitope; simulations.