Background: Zika virus (ZIKV) is an arbovirus that belongs to family Flaviviridae. The virus has emerged as a global threat and no FDA approved vaccine is available, so an efficient vaccine needs to be designed in order to prevent the infection. Computationally designed vaccines can be used for broad-spectrum therapeutics as they can evoke response against viral infections. In the current study, we have predicted antigenic promiscuous T cell epitopes from Zika virus polyprotein using a range of immune-informatics tools and servers.Methods: A total of 238 polyprotein sequences derived from 238 complete genomes were retrieved using NIAID Virus Pathogen Resource and multiple aligned. Using a consensus sequence, the promiscuous CD8-T cell epitopes were predicted from Propred I and CTLPred and their binding affinities were determined by NetMHC4.0. CD4-T cell epitopes were predicted using ProPred and the binding affinities were determined by MHCPred. Antigenicity score and Immunogenicity score was determined from Vaxijen 2.0 and IEDB immunogenicity tool. Homology was found by pBLAST.Results: Among 78 predicted HLA-I binding epitopes, 19 highly antigenic, immunogenic and high-affinity epitopes are prioritized among which 15 are novel vaccine candidates. However, 66 strong HLA-II interacting T cell epitopes are pooled out from 70 predicted epitopes. Among the shortlisted CD4-T cell epitopes 56 epitopes are novel. Conclusion:Epitope-based vaccines are robust and promising candidates against bacterial and viral infections. The predicted epitopes can serve as potential vaccine candidates. Our study shows promising epitopes that can be used to generate stimulate active immune responses in the majority of the human population around the world, However, our results need validation through experimental studies for confirmation. PeerJ Preprints Abstract:Background:

Background: Zika virus (ZIKV) is an arbovirus that belongs to family Flaviviridae. The virus has emerged as a global threat and no FDA approved vaccine is available, so an efficient vaccine needs to be designed in order to prevent the infection. Computationally designed vaccines can be used for broad-spectrum therapeutics as they can evoke response against viral infections. In the current study, we have predicted antigenic promiscuous T cell epitopes from Zika virus polyprotein using a range of immune-informatics tools and servers.Methods: A total of 238 polyprotein sequences derived from 238 complete genomes were retrieved using NIAID Virus Pathogen Resource and multiple aligned. Using a consensus sequence, the promiscuous CD8-T cell epitopes were predicted from Propred I and CTLPred and their binding affinities were determined by NetMHC4.0. CD4-T cell epitopes were predicted using ProPred and the binding affinities were determined by MHCPred. Antigenicity score and Immunogenicity score was determined from Vaxijen 2.0 and IEDB immunogenicity tool. Homology was found by pBLAST.Results: Among 78 predicted HLA-I binding epitopes, 19 highly antigenic, immunogenic and high-affinity epitopes are prioritized among which 15 are novel vaccine candidates. However, 66 strong HLA-II interacting T cell epitopes are pooled out from 70 predicted epitopes. Among the shortlisted CD4-T cell epitopes 56 epitopes are novel. Conclusion:Epitope-based vaccines are robust and promising candidates against bacterial and viral infections. The predicted epitopes can serve as potential vaccine candidates. Our study shows promising epitopes that can be used to generate stimulate active immune responses in the majority of the human population around the world, However, our results need validation through experimental studies for confirmation. PeerJ Preprints Abstract:Background: