In silico Prediction of Epitope Based Vaccine Candidates against Powassan Virus Infection

Document Type : Original Article

Author

Research and Scientific Studies Unit, College of Nursing, Jazan University, Jazan - 45142, Saudi Arabia

Abstract

Powassan virus (POWV) is responsible for encephalitis and severe neurological sequelae globally. Peptide target based designing offers a promising therapeutic invention for the eradication of viral infection. Immunoinformatics serves as a powerful tool to screen and select antigenic peptide sequences as potential epitopes for binding affinity with HLA alleles.
In the present study, a computational pipeline was developed for the identification of B-cell and T-cell epitopes for suitable vaccine candidates. Further, immunogenicity and physico-chemical prediction studies enable the discrimination between antigens and non-antigens. Considering the population setting globally, population coverage analysis was also performed for the identification of possible binding alleles (MHC class-I and MHC class-II) of T-cell epitopes.This computational prediction analysis will enhance our understanding of B-cell/T-cell immune response and assist in selecting the antigenic peptide(s) for the formulation of antigen based diagnostic kit or peptide based subunit vaccine design against POWV.

Keywords

Files

Share

How to cite

Statistics