In silico Prediction of Epitope Based Vaccine Candidates against Powassan Virus Infection | ||||
| Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology | ||||
| Article 4, Volume 10, Issue 1, June 2018, Page 39-47 PDF (348.76 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/eajbsc.2018.13654 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Mohammed Yahya Areeshi | ||||
| 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 | ||||
| POWV; epitope prediction; toxicity prediction; population coverage analysis | ||||
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