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Immunoinformatics Aided Prediction of Cytotoxic T Cell Epitope of Respiratory Syncytial Virus

Md Nur Ahad Shah, Payal Barua and Md Kawsar Khan*

Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh.

ABSTRACT: The Respiratory Syncytial Virus (RSV) poses the threat of lower respiratory tract infection to the
infants as well as elderlies. As there is no licensed vaccine, alternative vaccine candidates like Epitope-based
vaccines can be considered as a potential candidate. Being conserved among strains and reported to elicit
cytotoxic T cell (CTL) response, the fusion glycoprotein of RSV (RSV-FP) is a first-rate target for epitope based
vaccine designing. As RSV specific CD8+ CTLs are the central cell of viral clearance, the epitopes capable to
generate CTL response are desirable. In this study, available immunoinformatics tools are utilized with a target to predict epitopes on the RSV-FP that elicit strong (CTL) responses. We report seven nine-mer peptides that bind strongly with 17 different HLA, have 100% sequence conservancy and is projected to provide 76.03% population coverage worldwide.

KEYWORDS: epitope based vaccine, RSV-F protein, CTL epitope, human respiratory syncytial virus,
immunoinformatics.

CITATION: Shah, M. N. A., Barua, P. and Khan, M. K. 2015. Immunoinformatics Aided Prediction of Cytotoxic T Cell Epitope of Respiratory Syncytial Virus. Biores Comm. 1(2), 99-104.

CORRESPONDENCE: kawsarkhan-bmb@sust.edu

 

 
 
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