GENOME-WIDE PREDICTION OF HUMAN PAPILLOMA VIRUS SPECIFIC T-CELL EPITOPES USING A COMBINATION OF MATRIX BASED COMPUTATIONAL TOOLS

Objective: To predict the immunogenic epitopes from human papillomavirus (HPV) virus using matrix based computational tools.Methods: In the present study, three matrix based algorithms, SYFPETHI, BIMAS and RANKPEP were used to predict the cytotoxic T lymphocyte (CTL) epitopes of HPV 16 and 18. The ability of the peptides to bind HLA A_0201, a most common allele, was evaluated using these algorithms. High scoring peptides were considered as potential binders.Results: Evaluation of HPV 16 proteome resulted in the prediction of 249 peptides as potential binders. Out of these only 25 peptides were predicted as binders by all three algorithms. Analysis of HPV 18 predicted 215 peptides, as potential binders. Among the 215 peptides only 20 peptides were predicted as binders by all three algorithms.Conclusion: The efficacy of these peptides in inducing a stronger immune response needs to be tested using in vitro and in vivo assays. The identified epitopes could be used in designing a novel epitope vaccine for HPV.