Virus-epitope vaccine design: Informatic matching the HLA-I polymorphism to the virus genome

Attempts to develop peptide vaccines, based on a limited number of peptides face two problems: HLA polymorphism and the high mutation rate of viral epitopes. We have developed a new genomic method that ensures maximal coverage and thus maximal applicability of the peptide vaccine. The same method also promises a large number of epitopes per HLA to prevent escape via mutations. Our design can be applied swiftly in order to face rapidly emerging viral diseases. We use a genomic scan of all candidate peptides and join them optimally. For a given virus, we use algorithms computing: peptide cleavage probability, transfer through TAP and MHC binding for a large number of HLA alleles. The resulting peptide libraries are pruned for peptides that are not conserved or are too similar to self peptides. We then use a genetic algorithm to produce an optimal protein composed of peptides from this list properly ordered for cleavage. The selected peptides represent an optimal combination to cover all HLA alleles and all viral proteins. We have applied this method to HCV and found that some HCV proteins (mainly envelope proteins) represent much less peptide than expected. A more detailed analysis of the peptide variability shows a balance between the attempts of the immune system to detect less mutating peptides, and the attempts of viruses to mutate peptides and avoid detection by the immune system. In order to show the applicability of our method, we have further used it on HIV-I, Influenza H3N2 and the Avian Flu Viruses.