The goal of this project is the application of computational solutions for systematic identification of promiscuous and allele-specific T-cell epitopes to the dengue virus genome for the development of an epitope-based genetic vaccine. Promiscuous T-cell epitopes are the best candidates for vaccine targets and vaccine formulations because they are potentially effective in the broad population. We will focus on systematic computational screening of the dengue virus genome and identification of the HLA-class II and class I "hot-spots" in the viral genome suitable for use in vaccine formulations. The hot-spots are regions of DNA that encode protein sequences with a high density of potential T-cell epitopes in the context of multiple HLA alleles, which are critical for the initiation and regulation of immune responses. Our published and new results show that computational methods can effectively be used for identification of class I (HLA-A2 and -A3 supertype) and class II (HLA-DR) promiscuous T-cell epitopes. These studies use peptide binding data, HLA sequence data, and computational methods of hidden Markov models and artificial neural networks. The preliminary models have been supported with experimental validation. This project will extend the computational screening approach to other major supertypes of class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DQ) molecules. This project will be combined with projects 2 and 4 of this multi-project proposal, which will provide experimental validation of dengue virus hot-spots and enable the refinement of the computational selection of epitopes and the final selection of the peptide sequences to be encoded in a tetravalent dengue vaccine formulation designed to be effective in recipients covering a broad spectrum (>90%) of HLA alleles. Initially, this project will focus on identification of HLA class II T-cell epitopes from a single serotype, and later be extended to all four serotypes of dengue virus. The analysis will also be extended to HLA class I epitopes and analysis of their role in the severe manifestation of the infection, dengue hemorrhagic fever. Dengue virus has a small genome (10.7 kb RNA) and represents an ideal model for establishing protocols for systematic screening of complete genomes of pathogenic organisms. These results will provide the rationale for experiment planning and are expected to result in major savings in the cost and time required for vaccine development. This multi-project program also provides a systematic analysis of the distribution of T-cell epitopes across complete genomes that can be applied in the future to other pathogens.