Discriminating antigen and non-antigen using proteome dissimilarity III: tumour and parasite antigens

West Nile Virus Vaccine Design by T Cell Epitope Selection: In Silico Analysis of Conservation, Functional Cross-Reactivity with the Human Genome, and Population Coverage

West Nile Virus (WNV) causes a debilitating and life-threatening neurological disease in humans. Since its emergence in Africa 50 years ago, new strains of WNV and an expanding geographical distribution have increased public health concerns. There are no licensed therapeutics against WNV, limiting effective infection control. Vaccines represent the most efficacious and efficient medical intervention known. Epitope-based vaccines against WNV remain significantly underexploited. Here, we use a selection protocol to identify a set of conserved prevalidated immunogenic T cell epitopes comprising a putative WNV vaccine. Experimentally validated immunogenic WNV epitopes and WNV sequences were retrieved from the IEDB and West Nile Virus Variation Database. Clustering and multiple sequence alignment identified a smaller subset of representative sequences. Protein variability analysis identified evolutionarily conserved sequences, which were used to select a diverse set of immunogenic candidate T cell epitopes. Cross-reactivity and human leukocyte antigen-binding affinities were assessed to eliminate unsuitable epitope candidates. Population protection coverage (PPC) quantified individual epitopes and epitope combinations against the world population. 3 CD8+ T cell epitopes (ITYTDVLRY, TLARGFPFV, and SYHDRRWCF) and 1 CD4+ epitope (VTVNPFVSVATANAKVLI) were selected as a putative WNV vaccine, with an estimated PPC of 97.14%.

Identification of Candidate Vaccine Antigens In Silico

The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental discovery of vaccine antigens, with particular reference to reverse vaccinology, this chapter adumbrates the principal computational approaches currently deployed in the hunt for novel antigens: genome-level prediction of antigens, antigen identification through the use of protein sequence alignment-based approaches, antigen detection through the use of subcellular location prediction, and the use of alignment-independent approaches to antigen discovery. Reference is also made to the recent emergence of various expert systems for protein antigen identification.