Bioinformatics And Vaccine Discovery

Immunoinformatics is a newly emergent subdiscipline within the informatic sciences that deals specifically with the unique problems of the immune system. Like bioinformatics, immunoinformatics complements, but never replaces, laboratory experimentation. It allows researchers to address, in a systematic manner, the most important questions in the still highly empirical world of immunology and vaccine discovery.

The first vaccine was discovered by Edward Jenner in 1796, when he used cowpox, a related virus, to build protective immunity against viral smallpox in his gardener's son. Later, Pasteur adopted "vaccination"—the word coined by Jenner for his treatment (from the Latin vacca: cow)—for immunization against any disease. In 1980, the World Health Organisation declared that worldwide vaccination had freed the world of smallpox. A vaccine is a molecular or supramolecular agent that induces specific, protective immunity (an enhanced adaptive immune response to subsequent infection) against micro-bial pathogens, and the diseases they cause, by potentiating immune memory and thus mitigating the effects of reinfection. It is now widely accepted that mass vaccination, which takes into account herd immunity, is the most efficacious prophylactic treatment for contagious disease. Traditionally, vaccines have been attenuated or "weakened" whole pathogen vaccines such as BCG

for TB or Sabin's polio vaccine. Issues of safety have encouraged other vaccine strategies to develop, focusing on antigen and epitope vaccines. Hepatitis B vaccine is an antigen—or subunit—vaccine, and many epitope-based vaccines have now entered clinical trials. A generally useful polyepitope vaccine might contain several T cell epitopes and several B cell epitopes, plus nonprotein-aceous "danger signals," and may be a synthetic vaccine or a natural antigen, delivered as a protein, via live viral vectors, or as raw DNA, possibly accompanied by administration of an adjuvant, a molecule or preparation that exacerbates immune responses.

However, despite their practical and societal value, vaccines remain only a small component of the global pharmaceutical market ($5 billion out of $350 billion sales in 2000). The vaccine market is dominated by just four large manufacturers: GlaxoSmithKline, Aventis Pasteur, Wyeth, and Merck & Co. There is, however, a strong resurgence of interest in vaccines, with a growing cluster of small vaccine companies and biotech firms, led by Chiron.

Vaccinology and immunology are now at a turning point. After centuries of empirical research, they are on the brink of reinventing themselves as a genome-based, quantitative science. Immunological disciplines must capitalize on an overwhelming deluge of data delivered by high-throughput, postge-nomic technologies, data that are mystifyingly complex and delivered on an inconceivable scale. High-throughput approaches are engineering a paradigm shift from hypothesis to data-driven research. Immunovaccinology is a rational form of vaccinology based on our growing understanding of the mechanisms that underpin immunology. It too must make full use of what postgenomic technologies can deliver.

Hitherto, bioinformatics support for preclinical drug discovery has focused on target discovery. Reflecting the economics, support for vaccines has not flourished. As interest in the vaccine sector grows, this situation is beginning to alter. There have been two main types of informatics support for vaccines. The first is standard bioinformatics support, technically indistinguishable from support for more general target discovery. This includes genomic annotation, not just of the human genome, but of pathogenic and opportunistic bacterial, viral, and parasite species. It also includes immunotranscriptomics, the application of microarray analysis to the immune system. The other type of support is focussed on immunoinformatics and addresses problems such as the accurate prediction of immunogenicity, manifest as the identification of epitopes or the prediction of whole protein antigenicity. The immune system is complex and hierarchical, exhibiting emergent behavior at all levels, yet at its heart are straightforward molecular recognition events that are indistinguishable from other types of biomacromolecular interaction. The T cell, a specialized type of immune cell mediating cellular immunity, constantly patrols the body seeking out foreign proteins originating from pathogens. T cells express a particular receptor: the T cell receptor (TCR), which exhibits a wide range of selectivities and affinities. TCRs bind to major histocompatibility complexes (MHCs) presented on the surfaces of other cells. These proteins bind small peptide fragments, or epitopes, derived from both host and pathogen proteins. It is recognition of such complexes that lies at the heart of both the adaptive, and memory, cellular immune response. The binding of an epitope to a MHC protein, or a TCR to a peptide-MHC complex, or an antigen to an antibody, is, at the level of underlying physicochemical phenomena, identical in nature to drug-receptor interactions. Thus we can use techniques of proven provenance developed in bioinformatics and computational chemistry to address these problems. Immunogenicity manifests itself through both humoral (mediated through the binding of whole protein antigens by antibodies) and cellular (mediated by the recognition of proteolytically cleaved peptides by T cells) immunology. Whereas the prediction of B cell epitopes remains primitive, or depends on an often-elusive knowledge of protein structure, many sophisticated methods for the prediction of T cell epitopes have been developed [12].

We have reached a turning point where several technologies have achieved maturity: predictive immunoinformatics methods on the one hand and post-genomic strategies on the other. Although more accurate prediction algorithms are needed, covering more MHC alleles in more species, the paucity of convincing evaluations of reported algorithms is a confounding factor in the take-up of this technology: For immunoinformatics approaches to be used routinely by experimental immunologists, methods must be tested rigorously for a large enough number of peptides that their accuracy can be seen to work to statistical significance. To enable this requires more than improved methods and software; it necessitates building immunoinformatics into the basic strategy of immunological investigation, and it needs the confidence of experimentalists to commit laboratory work on this basis.

The next stage will come with closer connections between immunoinfor-maticians and experimentalists searching for new vaccines, both academic and commercial, conducted under a collaborative or consultant regime. In such a situation, work progresses cyclically using and refining models and experiments, moving toward the goal of effective and efficient vaccine development. Methods that accurately predict individual epitopes or immunogenic proteins, or eliminate microbial virulence factors, will prove to be crucial tools for tomorrow's vaccinologist. Epitope prediction remains a grand scientific challenge, being both difficult, and therefore exciting, and of true utilitarian value. Moreover, it requires not only an understanding of immunology but also the integration of many disciplines, both experimental and theoretical. The synergy of these disciplines will greatly benefit immunology and vaccinology, leading to the enhanced discovery of improved laboratory reagents, diagnostics, and vaccine candidates.

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  • magnus
    What is the impact of vaccine discovery in computer application?
    12 months ago

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