Computational binding assays of antigenic peptides

Computational vaccinology and epitope vaccine design by immunoinformatics

Human immune system includes variety of different cells and molecules correlating with other body systems. These instances complicate the analysis of the system; particularly in postgenomic era by introducing more amount of data, the complexity is increased and necessity of using computational approaches to process and interpret them is more tangible.Immunoinformatics as a subset of bioinformatics is a new approach with variety of tools and databases that facilitate analysis of enormous amount of immunologic data obtained from experimental researches. In addition to directing the insight regarding experiment selections, it helps new thesis design which was not feasible with conventional methods due to the complexity of data. Considering this features immunoinformatics appears to be one of the fields that accelerate the immunological research progression.In this study we discuss advances in genomics and vaccine design and their relevance to the development of effective vaccines furthermore several division of this field and available tools in each item are introduced.

Dissecting the dynamics of HIV-1 protein sequence diversity

The rapid mutation of human immunodeficiency virus-type 1 (HIV-1) and the limited characterization of the composition and incidence of the variant population are major obstacles to the development of an effective HIV-1 vaccine. This issue was addressed by a comprehensive analysis of over 58,000 clade B HIV-1 protein sequences reported over at least 26 years. The sequences were aligned and the 2,874 overlapping nonamer amino acid positions of the viral proteome, each a possible core binding domain for human leukocyte antigen molecules and T-cell receptors, were quantitatively analyzed for four patterns of sequence motifs: (1) "index", the most prevalent sequence; (2) "major" variant, the most common variant sequence; (3) "minor" variants, multiple different sequences, each with an incidence less than that of the major variant; and (4) "unique" variants, each observed only once in the alignment. The collective incidence of the major, minor, and unique variants at each nonamer position represented the total variant population for the position. Positions with more than 50% total variants contained correspondingly reduced incidences of index and major variant sequences and increased minor and unique variants. Highly diverse positions, with 80 to 98% variant nonamer sequences, were present in each protein, including 5% of Gag, and 27% of Env and Nef, each. The multitude of different variant nonamer sequences (i.e. nonatypes; up to 68%) at the highly diverse positions, represented by the major, multiple minor, and multiple unique variants likely supported variants function both in immune escape and as altered peptide ligands with deleterious T-cell responses. The patterns of mutational change were consistent with the sequences of individual HXB2 and C1P viruses and can be considered applicable to all HIV-1 viruses. This characterization of HIV-1 protein mutation provides a foundation for the design of peptide-based vaccines and therapeutics.

Inflammatory and autoimmune reactions in atherosclerosis and vaccine design informatics

Atherosclerosis is the leading pathological contributor to cardiovascular morbidity and mortality worldwide. As its complex pathogenesis has been gradually unwoven, the regime of treatments and therapies has increased with still much ground to cover. Active research in the past decade has attempted to develop antiatherosclerosis vaccines with some positive results. Nevertheless, it remains to develop a vaccine against atherosclerosis with high affinity, specificity, efficiency, and minimal undesirable pathology. In this review, we explore vaccine development against atherosclerosis by interpolating a number of novel findings in the fields of vascular biology, immunology, and bioinformatics. With recent technological breakthroughs, vaccine development affords precision in specifying the nature of the desired immune response—useful when addressing a disease as complex as atherosclerosis with a manifold of inflammatory and autoimmune components. Moreover, our exploration of available bioinformatic tools for epitope-based vaccine design provides a method to avoid expenditure of excess time or resources.

Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding

Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-A11 binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes.