Structure modeling based computer aided T-cell epitope design

Progress in computational modeling for structural biology has motivated the use of molecular mechanics calculations for synthetic peptide design as potential T-cell epitopes (peptides inducing immunogenicity). Short antigen peptides from virus/ bacteria/parasite are recognized by host specific human leukocyte antigen (HLA) molecules for T-cell sensitive cellular immune response. However, HLA molecules are highly polymorphic at the sequence level among ethnic population (American Indian, Australian aboriginal, Black, Caucasoid, Hispanic, Mixed, Oriental, Pacific Islander and Unknown ethnicity). The binding of peptides to host HLA molecules are both specific and sensitive. The use of computer aided molecular modeling principles has been shown for the design of T-cell specific epitopes as potential vaccine candidates. Application of computational techniques such as molecular dynamics simulation (MDS), self consistent ensemble optimization (SCEO), free energy (FE) estimation, computational combinatorial ligand design (CCLD), 3D quantitative structure activity relationship (3D-QSAR) and structure based virtual pockets (SBVP) in HLA-peptide binding prediction is discussed. The ability of modeling and design to predict peptide binding to a wide array of defined HLA alleles finds application in proteome wide scanning of bacteria/virus/parasite proteomes towards cocktail peptide vaccines.