Abstract
The identification of major histocompatibility complex (MHC) class-II restricted peptides is an important goal in human immunological research leading to peptide based vaccine designing. These MHC class II peptides are predominantly recognized by CD4+ T-helper cells, which when turned on, have profound immune regulatory effects. Thus, prediction of such MHC class-II binding peptide is very helpful towards epitope based vaccine designing. HLA-DR proteins were found to be associated with autoimmune diseases e.g. HLA-DRB1*0401 with rheumatoid arthritis. It is important for the treatment of autoimmune diseases to determine, which peptides bind to MHC class II molecules. The experimental methods for identification of these peptides are both time consuming and cost intensive. Therefore, computational methods have been found helpful in classifying these peptides as binders or non-binders. We have applied negative selection algorithm, an artificial immune system approach to predict MHC class-II binders and non-binders. For the evaluation of the NSA algorithm, five fold cross validation has been used and six MHC class-II alleles have been taken. The average area under ROC curve for HLA-DRB1*0301, DRB1*0401, DRB1*0701, DRB1*1101, DRB1*1501, DRB1*1301 have been found to be 0.75, 0.77, 0.71, 0.72, 0.69, and 0.84, respectively indicating good predictive performance for the small training set. Key words: Negative selection algorithm, MHC class-II peptides, artificial immune system, epitope, vaccine designing, human immunology.
Highlights
The CD8+ cytotoxic T-cells (CTL) immune response and CD4+ T-helper (Th) immune response is stimulated by binding of peptides to major histocompatibility complex (MHC) Class I and MHC Class II molecules, respectively (Jacques and Steinman, 1998; De Groot et al, 2002)
Entered the endocytic pathway of the antigen processing cell (APC) are processed there. These are generally presented by MHC class II molecules to T-helper cells, which, when turned on, have profound immune regulatory effects
DRB1*0401-restricted T cell epitopes from human GAD65, 274-286, and 115-127 are immunogenic in transgenic mice expressing functional DRB1*0401 MHC class II molecules but not in non-transgenic littermates
Summary
The CD8+ cytotoxic T-cells (CTL) immune response and CD4+ T-helper (Th) immune response is stimulated by binding of peptides to major histocompatibility complex (MHC) Class I and MHC Class II molecules, respectively (Jacques and Steinman, 1998; De Groot et al, 2002). DRB1*0401-restricted T cell epitopes from human GAD65, 274-286, and 115-127 are immunogenic in transgenic mice expressing functional DRB1*0401 MHC class II molecules but not in non-transgenic littermates. The presentation of these two T-cell epitopes in the islets of DRB1*0401individuals who are at risk for type 1 diabetes may allow for antigen-specific recruitment of regulatory cells to the islets following peptide immunization. A number of methods have been developed for the prediction of MHC class-II binding peptides from an antigenic sequence, beginning with, early motif based methods (Chicz et al, 1993; Sette et al, 1993; Hammer et al, 1993), to different scoring matrices based methods (Rammensee et al, 1995; Marshal et al, 1995; Southwood et al, 1998; Wang et al, 2008). Other computational approaches used for epitope prediction are: genetic algorithm and fuzzy algorithm with artificial neural network, decision tree algorithms, quadratic and linear programming, support vector machine, Gibbs motif sampler, threading methods, structure based methods (Liliana et al, 2003; Soam et al, 2012; Singh and Mishra, 2008; Yael and Hanah, 2004; Ingvar et al, 2004)
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