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Bioinformatics: A Concept-Based Introduction pp 129–154Cite as

Computational Immunology: HLA-peptide Binding Prediction

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Abstract

HLA molecules are immune proteins that play an important role in T-cell mediated immune response. They bind short 8-20 residues long peptides from antigen proteins to induce immune response. Therefore, the binding of short antigen peptides to HLA molecules is the rate limiting step in T-cell mediated immune response. Several constructs of overlapping short peptides can be designed from a given protein antigen sequence. The number of overlapping peptides is large for systematic experimental testing. Moreover, HLA molecules are highly polymorphic and more than 1500 HLA alleles are known among the human population. Thus, the binding of short peptides to HLA is combinatorial and specific. The binding can be studied using expensive and laborious competitive binding assays. Alternatively, prediction of peptide binding to HLA molecules is highly useful. Efficient prediction models enable systematic scanning of candidate peptides in an effective manner. Here, we describe some commonly used prediction models.

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Authors and Affiliations

  1. Biomedical Informatics, India

    Pandjassarame Kangueane

  2. Nanyang Technological University, Singapore

    Bing Zhao & Meena K. Sakharkar

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  1. Pandjassarame Kangueane
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  2. Bing Zhao
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  1. Roskamp Institute, 2040 Whitfield Avenue, Sarasota, FL 34243

    Venkatarajan S. Mathura

  2. Biomed-Informatics, 17A Main Road, Irulan Chandai Annex, Pondicherry 607 402, India

    Pandjassarame Kangueane

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Kangueane, P., Zhao, B., Sakharkar, M.K. (2009). Computational Immunology: HLA-peptide Binding Prediction. In: Mathura, V.S., Kangueane, P. (eds) Bioinformatics: A Concept-Based Introduction. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-84870-9_11

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