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Major histocompatibility complex class I binding predictions as a tool in epitope discovery
Authors:Claus Lundegaard  Ole Lund  Søren Buus  Morten Nielsen
Affiliation:1Department of Systems Biology, Centre for Biological Sequence Analysis, Technical University of Denmark, Lyngby;2Faculty of Health Sciences, Laboratory of Experimental Immunology, University of Copenhagen, Copenhagen, Denmark
Abstract:Over the last decade, in silico models of the major histocompatibility complex (MHC) class I pathway have developed significantly. Before, peptide binding could only be reliably modelled for a few major human or mouse histocompatibility molecules; now, high‐accuracy predictions are available for any human leucocyte antigen (HLA) ‐A or ‐B molecule with known protein sequence. Furthermore, peptide binding to MHC molecules from several non‐human primates, mouse strains and other mammals can now be predicted. In this review, a number of different prediction methods are briefly explained, highlighting the most useful and historically important. Selected case stories, where these ‘reverse immunology’ systems have been used in actual epitope discovery, are briefly reviewed. We conclude that this new generation of epitope discovery systems has become a highly efficient tool for epitope discovery, and recommend that the less accurate prediction systems of the past be abandoned, as these are obsolete.
Keywords:cytotoxic T lymphocytes  epitope prediction  human leucocyte antigen  major histocompatibility complex class I  major histocompatibility complex–peptide binding
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