Article

The MHC motif viewer: A visualization tool for MHC binding motifs

Department of Pharmaceutics and Analytical Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, Denmark.
Current protocols in immunology / edited by John E. Coligan ... [et al.] 02/2010; Chapter 18:Unit 18.17. DOI: 10.1002/0471142735.im1817s88
Source: PubMed

ABSTRACT

In vertebrates, the onset of cellular immune reactions is controlled by presentation of peptides in complex with major histocompatibility complex (MHC) molecules to T cell receptors. In humans, MHCs are called human leukocyte antigens (HLAs). Different MHC molecules present different subsets of peptides, and knowledge of their binding specificities is important for understanding differences in the immune response between individuals. Algorithms predicting which peptides bind a given MHC molecule have recently been developed with high prediction accuracy. The utility of these algorithms is hampered by the lack of tools for browsing and comparing specificity of these molecules. We have developed a Web server, MHC Motif Viewer, which allows the display of the binding motif for MHC class I proteins for human, chimpanzee, rhesus monkey, mouse, and swine, as well as HLA-DR protein sequences. The binding motif for each MHC molecule is predicted using state-of-the-art, pan-specific peptide-MHC binding-prediction methods, and is visualized as a sequence logo, in a format that allows for a comprehensive interpretation of binding motif anchor positions and amino acid preferences.

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    • "HLA-B * 27:05 allele has been analyzed due to the previous experimental results demonstrating its interaction with LILRB1[46]and for its extensively studied MHC binding pocket capability. In particular HLA-B * 27:05 has been evaluated only for P1 residues with a positive score in the MHC motif Viewer matrix and therefore capable to be bonded in pocket A[47]. The presence of Arginine in pocket 1 induces the strongest number of contacts in HLA-B * 27:05/LILRB1.01 "
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    ABSTRACT: KIR3DL1 and LILRB1 interact with HLA class I. Using KIR3DL1/HLA-B interaction to set up the procedure, structural immune-informatics approaches have been performed in LILRB1/HLA-B alleles’ combination also considering the contribution of the HLA bound peptide. All KIR3DL1 alleles interact strongly with HLA-B alleles carrying Bw4 epitope and negative charged amino acid residues in peptide position P8 disrupt KIR3DL1 binding. HLA-B alleles carrying Ile 194 show a higher strength of interaction with LILRB1 in all the analyzed haplotypes. Finally, we hypothesize a contribution of the amino acid at position 1 of the HLA bound peptide in the modulation of HLA-B/LILRB1 interaction.
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    • "For each set of peptides, the retrieved scoring matrix was employed to identify the binding regions in the peptides. For datasets with small numbers of peptides, binding motifs were obtained using the MHC Motif Viewer [39]. PredivacDB was built using the identified nonameric regions and contains 2695 high-affinity sequences accounting for 29 HLA class II alleles (Additional file 1: Table S1). "
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    ABSTRACT: Background CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge. Results We developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design. Conclusions The comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/.
    Full-text · Article · Feb 2013 · BMC Bioinformatics
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    • "The total height of the stack represents the sequence conservation (the information content), while the individual height of the symbols relates to the relative frequency of that particular symbol at that position. Letter shown upside-down are underrepresented compared to the background (for details see Rapin et al. (2010)). "
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    ABSTRACT: In all vertebrate animals, CD8(+) cytotoxic T lymphocytes (CTLs) are controlled by major histocompatibility complex class I (MHC-I) molecules. These are highly polymorphic peptide receptors selecting and presenting endogenously derived epitopes to circulating CTLs. The polymorphism of the MHC effectively individualizes the immune response of each member of the species. We have recently developed efficient methods to generate recombinant human MHC-I (also known as human leukocyte antigen class I, HLA-I) molecules, accompanying peptide-binding assays and predictors, and HLA tetramers for specific CTL staining and manipulation. This has enabled a complete mapping of all HLA-I specificities ("the Human MHC Project"). Here, we demonstrate that these approaches can be applied to other species. We systematically transferred domains of the frequently expressed swine MHC-I molecule, SLA-1*0401, onto a HLA-I molecule (HLA-A*11:01), thereby generating recombinant human/swine chimeric MHC-I molecules as well as the intact SLA-1*0401 molecule. Biochemical peptide-binding assays and positional scanning combinatorial peptide libraries were used to analyze the peptide-binding motifs of these molecules. A pan-specific predictor of peptide-MHC-I binding, NetMHCpan, which was originally developed to cover the binding specificities of all known HLA-I molecules, was successfully used to predict the specificities of the SLA-1*0401 molecule as well as the porcine/human chimeric MHC-I molecules. These data indicate that it is possible to extend the biochemical and bioinformatics tools of the Human MHC Project to other vertebrate species.
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