Literature DB >> 10689116

Specific and general HLA-DR binding motifs: comparison of algorithms.

F Borrás-Cuesta1, J Golvano, M García-Granero, P Sarobe, J Riezu-Boj, E Huarte, J Lasarte.   

Abstract

Using panels of peptides well characterized for their ability to bind to HLA DR1, DRB1*1101, or DRB1*0401 molecules, algorithms were deduced to predict binding to these molecules. These algorithms consist of blocks of 8 amino acids containing an amino acid anchor (Tyr, Phe, Trp, Leu, Ile, or Val) at position i and different amino acid combinations at positions i+2 to i+7 depending on the class II molecule. The sensitivity (% of correctly predicted binder peptides) and specificity (% of correctly predicted non-binder peptides) of these algorithms, were tested against different independent panels of peptides and compared to other algorithms reported in the literature. Similarly, using a panel of 232 peptides able to bind to one or more HLA molecules as well as 43 non-binder peptides, we deduced a general motif for the prediction of binding to HLA-DR molecules. The sensitivity and specificity of this general motif was dependent on the threshold score used for the predictions. For a score of 0.1, the sensitivity and specificity were 84.7% and 69.8%, respectively. This motif was validated against several panels of binder and non-binder peptides reported in the literature, as well as against 35, 15-mer peptides from hepatitis C virus core protein, that were synthesized and tested in a binding assay against a panel of 19 HLA-DR molecules. The sensitivities and specificities against these panels of peptides were similar to those attained against the panels used to deduce the algorithm. These results show that comparison of binder and non-binder peptides, as well as correcting for the relative abundance of amino acids in proteins, is a useful approach to deduce performing algorithms to predict binding to HLA molecules.

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Year:  2000        PMID: 10689116     DOI: 10.1016/s0198-8859(99)00153-6

Source DB:  PubMed          Journal:  Hum Immunol        ISSN: 0198-8859            Impact factor:   2.850


  11 in total

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4.  HLA-DM constrains epitope selection in the human CD4 T cell response to vaccinia virus by favoring the presentation of peptides with longer HLA-DM-mediated half-lives.

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5.  GM-CSF production allows the identification of immunoprevalent antigens recognized by human CD4+ T cells following smallpox vaccination.

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6.  Prediction of MHC class II binding peptides based on an iterative learning model.

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7.  Human CD4+ T cell epitopes from vaccinia virus induced by vaccination or infection.

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Journal:  PLoS Comput Biol       Date:  2013-06-06       Impact factor: 4.475

9.  A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach.

Authors:  Peng Wang; John Sidney; Courtney Dow; Bianca Mothé; Alessandro Sette; Bjoern Peters
Journal:  PLoS Comput Biol       Date:  2008-04-04       Impact factor: 4.475

10.  Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes.

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