Towards in silico prediction of immunogenic epitopes

Trends in Immunology - Tập 24 - Trang 667-674 - 2003
Darren R. Flower1
1Edward Jenner Institute for Vaccine Research, Compton, Berkshire RG20 7NN, UK

Tài liệu tham khảo

Alix, 1999, Predictive estimation of protein linear epitopes by using the program PEOPLE, Vaccine, 18, 311, 10.1016/S0264-410X(99)00329-1 Thornton, 1986, Location of ‘continuous’ antigenic determinants in the protruding regions of proteins, EMBO J., 5, 409, 10.1002/j.1460-2075.1986.tb04226.x Flower, 2002, Computational Vaccine Design, 136 Deavin, 1996, Statistical comparison of established T-cell epitope predictors against a large database of human and murine antigens, Mol. Immunol., 33, 145, 10.1016/0161-5890(95)00120-4 Nussbaum, 2003, Using the world wide web for predicting CTL epitopes, Curr. Opin. Immunol., 15, 69, 10.1016/S0952791502000043 Brusic, 1999, A neural network model approach to the study of human TAP transporter, Silico Biol., 1, 109 Holzhutter, 1999, A theoretical approach towards the identification of cleavage-determining amino acid motifs of the 20 S proteasome, J. Mol. Biol., 286, 1251, 10.1006/jmbi.1998.2530 Holzhutter, 2000, A kinetic model of vertebrate 20S proteasome accounting for the generation of major proteolytic fragments from oligomeric peptide substrates, Biophys. J., 79, 1196, 10.1016/S0006-3495(00)76374-0 Nussbaum, 2001, PAProC: a prediction algorithm for proteasomal cleavages available on the WWW, Immunogenetics, 53, 87, 10.1007/s002510100300 Kesmir, 2002, Prediction of proteasome cleavage motifs by neural networks, Protein Eng., 15, 287, 10.1093/protein/15.4.287 Altuvia, 2000, Sequence signals for generation of antigenic peptides by the proteasome: implications for proteasomal cleavage mechanism, J. Mol. Biol., 295, 879, 10.1006/jmbi.1999.3392 Housset, 2003, What do TCR–pMHC crystal structures teach us about MHC restriction and alloreactivity?, Trends Immunol., 24, 429, 10.1016/S1471-4906(03)00180-7 Sette, 1989, Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis, Proc. Natl. Acad. Sci. U. S. A., 86, 3296, 10.1073/pnas.86.9.3296 De Groot, 2002, Immuno-informatics: Mining genomes for vaccine components, Immunol. Cell Biol., 80, 255, 10.1046/j.1440-1711.2002.01092.x Bian, 2003, The use of bioinformatics for identifying class II-restricted T-cell epitopes, Methods, 29, 299, 10.1016/S1046-2023(02)00352-3 Schonbach, 2002, Large-scale computational identification of HIV T-cell epitopes, Immunol. Cell Biol., 80, 300, 10.1046/j.1440-1711.2002.01089.x Nielsen, 2003, Reliable prediction of T-cell epitopes using neural networks with novel sequence representations, Protein Sci., 12, 1007, 10.1110/ps.0239403 Udaka, 2002, Empirical evaluation of a dynamic experiment design method for prediction of MHC class I-binding peptides, J. Immunol., 169, 5744, 10.4049/jimmunol.169.10.5744 Donnes, 2002, Prediction of MHC class I binding peptides, using SVMHC, BMC Bioinformatics, 3, 25, 10.1186/1471-2105-3-25 Reche, 2002, Prediction of MHC class I binding peptides using profile motifs, Hum. Immunol., 63, 701, 10.1016/S0198-8859(02)00432-9 Doytchinova, 2002, Additive method for the prediction of protein-peptide binding affinity. application to the MHC class I molecule HLA-A*0201, J. Proteome Res., 1, 263, 10.1021/pr015513z Doytchinova, I.A. and Flower, D.R. Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction of peptides binding to MHC class II molecule DRB1*0401. Bioinformatics (in press). Guan, 2003, HLA-A3 supermotif defined by quantitative structure-activity relationship analysis, Protein Eng., 16, 11, 10.1093/proeng/gzg005 Doytchinova, 2003, The HLA-A2 supermotif: A QSAR definition, Org. Biomol. Chem., 1, 2648, 10.1039/b300707c Yu, 2002, Methods for prediction of peptide binding to MHC molecules: a comparative study, Mol. Med., 8, 137, 10.1007/BF03402006 Blythe, 2002, JenPep, a database of quantitative functional peptide data for immunology, Bioinformatics, 18, 434, 10.1093/bioinformatics/18.3.434 McSparron, 2003, JenPep: a novel computational information resource for immunobiology and vaccinology, J. Chem. Inf. Comput. Sci., 43, 1276, 10.1021/ci030461e Doytchinova, 2002, Physicochemical explanation of peptide binding to HLA-A*0201 major histocompatibility complex: a three-dimensional quantitative structure-activity relationship study, Proteins, 48, 505, 10.1002/prot.10154 Doytchinova, 2002, A comparative molecular similarity index analysis (CoMSIA), study identifies an HLA-A2 binding supermotif, J. Comput. Aided Mol. Des., 16, 535, 10.1023/A:1021917203966 Guan, 2003, A comparative molecular similarity indices (CoMSIA), study of peptide binding to the HLA-A3 superfamily, Bioorg. Med. Chem., 11, 2307, 10.1016/S0968-0896(03)00109-3 Sturniolo, 1999, Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices, Nat. Biotechnol., 17, 555, 10.1038/9858 Zhang, 1998, Structural principles that govern the peptide-binding motifs of class I MHC molecules, J. Mol. Biol., 281, 929, 10.1006/jmbi.1998.1982 Chelvanayagam, 1996, A roadmap for HLA-A, HLA-B, and HLA-C peptide binding specificities, Immunogenetics, 45, 15, 10.1007/s002510050162 Chelvanayagam, 1997, A roadmap for HLA-DR peptide binding specificities, Hum. Immunol., 58, 61, 10.1016/S0198-8859(97)00185-7 Rognan, 1999, Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class I major histocompatibility proteins, J. Med. Chem., 42, 4650, 10.1021/jm9910775 Schueler-Furman, 2000, Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles, Protein Sci., 9, 1838, 10.1110/ps.9.9.1838 Logean, 2001, Customized versus universal scoring functions: application to class I MHC–peptide binding free energy predictions, Bioorg. Med. Chem. Lett., 11, 675, 10.1016/S0960-894X(01)00021-X Logean, 2002, Recovery of known T-cell epitopes by computational scanning of a viral genome, J. Comput. Aided Mol. Des., 16, 229, 10.1023/A:1020244329512 Vasmatzis, 1996, Computational determination of side chain specificity for pockets in class I MHC molecules, Mol. Immunol., 33, 1231, 10.1016/S0161-5890(96)00090-9 Rognan, 1994, Molecular dynamics simulation of MHC–peptide complexes as a tool for predicting potential T-cell epitopes, Biochemistry, 33, 11476, 10.1021/bi00204a009 Krebs, 1999, Long-range effects in protein–ligand interactions mediate peptide specificity in the human major histocompatibilty antigen HLA-B27 (B*2701), Protein Sci., 8, 1393, 10.1110/ps.8.7.1393 Flower, D.R. et al. Computational vaccinology: quantitative approaches. Bioinformatic Strategies for Better Understanding of Immune Function. Novartis Found. Symp., 254 (October 2003), Wiley & Sons (in press). Rammensee, 1999, SYFPEITHI: database for MHC ligands and peptide motifs, Immunogenetics, 50, 213, 10.1007/s002510050595 Doytchinova, 2002, Quantitative approaches to computational vaccinology, Immunol. Cell Biol., 80, 270, 10.1046/j.1440-1711.2002.01076.x Lu, 2000, Use of two predictive algorithms of the World Wide Web for the identification of tumor-reactive T-cell epitopes, Cancer Res., 60, 5223 Andersen, 2000, Poor correspondence between predicted and experimental binding of peptides to class I MHC molecules, Tissue Antigens, 55, 519, 10.1034/j.1399-0039.2000.550603.x Seifert, 2003, An essential role for tripeptidyl peptidase in the generation of an MHC class I epitope, Nat. Immunol., 4, 375, 10.1038/ni905 Saveanu, 2002, Beyond the proteasome: trimming, degradation and generation of MHC class I ligands by auxiliary proteases, Mol. Immunol., 39, 203, 10.1016/S0161-5890(02)00102-5 Kim, 2003, Regulation of cell surface major histocompatibility complex class I expression by the endopeptidase EP3.4.24.15 (thimet oligopeptidase), Biochem. J., 375, 111, 10.1042/bj20030490 Grandea, 2001, Tapasin: an ER chaperone that controls MHC class I assembly with peptide, Trends Immunol., 22, 194, 10.1016/S1471-4906(01)01861-0 Serwold, 2002, ERAAP customizes peptides for MHC class I molecules in the endoplasmic reticulum, Nature, 419, 480, 10.1038/nature01074 Lu, 2001, TAP-independent presentation of CTL epitopes by Trojan antigens, J. Immunol., 166, 7063, 10.4049/jimmunol.166.12.7063 Tanioka, 2003, Human leukocyte-derived arginine aminopeptidase. The third member of the oxytocinase subfamily of aminopeptidases, J. Biol. Chem., 278, 32275, 10.1074/jbc.M305076200 Levy, 2002, The final N-terminal trimming of a subaminoterminal proline-containing HLA class I-restricted antigenic peptide in the cytosol is mediated by two peptidases, J. Immunol., 169, 4161, 10.4049/jimmunol.169.8.4161 Parker, 1994, Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains, J. Immunol., 152, 163, 10.4049/jimmunol.152.1.163 Guan, 2003, MHCPred: a server for quantitative prediction of peptide-MHC binding, Nucleic Acids Res., 31, 3621, 10.1093/nar/gkg510 Swain, M.T. et al. (2001) An automated approach to modelling class II MHC alleles and predicting peptide binding. 2nd Annual IEEE International Symposium On Bioinformatics And Bioengineering, Proceedings 81–88, IEEE Computer Soc., Los Alamitos. Touloukian, 2000, Identification of a MHC class II-restricted human gp100 epitope using DR4-IE transgenic mice, J. Immunol., 164, 3535, 10.4049/jimmunol.164.7.3535 Singh, 2001, ProPred, prediction of HLA-DR binding sites, Bioinformatics, 17, 1236, 10.1093/bioinformatics/17.12.1236 Brusic, 1998, MHCPEP, a database of MHC-binding peptides: update 1997, Nucleic Acids Res., 26, 368, 10.1093/nar/26.1.368 Schonbach, 2002, FIMM, a database of functional molecular immunology: update 2002, Nucleic Acids Res., 30, 226, 10.1093/nar/30.1.226 Korber, B.T.M. et al. (2001). HIV Molecular Immunology, Los Alamos National Laboratory, Theoretical Biology and Biophysics, Los Alamos. Bhasin, 2003, MHCBN: a comprehensive database of MHC binding and non-binding peptides, Bioinformatics, 19, 665, 10.1093/bioinformatics/btg055 Chen, 2002, The binding database: data management and interface design, Bioinformatics, 18, 130, 10.1093/bioinformatics/18.1.130 Sathiamurthy, 2003, Population of the HLA ligand database, Tissue Antigens, 61, 12, 10.1034/j.1399-0039.2003.610102.x