Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone

The postgenomic era, as manifest, inter alia, by proteomics, offers unparalleled opportunities for the efficient discovery of safe, efficacious, and novel subunit vaccines targeting a tranche of modern major diseases. A negative corollary of this opportunity is the risk of becoming overwhelmed by this embarrassment of riches. Informatics techniques, working to address issues of both data management and through prediction to shortcut the experimental process, can be of enormous benefit in leveraging the proteomic revolution.In this disquisition, we evaluate proteomic approaches to the discovery of subunit vaccines, focussing on viral, bacterial, fungal, and parasite systems. We also adumbrate the impact that proteomic analysis of host-pathogen interactions can have. Finally, we review relevant methods to the prediction of immunome, with special emphasis on quantitative methods, and the subcellular localization of proteins within bacteria.

[1]  P Argos,et al.  Prediction of secondary structural content of proteins from their amino acid composition alone. II. The paradox with secondary structural class , 1996, Proteins.

[2]  Christina Kuttler.  An Algorithm for the Prediction of Proteasomal Cleavages , 2000, German Conference on Bioinformatics.

[3]  Y. Furuichi,et al.  Proteomic analysis of Epstein‐Barr virus‐transformed human B‐lymphoblastiod cell lines before and after immortalization , 2000, Electrophoresis.

[4]  K. Wiesmüller,et al.  Peptide length preferences for rat and mouse MHC class I molecules using random peptide libraries , 1998, European journal of immunology.

[5]  R. Fleischmann,et al.  Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. , 1995, Science.

[6]  J. Drijfhout,et al.  A computer program for predicting possible cytotoxic T lymphocyte epitopes based on HLA class I peptide-binding motifs. , 1995, Human immunology.

[7]  Maria Edman,et al.  Different sequence patterns in signal peptides from mycoplasmas, other gram‐positive bacteria, and Escherichia coli: A multivariate data analysis , 1999, Proteins.

[8]  K. Chou,et al.  Using discriminant function for prediction of subcellular location of prokaryotic proteins. , 1998, Biochemical and biophysical research communications.

[9]  D. Flower,et al.  The lipocalin website. , 2000, Biochimica et biophysica acta.

[10]  I. Bruchhaus,et al.  Comparative proteome analysis of Leishmania donovani at different stages of transformation from promastigotes to amastigotes , 2001, Medical Microbiology and Immunology.

[11]  B. Turgeon,et al.  Fungal genomics and pathogenicity. , 2001, Current opinion in plant biology.

[12]  R. Fleischmann,et al.  Complete Genome Sequence of the Methanogenic Archaeon, Methanococcus jannaschii , 1996, Science.

[13]  D. Flower,et al.  Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201. , 2002, Journal of proteome research.

[14]  R A Houghten,et al.  Combinatorial peptide libraries as an alternative approach to the identification of ligands for tumor-reactive cytolytic T lymphocytes. , 2001, Cancer research.

[15]  Vladimir Brusic,et al.  MHCPEP, a database of MHC-binding peptides: update 1996 , 1997, Nucleic Acids Res..

[16]  S. H. Kaufmann,et al.  Comparative proteome analysis of Mycobacterium tuberculosis and Mycobacterium bovis BCG strains: towards functional genomics of microbial pathogens , 1999, Molecular microbiology.

[17]  K. Parker,et al.  Pocket mutations of HLA-B27 show that anchor residues act cumulatively to stabilize peptide binding. , 1994, Biochemistry.

[18]  D. Colley,et al.  Parasitic diseases: opportunities and challenges in the 21st century. , 2000, Memorias do Instituto Oswaldo Cruz.

[19]  D. Flower,et al.  Physicochemical explanation of peptide binding to HLA‐A*0201 major histocompatibility complex: A three‐dimensional quantitative structure‐activity relationship study , 2002, Proteins.

[20]  K. Parker,et al.  Sequence motifs important for peptide binding to the human MHC class I molecule, HLA-A2. , 1992, Journal of immunology.

[21]  J. A. Gutierrez,et al.  Genomics: from novel genes to new therapeutics in parasitology. , 2000, International journal for parasitology.

[22]  B Honig,et al.  On the calculation of binding free energies using continuum methods: Application to MHC class I protein‐peptide interactions , 1997, Protein science : a publication of the Protein Society.

[23]  W. Goebel,et al.  Identification of Immunodominant Antigens fromHelicobacter pylori and Evaluation of Their Reactivities with Sera from Patients with Different Gastroduodenal Pathologies , 2000, Infection and Immunity.

[24]  D. Rognan,et al.  Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class I major histocompatibility proteins. , 1999, Journal of medicinal chemistry.

[25]  G. Reichmann,et al.  Towards the Toxoplasma gondii proteome: position of 13 parasite excretory antigens on a standardized map of two-dimensionally separated tachyzoite proteins , 2001, Parasitology Research.

[26]  K. Parker,et al.  Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. , 1994, Journal of immunology.

[27]  D Rognan,et al.  Molecular dynamics study of a complex between the human histocompatibility antigen HLA-A2 and the IMP58-66 nonapeptide from influenza virus matrix protein. , 1992, European journal of biochemistry.

[28]  A. Görg,et al.  Towards a two‐dimensional proteome map of Mycoplasma pneumoniae , 2000, Electrophoresis.

[29]  H. Rammensee,et al.  SYFPEITHI: database for MHC ligands and peptide motifs , 1999, Immunogenetics.

[30]  Michael T. Wilson,et al.  Analysis of the effect of changing environmental conditions on the expression patterns of exported surface-associated proteins of the oral pathogen Actinobacillus actinomycetemcomitans. , 2001, Microbial Pathogenesis.

[31]  P. Barker,et al.  Efficient Generation of Major Histocompatibility Complex Class I-Peptide Complexes Using Synthetic Peptide Libraries* , 1998, The Journal of Biological Chemistry.

[32]  M. Wilkins,et al.  Progress with gene‐product mapping of the Mollicutes: Mycoplasma genitalium , 1995, Electrophoresis.

[33]  P. Skuce,et al.  The contribution of molecular biology to the development of vaccines against nematode and trematode parasites of domestic ruminants. , 2001, Veterinary parasitology.

[34]  Francine B. Perler,et al.  InBase: the Intein Database , 2002, Nucleic Acids Res..

[35]  R. Lahesmaa,et al.  A proteome database of human primary T helper cells , 2001, Electrophoresis.

[36]  D. Rognan,et al.  Customized versus universal scoring functions: application to class I MHC-peptide binding free energy predictions. , 2001, Bioorganic & medicinal chemistry letters.

[37]  O. Schueler‐Furman,et al.  Structure‐based prediction of binding peptides to MHC class I molecules: Application to a broad range of MHC alleles , 2000, Protein science : a publication of the Protein Society.

[38]  A. Greco,et al.  Alteration of ribosomal protein maps in herpes simplex virus type 1 infection. , 2002, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[39]  D. O'Kane,et al.  Gene expression microarrays: a 21st century tool for directed vaccine design. , 2001, Vaccine.

[40]  S Vajda,et al.  Flexible docking of peptides to class I major-histocompatibility-complex receptors. , 1995, Genetic analysis : biomolecular engineering.

[41]  B. Klein,et al.  Virulence Factors of Medically Important Fungi , 1996 .

[42]  C. O'Connor,et al.  The proteome of Salmonella enterica serovar typhimurium: Current progress on its determination and some applications , 1997, Electrophoresis.

[43]  D. Berg,et al.  Identification of differentially regulated proteins in metronidozole resistant Helicobacter pylori by proteome techniques , 2001, Proteomics.

[44]  D. Thirumalai,et al.  Pair potentials for protein folding: Choice of reference states and sensitivity of predicted native states to variations in the interaction schemes , 2008, Protein science : a publication of the Protein Society.

[45]  A. Purcell,et al.  The use of post-source decay in matrix-assisted laser desorption/ionisation mass spectrometry to delineate T cell determinants. , 2001, Journal of immunological methods.

[46]  Darren R Flower,et al.  Bacterial bioinformatics: pathogenesis and the genome. , 2002, Journal of molecular microbiology and biotechnology.

[47]  B. Rost,et al.  Adaptation of protein surfaces to subcellular location. , 1998, Journal of molecular biology.

[48]  P. Andersen,et al.  Mapping and identification of Mycobacterium tuberculosis proteins by two‐dimensional gel electrophoresis, microsequencing and immunodetection , 2000, Electrophoresis.

[49]  Johannes Schuchhardt,et al.  Adaptive encoding neural networks for the recognition of human signal peptide cleavage sites , 2000, Bioinform..

[50]  B. Gibson,et al.  Identification of Fur, Aconitase, and Other Proteins Expressed by Mycobacterium tuberculosis under Conditions of Low and High Concentrations of Iron by Combined Two-Dimensional Gel Electrophoresis and Mass Spectrometry , 1999, Infection and Immunity.

[51]  Mark Borodovsky,et al.  The complete genome sequence of the gastric pathogen Helicobacter pylori , 1997, Nature.

[52]  N G Anderson,et al.  The Human Protein Index. , 1981, Clinical chemistry.

[53]  S. Brunak,et al.  Prediction of proteasome cleavage motifs by neural networks. , 2002, Protein engineering.

[54]  K. Gevaert,et al.  Proteome analysis of the Chlamydia pneumoniaeelementary body , 2001, Electrophoresis.

[55]  M H Van Regenmortel,et al.  An assessment of prediction methods for locating continuous epitopes in proteins. , 1988, Immunology letters.

[56]  A. Osbourn,et al.  Molecular dissection of fungal phytopathogenicity. , 1995, Microbiology.

[57]  Peter R. Jungblut,et al.  Proteomics Reveals Open Reading Frames inMycobacterium tuberculosis H37Rv Not Predicted by Genomics , 2001, Infection and Immunity.

[58]  P. Ghezzi,et al.  Identification by redox proteomics of glutathionylated proteins in oxidatively stressed human T lymphocytes , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[59]  Toni Aebischer,et al.  Immunoproteomics of Helicobacter pylori infection and relation to gastric disease , 2002, Proteomics.

[60]  S. Howell,et al.  Changes in gene expression in macrophages infected with Mycobacterium tuberculosis: a combined transcriptomic and proteomic approach , 2001, Immunology.

[61]  S. Watson,et al.  The immune system and gene expression microarrays--new answers to old questions. , 2001, The Journal of pathology.

[62]  W R Taylor,et al.  Location of ‘continuous’ antigenic determinants in the protruding regions of proteins. , 1986, The EMBO journal.

[63]  J. Barrett,et al.  Proteomic analysis of Fasciola hepatica excretory‐secretory products , 2001, Proteomics.

[64]  E. Golemis,et al.  Using the yeast interaction trap and other two-hybrid-based approaches to study protein-protein interactions. , 2001, Methods.

[65]  P. Cossart,et al.  Distinct protein patterns associated with Listeria monocytogenes InlA‐ or InlB‐phagosomes , 2002, Cellular microbiology.

[66]  Irini A. Doytchinova,et al.  JenPep: a database of quantitative functional peptide data for immunology , 2002, Bioinform..

[67]  A. Ljungh,et al.  Two‐dimensional electrophoretic and immunoblot analysis of cell surface proteins of spiral‐shaped and coccoid forms of Helicobacter pylori , 2000, Electrophoresis.

[68]  J. Risler,et al.  Codon usage as a tool to predict the cellular location of eukaryotic ribosomal proteins and aminoacyl-tRNA synthetases. , 1999, Nucleic acids research.

[69]  A Sette,et al.  A structure-based algorithm to predict potential binding peptides to MHC molecules with hydrophobic binding pockets. , 1997, Human immunology.

[70]  K. Kim,et al.  Selection of peptides that bind to the HLA-A2.1 molecule by molecular modelling. , 1996, Molecular immunology.

[71]  Antony Williams,et al.  Applications of computer software for the interpretation and management of mass spectrometry data in pharmaceutical science. , 2002, Current topics in medicinal chemistry.

[72]  S. Brunak,et al.  SHORT COMMUNICATION Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites , 1997 .

[73]  T. Hubbard,et al.  Using neural networks for prediction of the subcellular location of proteins. , 1998, Nucleic acids research.

[74]  K. Parker,et al.  Endogenous peptides bound to HLA-A3 possess a specific combination of anchor residues that permit identification of potential antigenic peptides. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[75]  M. V. Van Regenmortel,et al.  Predicting antigenic determinants in proteins: looking for unidimensional solutions to a three-dimensional problem? , 1994, Peptide research.

[76]  W Keilholz,et al.  Cleavage motifs of the yeast 20S proteasome beta subunits deduced from digests of enolase 1. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[77]  K. Parker,et al.  Identification of the peptide binding motif for HLA-B44, one of the most common HLA-B alleles in the Caucasian population. , 1995, Biochemistry.

[78]  Bulbul Chakravarti,et al.  Informatic tools for proteome profiling. , 2002, BioTechniques.

[79]  D. Bashford,et al.  Solvation energy density occlusion approximation for evaluation of desolvation penalties in biomolecular interactions , 2001, Proteins.

[80]  S. Engelmann,et al.  Proteomics, DNA arrays and the analysis of still unknown regulons and unknown proteins of Bacillus subtilis and pathogenic gram-positive bacteria. , 2000, International journal of medical microbiology : IJMM.

[81]  D. Flower,et al.  Toward the quantitative prediction of T-cell epitopes: coMFA and coMSIA studies of peptides with affinity for the class I MHC molecule HLA-A*0201. , 2001, Journal of medicinal chemistry.

[82]  Thomas Joos,et al.  Protein microarray technology , 2004, Expert review of proteomics.

[83]  Vladimir Brusic,et al.  A neural network model approach to the study of human TAP transporter , 1998, Silico Biol..

[84]  M. Moniatte,et al.  Towards the proteome of Mycobacterium tuberculosis , 2000, Electrophoresis.

[85]  C. DeLisi,et al.  Free energy mapping of class I MHC molecules and structural determination of bound peptides , 1996, Protein science : a publication of the Protein Society.

[86]  J. Thornton,et al.  Continuous and discontinuous protein antigenic determinants , 1986, Nature.

[87]  A. Alix,et al.  Predictive estimation of protein linear epitopes by using the program PEOPLE. , 1999, Vaccine.

[88]  J. Betts,et al.  Comparison of the proteome of Mycobacterium tuberculosis strain H37Rv with clinical isolate CDC 1551. , 2000, Microbiology.

[89]  M. Gerstein,et al.  Subcellular localization of the yeast proteome. , 2002, Genes & development.

[90]  E Westhof,et al.  PREDITOP: a program for antigenicity prediction. , 1993, Journal of molecular graphics.

[91]  I. Orme,et al.  The application of proteomics in defining the T cell antigens of Mycobacterium tuberculosis , 2001, Proteomics.

[92]  Olaf Wolkenhauer,et al.  Bioinformatic assessment of mass spectrometric chemical derivatisation techniques for proteome database searching , 2001, Proteomics.

[93]  D Rognan,et al.  Molecular modeling of an antigenic complex between a viral peptide and a class I major histocompatibility glycoprotein , 1992, Proteins.

[94]  D. Hochstrasser,et al.  Identification of ribosome‐associated viral and cellular basic proteins during the course of infection with herpes simplex virus type 1 , 2001, Proteomics.

[95]  M. Hecker,et al.  Influence of pathogenicity islands and the minor leuX-encoded tRNA5Leu on the proteome pattern of the uropathogenic Escherichia coli strain 536. , 2000, International journal of medical microbiology : IJMM.

[96]  B. Martoglio,et al.  Signal sequences: more than just greasy peptides. , 1998, Trends in cell biology.

[97]  G von Heijne,et al.  Signal sequences. The limits of variation. , 1985, Journal of molecular biology.

[98]  I. Svane,et al.  MHC class II-bound self-peptides can be effectively separated by isoelectric focusing and bind optimally to their MHC class II restriction elements around pH 5.0. , 1994, Immunology.

[99]  R Simon,et al.  Combinatorial Peptide Libraries and Biometric Score Matrices Permit the Quantitative Analysis of Specific and Degenerate Interactions Between Clonotypic TCR and MHC Peptide Ligands1 , 2001, The Journal of Immunology.

[100]  Vladimir Brusic,et al.  A Peptide-binding Motif for I-Ag7, the Class II Major Histocompatibility Complex (MHC) Molecule of NOD and Biozzi AB/H Mice , 1997, The Journal of experimental medicine.

[101]  A. Ljungh,et al.  Identification of novel immunogenic proteins of Helicobacter pylori by proteome technology. , 2002, Journal of immunological methods.

[102]  K. Parker,et al.  The HLA-B14 peptide binding site can accommodate peptides with different combinations of anchor residues. , 1994, The Journal of biological chemistry.

[103]  Andrew Brooks,et al.  Peptide binding to MHC class I molecules: Implications for antigenic peptide prediction , 1995, Immunologic research.

[104]  N. W. Davis,et al.  The complete genome sequence of Escherichia coli K-12. , 1997, Science.

[105]  J. Vilo,et al.  From genomes to vaccines: Leishmania as a model. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[106]  K. Nakai.  Predicting Various Targeting Signals in Amino Acid Sequences , 1991 .

[107]  A. Rudensky,et al.  In vivo MHC class II presentation of cytosolic proteins revealed by rapid automated tandem mass spectrometry and functional analyses , 2001, European journal of immunology.

[108]  K. Parker,et al.  The beta 2-microglobulin dissociation rate is an accurate measure of the stability of MHC class I heterotrimers and depends on which peptide is bound. , 1992, Journal of immunology.

[109]  H. Margalit,et al.  Ranking potential binding peptides to MHC molecules by a computational threading approach. , 1995, Journal of molecular biology.

[110]  K. Parker,et al.  Peptide binding to HLA-A2 and HLA-B27 isolated from Escherichia coli. Reconstitution of HLA-A2 and HLA-B27 heavy chain/beta 2-microglobulin complexes requires specific peptides. , 1992, The Journal of biological chemistry.

[111]  J. Derisi,et al.  DNA microarrays for malaria. , 2002, Trends in parasitology.

[112]  P. Butcher,et al.  Differential expression of mycobacterial proteins following phagocytosis by macrophages. , 2001, Microbiology.

[113]  Javier M Rodríguez,et al.  African swine fever virus‐induced polypeptides in porcine alveolar macrophages and in Vero cells: Two‐dimensional gel analysis , 2001, Proteomics.

[114]  K. Rigley,et al.  Microarrays in hematology , 2002, Current opinion in hematology.

[115]  M Vihinen,et al.  Bioinformatics in proteomics. , 2001, Biomolecular engineering.

[116]  M M Gromiha.  A simple method for predicting transmembrane alpha helices with better accuracy. , 1999, Protein engineering.

[117]  G. Siuzdak,et al.  Mass spectrometry in viral proteomics. , 2000, Accounts of chemical research.

[118]  D. Camus,et al.  Can software be used to predict antigenic regions in Plasmodium falciparum peptides? , 1996, Parasite immunology.

[119]  K Nishikawa,et al.  Discrimination of intracellular and extracellular proteins using amino acid composition and residue-pair frequencies. , 1994, Journal of molecular biology.

[120]  R. Zagursky,et al.  Application of genomics and proteomics for identification of bacterial gene products as potential vaccine candidates. , 2000, Vaccine.

[121]  A Caflisch,et al.  Monte Carlo docking of oligopeptides to proteins , 1992, Proteins.

[122]  K Nishikawa,et al.  Correlation of the amino acid composition of a protein to its structural and biological characters. , 1982, Journal of biochemistry.

[123]  V. Brusic,et al.  Neural network-based prediction of candidate T-cell epitopes , 1998, Nature Biotechnology.

[124]  K. Fry,et al.  Identification of Potential Diagnostic and Vaccine Candidates ofHelicobacter pylori by Two-Dimensional Gel Electrophoresis, Sequence Analysis, and Serum Profiling , 1998, Clinical Diagnostic Laboratory Immunology.

[125]  L C Harrison,et al.  Strategies for identifying and predicting islet autoantigen T-cell epitopes in insulin-dependent diabetes mellitus. , 1997, Annals of medicine.

[126]  K. Mathee,et al.  Proteome Analysis of the Effect of Mucoid Conversion on Global Protein Expression in Pseudomonas aeruginosa Strain PAO1 Shows Induction of the Disulfide Bond Isomerase, DsbA , 2000, Journal of bacteriology.

[127]  K. Becker,et al.  Identification of an epitope derived from human proteolipid protein that can induce autoreactive CD8+ cytotoxic T lymphocytes restricted by HLA-A3: evidence for cross-reactivity with an environmental microorganism , 1997, Journal of Neuroimmunology.

[128]  P. Kloetzel,et al.  A theoretical approach towards the identification of cleavage-determining amino acid motifs of the 20 S proteasome. , 1999, Journal of molecular biology.

[129]  C A Floudas,et al.  A predictive method for the evaluation of peptide binding in pocket 1 of HLA‐DRB1 via global minimization of energy interactions , 1997, Proteins.

[130]  K. Nakai.  Protein sorting signals and prediction of subcellular localization. , 2000, Advances in protein chemistry.

[131]  C DeLisi,et al.  Computational determination of side chain specificity for pockets in class I MHC molecules. , 1996, Molecular immunology.

[132]  G. Grandi,et al.  Antibacterial vaccine design using genomics and proteomics. , 2001, Trends in biotechnology.

[133]  Qing Zhou,et al.  AsMamDB: an alternative splice database of mammals , 2001, Nucleic Acids Res..

[134]  X. Yao,et al.  Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus. , 2001, Analytical chemistry.

[135]  T. Meyer,et al.  Comparative proteome analysis of Helicobacter pylori , 2000, Molecular microbiology.

[136]  M. Reddehase,et al.  Two Antigenic Peptides from Genes m123 and m164 of Murine Cytomegalovirus Quantitatively Dominate CD8 T-Cell Memory in the H-2d Haplotype , 2002, Journal of Virology.

[137]  Vladimir Brusic,et al.  MHCPEP, a database of MHC-binding peptides: update 1996 , 1997, Nucleic Acids Res..

[138]  J. Belisle,et al.  Identification of putative exported/secreted proteins in prokaryotic proteomes. , 2001, Gene.

[139]  W Fierz,et al.  Using a neural network to identify potential HLA‐DR1 binding sites within proteins , 1993, Journal of molecular recognition : JMR.

[140]  R. Fleischmann,et al.  The Minimal Gene Complement of Mycoplasma genitalium , 1995, Science.

[141]  Taku Suto,et al.  An automated prediction of MHC class I-binding peptides based on positional scanning with peptide libraries , 2000, Immunogenetics.

[142]  J. Špaček,et al.  Proteome study of Francisella tularensis live vaccine strain‐containing phagosome in Bcg/Nramp1 congenic macrophages: Resistant allele contributes to permissive environment and susceptibility to infection , 2002, Proteomics.

[143]  G. H. Coombs,et al.  Characterisation of global protein expression by two-dimensional electrophoresis and mass spectrometry: proteomics of Toxoplasma gondii. , 2002, International journal for parasitology.

[144]  P. Roepstorff,et al.  Comparative proteome analysis of Chlamydia trachomatis serovar A, D and L2 , 2002, Proteomics.

[145]  M. Reddehase,et al.  Early gene m18, a novel player in the immune response to murine cytomegalovirus. , 2002, The Journal of general virology.

[146]  Truffa-Bachi,et al.  Proteomic analysis of T cell activation in the presence of cyclosporin A: immunosuppressor and activator removal induces de novo protein synthesis. , 2000, Molecular immunology.

[147]  R. Jernigan,et al.  Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading. , 1996, Journal of molecular biology.

[148]  L. Gierasch,et al.  In vivo function and membrane binding properties are correlated for Escherichia coli lamB signal peptides. , 1985, Science.

[149]  M. Michael Gromiha,et al.  A simple method for predicting transmembrane α helices with better accuracy , 1999 .

[150]  J. Dalton,et al.  Parasite vaccines--a reality? , 2001, Veterinary parasitology.

[151]  Søren Buus,et al.  Peptide binding specificity of major histocompatibility complex class I resolved into an array of apparently independent subspecificities: quantitation by peptide libraries and improved prediction of binding , 1996, European journal of immunology.

[152]  Victor Ciesielski,et al.  Application of Genetic Search in Derivation of Matrix Models of Peptide Binding to MHC Molecules , 1997, ISMB.

[153]  K. Hadeler,et al.  PAProC: a prediction algorithm for proteasomal cleavages available on the WWW , 2001, Immunogenetics.

[154]  J. Betts,et al.  Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling , 2002, Molecular microbiology.

[155]  H. Grey,et al.  Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[156]  M. Wilkins,et al.  Serotype classification and characterisation of the rotavirus SA11 VP6 protein using mass spectrometry and two-dimensional gel electrophoresis , 2000, Functional & Integrative Genomics.

[157]  K. Parker,et al.  HLA-A1 and HLA-A3 T cell epitopes derived from influenza virus proteins predicted from peptide binding motifs. , 1993, Journal of immunology.

[158]  H. Chapman,et al.  Endosomal proteolysis and MHC class II function. , 1998, Current opinion in immunology.

[159]  P. Aloy,et al.  Relation between amino acid composition and cellular location of proteins. , 1997, Journal of molecular biology.

[160]  V Brusic,et al.  Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules. , 1998, Journal of immunology.

[161]  D Rognan,et al.  Molecular dynamics simulation of MHC-peptide complexes as a tool for predicting potential T cell epitopes. , 1994, Biochemistry.

[162]  B. Williams,et al.  Functional classification of interferon‐stimulated genes identified using microarrays , 2001, Journal of leukocyte biology.

[163]  S. Wold,et al.  Signal peptide amino acid sequences in Escherichia coli contain information related to final protein localization. A multivariate data analysis. , 1987, The EMBO journal.

[164]  H. Mollenkopf,et al.  Identification of proteins from Mycobacterium tuberculosis missing in attenuated Mycobacterium bovis BCG strains , 2001, Electrophoresis.