Skip to main content

Advertisement

SpringerLink
Log in

Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles

  • Original Paper
  • Published:
Immunogenetics Aims and scope Submit manuscript

Abstract

We introduced previously an on-line resource, RANKPEP that uses position specific scoring matrices (PSSMs) or profiles for the prediction of peptide-MHC class I (MHCI) binding as a basis for CD8 T-cell epitope identification. Here, using PSSMs that are structurally consistent with the binding mode of MHC class II (MHCII) ligands, we have extended RANKPEP to prediction of peptide-MHCII binding and anticipation of CD4 T-cell epitopes. Currently, 88 and 50 different MHCI and MHCII molecules, respectively, can be targeted for peptide binding predictions in RANKPEP. Because appropriate processing of antigenic peptides must occur prior to major histocompatibility complex (MHC) binding, cleavage site prediction methods are important adjuncts for T-cell epitope discovery. Given that the C-terminus of most MHCI-restricted epitopes results from proteasomal cleavage, we have modeled the cleavage site from known MHCI-restricted epitopes using statistical language models. The RANKPEP server now determines whether the C-terminus of any predicted MHCI ligand may result from such proteasomal cleavage. Also implemented is a variability masking function. This feature focuses prediction on conserved rather than highly variable protein segments encoded by infectious genomes, thereby offering identification of invariant T-cell epitopes to thwart mutation as an immune evasion mechanism.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1a, b
Fig. 2a, b
Fig. 3a, b
Fig. 4
Fig. 5a, b

Similar content being viewed by others

References

  • Adams HP, Koziol JA (1995) Prediction of binding to MHC class I molecules. J Immunol Methods 185:181–190

    Article  CAS  PubMed  Google Scholar 

  • Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    CAS  PubMed  Google Scholar 

  • Altuvia Y, Margalit H (2000) Sequence signals for generation of antigenic peptides by the proteasome: implications for proteasomal cleavage mechanism. J Mol Biol 295:879–890

    Article  CAS  PubMed  Google Scholar 

  • Altuvia Y, Sette A, Sidney J, Southwood S, Margalit H (1997) A structure-based algorithm to predict potential binding peptides to MHC molecules with hydrophobic binding pockets. Hum Immunol 58:1–11

    Article  CAS  PubMed  Google Scholar 

  • Bailey TL, Elkan C (1995) The value of prior knowledge in discovering motifs with MEME. Proc Int Conf Intell Syst Mol Biol 3:21–29

    CAS  PubMed  Google Scholar 

  • Barber LD, Parham P (1993) Peptide binding to major histocompatibility complex molecules. Annu Rev Cell Biol 9:163–206

    CAS  PubMed  Google Scholar 

  • Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL (2003) GenBank. Nucleic Acids Res 31:23–27

    Article  CAS  PubMed  Google Scholar 

  • Brusic V, Rudy G, Honeyman JH, Harrison LC (1998a) Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neuronal network. Bioinformatics 14:121–130

    Article  CAS  PubMed  Google Scholar 

  • Brusic V, Rudy G, Kyne AP, Harrison LC (1998b) MHCPEP, a database of MHC-binding peptides: update 1997. Nucleic Acids Res 26:368–371

    Article  CAS  PubMed  Google Scholar 

  • Carson RT, Vignali KM, Woodland DL, Vignali DA (1997) T-cell receptor recognition of MHC class II-bound peptide flanking residues enhances immunogenicity and results in altered TCR V region usage. Immunity 7:387–399

    Article  CAS  PubMed  Google Scholar 

  • Chen W, Norbury CC, Cho Y, Yewdell JW, Bennink JR (2001) Immunoproteasomes shape immunodominance hierarchies of antiviral CD8(+) T-cells at the levels of T-cell repertoire and presentation of viral antigens. J Exp Med 193:1319–1326

    Article  CAS  PubMed  Google Scholar 

  • Craiu A, Akopian T, Goldberg A, Rock KL (1997) Two distinct proteolytic processes in the generation of a major histocompatibility complex class I-presented peptide. Proc Natl Acad Sci USA 94:10850–10855

    Article  CAS  PubMed  Google Scholar 

  • De Groot AS, Jesdale BM, Szu E, Schafer JR, Chicz RM, Deocampo G (1997) An interactive web site providing major histocompatibility ligand predictions: application to HIV research and AIDS. AIDS Res Hum Retroviruses 13:529–531

    PubMed  Google Scholar 

  • Donnes P, Elofsson A (2002) Prediction of MHC class I binding peptides, using SVMHC. BMC Bioinform 529–531:25

    Article  Google Scholar 

  • Draenert R, Altfeld M, Brander C, Basgoz N, Corcoran C, Wurcel AG, Stone DR, Kalams SA, Trocha A, Addo MM, Goulder PJ, Walker BD (2003) Comparison of overlapping peptide sets for detection of antiviral CD8 and CD4 T-cell responses. J Immunol Methods 275:19–29

    Article  CAS  PubMed  Google Scholar 

  • Falk K, Rotzschke O, Stevanovic S, Jung G, Rammensee HG (1991) Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature 351:290–296

    Article  CAS  PubMed  Google Scholar 

  • Fruh K, Yang Y (1999) Antigen presentation by MHC class I and its regulation by interferon gamma. Curr Opin Immunol 11:76–81

    Article  CAS  PubMed  Google Scholar 

  • Garcia KC, Teyton L, Wilson IA (1999) Structural basis of T-cell recognition. Annu Rev Immunol 17:369–397

    Article  CAS  PubMed  Google Scholar 

  • Gribskov M, McLachlan AD, Eisenberg D (1987) Profile analysis: detection of distantly related proteins. Proc Natl Acad Sci USA 84:4355–4358

    CAS  PubMed  Google Scholar 

  • Guan P, Doytchinova IA, Zygouri C, Flower DR (2003) MHCPred: a server for quantitative prediction of peptide-MHC binding. Nucleic Acids Res 31:3621–3624

    Article  CAS  PubMed  Google Scholar 

  • Gulukota K, Sidney J, Sette A, DeLisi C (1997) Two complementary methods for predicting peptides binding major histocompatibility complex molecules. J Mol Biol 267:1258–1267

    Article  CAS  PubMed  Google Scholar 

  • van Hall T, Sijts A, Camps M, Offringa R, Melief C, Kloetzel PM, Ossendorp F (2000) Differential influence on cytotoxic T lymphocyte epitope presentation by controlled expression of either proteasome immunosubunits or PA28. J Exp Med 192:483–494

    Article  PubMed  Google Scholar 

  • Hammer J (1995) New methods to predict MHC-binding sequences within protein antigens. Curr Opin Immunol 7:263–269

    Article  CAS  PubMed  Google Scholar 

  • Hammer J, Bono E, Gallazzi F, Belunis C, Nagy Z, Sinigaglia F (1994) Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning. J Exp Med 267:1258–1267

    Google Scholar 

  • Henikoff S, Henikoff JG (1994) Position-based sequence weights. J Mol Biol 243:574–578

    Article  CAS  PubMed  Google Scholar 

  • Henikoff JG, Henikoff S (1996) Using substitution probabilities to improve position-specific scoring matrices. Comput Appl Biosci 12:135–143

    CAS  PubMed  Google Scholar 

  • Henikoff S, Henikoff JG, Pietrokovski S (1999) Blocks+: a non-redundant database of protein alignment blocks derived from multiple compilations. Bioinformatics 15:471–479

    Article  CAS  PubMed  Google Scholar 

  • Hennecke J, Carfi A, Wiley DC (2000) Structure of a covalently stabilized complex of a human alphabeta T-cell receptor, influenza HA peptide and MHC class II molecule, HLA-DR1. EMBO J 19:5611–5624

    Article  CAS  PubMed  Google Scholar 

  • Hofmann K, Bucher P, Falquet L, Bairoch A (1999) The PROSITE database, its status in 1999. Nucleic Acids Res 27:215–219

    Article  CAS  PubMed  Google Scholar 

  • Holzhutter HG, Kloetzel PM (2000) A kinetic model of vertebrate 20S proteasome accounting for the generation of major proteolytic fragments from oligomeric peptide substrates. Biophys J 79:1196–1205

    CAS  PubMed  Google Scholar 

  • Honeyman MC, Brusic V, Stone NL, Harrison LC (1998) Neural network-based prediction of candidate T-cell epitopes. Nat Biotechnol 16:966–969

    Article  CAS  PubMed  Google Scholar 

  • Jimenez-Montano MA, Ebeling W, Pohl T, Rapp PE (2002) Entropy and complexity of finite sequences as fluctuating quantities. Biosystems 64:23–32

    Article  PubMed  Google Scholar 

  • Kesmir C, Nussbaum AK, Schild H, Detours V, Brunak S (2002) Prediction of proteasome cleavage motifs by neural networks. Protein Eng 15:287–296

    Article  CAS  PubMed  Google Scholar 

  • Kisselev AF, Akopian TN, Woo KM, Goldberg AL (1999) The sizes of peptides generated from protein by mammalian 26 and 20 S proteasomes. Implications for understanding the degradative mechanism and antigen presentation. J Biol Chem 274:3363–3371

    Article  CAS  PubMed  Google Scholar 

  • Kuttler C, Nussbaum AK, Dick TP, Rammensee HG, Schild H, Hadeler KP (2000) An algorithm for the prediction of proteasomal cleavages. J Mol Biol 298:417–429

    Article  CAS  PubMed  Google Scholar 

  • Madden DR (1995) The three-dimensional structure of peptide-MHC complexes. Annu Rev Immunol 13:587–622

    Article  CAS  PubMed  Google Scholar 

  • Madden DR, Garboczi DN, Wiley DC (1993) The antigenic identity of peptide-MHC complexes: a comparison of the conformations of five viral peptides presented by HLA-A2. Cell 75:693–708

    Article  CAS  PubMed  Google Scholar 

  • Maenaka K, Jones EY (1999) MHC superfamily structure and the immune system. Curr Opin Struct Biol 9:745–753

    Article  CAS  PubMed  Google Scholar 

  • Mallios RR (1999) Class II MHC quantitative binding motifs derived from a large molecular database with a versatile iterative stepwise discriminant analysis meta-algorithm. Bioinformatics 15:432–439

    Article  CAS  PubMed  Google Scholar 

  • Mamitsuka H (1998) Predicting peptides that bind to MHC molecules using supervised learning of hidden Markov models. Proteins 33:460–474

    Article  CAS  PubMed  Google Scholar 

  • Margulies DH (1997) Interactions of TCRs with MHC-peptide complexes: a quantitative basis for mechanistic models. Curr Opin Immunol 9:390–395

    Article  CAS  PubMed  Google Scholar 

  • Matsumura M, Fremont D, Peterson PA, Wilson IA (1992) Emerging principles for the recognition of peptide antigens by MHC class I molecules. Science 257:927–934

    CAS  PubMed  Google Scholar 

  • Meister GE, Roberts CG, Berzofsky JA, De Groot AS (1995) Two novel T-cell epitope prediction algorithms based on MHC-binding motifs; comparison of predicted and published epitopes from Mycobacterium tuberculosis and HIV protein sequences. Vaccine 13:581–591

    Article  CAS  PubMed  Google Scholar 

  • Nicholls A, Sharp K, Honig B (1991) Protein folding and association insights from the interfacial and thermodynamic properties of hydrocarbons. Proteins 11:281–296

    CAS  PubMed  Google Scholar 

  • Pamer E, Cresswell P (1998) Mechanisms of MHC class I—restricted antigen processing. Annu Rev Immunol 16:323–358

    Article  CAS  PubMed  Google Scholar 

  • Parker KC, Bednarek MA, Coligan JE (1994) Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side chains. J Immunol 152:163–175

    CAS  PubMed  Google Scholar 

  • Peters B, Tong W, Sidney J, Sette A, Weng Z (2003) Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules. Bioinformatics 19:1765–1772

    Article  CAS  PubMed  Google Scholar 

  • Pieters J (2000) MHC class II-restricted antigen processing and presentation. Adv Immunol 75:159–208

    Article  CAS  PubMed  Google Scholar 

  • Raddrizzani L, Hammer J (2000) Epitope scanning using virtual matrix-based algorithms. Brief Bioinform 1:179–189

    CAS  PubMed  Google Scholar 

  • Rammensee HG (2002) Survival of the fitters. Nature 419:443–445

    Article  CAS  PubMed  Google Scholar 

  • Rammensee HG, Friede T, Stevanoviic S (1995) MHC ligands and peptide motifs: first listing. Immunogenetics 41:178–228

    Article  CAS  PubMed  Google Scholar 

  • Rammensee HG, Bachmann J, Emmerich NPN, Bacho OA, Stevanovic S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50:213–219

    Article  CAS  PubMed  Google Scholar 

  • Reche PA, Reinherz EL (2003) Sequence variability analysis of human class I and class II MHC molecules: functional and structural correlates of amino acid polymorphisms. J Mol Biol 331:623–641

    Article  CAS  PubMed  Google Scholar 

  • Reche PA, Glutting JP, Reinherz EL (2002) Prediction of MHC class I binding peptides using profile motifs. Hum Immunol 63:701–709

    Article  CAS  PubMed  Google Scholar 

  • Rosenfeld R (2000) Two decades of statistical language modeling: where do we go from here? Proc IEEE 88:1–11

    Article  Google Scholar 

  • Sant’Angelo DB, Robinson E, Janeway CA Jr, Denzin LK (2002) Recognition of core and flanking amino acids of MHC class II-bound peptides by the T-cell receptor. Eur J Immunol 32:2510–2520

    Article  CAS  PubMed  Google Scholar 

  • Schaffer AA, Wolf YI, Ponting CP, Koonin EV, Aravind L, Altschul SF (1999) IMPALA: matching a protein sequence against a collection of PSI-BLAST-constructed position-specific score matrices. Bioinformatics 15:1000–1011

    Article  CAS  PubMed  Google Scholar 

  • Schneider TD, Stephens RM (1990) Sequence logos: a new way to display consensus sequences. Nucleic Acids Res 18:6097–6100

    CAS  PubMed  Google Scholar 

  • Schueler-Furman O, Altuvia Y, Sette A, Margalit H (2000) Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles. Protein Sci 9:1838–1846

    CAS  PubMed  Google Scholar 

  • Serwold T, Gonzalez F, Kim J, Jacob R, Shastri N (2002) ERAAP customizes peptides for MHC class I molecules in the endoplasmic reticulum. Nature 419:480–483

    Article  CAS  PubMed  Google Scholar 

  • Sette A, Buus S, Appella E, Smith JA, Chesnut R, Miles C, Colon SM, Grey HM (1989) Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis. Proc Natl Acad Sci USA 86:3296–3300

    CAS  PubMed  Google Scholar 

  • Shannon CE (1948) The mathematical theory of communication. Bell Syst Tech J 27:379–423, 623–656

    Google Scholar 

  • Stern LJ, Wiley DC (1994) Antigen peptide binding by class I and class II histocompatibility proteins. Structure 2:245–251

    Article  CAS  PubMed  Google Scholar 

  • Stewart JJ, Lee CY, Ibrahim S, Watts P, Shlomchik M, Weigert M, Litwin S (1997) A Shannon entropy analysis of immunoglobulin and T-cell receptor. Mol Immunol 34:1067–1082

    Article  CAS  PubMed  Google Scholar 

  • Stolcke A (2002) SRILM—an extensible language modeling toolkit. In: Ohala TMNJJ, Derwing BL, Hodge MM, Wiebe GE (eds) Proceedings of the International Conference of Spoken Language Processing. Center for Spoken Language Research, Boulder, pp 901–904

    Google Scholar 

  • Stryhn A, Pederson LO, Romme T, Holm A, Buus S (1996) 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. Eur J Immunol 26:1911–1918

    CAS  PubMed  Google Scholar 

  • Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Sinigaglia F, Hammer J (1999) Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nature Biotech 17:555–561

    Google Scholar 

  • Swain MT, Brooks AJ, Kemp GJL (2001) An automated approach to modelling class II MHC alleles and predicting peptide binding. Proceedings of the IEEE International Symposium on Bio-Informatics and Biomedical Engineering. IEEE Computer Society, New York, pp 81–88

    Google Scholar 

  • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

    CAS  PubMed  Google Scholar 

  • Thompson JD, Higgins DG, Gibson TJ (1994a) CLUSTALW: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weigh matrix choice. Nucleic Acids Res 2:4673–4680

    Google Scholar 

  • Thompson JD, Higgins DG, Gibson TJ (1994b) Improved sensitivity of profile searches through the use of sequence weights and gap excision. Comput Appl Biosci 10:19–29

    CAS  PubMed  Google Scholar 

  • Toes RE, Nussbaum AK, Degermann S, Schirle M, Emmerich NP, Kraft M, Laplace C, Zwinderman A, Dick TP, Muller J, Schonfisch B, Schmid C, Fehling HJ, Stevanovic S, Rammensee HG, Schild H (2001) Discrete cleavage motifs of constitutive and immunoproteasomes revealed by quantitative analysis of cleavage products. J Exp Med 194:1–12

    Article  CAS  PubMed  Google Scholar 

  • Udaka K, Wiesmuller KH, Kienle S, Jung G, Tamamura H, Yamigishi H, Okumura K, Walden P, Suto T, Kawasaki T (2000) An automated prediction of MHC class I-binding peptides based on positional scanning with peptide libraries. Immunogenetics 51:816–828

    Article  CAS  PubMed  Google Scholar 

  • Udaka K, Mamitsuka H, Nakaseko Y, Abe N (2002) Empirical evaluation of a dynamic experiment design method for prediction of MHC class I-binding peptides. J Immunol 169:5744–5753

    CAS  PubMed  Google Scholar 

  • Wang J-H, Reinherz E (2001) Structural basis of T-cell recognition of peptides bound to MHC molecules. Mol Immunol 38:1039–1049

    Article  Google Scholar 

  • Watts C (2001) Antigen processing in the endocytic compartment. Curr Opin Immunol 13:26–31

    Article  CAS  PubMed  Google Scholar 

  • Wu C, Shivakumar S (1994) Back-propagation and counter-propagation neural networks for phylogenetic classification of ribosomal RNA sequences. Nucleic Acids Res 22:4291–4299

    CAS  PubMed  Google Scholar 

  • Wu CH, Zhao S, Chen HL, Lo CJ, McLarty J (1996) Motif identification neural design for rapid and sensitive protein family search. Comput Appl Biosci 12:109–118

    CAS  PubMed  Google Scholar 

  • Zhang C, Anderson A, DeLisi C (1998) Structural principles that govern the peptide-binding motifs of class I MHC molecules. J Mol Biol 281:929–947

    Article  CAS  PubMed  Google Scholar 

  • Zhao Y, Pinilla C, Valmori D, Martin R, Simon R (2003) Application of support vector machines for T-cell epitopes prediction. Bioinformatics 19:1978–1984

    Article  CAS  PubMed  Google Scholar 

  • Zhong W, Reche PA, Lai CC, Reinhold B, Reinherz EL (2003) Genome-wide characterization of a viral cytotoxic T lymphocyte epitope repertoire. J Biol Chem 278:45135–45144

    Article  CAS  PubMed  Google Scholar 

  • Zinkernagel RM, Doherty PC (1974) Restriction of in vitro T-cell-mediated cytotoxicity in lymphocytic choriomeningitis within a syngeneic or semiallogeneic system. Nature 248:701–702

    CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This manuscript was supported by NIH grant AI50900 and the Molecular Immunology Foundation. We wish to acknowledge the insightful comments and corrections provided by Drs Esther Lafuente, Robert Mallis, and Weimin Zhong.

Author information

Authors and Affiliations

  1. Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA

    Pedro A. Reche, John-Paul Glutting, Hong Zhang & Ellis L. Reinherz

  2. Department of Medicine, Harvard Medical School, 44 Binney Street, Boston, MA 02115, USA

    Pedro A. Reche & Ellis L. Reinherz

Authors
  1. Pedro A. Reche
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John-Paul Glutting
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ellis L. Reinherz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pedro A. Reche.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Reche, P.A., Glutting, JP., Zhang, H. et al. Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics 56, 405–419 (2004). https://doi.org/10.1007/s00251-004-0709-7

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00251-004-0709-7

Keywords

Search

Navigation