Skip to main content
SpringerLink
Log in

Bioinformatics Identification of Antigenic Peptide: Predicting the Specificity of Major MHC Class I and II Pathway Players

  • Protocol
  • First Online:
Antigen Processing

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 960))

Abstract

Bioinformatics methods for immunology have become increasingly used over the last decade and now form an integrated part of most epitope discovery projects. This wide usage has led to the confusion of defining which of the many methods to use for what problems. In this chapter, an overview is given focusing on the suite of tools developed at the Technical University of Denmark.

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

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Sette A, Sidney J (1999) Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics 50(3–4):201–212

    Article  CAS  PubMed  Google Scholar 

  2. 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(1):163–175

    CAS  PubMed  Google Scholar 

  3. Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50(3–4):213–219

    Article  CAS  PubMed  Google Scholar 

  4. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M (2008) NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Res 36(Web Server issue):W509–W512. doi:gkn202 (pii) 10.1093/nar/gkn202

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S, Brunak S, Lund O (2003) Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci 12(5):1007–1017. doi:10.1110/ps.0239403

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hoof I, Peters B, Sidney J, Pedersen LE, Sette A, Lund O, Buus S, Nielsen M (2009) NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 61(1):1–13. doi:10.1007/s00251-008-0341-z

    Article  CAS  PubMed  Google Scholar 

  7. Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, Roder G, Peters B, Sette A, Lund O, Buus S (2007) NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. PLoS One 2(8):e796. doi:10.1371/journal.pone.0000796

    Article  PubMed  PubMed Central  Google Scholar 

  8. Zhang H, Lund O, Nielsen M (2009) The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding. Bioinformatics 25(10):1293–1299. doi:10.1093/bioinformatics/btp137

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Peters B, Bui HH, Frankild S, Nielson M, Lundegaard C, Kostem E, Basch D, Lamberth K, Harndahl M, Fleri W, Wilson SS, Sidney J, Lund O, Buus S, Sette A (2006) A community resource benchmarking predictions of peptide binding to MHC-I molecules. PLoS Comput Biol 2(6):e65. doi:06-PLCB-RA-0058R2 (pii) 10.1371/journal.pcbi.0020065

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunol 9:8. doi:1471-2172-9-8 (pii) 10.1186/1471-2172-9-8

    Article  PubMed  PubMed Central  Google Scholar 

  11. Zhang GL, Ansari HR, Bradley P, Cawley GC, Hertz T, Hu X, Jojic N, Kim Y, Kohlbacher O, Lund O, Lundegaard C, Magaret CA, Nielsen M, Papadopoulos H, Raghava GP, Tal VS, Xue LC, Yanover C, Zhu S, Rock MT, Crowe JE Jr, Panayiotou C, Polycarpou MM, Duch W, Brusic V (2011) Machine learning competition in immunology—Prediction of HLA class I binding peptides. J Immunol Methods. doi:S0022-1759(11)00255-9 (pii) 10.1016/j.jim.2011.09.010

    Google Scholar 

  12. Zhang H, Lundegaard C, Nielsen M (2009) Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods. Bioinformatics 25(1):83–89. doi:10.1093/bioinformatics/btn579

    Article  PubMed  Google Scholar 

  13. Zhang L, Udaka K, Mamitsuka H, Zhu S (2011) Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools. Brief Bioinform. doi:bbr060 (pii) 10.1093/bib/bbr060

    Google Scholar 

  14. Lundegaard C, Hoof I, Lund O, Nielsen M, Lundegaard C, Hoof I, Lund O, Nielsen M (2010) State of the art and challenges in sequence based T-cell epitope prediction. Immunome Res 6(Suppl 2):S3. doi:1745-7580-6-S2-S3 (pii) 10.1186/1745-7580-6-S2-S3

    Article  PubMed  PubMed Central  Google Scholar 

  15. Karosiene E, Lundegaard C, Lund O, Nielsen M (2011) NetMHCcons: a consensus method for the major histocompatibility complex class I predictions. Immunogenetics. doi:10.1007/s00251-011-0579-8

  16. Nielsen M, Lund O, Buus S, Lundegaard C (2010) MHC class II epitope predictive algorithms. Immunology 130(3):319–328. doi:10.1111/j.1365-2567.2010.03268.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Godkin AJ, Smith KJ, Willis A, Tejada-Simon MV, Zhang J, Elliott T, Hill AV (2001) Naturally processed HLA class II peptides reveal highly conserved immunogenic flanking region sequence preferences that reflect antigen processing rather than peptide-MHC interactions. J Immunol 166(11):6720–6727

    Article  CAS  PubMed  Google Scholar 

  18. Lovitch SB, Pu Z, Unanue ER (2006) Amino-terminal flanking residues determine the conformation of a peptide-class II MHC complex. J Immunol 176(5):2958–2968. doi:176/5/2958 (pii)

    Article  CAS  PubMed  Google Scholar 

  19. Nielsen M, Lund O (2009) NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction. BMC Bioinformatics 10:296. doi:10.1186/1471-2105-10-296

    Article  PubMed  PubMed Central  Google Scholar 

  20. Nielsen M, Lundegaard C, Blicher T, Peters B, Sette A, Justesen S, Buus S, Lund O (2008) Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol 4(7):e1000107. doi:10.1371/journal.pcbi.1000107

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nielsen M, Justesen S, Lund O, Lundegaard C, Buus S (2010) NetMHCIIpan-2.0—Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure. Immunome Res 6:9. doi:1745-7580-6-9 (pii) 10.1186/1745-7580-6-9

    Article  PubMed  PubMed Central  Google Scholar 

  22. Lin HH, Zhang GL, Tongchusak S, Reinherz EL, Brusic V (2008) Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research. BMC Bioinformatics 9(Suppl 12):S22. doi:10.1186/1471-2105-9-S12-S22

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B (2008) A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol 4(4):e1000048. doi:10.1371/journal.pcbi.1000048

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bordner AJ, Mittelmann HD (2010) MultiRTA: a simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes. BMC Bioinformatics 11:482. doi:10.1186/1471-2105-11-482

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zhang GL, Deluca DS, Keskin DB, Chitkushev L, Zlateva T, Lund O, Reinherz EL, Brusic V (2010) MULTIPRED2: a computational system for large-scale identification of peptides predicted to bind to HLA supertypes and alleles. J Immunol Methods. doi:S0022-1759(10)00345-5 (pii) 10.1016/j.jim.2010.11.009

    Google Scholar 

  26. Kullback S, Leibler RA (1951) On Information and Sufficiency. Ann Math Statist 22:76–86

    Article  Google Scholar 

  27. Rapin N, Hoof I, Lund O, Nielsen M. The MHC motif viewer: a visualization tool for MHC binding motifs. Curr Protoc Immunol. 2010; Chapter 18: Unit 18 17. doi:10.1002/0471142735.im1817s88.

  28. Erup Larsen M, Kloverpris H, Stryhn A, Koofhethile CK, Sims S, Ndung’u T, Goulder P, Buus S, Nielsen M (2011) HLArestrictor–a tool for patient-specific predictions of HLA restriction elements and optimal epitopes within peptides. Immunogenetics 63(1):43–55. doi:10.1007/s00251-010-0493-5

    Article  PubMed  Google Scholar 

  29. Rao X, Costa AI, van Baarle D, Kesmir C (2009) A comparative study of HLA binding affinity and ligand diversity: implications for generating immunodominant CD8+ T cell responses. J Immunol 182(3):1526–1532. doi:182/3/1526 (pii)

    Article  CAS  PubMed  Google Scholar 

  30. Stranzl T, Larsen MV, Lundegaard C, Nielsen M (2010) NetCTLpan: pan-specific MHC class I pathway epitope predictions. Immunogenetics 62(6):357–368. doi:10.1007/s00251-010-0441-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hoof I, Perez CL, Buggert M, Gustafsson RK, Nielsen M, Lund O, Karlsson AC (2010) Interdisciplinary analysis of HIV-specific CD8+ T cell responses against variant epitopes reveals restricted TCR promiscuity. J Immunol 184(9):5383–5391. doi:jimmunol.0903516 (pii) 10.4049/jimmunol.0903516

    Article  CAS  PubMed  Google Scholar 

  32. Larsen MV, Lelic A, Parsons R, Nielsen M, Hoof I, Lamberth K, Loeb MB, Buus S, Bramson J, Lund O (2010) Identification of CD8+ T cell epitopes in the West Nile virus polyprotein by reverse-immunology using NetCTL. PLoS One 5(9):e12697. doi:10.1371/journal.pone.0012697

    Article  PubMed  PubMed Central  Google Scholar 

  33. Nielsen M, Lundegaard C, Lund O, Kesmir C (2005) The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenetics 57(1–2):33–41. doi:10.1007/s00251-005-0781-7

    Article  CAS  PubMed  Google Scholar 

  34. Larsen MV, Lundegaard C, Lamberth K, Buus S, Brunak S, Lund O, Nielsen M (2005) An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions. Eur J Immunol 35(8):2295–2303. doi:10.1002/eji.200425811

    Article  CAS  PubMed  Google Scholar 

  35. Peters B, Bulik S, Tampe R, Van Endert PM, Holzhutter HG (2003) Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors. J Immunol 171(4):1741–1749

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Kongens Lyngby, Denmark

    Ole Lund & Claus Lundegaard

  2. Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kongens Lyngby, Denmark

    Edita Karosiene, Mette Voldby Larsen & Morten Nielsen

Authors
  1. Ole Lund
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edita Karosiene
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Claus Lundegaard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mette Voldby Larsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Morten Nielsen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ole Lund .

Editor information

Editors and Affiliations

  1. Institut National de la Santé et de la Recherche Médicale, Unité 1013, Université Paris Descartes, Faculté de médecine, Paris, France

    Peter van Endert

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Lund, O., Karosiene, E., Lundegaard, C., Larsen, M.V., Nielsen, M. (2013). Bioinformatics Identification of Antigenic Peptide: Predicting the Specificity of Major MHC Class I and II Pathway Players. In: van Endert, P. (eds) Antigen Processing. Methods in Molecular Biology™, vol 960. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-218-6_19

Download citation

  • DOI: https://doi.org/10.1007/978-1-62703-218-6_19

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-217-9

  • Online ISBN: 978-1-62703-218-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation