Skip to main content
SpringerLink
Log in

T-Cell Epitope Prediction

  • Protocol
  • First Online:
Food Allergens

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1592))

Abstract

An epitope is a part of an immunogenic protein that can be recognized by the immune system. The peptides that can be recognized by the T-cell receptors after a particular antigen has been intracellularly processed, bound to at least one MHC molecule and expressed on the surface of the antigen presenting cell as a MHC-peptide complex, are called a T-cell epitope. Individuals who have at least one MHC molecule able to most avidly bind to allergenic amino acid sequences from an allergen, and at the same time have the appropriate T-cell clone that can recognize this MHC-peptide complex, are expected to be genetically prone to allergic reactions against that allergen. This possibility can be examined in silico by utilizing modern computational techniques that are based on sophisticated mathematics and statistics. The design principles of these techniques are different and therefore variations in their predictions are expected. The available software programs that have been developed on this basis are able to combine the increasing amount and complexity of the available experimental data that have been organized in immunoinformatics databases to predict potential allergen T-cell epitopes. All relevant T-cell epitope prediction methods can be accessed online as a freeware.

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 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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. Barlow DJ, Edwards MS, Thornton JM (1986) Continuous and discontinuous protein antigenic determinants. Nature 322(6081):747–748. doi:10.1038/322747a0

    Article  CAS  PubMed  Google Scholar 

  2. Abbas AK, Lichtman AH, Pillai S (2015) Cellular and molecular immunology, 8th edn. Saunders/Elsevier, Philadelphia, PA

    Google Scholar 

  3. Reche PA, Reinherz EL (2007) Definition of MHC supertypes through clustering of MHC peptide-binding repertoires. Methods Mol Biol 409:163–173. doi:10.1007/978-1-60327-118-9_11

    Article  CAS  PubMed  Google Scholar 

  4. Pascal M, Konstantinou GN, Masilamani M, Lieberman J, Sampson HA (2013) In silico prediction of Ara h 2 T cell epitopes in peanut-allergic children. Clin Exp Allergy 43(1):116–127. doi:10.1111/cea.12014

    Article  CAS  PubMed  Google Scholar 

  5. Ramesh M, Yuenyongviwat A, Konstantinou GN, Lieberman J, Pascal M, Masilamani M, Sampson HA (2016) Peanut T-cell epitope discovery: Ara h 1. J Allergy Clin Immunol. doi:10.1016/j.jaci.2015.12.1327

    Google Scholar 

  6. 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 

  7. Peters B, Sette A (2005) Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6:132. doi:10.1186/1471-2105-6-132

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kim Y, Sidney J, Pinilla C, Sette A, Peters B (2009) Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. BMC Bioinformatics 10:394. doi:10.1186/1471-2105-10-394

    Article  PubMed  PubMed Central  Google Scholar 

  9. Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A, Peters B (2008) Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunol Res 4:2. doi:10.1186/1745-7580-4-2

    Google Scholar 

  10. Moutaftsi M, Peters B, Pasquetto V, Tscharke DC, Sidney J, Bui HH, Grey H, Sette A (2006) A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus. Nat Biotechnol 24(7):817–819. doi:10.1038/nbt1215

    Article  CAS  PubMed  Google Scholar 

  11. 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 

  12. Karosiene E, Lundegaard C, Lund O, Nielsen M (2012) NetMHCcons: a consensus method for the major histocompatibility complex class I predictions. Immunogenetics 64(3):177–186. doi:10.1007/s00251-011-0579-8

    Article  CAS  PubMed  Google Scholar 

  13. 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 

  14. 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 

  15. 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 

  16. Nielsen M, Lundegaard C, Lund O (2007) Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics 8:238. doi:10.1186/1471-2105-8-238

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, Hammer J (1999) Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol 17(6):555–561. doi:10.1038/9858

    Article  CAS  PubMed  Google Scholar 

  18. 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 

  19. Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, Peters B (2010) Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics 11:568. doi:10.1186/1471-2105-11-568

    Article  PubMed  PubMed Central  Google Scholar 

  20. Zhang L, Udaka K, Mamitsuka H, Zhu S (2012) Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools. Brief Bioinform 13(3):350–364. doi:10.1093/bib/bbr060

    Article  CAS  PubMed  Google Scholar 

  21. Calis JJ, Maybeno M, Greenbaum JA, Weiskopf D, De Silva AD, Sette A, Kesmir C, Peters B (2013) Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput Biol 9(10):e1003266. doi:10.1371/journal.pcbi.1003266

    Article  PubMed  PubMed Central  Google Scholar 

  22. Altrichter S, Peter HJ, Pisarevskaja D, Metz M, Martus P, Maurer M (2011) IgE mediated autoallergy against thyroid peroxidase--a novel pathomechanism of chronic spontaneous urticaria? PLoS One 6(4):e14794. doi:10.1371/journal.pone.0014794

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Valenta R, Seiberler S, Natter S, Mahler V, Mossabeb R, Ring J, Stingl G (2000) Autoallergy: a pathogenetic factor in atopic dermatitis? J Allergy Clin Immunol 105(3):432–437. doi:10.1067/mai.2000.104783

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Allergy and Clinical Immunology, 424 General Military Training Hospital, 11 Eleftheriou Venizelou Street, Kalamaria, 55 133, Thessaloniki, Greece

    George N. Konstantinou

  2. Division of Allergy and Immunology and Jaffe Food Allergy Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA

    George N. Konstantinou

Authors
  1. George N. Konstantinou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to George N. Konstantinou .

Editor information

Editors and Affiliations

  1. Bioinformatics Institute, A*STAR, Singapore, Singapore

    Jing Lin

  2. School of Biosciences, University of Nottingham, Sutton Bonington Campus, Leicestershire, United Kingdom

    Marcos Alcocer

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this protocol

Cite this protocol

Konstantinou, G.N. (2017). T-Cell Epitope Prediction. In: Lin, J., Alcocer, M. (eds) Food Allergens. Methods in Molecular Biology, vol 1592. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6925-8_17

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6925-8_17

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6923-4

  • Online ISBN: 978-1-4939-6925-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation