Skip to main content
SpringerLink
Log in

Genome-Based Bioinformatic Prediction of Major Histocompatibility (MHC)

  • Protocol
  • First Online:
Book cover Immunoproteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2024))

  • 2374 Accesses

Abstract

Over the last 17 years, a large amount of knowledge has been accumulated on various aspects of major histocompatibility complex (MHC) molecules. In conjunction, numerous algorithms and tools have been developed to screen protein molecules for these MHC receptor sites. By combining these computational tools and databases with genomic sequence information that is now widely available for a vast range of organisms, it is possible to screen whole genomes for MHC epitopes. By pre-screening these genomes, it allows the researcher to narrow down possible protein targets for further analysis by traditional tools such as gene knockouts and animal efficacy studies.

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 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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. Falk K, Rötzschke O, Stevanović S et al (1991) Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature 351:290–296

    Article  CAS  Google Scholar 

  2. Chicz RM, Urban RG, Gorga JC et al (1993) Specificity and promiscuity among naturally processed peptides bound to HLA-DR alleles. J Exp Med 178:27–47

    Article  CAS  Google Scholar 

  3. Shen H, Harris G, Chen W et al (2010) Molecular immune responses to aerosol challenge with Francisella tularensis in mice inoculated with live vaccine candidates of varying efficacy. PLoS One 5:e13349

    Article  Google Scholar 

  4. Singh H, Raghava GPS (2003) ProPred1: prediction of promiscuous MHC Class-I binding sites. Bioinformatics 19:1009–1014

    Article  CAS  Google Scholar 

  5. Jurtz V, Paul S, Andreatta M, Marcatili P et al (2017) NetMHCpan-4.0: improved peptide–MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J Immunol 199(9):3360–3368

    Article  CAS  Google Scholar 

  6. Jensen KK, Andreatta M, Marcatili P et al (2018) Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology 154:394–406

    Article  CAS  Google Scholar 

  7. Zhang L, Chen Y, Wong H-S et al (2012) TEPITOPEpan: extending TEPITOPE for peptide binding prediction covering over 700 HLA-DR molecules. PLoS One 7:e30483

    Article  CAS  Google Scholar 

  8. Lata S, Bhasin M, Raghava GPS (2009) MHCBN 4.0: a database of MHC/TAP binding peptides and T-cell epitopes. BMC Res Notes 2:61

    Article  Google Scholar 

  9. Reche PA, Glutting J-P, Zhang H, Reinherz EL (2004) Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics 56:405–419

    Article  CAS  Google Scholar 

  10. Vita R, Zarebski L, Greenbaum JA et al (2010) The immune epitope database 2.0. Nucleic Acids Res 38:D854–D862

    Article  CAS  Google Scholar 

  11. Gardy JL, Spencer C, Wang K et al (2003) PSORT-B: improving protein subcellular localization prediction for Gram-negative bacteria. Nucleic Acids Res 31:3613–3617

    Article  CAS  Google Scholar 

  12. Nielsen H (2017) Predicting secretory proteins with SignalP. Methods Mol Biol 1611:59–73

    Article  CAS  Google Scholar 

  13. Bendtsen JD, Kiemer L, Fausbøll A, Brunak S (2005) Non-classical protein secretion in bacteria. BMC Microbiol 5:58

    Article  Google Scholar 

  14. Bendtsen JD, Jensen LJ, Blom N et al (2004) Feature-based prediction of non-classical and leaderless protein secretion. Protein Eng Des Sel 17:349–356

    Article  CAS  Google Scholar 

  15. Juncker AS, Willenbrock H, Von Heijne G et al (2003) Prediction of lipoprotein signal peptides in Gram-negative bacteria. Protein Sci 12:1652–1662

    Article  CAS  Google Scholar 

  16. Lin HH, Ray S, Tongchusak S et al (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunol 9:8

    Article  Google Scholar 

  17. Soria-Guerra RE, Nieto-Gomez R, Govea-Alonso DO, Rosales-Mendoza S (2015) An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform 53:405–414

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, ON, Canada

    Simon J. Foote

Authors
  1. Simon J. Foote
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Simon J. Foote .

Editor information

Editors and Affiliations

  1. Human Health Therapeutics Research Centre, National Research Council of Canada, Ottawa, ON, Canada

    Kelly M. Fulton

  2. Human Health Therapeutics Research Centre, National Research Council of Canada, Ottawa, ON, Canada

    Susan M. Twine

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Foote, S.J. (2019). Genome-Based Bioinformatic Prediction of Major Histocompatibility (MHC). In: Fulton, K., Twine, S. (eds) Immunoproteomics. Methods in Molecular Biology, vol 2024. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9597-4_18

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-9597-4_18

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9596-7

  • Online ISBN: 978-1-4939-9597-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation