PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

Oyarzun, Patricio, Ellis, Jonathan J., Boden, Mikael and Kobe, Bostjan (2013) PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity. BMC Bioinformatics, 14 1: . doi:10.1186/1471-2105-14-52

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Author Oyarzun, Patricio
Ellis, Jonathan J.
Boden, Mikael
Kobe, Bostjan
Title PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity
Journal name BMC Bioinformatics   Check publisher's open access policy
ISSN 1471-2105
Publication date 2013-02-14
Year available 2013
Sub-type Article (original research)
DOI 10.1186/1471-2105-14-52
Open Access Status DOI
Volume 14
Issue 1
Total pages 11
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Background: CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge.
Results: We developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design.
Conclusions: The comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/
Keywords: CD4+ T-cell epitope prediction; Epitope-based vaccination; Immunodominance; MHC (HLA) class II proteins; MHC (HLA) class II polymorphism; Pan-specific; Peptide binding prediction; Peptide vaccination, Specificity-determining residues
Keyword CD4+T-cell epitope prediction
Epitope-based vaccination
Immunodominance
MHC (HLA) class II proteins
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article # 52

 
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Created: Fri, 05 Apr 2013, 23:16:18 EST by Mrs Louise Nimwegen on behalf of School of Chemistry & Molecular Biosciences