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Open Access Research article

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

Patricio Oyarzún12*, Jonathan J Ellis1, Mikael Bodén13 and Boštjan Kobe1*

Author Affiliations

1 School of Chemistry and Molecular Biosciences, Institute for Molecular Bioscience and Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD, 4072, Australia

2 Biotechnology Centre, Universidad San Sebastian, Bellavista 7, Recoleta, Santiago, 8420524, Chile

3 School of Information Technology and Electrical Engineering, University of Queensland, Queensland, 4072, Australia

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BMC Bioinformatics 2013, 14:52  doi:10.1186/1471-2105-14-52

Published: 14 February 2013

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/ webcite.

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