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Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W138-42.

PEPVAC: a web server for multi-epitope vaccine development based on the prediction of supertypic MHC ligands.

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  • 1Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, MA 02115, USA. reche@research.dfci.harvard.edu

Abstract

Prediction of peptide binding to major histocompatibility complex (MHC) molecules is a basis for anticipating T-cell epitopes, as well as epitope discovery-driven vaccine development. In the human, MHC molecules are known as human leukocyte antigens (HLAs) and are extremely polymorphic. HLA polymorphism is the basis of differential peptide binding, until now limiting the practical use of current epitope-prediction tools for vaccine development. Here, we describe a web server, PEPVAC (Promiscuous EPitope-based VACcine), optimized for the formulation of multi-epitope vaccines with broad population coverage. This optimization is accomplished through the prediction of peptides that bind to several HLA molecules with similar peptide-binding specificity (supertypes). Specifically, we offer the possibility of identifying promiscuous peptide binders to five distinct HLA class I supertypes (A2, A3, B7, A24 and B15). We estimated the phenotypic population frequency of these supertypes to be 95%, regardless of ethnicity. Targeting these supertypes for promiscuous peptide-binding predictions results in a limited number of potential epitopes without compromising the population coverage required for practical vaccine design considerations. PEPVAC can also identify conserved MHC ligands, as well as those with a C-terminus resulting from proteasomal cleavage. The combination of these features with the prediction of promiscuous HLA class I ligands further limits the number of potential epitopes. The PEPVAC server is hosted by the Dana-Farber Cancer Institute at the site http://immunax.dfci.harvard.edu/PEPVAC/.

PMID:
15980443
[PubMed - indexed for MEDLINE]
PMCID:
PMC1160118
Free PMC Article
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