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. 2010;2010:910524.
doi: 10.1155/2010/910524. Epub 2010 Mar 30.

Benchmarking B-cell Epitope Prediction for the Design of Peptide-Based Vaccines: Problems and Prospects

Free PMC article

Benchmarking B-cell Epitope Prediction for the Design of Peptide-Based Vaccines: Problems and Prospects

Salvador Eugenio C Caoili. J Biomed Biotechnol. .
Free PMC article


To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments). If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design.

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