An in silico method using an epitope motif database for predicting the location of antigenic determinants on proteins in a structural context.

Presently X-ray crystallography of protein-antibody complexes is still the most direct way of identifying B-cell epitopes. The objective of this study was to assess the potential of a computer-based epitope mapping tool (EMT) using antigenic amino acid motifs as a fast alternative in a number of applications not requiring detailed information, e.g. development of pharmaceutical proteins, vaccines and industrial enzymes. Using Gal d 4 as a model protein, the EMT was capable of identifying, in the context of the folded protein, amino acid positions known to be involved in antibody binding. The high sensitivity and positive predictive value of the EMT as well as the relevance of the structural associations suggested by the EMT indicated the existence of amino acid motifs that are likely to be involved in antigenic determinants. In addition, differential mapping revealed that sensitivity and positive predictive value were dependent on the minimum relative surface accessibility (RSA) of the amino acids included in the mapping, demonstrating that the EMTs accommodated for the fact that epitopes are three-dimensional entities with various degrees of accessibility. The comparison with existing prediction scales demonstrated the superiority of the EMT with respect to physico-chemical scales. The mapping tool also performed better than the available structural scales, but the significance of the differences remains to be established. Thus, the EMT has the potential of becoming a fast and simple alternative to X-ray crystallography for predicting structural antigenic determinants, if detailed epitope information is not required.