B-cell epitope mapping within the MA16 antigenic sequence found in Eimeria acervulina merozoites and sporozoites

Recent developments with B-cell epitope identification for predictive studies

This review discusses currently available methods for predicting B-cell epitopes on proteins. The use of animals for assessing protein immunogenicity is addressed primarily to highlight the differences in B- and T-cell epitope recognition between species. These differences have to be considered when interpreting potential B-cell epitopes identified by the methods addressed here. "In vitro alternatives" focuses on the strengths and limitations of peptide-based technologies. Three types of computer-based methods for identifying potential B-cell epitopes are discussed: (i) methods applying physico-chemical and structural propensity scales for predicting linear epitopes from the primary structure of a protein, (ii) comparative methods basing prediction upon amino acid sequence and structural similarities between antigenically known and unknown proteins, and (iii) a method combining structural features with a B-cell epitope motif database for predicting linear and conformational antigenic determinants. With respect to human safety, the usefulness of antibody-based tests is limited to comparative studies between an antigenically known protein and variants thereof. Similarly, computer-based methods using data mining can address similarities in B-cell epitope profiles between related proteins, if a proper cut off can be defined for the minimal amino acid sequence similarity required for obtaining an acceptable accuracy. Among the physico-chemical and structural scales, scales identifying in a protein hairpin and non-specific turns seem useful for predicting epitopes with a continuous primary binding site. When conformational epitopes have to be identified as well, a novel computer-based tool seems to be the most promising alternative to X-ray crystallography. However, both methods remain to be extensively evaluated and validated. Thus, promising tools for B-cell epitope identification have been developed. But, no validated method for B-cell epitope identification on antigenically unknown proteins is available yet.

A novel anti-tissue factor monoclonal antibody with anticoagulant potency derived from synthesized multiple antigenic peptide through blocking FX combination with TF

Tissue factor (TF) has been implicated in the pathogenesis of various thrombotic disorders. Monoclonal antibodies (mAb) that specifically target TF may have potential as antithrombotic therapy. We designed a unique TF peptide (TFP) that was specific for the binding site to factor X (FX). This peptide was used to develop TF mAb that block the coagulation cascade by interfering with the combination of FX with the TF/FVIIa complex. Chemically synthesized TFP coupled to polylysine matrix was used as multiple antigenic peptide (TF-MAP) and this was used to immunize Balb/c mice for the preparation of hybridomas. One hybridoma cell line released an antibody, named TF4A12, which had high anticoagulant potency (by dilute prothrombin time assay). Western blotting showed that TF4A12 could bind TF-MAP and the soluble TF extracellular domain (sTF(1-219)). Results of FX activation assay and amidolytic activity assay showed that the anticoagulant ability of TF4A12 is due to blocking FX, but not FVII, binding to TF. Our study identified an efficient method of developing TF mAb that could block the coagulation cascade.

Anin 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.

Mapping for B-cell epitopes in the GX3262 antigenic sequence derived from Eimeria tenella sporulated oocysts

Polypropylene pins were impregnated with synthetic overlapping heptapeptides based on the GX3262 Eimeria tenella antigenic sequence (Miller et al., 1989). Using these coated pins as the solid phase of an enzyme immunoassay (EIA), binding of sera from chickens and rabbits infected and immunised respectively with five different species of Eimeria were examined. Antibody reactions to the individual heptapeptides were then analysed by a number of criteria based on the amino acid sequence including hydropathy, chain flexibility and secondary structure.