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In sílico prediction of cross-reactive epitopes of the major soybean allergen Gly m Bd 30K (P34) with bovine caseins and their analysis by immunochemical methods
CANDREVA ANGELA; PARISI, GUSTAVO; DOCENA, GUILLERMO HORACIO; PETRUCCELLI, SILVANA
Oro Verde, Entre Ríos, Argentina
Congreso; 3er. Congreso Argentino de Bioinformática y Biología Computacional,; 2012
Sociedad Argentina de Bioinformática y Biología Computacional,
Background Cow?s milk allergy (CMA) constitutes the main food allergy in Argentina. The nutritional substitutes mostly used are soy-based formulas; however, 40% of the patients do not tolerate soybean milk. The molecular bases of these reactions are not fully understood. Our group has shown that the major proteins of soybean 11S and 7S storage proteins, shared cross-reactive epitopes with bovine caseins. The aim of this work was to predict potential cross reactive epitopes in the major soy allergen P34. Although P34 is a minor seed component is considered a major soybean allergen. Servers currently available on the internet are not able to predict cross-reactive proteins between soybean proteins and cow?s milk proteins. Since the relevance of cross reactive epitopes between soybean and CMP has been confirmed by our group by in vitro immunochemical studies and in vivo using a mouse model for CMA, the performance of the in sílico prediction method needs to be improved it. Our objective was to develop a computational strategy to predict P34 and bovine caseins common epitopes and then compare the in sílico results with immunochemical analysis. Material and Methods For analysis of P34: bovine casein allergenic epitopes were obtained from the database IEDB , and then were aligned with P34 protein, the obtained results were plot in graphic built based on the consensus amino acid accumulation. P34 homology modeling, solvent accessibility and discontinuous epitopes: To build 3D models we used homology modeling with the sequence of the protein P34 (gi 195957142) as target. With this sequence we searched Protein Data Bank (PDB) to obtain putative templates. Using this model we obtained the positions exposed to solvent using the program DSSP. In addition, P34 modeled structure was used to analyzed if the cross reactive epitopes identified by the sequential analysis were predictive as B-cell epitopes by the Discotope server. Immunochemical analysis using Overlapping Synthetic Peptides: to test our prediction the entire protein sequence of P34 was synthesized as linear 15-mer overlapping peptides with five-residue shifts immobilized on paper. The recognition of the synthetic peptides by different primary antibodies: pool of IgE allergic patient sera reactive and mouse monoclonal antibodies (mAbs): specific of α, ß and κ-casein were assayed. Results The sequential analyzes detect two main regions with potential cross reactive epitopes: region A and B. Six 15 mer peptides in region A with the highest score were recognized by the two different pools of IgE patient sera, and the 3 casein specific mAbs. Only one region B peptides was recognized by the 3 mAbs. The predicted peptides were on the surface of the molecule exposed to the solvent. Conclusion In conclusion, the in sílico methods used in this work allow as predicting cross-reactive epitopes between P34 and bovine caseins that were confirmed by experimental analysis.