Detecting potential IgE-reactive sites on food proteins using a sequence and structure database, SDAP-food

Area of Science:

• Food Science
• Allergy Research
• Bioinformatics

Background:

• Food allergies and oral allergy syndrome are significant public health concerns.
• Introducing novel foods requires careful assessment of potential allergenicity.
• Predicting IgE-binding potential and cross-reactivities is crucial for food safety.

Purpose of the Study:

• To introduce SDAP-Food, a structural database for predicting food allergenicity.
• To facilitate early-stage assessment of novel food protein allergenicity.
• To identify potential cross-reactivities between food allergens and known allergenic proteins.

Main Methods:

• Development of SDAP-Food database for allergenic proteins.
• Utilizing a decision tree approach based on sequence and structural similarity.
• Employing a hierarchical procedure with a physical property-based sequence similarity index.
• Using homology modeling (EXDIS/DIAMOD/FANTOM) to assess epitope structure and location.

Main Results:

• SDAP-Food aids in predicting IgE-binding potential of novel food proteins.
• Identified sequence similarity between mountain cedar pollen allergen (Jun a 3) and food allergens (cherry, apple, pepper).
• Homology modeling revealed similar surface location and structure for potential epitopes in these allergens.
• Demonstrated a quantitative approach for screening potential allergenicity in recombinant food products.

Conclusions:

• SDAP-Food provides a valuable tool for predicting food allergenicity and cross-reactivities.
• The approach aids in identifying potential allergens early in the food development process.
• This method supports the safety assessment of new food crops and recombinant food products.