Data mining of sequences and 3D structures of allergenic proteins

Area of Science:

• Immunology and Bioinformatics
• Protein Science

Background:

• Allergens, despite diverse sources, belong to distinct protein families.
• Clinical cross-reactivities between allergens suggest underlying sequence similarities.
• Existing databases lack detailed protein sequence and structure comparisons for allergens.

Purpose of the Study:

• To develop a computer-aided system for comparing sequential and structural details of known allergens.
• To predict allergenic cross-responses and identify common features of IgE recognition.

Main Methods:

• Developed a web-based Structural Database of Allergenic Proteins (SDAP).
• Integrated literature data and existing allergen lists into a MySQL database.
• Implemented a novel similarity search using five-dimensional amino acid property descriptors.

Main Results:

• SDAP enables rapid comparison of allergenic protein sequences and structures.
• The system can screen novel proteins for shared IgE or T-cell epitopes.
• A similarity search successfully identified cross-reactive epitopes in shrimp tropomyosin, shellfish, and insect allergens, consistent with clinical data.

Conclusions:

• SDAP facilitates the study of allergen relationships and cross-reactivity prediction.
• The database and search method aid in understanding IgE binding and allergic mechanisms.
• SDAP is a valuable resource for researchers investigating allergies and protein similarities.