AllerCatPro 2.0: a web server for predicting protein allergenicity potential

Area of Science:

• Bioinformatics
• Immunology
• Computational Biology

Background:

• Proteins in food and personal care products can trigger immediate immunoglobulin E (IgE)-mediated allergic reactions.
• Bioinformatic tools are crucial for predicting and investigating the allergenic potential of proteins.
• Accurate assessment of protein allergenicity is vital for public health and product safety.

Purpose of the Study:

• To introduce AllerCatPro 2.0, an enhanced web server for predicting protein allergenicity.
• To improve the accuracy of computational methods for allergenicity prediction.
• To provide new features that assist assessors in making informed decisions regarding protein allergens.

Main Methods:

• AllerCatPro 2.0 predicts protein allergenicity by comparing input sequences and structures against comprehensive, curated datasets.
• Utilizes datasets including 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens.
• Integrates data from expert-curated databases like WHO/IUIS, COMPARE, FARRP, UniProtKB, and Allergome.

Main Results:

• AllerCatPro 2.0 demonstrates improved accuracy in predicting protein allergenicity compared to existing computational methods.
• The server effectively analyzes various protein types, including profilins, autoimmune allergens, and low allergenic proteins.
• Demonstrates utility across diverse inputs, including nucleotide sequences and very large proteins.

Conclusions:

• AllerCatPro 2.0 is a valuable web server for accurate protein allergenicity prediction.
• The tool enhances decision-making for assessors by providing reliable allergenicity assessments.
• Freely accessible at https://allercatpro.bii.a-star.edu.sg, AllerCatPro 2.0 supports research in food and personal care product safety.