Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg.
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.