Modeling Antigen Allergenicity with Bioinformatics Approaches

Allergenicity is a multifactorial and context-dependent property that emerges from the interaction between intrinsic protein features and host immune mechanisms. Although regulatory frameworks rely primarily on sequence homology to known allergens, increasing numbers of novel and engineered proteins require more comprehensive computational strategies for preclinical assessment. This chapter describes a modular bioinformatic pipeline for the prediction and characterization of potential protein allergens. The workflow integrates FAO/WHO sequence-based criteria for regulatory compliance, structure-informed homology methods, and machine learning-based classifiers. Proteins identified as potential allergens are subsequently subjected to downstream immunological characterization. This stepwise decision framework enables flexible and biologically informed prescreening of candidate proteins, providing a structured approach prior to experimental validation or systems biology-based analyses.