Computational analysis of the relationship between allergenicity and digestibility of allergenic proteins in simulated gastric fluid

BACKGROUND: Safety assessment of genetically modified (GM) food, with regard to allergenic potential of transgene-encoded xenoproteins, typically involves several different methods, evaluation by digestibility being one thereof. However, there are still debates about whether the allergenicity of food allergens is related to their resistance to digestion by the gastric fluid. The disagreements may in part stem from classification of allergens only by their sources, which we believe is inadequate, and the difficulties in achieving identical experimental conditions for studying digestion by simulated gastric fluid (SGF) so that results can be compared. Here, we reclassify allergenic food allergens into alimentary canal-sensitized (ACS) and non-alimentary canal-sensitized (NACS) allergens and use a computational model that simulates gastric fluid digestion to analyze the digestibilities of these two types. RESULTS: The model presented in this paper is as effective as SGF digestion experiments, but more stable and reproducible. On the basis of this model, food allergens are satisfactorily classified as ACS and NACS types by their pathways for sensitization; the former are relatively resistant to gastric fluid digestion while the later are relatively labile. CONCLUSION: The results suggest that it is better to classify allergens into ACS and NACS types when understanding the relationship between their digestibility and allergenicity and the digestibility of a target foreign protein is a parameter for evaluating its allergenicity during safety assessments of GM food.