The prevalence of food allergies has increased in recent decades and affects up to 5% of the population, frequently resulting in severe symptoms. Specific structures of the corresponding proteins, the epitopes, are recognized by T‐cell receptors or IgE antibodies, resulting in an immune response. Many food allergens and immunogenic proteins for various plant‐based foods have been investigated thoroughly on different levels. However, research into the gastrointestinal metabolism of plant‐based food allergens on the molecular level is scarce, so far. The aim of this thesis was to characterize the gastrointestinal metabolism of food allergens and proteins involved in celiac disease, and to derive global properties that account for the immunogenic and allergenic potential of these proteins. Raw walnut, raw and cooked soybeans, and wheat‐based bread have been chosen as representatives for tree nuts, legumes and cereals, in order to adress the given research question. The project is divided into three sub‐steps, which are as follows: Adaption of the in vitro digestion model to different matrices and comprehensive analysis of proteins and peptides Development of a data‐processing strategy to enable visualisation of the resulting data Interpretation of the data regarding the gastrointestinal metabolism of relevant proteins in different matrices The in vitro digestion model by Minekus et al. was successfully adapted to simulate gastrointestinal digestion of a variety of food matrices. The analytical approach at protein level by SDS‐PAGE analysis and in‐gel digestion, combined with mass spectrometry at peptide level, enabled comprehensive identification of degradation products. As an example, up to 7279 peptides were assigned to soy proteins over the course of gastral digestion of raw soy, and a further 1027 peptides for samples of simulated intestinal digestion. In order to deal with these huge amounts of data, various data processing steps have been designed. Peptide identification by PEAKS® was extended using scripts in Python, to perform label‐free quantification of mass spectrometry data and to compare the identified degradation products with known epitopes. The multistage preprocessing approach developed in Python provided the basis for a set of data visualisations to further interpret the behaviour of proteins during gastrointestinal digestion. Analysis at protein and peptide levels revealed that quantities of most of the analysed proteins for all matrices exhibited stability against gastrointestinal digestion. Analysis of the resulting sequence coverage over the course of gastrointestinal digestion, combined with label‐free quantification in 3D surface plots, allowed conclusions on the behaviour of distinct protein regions over time. This approach provided detailed insights into the multistage formation and degradation mechanisms of differently sized peptides. ‐gliadin‐assigned peptides covering epitopes related to food allergy, as well as eight peptides covering celiac disease related epitopes, was characterized by label‐free quantification, outlining enhanced resistance against gastrointestinal digestion. Bioinformatic tools were applied to provide further characteristics of all proteins of interest related to the amino acid sequence. Sequence alignment with secondary structure features. The given results of this thesis provide insight into the stability of the proteins involved in adverse reactions to food, such as allergy or celiac disease, throughout the process of gastrointestinal digestion.