Coeliac disease (CeD) is an autoimmune disease caused by gluten ingestion, in which gluten peptides derived predominantly from wheat, barley, and rye initiate immune responses in genetically predisposed individuals. According to new research, the gut microbiota might play a role in CeD by generating enzymes such as prolyl oligopeptidases (POPs), glutamine-specific cysteine endoproteases, and subtilisins that can break immunogenic gluten peptides, potentially reducing their toxicity (1,2). However, nothing is known about the precise bacterial taxa responsible for these enzymatic activities, or how they influence CeD progression. In this study, we describe an integrative bioinformatic and computational approach for identifying and characterising bacterial proteases in the gut microbiome that may degrade gluten epitopes linked to CeD. We created a meta-analysis dataset by combining over 17 datasets from CeD microbiome studies. We then used bacterial genome datasets to create a proteomic resource focusing on enzymes capable of degrading gluten. By integrating microbiome and proteome data, we investigated interactions between CeD-associated bacterial taxa and potential gluten-degrading enzymes. We next used computational tools like MODELLER and PEP-FOLD to model selected enzymes and begin experimental validation of their gluten-degrading capabilities. Our approach identified prospective proteins and novel relationships between the gut microbiome and the host, broadening our understanding of microbial protease activity and its potential to reduce gluten immunotoxicity in CeD. Moving forward, we intend to conduct more experiments to validate and characterise these enzymes, which will provide novel insights into potential future therapeutic strategies for CeD.