Expanding the drug discovery space with predicted metabolite-target interactions

Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potential metabolite-target interactions using the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2). Using a consensus of multiple machine learning methods, we ranked metabolites based on importance to IBD, followed by virtual ligand-based screening to identify possible human targets and adding evidence from compound assay, differential gene expression, pathway enrichment, and genome-wide association studies. We confirmed known metabolite-target pairs such as nicotinic acid-GPR109a or linoleoyl ethanolamide-GPR119 and inferred interactions of interest including oleanolic acid-GABRG2 and alpha-CEHC-THRB. Eleven metabolites were tested for bioactivity in vitro using human primary cell-types. By expanding the universe of possible microbial metabolite-host protein interactions, we provide multiple drug targets for potential immune-therapies. Using computational approaches, Nuzzo et al. identify 983 potential metabolite-human target interactions from the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2) and public databases. These predicted interactions can further the understanding of host-microbiome interactions and assist in drug discovery for IBD and other diseases.

Automated summary

Using computational approaches, Nuzzo et al. identified 983 potential metabolite-human target interactions from the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2) and public databases. These predicted interactions can further the understanding of host-microbiome interactions and assist in drug discovery for IBD and other diseases.