Human gut microbial metabolites are currently undergoing much research due to their involvement in multiple biological processes that are important for health, including immunity, metabolism, nutrition, and the nervous system. Metabolites exert their effect through interaction with host and bacterial proteins, suggesting the use of "metabolite-mimetic" molecules as drugs and nutraceutics. In the present work, we retrieve and analyze the full set of published interactions of these compounds with human and microbiome-relevant proteins and find patterns in their structure, chemical class, target class, and biological origins. In addition, we use virtual screening to expand (more than 4-fold) the interactions, validate them with retrospective analyses, and use bioinformatic tools to prioritize them based on biological relevance. In this way, we fill many of the chemobiological gaps observed in the published data. By providing these interactions, we expect to speed up the full clarification of the chemobiological space of these compounds by suggesting many reliable predictions for fast, focused experimental testing.