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However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, <jats:italic>Clostridium sporogenes<\/jats:italic>, against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in <jats:italic>C. sporogenes<\/jats:italic> culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of <jats:italic>C. sporogenes<\/jats:italic> responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches.<\/jats:p>","DOI":"10.1002\/anie.202319925","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T03:25:11Z","timestamp":1706585111000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Mining the Metabolic Capacity of <i>Clostridium sporogenes<\/i> Aided by Machine Learning"],"prefix":"10.1002","volume":"63","author":[{"given":"Huanrong","family":"Ouyang","sequence":"first","affiliation":[{"name":"Department of Chemical Engineering Texas A&amp;M University  College Station 77843 United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhao","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of 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