UC San Diego

Natural products have an unparalleled track record as sources of clinical drugs. Among them, nonribosomal peptides (NRPs) stand as one of the most therapeutically significant classes, encompassing numerous approved anti-infective and anticancer agents. Yet, discovering bioactive NRPs remains profoundly challenging due to their complex biosynthesis and chemical architecture. Here, we present NPDiscover, a pathogen-oriented, scalable bioinformatics platform that integrates genome mining, metabolomics, and machine learning to identify NRPs active against drug-resistant pathogens. Applying NPDiscover to Actinobacteria datasets, we discovered edaphochelin A, a previously unreported NRP that kills multi-drug-resistant Candida auris and Candida glabrata by disrupting respiratory chain proteins. Structural elucidation via nuclear magnetic resonance and mass spectrometry, alongside in vitro and in vivo validation, confirmed its efficacy, safety, and a mode of action distinct from existing antifungals-establishing edaphochelin A as a compelling drug candidate and NPDiscover as a powerful engine for scalable natural product discovery.