Self-resistance as a guide to discovering bioactive natural products

Natural products (NPs) remain vital to drug discovery, yet the identification of novel bioactive NPs is frequently hampered by the rediscovery of known compounds in traditional screening and the "bioactivity gap" in genome mining. Self-resistance-guided genome mining has emerged as a transformative strategy to address these challenges, leveraging co-localized resistance genes within biosynthetic gene clusters (BGCs) to predict NPs' molecular targets. This review summarizes recent progress in discovering novel NPs that target essential cellular processes, including protein synthesis, protein degradation, DNA integrity, and primary metabolism. We further highlight key technologies and strategies designed to accelerate this discovery workflow and discuss the limitations and opportunities of self-resistance-guided genome mining for the systematic discovery of precision therapeutics in the genomic era.