ReviewCurrent opinion in chemical biology2026
Self-resistance as a guide to discovering bioactive natural products.
Review in Current opinion in chemical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.