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Elucidating the Biosynthesis of the Core Structure of Enediyne Natural Products

Subject Area Biochemistry
Term from 2022 to 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 509137346
 
Final Report Year 2024

Final Report Abstract

Enediyne natural products and their biosynthesis have been an enigmatic topic to the scientific community since their initial discovery in 1983. Only 20 compounds with this structure have been identified since, and they can all be grouped into three types: 9-membered enediynes (C-1027-type), 10-membered enediynes (CAL-type), and 10-membered enediynes, fused to an anthraquinone (AFE-type). A better understanding of enediynes is of crucial interest, as they posses a unique and highly potent DNA-cleavage activity. This makes them valuable chemotherapeutics in cancer treatments, where they are used, coupled with antibodies, as antibody-drug-conjugates. While new but related structures have steadily been discovered, only miniscule progress has been made regarding the biosynthesis of these compounds. The biosynthetic gene clusters (BGCs) for C-1027 and calicheamicin were reported in 2002, which allowed the identification of enediynes as polyketides, with their linear precursor being tetradecaheptaene. How this molecule, which was only unambiguously established as the precursor in 2022, is further converted remained unclear to this point. As a part of this study, a five gene cassette was identified as essential and universal to all known enediyne BGCs. Apart from the polyketide synthase and the thioesterase to make tetradecaheptaene, this cassette consists of three additional enzymes of unknown function that transform this intermediate into a double-iodinated ene-tetrayne. This molecule could be identified as a universal intermediate to the three known types of enediynes, and the cryptic iodination can be utilized as an on/off-switch in future enediyne discovery studies. Furthermore, the identification of the unified and highly conserved five-gene-cassette allows for the bioinformatic identification of putative enediyne BGCs and the prioritization of strains for fermentation based on these predictions.

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