Zhao Yong, Duan Yao-Tao, Zang Jie, Raadam Morten H, Pateraki Irini, Miettinen Karel, Staerk Dan, Kampranis Sotirios C
Biochemical Engineering Group, Department of Plant and Environment Sciences, Faculty of Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark.
Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, DK-2100, Copenhagen, Denmark.
Angew Chem Int Ed Engl. 2025 Jan 21;64(4):e202416218. doi: 10.1002/anie.202416218. Epub 2024 Oct 31.
Although combinatorial biosynthesis can dramatically expand the chemical structures of bioactive natural products to identify molecules with improved characteristics, progress in this direction has been hampered by the difficulty in isolating and characterizing the numerous produced compounds. This challenge could be overcome with improved designs that enable the analysis of the bioactivity of the produced metabolites ahead of the time-consuming isolation procedures. Herein, we showcase a structure-agnostic bioactivity-driven combinatorial biosynthesis workflow that introduces bioactivity assessment as a selection-driving force to guide iterative combinatorial biosynthesis rounds towards enzyme combinations with increasing bioactivity. We apply this approach to produce triterpenoids with potent bioactivity against PTP1B, a promising molecular target for diabetes and cancer treatment. We demonstrate that the bioactivity-guided workflow can expedite the combinatorial process by enabling the narrowing down of more than 1000 possible combinations to only five highly potent candidates. By focusing the isolation and structural elucidation effort on only these five strains, we reveal 20 structurally diverse triterpenoids, including four new compounds and a novel triterpenoid-anthranilic acid hybrid, as potent PTP1B inhibitors. This workflow expedites hit identification by combinatorial biosynthesis and is applicable to many other types of bioactive natural products, therefore providing a strategy for accelerated drug discovery.
尽管组合生物合成能够显著扩展生物活性天然产物的化学结构,以鉴定具有更优特性的分子,但由于难以分离和表征众多产生的化合物,这一方向的进展受到了阻碍。通过改进设计,在耗时的分离步骤之前就能分析所产生代谢物的生物活性,这一挑战有望得到克服。在此,我们展示了一种与结构无关的生物活性驱动的组合生物合成工作流程,该流程将生物活性评估作为一种选择驱动力,以指导迭代组合生物合成轮次,朝着具有更高生物活性的酶组合方向发展。我们应用这种方法来生产对蛋白酪氨酸磷酸酶1B(PTP1B)具有强效生物活性的三萜类化合物,PTP1B是糖尿病和癌症治疗中一个很有前景的分子靶点。我们证明,这种生物活性导向的工作流程能够将1000多种可能的组合缩小到仅5种高效能候选物,从而加快组合过程。通过仅将分离和结构解析工作集中在这5个菌株上,我们发现了20种结构多样的三萜类化合物,包括4种新化合物和一种新型三萜类化合物 - 邻氨基苯甲酸杂化物,它们都是强效的PTP1B抑制剂。这种工作流程通过组合生物合成加快了活性化合物的鉴定,并且适用于许多其他类型的生物活性天然产物,因此为加速药物发现提供了一种策略。