Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 4, Zurich, 8093, Switzerland.
Department of Biochemistry and Molecular Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, 1020 Locust Street, Philadelphia, PA, 19107, USA.
Adv Sci (Weinh). 2021 Aug;8(16):e2100832. doi: 10.1002/advs.202100832. Epub 2021 Jun 27.
The repertoire of natural products offers tremendous opportunities for chemical biology and drug discovery. Natural product-inspired synthetic molecules represent an ecologically and economically sustainable alternative to the direct utilization of natural products. De novo design with machine intelligence bridges the gap between the worlds of bioactive natural products and synthetic molecules. On employing the compound Marinopyrrole A from marine Streptomyces as a design template, the algorithm constructs innovative small molecules that can be synthesized in three steps, following the computationally suggested synthesis route. Computational activity prediction reveals cyclooxygenase (COX) as a putative target of both Marinopyrrole A and the de novo designs. The molecular designs are experimentally confirmed as selective COX-1 inhibitors with nanomolar potency. X-ray structure analysis reveals the binding of the most selective compound to COX-1. This molecular design approach provides a blueprint for natural product-inspired hit and lead identification for drug discovery with machine intelligence.
天然产物的组成提供了巨大的化学生物学和药物发现机会。受天然产物启发的合成分子是直接利用天然产物的生态和经济可持续替代方案。利用机器智能进行从头设计,弥合了生物活性天然产物和合成分子之间的鸿沟。在以海洋链霉菌中的 Marinopyrrole A 作为设计模板的情况下,该算法构建了可以通过三步合成的创新小分子,遵循计算建议的合成路线。计算活性预测表明环氧化酶 (COX) 既是 Marinopyrrole A 又是从头设计的潜在靶标。分子设计被实验证实为具有纳摩尔效力的选择性 COX-1 抑制剂。X 射线结构分析揭示了最具选择性的化合物与 COX-1 的结合。这种分子设计方法为利用机器智能进行天然产物启发的命中和先导化合物识别提供了蓝图,以用于药物发现。