Learning from Nature: From a Marine Natural Product to Synthetic Cyclooxygenase‐1 Inhibitors by Automated De Novo Design

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. Machine learning models identify cyclooxygenase (COX) activity of the anticancer marine natural product Marinopyrrole A, and automatically construct potent new COX‐1 inhibitors, taking only the natural product as a design template. Crystallographic analysis reveals a unique binding mode of the computer‐generated COX‐1 inhibitor. This approach can provide a template for future drug design in low‐data scenarios.