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

Advanced Science

Ying‐Hui Ko¹  Gino Cingolani¹  Veronika Bobinger²  Gisbert Schneider²  Daniel Merk²  Lukas Friedrich²  Oliver Werz³  Robert Klaus Hofstetter³  Maria Grazia Perrone⁴  Morena Miciaccia⁴  Antonio Scilimati⁴  Mariaclara Iaselli⁴  Konstantin Neukirch⁵  Andreas Koeberle⁵ 

[1] Department of Biochemistry and Molecular Biology Sidney Kimmel Cancer Center Thomas Jefferson University 1020 Locust Street Philadelphia PA 19107 USA;Department of Chemistry and Applied Biosciences ETH Zurich Vladimir‐Prelog‐Weg 4 Zurich 8093 Switzerland;Department of Pharmaceutical/Medicinal Chemistry Friedrich‐Schiller‐University Jena Philosophenweg 14 Jena 07743 Germany;Department of Pharmacy – Pharmaceutical Sciences University of Bari Via E. Orabona 4 Bari 70125 Italy;Michael Popp Institute and Center for Molecular Biosciences Innsbruck (CMBI) University of Innsbruck Innsbruck 6020 Austria;

关键词: chemoinformatics;    computational chemistry;    drug design;    machine learning;    natural product;   

DOI  :  10.1002/advs.202100832

来源: DOAJ

【 摘 要 】

Abstract 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.

【 授权许可】

Unknown