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

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.

Exploration of Ultralarge Compound Collections for Drug Discovery

“…98 The reaction-based de novo design system, Design of Genuine Structures (DOGS) 92,93 has been used in conjunction with the chemically advanced template search (CATS) metric 99−101 to study the pharmacophoric similarity of DOGS hits to known drugs. 102 Schrodinger's PathFinder uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Path-Finder-driven compound generation, cloud-based free-energy perturbation simulations, and active learning are used to optimize R-groups rapidly and generate new cores.…”

“…Retrosynthetic analysis of compounds has a long tradition in computational chemistry and gained a lot of attention recently due to the rise of novel machine learning methods . The reaction-based de novo design system, Design of Genuine Structures (DOGS) , has been used in conjunction with the chemically advanced template search (CATS) metric − to study the pharmacophoric similarity of DOGS hits to known drugs …”

Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases

“…(Figure 2). Based on the idea of that marine molecules are a rich source of potential drugs [17,18,21,28] and on the fact of CADD techniques have been used to successfully de-orphanize NPs (from terrestrial and marine origin) [29][30][31][32][33][34], the aim of the present study is (1) to disentangle the possible therapeutic potential of a set of marine molecules, as well as (2) to devise a plausible computational workflow for future studies. To do that, three main milestones were established: (1) to elucidate a list of possible targets, performing two dimensions (2D) and three dimensions (3D) ligand-based virtual profiling (VP) experiments;…”

Reversal of Peripheral Neuropathic Pain by the Small-Molecule Natural Product Narirutin via Block of Nav1.7 Voltage-Gated Sodium Channel

“…The multiple structures of active components isolated from natural products provide new templates for developing novel analgesics [ 4 , 5 ]. Unlike artificial synthetic small-molecule compounds, natural products usually exhibit better biocompatibility and fewer side effects [ 6 ]. However, one difficulty of natural products in clinical translation is identifying their targets and underlying mechanisms to maximize their efficacy while reducing side effects.…”