Mining Natural Products for Macrocycles to Drug Difficult Targets

J Med Chem. 2021 Jan 28;64(2):1054-1072. doi: 10.1021/acs.jmedchem.0c01569. Epub 2020 Dec 18.

Abstract

Lead generation for difficult-to-drug targets that have large, featureless, and highly lipophilic or highly polar and/or flexible binding sites is highly challenging. Here, we describe how cores of macrocyclic natural products can serve as a high-quality in silico screening library that provides leads for difficult-to-drug targets. Two iterative rounds of docking of a carefully selected set of natural-product-derived cores led to the discovery of an uncharged macrocyclic inhibitor of the Keap1-Nrf2 protein-protein interaction, a particularly challenging target due to its highly polar binding site. The inhibitor displays cellular efficacy and is well-positioned for further optimization based on the structure of its complex with Keap1 and synthetic access. We believe that our work will spur interest in using macrocyclic cores for in silico-based lead generation and also inspire the design of future macrocycle screening collections.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Products / chemistry*
  • Computer Simulation
  • Data Mining
  • Databases, Factual
  • Drug Discovery
  • Drug Evaluation, Preclinical
  • Humans
  • Kelch-Like ECH-Associated Protein 1 / antagonists & inhibitors
  • Kelch-Like ECH-Associated Protein 1 / chemistry
  • Microsomes, Liver
  • Models, Molecular
  • Molecular Docking Simulation
  • NF-E2-Related Factor 2
  • Polycyclic Compounds / chemical synthesis*
  • Polycyclic Compounds / chemistry
  • Polycyclic Compounds / pharmacology*
  • Solubility
  • Structure-Activity Relationship

Substances

  • Biological Products
  • KEAP1 protein, human
  • Kelch-Like ECH-Associated Protein 1
  • NF-E2-Related Factor 2
  • Polycyclic Compounds