4.7 Article

Virtual High-Throughput-Screening To Identify Novel Activin Antagonists

Journal

JOURNAL OF MEDICINAL CHEMISTRY
Volume 58, Issue 14, Pages 5637-5648

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jmedchem.5b00753

Keywords

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Funding

  1. Watkins Chair of Obstetrics and Gynecology
  2. Richard Silverman-CMIDD Research Award
  3. Australian National Health and Medical Research Council [GNT1016460]
  4. Robert H. Lurie Comprehensive Cancer Center
  5. Lynn Sage Foundation through Northwestern Memorial Foundation
  6. Chicago Biomedical Consortium
  7. Searle Funds at The Chicago Community Trust
  8. Cancer Center Support Grant from the National Cancer Institute [P30 CA060553]
  9. Northwestern University [HD076188]

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Activin belongs to the TGF beta superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin beta A subunits and was used for a virtual high-throughput in silico Screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSH beta transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex's binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGF beta superfamily member myostatin (GDR). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonist's. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGF beta receptor superfamily members, in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases.

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