Structure-Based Discovery of CF53 as a Potent and Orally Bioavailable Bromodomain and Extra-Terminal (BET) Bromodomain Inhibitor
- Univ. of Michigan, Ann Arbor, MI (United States); Chinese Academy of Sciences, Shanghai (China)
- Univ. of Michigan, Ann Arbor, MI (United States)
- Univ. of Michigan, Ann Arbor, MI (United States); Univ. of California, San Francisco, CA (United States)
We report the structure-based discovery of CF53 (28) as a highly potent and orally active inhibitor of bromodomain and extra-terminal (BET) proteins. By the incorporation of a NH-pyrazole group into the 9H-pyrimido[4,5-b]indole core, we identified a series of compounds that bind to BRD4 BD1 protein with Ki values of <1 nM and achieve low nanomolar potencies in the cell growth inhibition of leukemia and breast cancer cells. The most-promising compound, CF53, possesses excellent oral pharmacokinetic properties and achieves significant antitumor activity in both triple-negative breast cancer and acute leukemia xenograft models in mice. Determination of the co-crystal structure of CF53 with the BRD4 BD1 protein provides a structural basis for its high binding affinity to BET proteins. CF53 is very selective over non-BET bromodomain-containing proteins. Furthermore, these data establish CF53 as a potent, selective, and orally active BET inhibitor, which warrants further evaluation for advanced preclinical development.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); National Inst. of Health; Michigan Economic Development Corporation; Michigan Technology Tri-Corridor
- Grant/Contract Number:
- AC02-06CH11357; P50 CA186786; P30CA046592; 085P1000817
- OSTI ID:
- 1471643
- Journal Information:
- Journal of Medicinal Chemistry, Vol. 61, Issue 14; ISSN 0022-2623
- Publisher:
- American Chemical Society (ACS)Copyright Statement
- Country of Publication:
- United States
- Language:
- ENGLISH
Web of Science
BET bromodomain inhibitors: fragment-based in silico design using multi-target QSAR models
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journal | November 2018 |
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