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ATAD2 is an epigenetic bromodomain-containing target which is overexpressed in many cancers and has been suggested as a potential oncology target. While several small molecule inhibitors have been described in the literature, their cellular activity has proved to be underwhelming. In this work, we describe the identification of a novel series of ATAD2 inhibitors by high throughput screening, confirmation of the bromodomain region as the site of action, and the optimization campaign undertaken to improve the potency, selectivity, and permeability of the initial hit. The result is compound 5 (AZ13824374), a highly potent and selective ATAD2 inhibitor which shows cellular target engagement and antiproliferative activity in a range of breast cancer models.

Here we report the discovery and optimization of a series of bivalent bromodomain and extraterminal inhibitors. Starting with the observation of BRD4 activity of compounds from a previous program, the compounds were optimized for BRD4 potency and physical properties. The optimized compound from this campaign exhibited excellent pharmacokinetic profile and exhibited high potency in vitro and in vivo effecting c-Myc downregulation and tumor growth inhibition in xenograft studies. This compound was selected as the development candidate, AZD5153. The series showed enhanced potency as a result of bivalent binding and a clear correlation between BRD4 activity and cellular potency.

A series of tetrahydroisoquinoline phenols was modified to give an estrogen receptor downregulator-antagonist profile. Optimization around the core, alkyl side chain, and pendant aryl ring resulted in compounds with subnanomolar levels of potency. The phenol functionality was shown to be required to achieve highly potent compounds, but unusually this was compatible with obtaining high oral bioavailabilities in rat.

The discovery of an orally bioavailable selective estrogen receptor downregulator (SERD) with equivalent potency and preclinical pharmacology to the intramuscular SERD fulvestrant is described. A directed screen identified the 1-aryl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indole motif as a novel, druglike ER ligand. Aided by crystal structures of novel ligands bound to an ER construct, medicinal chemistry iterations led to (E)-3-(3,5-difluoro-4-((1R,3R)-2-(2-fluoro-2-methylpropyl)-3-methyl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl)acrylic acid (30b, AZD9496), a clinical candidate with high oral bioavailability across preclinical species that is currently being evaluated in phase I clinical trials for the treatment of advanced estrogen receptor (ER) positive breast cancer.

In an effort to enhance access to information available in the National Cancer Institute's (NCI) anticancer drug-screening database, a new suite of Internet accessible (http://spheroid. ncifcrf.gov) computational tools has been assembled for self-organizing map-based (SOM) cluster analysis and data visualization. A range of analysis questions were initially addressed to evaluate improvements in SOM cluster quality based on the data-conditioning procedures of Z-score normalization, capping, and treatment of missing data as well as completeness of drug cell-screening data. These studies established a foundation for SOM cluster analysis of the complete set of NCI's publicly available antitumor drug-screening data. This analysis identified relationships between chemotypes of screened agents and their effect on four major classes of cellular activities: mitosis, nucleic acid synthesis, membrane transport and integrity, and phosphatase- and kinase-mediated cell cycle regulation. Validations of these cellular activities, obtained from literature sources, found (i) strong evidence supporting within cluster memberships and shared cellular activity, (ii) indications of compound selectivity between various types of cellular activity, and (iii) strengths and weaknesses of the NCI's antitumor drug screen data for assigning compounds to these classes of cellular activity. Subsequent analyses of averaged responses within these tumor panel types find a strong dependence on chemotype for coherence among cellular response patterns. The advantages of a global analysis of the complete screening data set are discussed.