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UBC Theses and Dissertations

Quantitative structure-activity relationship based virtual screening for novel androgen receptor antagonists Ren, Xin


Androgen receptor (AR) plays a critical role in prostate cancer development and progression. All current therapeutic AR inhibitors modulate the receptor via direct binding to its Hormone Binding Site (HBS). Despite the identification of other small molecule binding areas on the AR surface including Activation Function 2 (AF2), binding function 3 (BF3), and N-terminal domain (NTD), HBS continues to be the major target site for AR antagonists (even though this site is prone to resistant mutations). Thus, there is a high need for the identification and development of novel antagonists targeting HBS of the AR. In this study, an effective QSAR modeling pipeline was set up and proved to be capable of identifying new AR antagonists from a large ZINC collection of purchasable chemicals. In particular, we have utilized DRAGON, INDUCTIVE and MOE descriptors to create various binary QSAR models of anti-AR activity. When we have applied the developed QSAR solutions to screen more than 2 million chemicals from the ZINC database, we were able to identify 39 potential candidate AR HBS binders. When they were tested in the DHT displacement assay, 9 chemicals demonstrated the corresponding IC₅₀ values in efficient low-micromole range. Of those, 9 compounds later exhibited ability to inhibit AR in the eGFP transcriptional assay with the IC₅₀ values established at 1.04-16.18 μM level. Notably, 6 discovered chemicals demonstrated concentration-dependent suppression of survival of LNCaP prostate cancer cell lines. The results of this study set a ground for the development of an entire novel chemical class of AR antagonists that are distinct for the currently marketed drugs such as Nitalutamide, Flutomide, Cassodex, and MDV3100 that all share significant structural similarity.

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