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. 2021 Mar 23;118(12):e2100918118.
doi: 10.1073/pnas.2100918118.

Paradoxical androgen receptor regulation by small molecule enantiomers

Affiliations

Paradoxical androgen receptor regulation by small molecule enantiomers

Katherin Patsch et al. Proc Natl Acad Sci U S A. .

Abstract

Small molecules that target the androgen receptor (AR) are the mainstay of therapy for lethal castration-resistant prostate cancer (CRPC), yet existing drugs lose their efficacy during continued treatment. This evolution of resistance is due to heterogenous mechanisms which include AR mutations causing the identical drug to activate instead of inhibit the receptor. Understanding in molecular detail the paradoxical phenomenon wherein an AR antagonist is transformed into an agonist by structural mutations in the target receptor is thus of paramount importance. Herein, we describe a reciprocal paradox: opposing antagonist and agonist AR regulation determined uniquely by enantiomeric forms of the same drug structure. The antiandrogen BMS-641988, which has (R)-chirality at C-5 encompasses a previously uncharacterized (S)-stereoisomer that is, surprisingly, a potent agonist of AR, as demonstrated by transcriptional assays supported by cell imaging studies. This duality was reproduced in a series of novel compounds derived from the BMS-641988 scaffold. Coupled with in silico modeling studies, the results inform an AR model that explains the switch from potent antagonist to high-affinity agonist in terms of C-5 substituent steric interactions with helix 12 of the ligand binding site. They imply strategies to overcome AR drug resistance and demonstrate that insufficient enantiopurity in this class of AR antagonist can confound efforts to correlate structure with function.

Keywords: androgen receptor; cancer; chirality; drug testing.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Agonist/antagonist duality of enantiomers. (A) Confocal microscopy of PC3 GFP-AR cells treated with 10 µM purified enantiomers (180 min) and 1 nM R1881 (90 min). Representative cells are depicted. (B) Chemical structures of EITM-17## enantiomers. (C) Nuclear speckling quantification of EITM drug pairs. Data (n = 3 encompassing 11,188 cells) are mean ± SD (wide) and SE (narrow), linear model (two-sided) significance tests for difference from controls. (D) ARE-luciferase assays in cells treated with 10 µM drug + 1 nM R1881. Data (n ≥ 4) are mean ± SD, linear model (two-sided), (EITM-drugs + R1881) vs. R1881, and (− R1881) vs. NTC. (E) Expression of 82 AR-regulated genes in VCaP cells treated with EITM-1707 enantiomers via qPCR Array. Gene expressions were projected along the expression change vector between NTC (0%) and DHT (100%). Data (n = 3) are mean ± SD, ANOVA with post hoc correction, vs. NTC (Left) and DHT (Right). (F) Proposed model of AR antagonist/agonist duality. Overlay of (S)-EITM-1703 (blue) docked onto AR-LBD in closed conformation (turquoise), and (R)-EITM-1703 (gold) in open AR homology model (gray). (G) ARE-luciferase assays in cells expressing GFP-AR with point mutations to predicted binding sites and treated with 10 µM drug + 1 nM R1881. Data (n ≥ 3) are mean ± SD (wide) and SE (narrow), linear model significance tests for difference (relative to NTC − R1881) from WT AR and the corresponding mutation (corrected for multiple comparisons). NTC = no treatment control, ENZ = enzalutamide, DHT = dihydrotestosterone, (R)-BMS = BMS-641988 and its (S)-isomer (S)-BMS. *P < 0.05, **P < 0.01, ***P < 0.001, n.s., not significant. P values corrected for multiple comparisons at a familywise error rate of 0.05.
Fig. 2.
Fig. 2.
Role of enantiomer duality in in vitro drug testing. (A and B) Assays in cells treated with 10 µM drug with increasing fractions of (S)-enantiomer + 1 nM R1881. (A) ARE-luciferase was measured after 24 h and (B) VCaP cell viability after 6 d of treatment using CellTiter-Glo. Data (n = 3) are mean ± SD, one-sided Wilcoxon test for decrease from R1881 across both drugs. Dashed lines represent relative EC50 for EITM-1702. Zero% data points were not used to fit the curves. (C and D) Pairwise EC50 values computed from (C) competition binding curves obtained via fluorescence polarization and (D) ARE-luciferase dose–response curves run in antagonist mode (1 nM R1881) with (R)-drugs and in agonist mode (−R1881) with their respective (S)-isomers. Data (n ≥ 3) are mean ± SD, two-sided Welch t test, **P < 0.01, ***P < 0.001, n.s., not significant. NTC = no treatment control, ENZ = enzalutamide.

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