Identification of Novel Androgen Receptor Antagonists Using Structure- and Ligand-Based Methods

Li, Huifang; Ren, Xin; Leblanc, Éric; Frewin, Kate; Rennie, Paul S.; Cherkasov, Artem

doi:10.1021/ci300514v

Cited by 34 publications

(23 citation statements)

References 44 publications

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“…The AR antagonist DIMN (12) was screened out by structure-based VS based on the docking algorithm FlexX, 57 and it inhibited the AR transactivation activity with an IC 50 value of 3 µM that is comparable to that of bicalutamide (IC 50 = 1.6 µM). Another AR antagonist VPC-12060 (13) was discovered by structure-and ligand-based VS based on two docking programs (Glide SP and eHiTs) and a QSAR (quantitative SAR) model, 58 and it exhibited submicromolar activity (eGFP IC 50 = 0.378 μM) through an AR transcriptional activity assay with the engineered LNCaP PCa cells containing the androgen responsive eGFP reporter, which is comparative to that of bicalutamide (0.382 μM). Very recently, we have also identified a series of novel AR ligands through an integrated strategy by combining docking-based VS and bioassays, and two of them 49,50,71 Abbreviations: AF2, activation function-2; AR, androgen receptor; BF3, binding function-3; DBD, DNA-binding domain; DHT, 5α-dihydrotestosterone; GFP, green fluorescence protein;…”

Section: Ar Antagonists Targeting Lbp Of Lbdmentioning

confidence: 99%

A magic drug target: Androgen receptor

Zhou

Pang

et al. 2018

Medicinal Research Reviews

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Androgen receptor (AR) is closely associated with a group of hormone‐related diseases including the cancers of prostate, breast, ovary, pancreas, etc and anabolic deficiencies such as muscle atrophy and osteoporosis. Depending on the specific type and stage of the diseases, AR ligands including not only antagonists but also agonists and modulators are considered as potential therapeutics, which makes AR an extremely interesting drug target. Here, we at first review the current understandings on the structural characteristics of AR, and then address why and how AR is investigated as a drug target for the relevant diseases and summarize the representative antagonists and agonists targeting five prospective small molecule binding sites at AR, including ligand‐binding pocket, activation function‐2 site, binding function‐3 site, DNA‐binding domain, and N‐terminal domain, providing recent insights from a target and drug development view. Further comprehensive studies on AR and AR ligands would bring fruitful information and push the therapy of AR relevant diseases forward.

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Section: Ar Antagonists Targeting Lbp Of Lbdmentioning

confidence: 99%

A magic drug target: Androgen receptor

Zhou

Pang

et al. 2018

Medicinal Research Reviews

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“…Many of these models can be applied only to a limited number of compounds. Models with relatively wide applicability have been developed for predicting binding affinity to the estrogen Serafimova et al, 2007;Li and Gramatica, 2010b;Toropov et al, 2012;Yi and Zhang, 2012;Zhang et al, 2013) and androgen receptors Li et al, 2009Li et al, , 2013aLi and Gramatica, 2010a;Jensen et al, 2011;Todorov et al, 2011). To our knowledge, studies on the use of QSAR models for prioritizing potential endocrine disruptors considering multiple endpoints were limited to two mechanisms of action (Li and Gramatica, 2010b) or to one group of compounds sharing similar structural features (Juberg et al, 2013), for example brominated flame retardants (Kovarich et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Identifying potential endocrine disruptors among industrial chemicals and their metabolites – development and evaluation of in silico tools

et al. 2015

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The aim of this study was to improve the identification of endocrine disrupting chemicals (EDCs) by developing and evaluating in silico tools that predict interactions at the estrogen (E) and androgen (A) receptors, and binding to transthyretin (T). In particular, the study focuses on evaluating the use of the EAT models in combination with a metabolism simulator to study the significance of bioactivation for endocrine disruption. Balanced accuracies of the EAT models ranged from 77-87%, 62-77%, and 65-89% for E-, A-, and T-binding respectively. The developed models were applied on a set of more than 6000 commonly used industrial chemicals of which 9% were predicted E- and/or A-binders and 1% were predicted T-binders. The numbers of E- and T-binders increased 2- and 3-fold, respectively, after metabolic transformation, while the number of A-binders marginally changed. In-depth validation confirmed that several of the predicted bioactivated E- or T-binders demonstrated in vivo estrogenic activity or influenced blood levels of thyroxine in vivo. The metabolite simulator was evaluated using in vivo data from the literature which showed a 50% accuracy for studied chemicals. The study stresses, in summary, the importance of including metabolic activation in prioritization activities of potentially emerging contaminants.

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“…The AR agonists and antagonists modulated AR function by binding to the AR-LBD (31). Given that AR-LBD was required for binding to FLII, we hypothesized that ligands regulate binding of FLII to AR.…”

Section: Dht Treatment Abolishes Ar and Flii Bindingmentioning

confidence: 99%

Flightless I Homolog Represses Prostate Cancer Progression through Targeting Androgen Receptor Signaling

Wang

Song

Chen

et al. 2016

Clinical Cancer Research

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Purpose: Flightless I (FLII), member of the gelsolin superfamily of actin-remodeling proteins, functions as a transcriptional coregulator. We aim to evaluate a tumor-suppressive function of FLII in regulating androgen receptor (AR) in prostate cancer progression.Experimental Design: We examined FLII protein and mRNA expression in clinical prostate cancer specimens by immunohistochemistry. Kaplan-Meier analysis was conducted to evaluate the difference in disease-overall survival associated with the expression levels of FLII and AR. Prostate cancer cells stably expressing FLII or shRNA knockdown were used for functional analyses. Immunoprecipitation, Luciferase reporter, and immunofluorescence staining assays were performed to examine the functional interaction between FLII and AR.Results: Our analysis of the expression levels of FLII in a clinical gene expression array dataset showed that the expression of FLII was positively correlated with the overall survival of prostate cancer patients exhibiting high levels of AR expression. Examination of protein and mRNA levels of FLII showed a significant decrease of FLII expression in human prostate cancers. AR and FLII formed a complex in a ligand-dependent manner through the ligand-binding domain (LBD) of AR. Subsequently, we observed a competitive binding to AR between FLII and the ligand. FLII inhibited AR transactivation and decreased AR nuclear localization. Furthermore, FLII contributed to castration-sensitive and castration-resistant prostate cancer cell growth through AR-dependent signaling, and reintroduction of FLII in prostate cancer cells sensitized the cells to bicalutamide and enzalutamide treatment.Conclusions: FLII plays a tumor-suppressive role and serves as a crucial determinant of resistance of prostate cancer to endocrine therapies.

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Identification of Novel Androgen Receptor Antagonists Using Structure- and Ligand-Based Methods

Cited by 34 publications

References 44 publications

A magic drug target: Androgen receptor

A magic drug target: Androgen receptor

Identifying potential endocrine disruptors among industrial chemicals and their metabolites – development and evaluation of in silico tools

Flightless I Homolog Represses Prostate Cancer Progression through Targeting Androgen Receptor Signaling

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