Previous studies indicate that BRCA1 protein binds to estrogen receptor-alpha (ER) and inhibits its activity. Here, we found that BRCA1 over-expression not only inhibits ER activity in anti-estrogen-resistant LCC9 cells but also partially restores their sensitivity to Tamoxifen. To simulate the mechanism of BRCA1 inhibition of ER in the setting of Tamoxifen resistance, we created a three-dimensional model of a BRCA1-binding cavity within the ER/Tamoxifen complex; and we screened a pharmacophore database to identify small molecules that could fit into this cavity. Among the top 40 "hits", six exhibited potent ER inhibitory activity in anti-estrogen-sensitive MCF-7 cells and four of the six exhibited similar activity (IC50 ≤ 1.0 μM) in LCC9 cells. We validated the model by mutation analysis. Two representative compounds (4631-P/1 and 35466-L/1) inhibited ER-dependent cell proliferation in Tamoxifen-resistant cells (LCC9 and LCC2) and partially restored sensitivity to Tamoxifen. The compounds also disrupted the association of BRCA1 with ER. In electrophoretic mobility shift assays, the compounds caused dissociation of ER from a model estrogen response element. Finally, a modified form of compound 35446 (hydrochloride salt) inhibited growth of LCC9 tumor xenografts at non-toxic concentrations. These results identify a novel group of small molecules that can overcome Tamoxifen resistance.

Major roadblocks to developing effective progesterone receptor (PR)-targeted therapies in breast cancer include the lack of highly-specific PR modulators, a poor understanding of the pro- or anti-tumorigenic networks for PR isoforms and ligands, and an incomplete understanding of the cross talk between PR and estrogen receptor (ER) signaling. Through genomic analyses of xenografts treated with various clinically-relevant ER and PR-targeting drugs, we describe how the activation or inhibition of PR differentially reprograms estrogen signaling, resulting in the segregation of transcriptomes into separate PR agonist and antagonist-mediated groups. These findings address an ongoing controversy regarding the clinical utility of PR agonists and antagonists, alone or in combination with tamoxifen, for breast cancer management. Additionally, the two PR isoforms PRA and PRB, bind distinct but overlapping genomic sites and interact with different sets of co-regulators to differentially modulate estrogen signaling to be either pro- or anti-tumorigenic. Of the two isoforms, PRA inhibited gene expression and ER chromatin binding significantly more than PRB. Differential gene expression was observed in PRA and PRB-rich patient tumors and PRA-rich gene signatures had poorer survival outcomes. In support of antiprogestin responsiveness of PRA-rich tumors, gene signatures associated with PR antagonists, but not PR agonists, predicted better survival outcomes. The better patient survival associated with PR antagonists versus PR agonists treatments was further reflected in the higher in vivo anti-tumor activity of therapies that combine tamoxifen with PR antagonists and modulators. This study suggests that distinguishing common effects observed due to concomitant interaction of another receptor with its ligand (agonist or antagonist), from unique isoform and ligand-specific effects will inform the development of biomarkers for patient selection and translation of PR-targeted therapies to the clinic.

Eugenol is an essential oil mainly found in the buds and leaves of clove (Syzygium aromaticum (L.) Merrill and Perry), which has been reported to have activity on inhibition of cell proliferation and apoptosis induction in human MCF-7 breast cancer cells. This biological activity is correlated to its activity as an estrogen receptor antagonist. In this article, we present the construction and validation of structure-based virtual screening (SBVS) protocols to identify the potent estrogen receptor α (ER) antagonists. The selected protocol, which gave acceptable enrichment factors as a virtual screening protocol, subsequently used to virtually screen eugenol, its analogs and their dimers. Based on the virtual screening results, dimer eugenol of 4-[4-hydroxy-3-(prop-2-en-1- yl)phenyl]-2-(prop-2-en-1-yl)phenol is recommended to be developed further in order to discover novel and potent ER antagonists.

Estrogen antagonists are universally employed in the breast cancer therapy, although antagonist therapy is limited by the inevitable development of cellular resistance. The molecular mechanisms by which these agents inhibit cellular proliferation in breast cancer cells are not fully defined. Recent studies have shown the involvement of the E2F pathway in tamoxifen-induced growth arrest. We show that an E2F repressor, prohibitin, and the chromatin modifiers Brg1/Brm are required for estrogen antagonist-mediated growth suppression through the estrogen receptor, and that their recruitment to native promoter-bound E2F is induced via a JNK1 pathway. In addition, we demonstrate major mechanistic differences among the signaling pathways initiated by estrogen, estrogen deprivation, and estrogen antagonists. Collectively, these findings suggest that the prohibitin/Brg1/Brm node is a major cellular target for estrogen antagonists, and thereby also implicate prohibitin/Brg1/Brm as potentially important targets for breast cancer therapy.

Endocrine disrupting chemicals (EDCs) are exogenous compounds that interfere with the endocrine system of vertebrates, often through direct or indirect interactions with nuclear receptor proteins. Estrogen receptors (ERs) are particularly important protein targets and many EDCs are ER binders, capable of altering normal homeostatic transcription and signaling pathways. An estrogenic xenobiotic can bind ER as either an agonist or antagonist to increase or inhibit transcription, respectively. The receptor conformations in the complexes of ER bound with agonists and antagonists are different and dependent on interactions with co-regulator proteins that vary across tissue type. Assessment of chemical endocrine disruption potential depends not only on binding affinity to ERs, but also on changes that may alter the receptor conformation and its ability to subsequently bind DNA response elements and initiate transcription. Using both agonist and antagonist conformations of the ERα, we developed an in silico approach that can be used to differentiate agonist versus antagonist status of potential binders.

Estrogen receptors alpha and beta (ERα and ERβ) are responsible for breast cancer metastasis through their involvement of clinical outcomes. Estradiol and hormone replacement therapy targets both ERs, but this often leads to an increased risk of breast and endometrial cancers as well as thromboembolism. A major challenge is posed for the development of compounds possessing ER subtype specificity. Herein, we present a large-scale classification structure-activity relationship (CSAR) study of inhibitors from the ChEMBL database which consisted of an initial set of 11,618 compounds for ERα and 7,810 compounds for ERβ. The IC50 was selected as the bioactivity unit for further investigation and after the data curation process, this led to a final data set of 1,593 and 1,281 compounds for ERα and ERβ, respectively. We employed the random forest (RF) algorithm for model building and of the 12 fingerprint types, models built using the PubChem fingerprint was the most robust (Ac of 94.65% and 92.25% and Matthews correlation coefficient (MCC) of 89% and 76% for ERα and ERβ, respectively) and therefore selected for feature interpretation. Results indicated the importance of features pertaining to aromatic rings, nitrogen-containing functional groups and aliphatic hydrocarbons. Finally, the model was deployed as the publicly available web server called ERpred at http://codes.bio/erpred where users can submit SMILES notation as the input query for prediction of the bioactivity against ERα and ERβ.

Estrogen receptor (ER) antagonists have been widely used for breast cancer treatment, but the efficacy and drug resistance remain to be clinical concerns. The purpose of this study was to determine whether the extracts of coptis, an anti-inflammatory herb, improve the anticancer efficacy of ER antagonists. The results showed that the combined treatment of ER antagonists and the crude extract of coptis or its purified compound berberine conferred synergistic growth inhibitory effect on MCF-7 cells (ER+), but not on MDA-MB-231 cells (ER-). Similar results were observed in the combined treatment of fulvestrant, a specific aromatase antagonist. Analysis of the expression of breast cancer related genes indicated that EGFR, HER2, bcl-2, and COX-2 were significantly downregulated, while IFN-beta and p21 were remarkably upregulated by berberine. Our results suggest that coptis extracts could be promising adjuvant to ER antagonists in ER positive breast cancer treatment through regulating expression of multiple genes.

The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interactions and specific hydrogen bonds with the ligand. Here we present a framework for quantitative analysis of the steric and electronic features of the human ERα-ligand complex using three dimensional (3D) protein-ligand interaction description combined with 3D-QSAR approach. An empirical hydrophobicity density field is applied to account for hydrophobic contacts of ligand within the LBP. The obtained 3D-QSAR model revealed that hydrophobic contacts primarily determine binding affinity and govern binding mode with hydrogen bonds. Several residues of the LBP appear to be quite flexible and adopt a spectrum of conformations in various ERα-ligand complexes, in particular His524. The 3D-QSAR was combined with molecular docking based on three receptor conformations to accommodate receptor flexibility. The model indicates that the dynamic character of the LBP allows accommodation and stable binding of structurally diverse ligands, and proper representation of the protein flexibility is critical for reasonable description of binding of the ligands. Our results provide a quantitative and mechanistic understanding of binding affinity and mode of ERα agonists and antagonists that may be applicable to other nuclear receptors.

THE AIMS OF THIS STUDY WERE AS FOLLOW: 1) to de scribe the expression status of estrogen receptor-α and -β mRNAs in five gastric carcinoma cell lines; 2) to evaluate in vitro the effects of 17β-estradiol and estrogen receptor antagonists on the proliferation of the cell lines.

Estrogen receptor α (ERα) is a successful target for ER-positive breast cancer and also reported to be relevant in many other diseases. Selective estrogen receptor modulators (SERMs) make a good therapeutic effect in clinic. Because of the drug resistance and side effects of current SERMs, the discovery of new SERMs is given more and more attention. Virtual screening is a validated method to high effectively to identify novel bioactive small molecules. Ligand-based machine learning methods and structure-based molecular docking were first performed for identification of ERα antagonist from in-house natural product library. Naive Bayesian and recursive partitioning models with two kinds of descriptors were built and validated based on training set, test set, and external test set and then were utilized for distinction of active and inactive compounds. Totally, 162 compounds were predicted as ER antagonists and were further evaluated by molecular docking. According to docking score, we selected 8 representative compounds for both ERα competitor assay and luciferase reporter gene assay. Genistein, daidzein, phloretin, ellagic acid, ursolic acid, (-)-epigallocatechin-3-gallate, kaempferol, and naringenin exhibited different levels for antagonistic activity against ERα. These studies validated the feasibility of machine learning methods for predicting bioactivities of ligands and provided better insight into the natural products acting as estrogen receptor modulator, which are important lead compounds for future new drug design.

New estrogen receptor α (ERα) antagonists - 3,20-dihydroxy-19-norpregna-1,3,5(10)-trienes containing an additional carbocyclic ring D' at the 16α,17α positions - were synthesized. The effects of the new compounds on the MCF-7 breast cancer cells and ERα activation were investigated. All the steroids studied were synthesized starting from estrone methyl ether. The scaffold of compounds containing the six-membered ring D' was constructed via the Diels-Alder reaction of butadiene with 3-methoxy-19-norpregna-1,3,5(10),16-tetraen-20-one 5. The hydrogenation of primary 16α,17α-cyclohexeno-adduct 7 followed by 3-demethylation (by HBr-AcOH) and reduction of 20-oxo group (by LiAlH4) or in one step by DIBAH gave target mono- and dihydroxy steroids 9-11. The Corey-Chaykovsky reaction of the same 3-methoxy-19-norpregna-1,3,5(10),16-tetraen-20-one 5 gave 16α,17α-methylene-substituted compound. The reaction of the latter with DIBAH immediately yielded 3,20-dihydroxy-16α,17α-methyleno-19-norpregna-1,3,5(10)-triene 13. The same procedures using 3-methoxy-19-norpregna-1,3,5(10),16-tetraen-20-one 5 produced corresponding 3,20-dihydroxy-16,17-19-norpregna-1,3,5(10)-triene 16 and 3,20-dihydroxy-19-norpregna-1,3,5(10),16-tetraene 17. All compounds were fully characterized by 1D and 2D NMR, HRMS, and X-ray diffraction. The molecular docking showed that the target compounds can bind to ER, their binding mode being similar to that of natural estradiol. 16α,17α-Methylene- or unsubstituted compounds exhibit the highest cytotoxicity against MCF-7 cells, being simultaneously relatively weak ERα inhibitors. 3,20-Dihydroxy steroids containing the six-membered ring D' proved to be the most effective ERα inhibitors. These compounds displayed moderate cytotoxicity comparable of that of tamoxifen and showed no toxic effect on MCF-10A normal, nontumorigenic epithelial cells. The new ER antagonists were found to be good candidates for further testing as agents for the treatment and prevention of ERα-positive breast cancers.

Cryptococcosis is an infectious disease of global significance for which new therapies are needed. Repurposing previously developed drugs for new indications can expedite the translation of new therapies from bench to beside. Here, we characterized the anti-cryptococcal activity and antifungal mechanism of estrogen receptor antagonists related to the breast cancer drugs tamoxifen and toremifene. Tamoxifen and toremifene are fungicidal and synergize with fluconazole and amphotericin B in vitro. In a mouse model of disseminated cryptococcosis, tamoxifen at concentrations achievable in humans combines with fluconazole to decrease brain burden by ~1 log10. In addition, these drugs inhibit the growth of Cryptococcus neoformans within macrophages, a niche not accessible by current antifungal drugs. Toremifene and tamoxifen directly bind to the essential EF hand protein calmodulin, as determined by thermal shift assays with purified C. neoformans calmodulin (Cam1), prevent Cam1 from binding to its well-characterized substrate calcineurin (Cna1), and block Cna1 activation. In whole cells, toremifene and tamoxifen block the calcineurin-dependent nuclear localization of the transcription factor Crz1. A large-scale chemical genetic screen with a library of C. neoformans deletion mutants identified a second EF hand-containing protein, which we have named calmodulin-like protein 1 (CNAG_05655), as a potential target, and further analysis showed that toremifene directly binds Cml1 and modulates its ability to bind and activate Cna1. Importantly, tamoxifen analogs (idoxifene and methylene-idoxifene) with increased calmodulin antagonism display improved anti-cryptococcal activity, indicating that calmodulin inhibition can be used to guide a systematic optimization of the anti-cryptococcal activity of the triphenylethylene scaffold.

Somatic mutations of the Estrogen Receptor α (ERα) occur with an up to 40% incidence in ER sensitive breast cancer (BC) patients undergoing prolonged endocrine treatments. These polymorphisms are implicated in acquired resistance, disease relapse, and increased mortality rates, hence representing a current major clinical challenge. Here, multi-microseconds (12.5 µs) molecular dynamics simulations revealed that recurrent ERα polymorphisms (i. e. L536Q, Y537S, Y537N, D538G) (mERα) are constitutively active in their apo form and that they prompt the selection of an agonist (active)-like conformation even upon antagonists binding. Interestingly, our simulations rationalize, for the first time, the efficacy profile of (pre)clinically used Selective Estrogen Receptor Modulators/Downregulators (SERMs/SERDs) against these variants, enlightening, at atomistic level of detail, the key common structural traits needed by drugs able to effectively fight refractory BC types. This knowledge represents a key advancement for mechanism-based therapeutics targeting resistant ERα isoforms, potentially allowing the community to move a step closer to 'precision medicine' calibrated on patients' genetic profiles and disease progression.

The estrogen receptor is capable of binding a diverse set of ligands that are broadly categorized as agonists or antagonists, depending on their abilities to induce or interfere with transcriptional responsiveness. We show, using a fusion protein assay for ligand-binding which does not rely on transcriptional responsiveness, that agonists and antagonists differently position the C-terminus of the ligand-binding domain (helix 12) and the F domain. Upon antagonist binding, the F domain interferes with the fusion protein activity. Mutational disruption of helix 12 alters the position of the F domain, imposing interference after agonist or antagonist binding. Genetically selected inversion mutations where only agonists, but not antagonists, induce interference are similarly reliant on helix 12 and F domain positioning. Our results demonstrate that agonists and antagonists differently position helix 12 and implicate the F domain in mechanisms of antagonist action.

Vascular endothelial growth factor (VEGF) is essential for embryonic lung development and has been shown to be regulated by estradiol (E2) and progesterone (P).

The estrogen receptor α (ERα) is an important biological target mediating 17β-estradiol driven breast cancer (BC) development. Aiming to develop innovative drugs against BC, either wild-type or mutated ligand-ERα complexes were used as source data to build structure-based 3-D pharmacophore and 3-D QSAR models, afterward used as tools for the virtual screening of National Cancer Institute datasets and hit-to-lead optimization. The procedure identified Brefeldin A (BFA) as hit, then structurally optimized toward twelve new derivatives whose anticancer activity was confirmed both in vitro and in vivo. Compounds as SERMs showed picomolar to low nanomolar potencies against ERα and were then investigated as antiproliferative agents against BC cell lines, as stimulators of p53 expression, as well as BC cell cycle arrest agents. Most active leads were finally profiled upon administration to female Wistar rats with pre-induced BC, after which 3DPQ-12, 3DPQ-3, 3DPQ-9, 3DPQ-4, 3DPQ-2, and 3DPQ-1 represent potential candidates for BC therapy.

Most breast cancer deaths are caused by malignant estrogen receptor-positive breast tumors that later recur as metastatic disease. Prolactin (PRL) has been documented as a factor promoting breast cancer development and metastasis. We therefore developed superactive prolactin receptor (PRLR) antagonists aimed at blocking PRL action. We purified 12 novel mutants to homogeneity as monomers, and the most potent antagonist was over 95-fold more active than the previously reported weak antagonist, the mutant Del 1-9 human PRL G129R. This enhanced antagonistic activity resulted mostly from prolonged interaction with the extracellular domain (ECD) of PRLR. All mutants were properly refolded, as indicated by interaction with human PRLR-ECD and by circular dichroism analysis. We then prepared monopegylated variants of the most active mutants to extend their biological half-life in vivo.

Bisphenol A (BPA), a ubiquitous environmental contaminant, has been shown to cause developmental toxicity and carcinogenic effects. BPA may have physiological activity through estrogen receptor (ER) -alpha and -beta, which are expressed in the central nervous system. We previously found that exposure of BPA to immature mice resulted in behavioral alternation, suggesting that overexposure of BPA could be neurotoxic. In this study, we further investigated the molecular neurotoxic mechanisms of BPA. BPA increased vulnerability (decrease of cell viability and differentiation, and increase of apoptotic cell death) of undifferentiated PC12 cells and cortical neuronal cells isolated from gestation 18 day rat embryos in a concentration-dependent manner (more than 50 microM). The ER antagonists, ICI 182,780, and tamoxifen, did not block these effects. The cell vulnerability against BPA was not significantly different in the PC12 cells overexpressing ER-alpha and ER-beta compared with PC12 cells expressing vector alone. In addition, there was no difference observed between BPA and 17-beta estradiol, a well-known agonist of ER receptor in the induction of neurotoxic responses. Further study of the mechanism showed that BPA significantly activated extracellular signal-regulated kinase (ERK) but inhibited anti-apoptotic nuclear factor kappa B (NF-kappaB) activation. In addition, ERK-specific inhibitor, PD 98,059, reversed BPA-induced cell death and restored NF-kappaB activity. This study demonstrated that exposure to BPA can cause neuronal cell death which may eventually be related with behavioral alternation in vivo. However, this neurotoxic effect may not be directly mediated through an ER receptor, as an ERK/NF-kappaB pathway may be more closely involved in BPA-induced neuronal toxicity.

Progesterone receptor (PR) regulates various physiological processes, including the female reproductive system, and development of nonsteroidal PR antagonists is considered desirable for clinical application, as they are expected to have reduced side effects. We have synthesized a series of nonsteroidal PR antagonists using a 4-cyanophenyl-p-carborane core structure. Among them, compound 14d exhibited potent PR-antagonistic activity (IC50: 27 nM). It showed high binding affinity for PR, but did not bind to androgen receptor or estrogen receptor. This PR-selective antagonist may be a promising lead compound for clinically applicable progesterone receptor modulators.

Selective estrogen receptor modulators (SERMs), such as tamoxifen and raloxifene can act as estrogen receptor (ER) antagonists or agonists depending on the cell type. The antagonistic action of tamoxifen has been invaluable for treating breast cancer, whereas the agonist activity of SERMs also has important clinical applications as demonstrated by the use of raloxifene for osteoporosis. Whereas the mechanism whereby SERMs function as antagonists has been studied extensively very little is known about how SERMs produce agonist effects in different tissues with the two ER types; ERalpha and ERbeta. We examined the regulation of 32 SERM-responsive regions with ERalpha and ERbeta in transiently transfected MCF-7 breast, Ishikawa endometrial, HeLa cervical and WAR-5 prostate cancer cells. The regions were regulated by tamoxifen and raloxifene in some cell types, but not in all cell lines. Tamoxifen activated similar number of regions with ERalpha and ERbeta in the cell lines, whereas raloxifene activated over twice as many regions with ERbeta compared to ERalpha. In Ishikawa endometrial cancer cells, tamoxifen activated 17 regions with ERalpha, whereas raloxifene activated only 2 regions, which might explain their different effects on the endometrium. Microarray studies also found that raloxifene regulated fewer genes than tamoxifen in U2OS bone cancer cells expressing ERalpha, whereas tamoxifen was equally effective at regulating genes with ERalpha and ERbeta. Our studies indicate that tamoxifen is a non-selective agonist, whereas raloxifene is a relative ERbeta-selective agonist, and suggest that ERbeta-selective SERMs might be safer for treating clinical conditions that are dependent on the agonist property of SERMs.