A screening cascade to identify ERβ ligands

Abstract

The establishment of effective high throughput screening cascades to identify nuclear receptor (NR) ligands that will trigger defined, therapeutically useful sets of NR activities is of considerable importance. Repositioning of existing approved drugs with known side effect profiles can provide advantages because de novo drug design suffers from high developmental failure rates and undesirable side effects which have dramatically increased costs. Ligands that target estrogen receptor β (ERβ) could be useful in a variety of diseases ranging from cancer to neurological to cardiovascular disorders. In this context, it is important to minimize cross-reactivity with ERα, which has been shown to trigger increased rates of several types of cancer. Because of high sequence similarities between the ligand binding domains of ERα and ERβ, preferentially targeting one subtype can prove challenging. Here, we describe a sequential ligand screening approach comprised of complementary in-house assays to identify small molecules that are selective for ERβ. Methods include differential scanning fluorimetry, fluorescence polarization and a GAL4 transactivation assay. We used this strategy to screen several commercially-available chemical libraries, identifying thirty ERβ binders that were examined for their selectivity for ERβ versus ERα, and tested the effects of selected ligands in a prostate cancer cell proliferation assay. We suggest that this approach could be used to rapidly identify candidates for drug repurposing.

Keywords: Screening; chemical libraries; drugs; gene expression; gene regulation; nuclear receptors.

Figure 1. ÄKTA chromatogram and SDS-PAGE for the purification of ERβ LBD.

Representative size-exclusion chromatogram from the ÄKTA purifier FPLC for the purification of ERβ LBD (A) and Coomassie stained SDS-PAGE gel after SEC of the pooled and concentrated eluted fractions at ~61 mL corresponding to ERβ LBD (B).

Figure 2. DSF assay to determine the binding of ligands from compound libraries to ERβ LBD.

Representative DSF output from the RT-PCR machine as graphs displaying the first derivative of fluorescence versus temperature for (A) unliganded ERβ LBD and unliganded ERβ LBD with DMSO and (B-D) ERβ LBD with the addition of ligand (final concentration 500 μM). Ethinyl estradiol (EE) is represented by the purple trace in B.

Figure 3. FP assay to verify ligand hits from compound libraries and determine selectivity for ERβ and ERα.

Fluorescence Polarization versus concentration with (A-C) ERβ and (D-F) ERα for ligands identified as ERβ binders from the primary DSF assay. Curves shifted the furthest to the left represent those compounds with the greatest affinity for the protein. Error bars represent one standard deviation from the mean of triplicate reaction wells.

Figure 4. Cell-based transactivation assay to evaluate the ability of ligands to modulate the transcriptional activity of ERβ.

Relative transactivation activity for the ligands identified as ERβ binders from the primary and secondary assays using HEK293T cells transiently transfected with GALDBD-ERβLBD. Data are means ± SE of triplicate wells and normalized to Dimethyl Sulfoxide (DMSO). Charcoal stripped serum was used.

Figure 5. Cell-based transactivation assay to evaluate the ability of ligands to modulate the transcriptional activity of ERβ.

(A) Relative transactivation activity for selected ligands (final concentration 1 μM) using HeLa cells transiently transfected with full length ERα and full length ERβ. (B) Cell viability assay measured in LNCaP cells after 24 h treatment with selected ligands at a final concentration 1 μM. Average of three wells each for three independent experiments.