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Estrogen receptor (ER) is a ligand-inducible transcriptional factor involving in cell growth, differentiation, and diseases, so detection and identification of compounds having estrogenic effects are of great importance in the drug discovery industry. We have developed and validated a rapid, simple, and homogeneous method that can detect estrogenic compounds. This human ERα/β binding assay uses fluorescence polarization (FP) by applying an autofluorescent phytoestrogen, coumestrol (CS). A nonspecific adsorption assay shows that no obvious nonspecific adsorption is detected between CS and ERs. In the Scatchard plot analysis, the convex curve exhibits a positive cooperative binding, indicating that the binding of CS induces a conformational change of the ER to form a dimer and increases the affinity for the additional CS. In the Hill plot analysis, CS shows moderate binding affinity with both ERα and ERβ, and the measured Kdof CS is 32.66 µM and 36.14 µM, respectively, indicating that CS is applicable to the ER binding assay for determination of potent ligands of moderate binding affinity. Four typical ligands are selected to verify the ER binding assays, and the results are consistent with the reported data. All of above make the FP method based on CS suitable for high-throughput screening.

BackgroundCell proliferation, differentiation, Gene expression, metabolism, immunization and signal transduction require the participation of ligands and targets. It is a great challenge to identify rules governing molecular recognition between chemical topological substructures of ligands and the binding sites of the targets.MethodsWe suppose that the ligand-target interactions are determined by ligand substructures as well as the physical-chemical properties of the binding sites. Therefore, we propose a fragment interaction model (FIM) to describe the interactions between ligands and targets, with the purpose of facilitating the chemical interpretation of ligand-target binding. First we extract target-ligand complexes from sc-PDB database, based on which, we get the target binding sites and the ligands. Then we represent each binding site as a fragment vector based on a target fragment dictionary that is composed of 199 clusters (denoted as fragements in this work) obtained by clustering 4200 trimers according to their physical-chemical properties. And then, we represent each ligand as a substructure vector based on a dictionary containing 747 substructures. Finally, we build the FIM by generating the interaction matrix M (representing the fragment interaction network), and the FIM can later be used for predicting unknown ligand-target interactions as well as providing the binding details of the interactions.ResultsThe five-fold cross validation results show that the proposed model can get higher AUC score (92%) than three prevalence algorithms CS-PD (80%), BLM-NII (85%) and RF (85%), demonstrating the remarkable predictive ability of FIM. We also show that the ligand binding sites (local information) overweight the sequence similarities (global information) in ligand-target binding, and introducing too much global information would be harmful to the predictive ability. Moreover, The derived fragment interaction network can provide the chemical insights on the interactions.ConclusionsThe target and ligand bindings are local events, and the local information dominate the binding ability. Though integrating of the global information can promote the predictive ability, the role is very limited. The fragment interaction network is helpful for understanding the mechanism of the ligand-target interaction.

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We have synthesized a series of novel SERMs bearing a ferrocenyl unit based on a three-dimensional oxabicyclo[2.2.1]heptene core scaffold. These compounds displayed high receptor binding affinities as well as ERα or ERβ selectivity. In cell proliferation assays, we found that these ligands were cytotoxic at micromolar concentrations in both ER-positive and ER-negative breast cancer cells. On further examination, we found that the antiproliferative effects of compounds 9b, 10h and 11b on MCF-7 cells line does not arise from antiestrogenicity, but rather proceeds through a cytotoxic pathway. Possible mechanisms for the unique activities of these ligands were also investigated by molecular modeling. These new ligands could act as scaffolds for the development of novel anti-breast cancer agents.