Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Ligand dissociation from estrogen receptor is mediated by receptor dimerization: Evidence from molecular dynamics simulations

Estrogen Receptor (ER) is an important target for pharmaceutical design. Like other ligand-dependent transcription factors, hormone binding regulates ER transcriptional activity. Nevertheless, the mechanisms by which ligands enter and leave ERs and other nuclear receptors remain poorly understood. Here, we report results of locally enhanced sampling molecular dynamics simulations to identify dissociation pathways of two ER ligands [the natural hormone 17 beta-estradiol (E-2) and the selective ER modulator raloxifene (RAL)] from the human ER alpha ligand-binding domain in monomeric and dimeric forms. E-2 dissociation occurs via three different pathways in ER monomers. One resembles the mousetrap mechanism (Path I), involving repositioning of helix 12 (H12), others involve the separation of H8 and H11 (Path II), and a variant of this pathway at the bottom of the ligand-binding domain (Path II`). RAL leaves the receptor through Path I and a Path I variant in which the ligand leaves the receptor through the loop region between H11 and H12 (Path I`). Remarkably, ER dimerization strongly suppresses Paths II and II` for E-2 dissociation and modifies RAL escape routes. We propose that differences in ligand release pathways detected in the simulations for ER monomers and dimers provide an explanation for previously observed effects of ER quaternary state on ligand dissociation rates and suggest that dimerization may play an important, and hitherto unexpected, role in regulation of ligand dissociation rates throughout the nuclear receptor family.