STRUCTURE AND DYNAMICS OF THE ESTROGEN RECEPTOR

University Of California San Francisco, San Francisco CA

Investigators

Linked publications & trials

Abstract

The human estrogen receptor alpha (hERalpha) is a ligand-modulated transcription factor that regulates that differentiation and maintenance of neural, skeletal, cardiovascular, and reproductive tissues. Transcriptional activation is mediated by two different activation functions, one of which is controlled by ligand binding (AF-2) to the receptor ligand binding domain (LBD) Ligands for the estrogen receptor can act as transcriptional agonists, antagonists or produce variable effects depending on this tissue and promoter contexts. These latter molecules, called selective estrogen receptor modifiers (SERMS) include the clinically important molecules tamoxifen and raloxifene. Agonists promote binding of transcriptional coactivators which link the receptor to the general transcriptional machinery. Antagonists promote binding of coactivator while antagonists block co-activator binding to hERalpha LBD. This agonists promote binding of coactivator while antagonists block coactivator binding to hERalpha LBD. This requires quantitative measurements on ligand and co-activator binding, structural analysis of ligand-induced alterations in receptor structure., and understanding the dynamics of the receptor and co-activator in detail. In addition, we wish to determine how ligands bind to and dissociate from the receptor and to explore differences in ligand binding specificity differences between hERalpha and hERbeta. We will employ a combination of X-ray crystallography to examine detailed of complexes; solution NMR (Core B) to study co-activator structures, co-activator-receptor interactions, helix 12 and ligand binding pocket dynamics; and chemistry (core C) to synthesize novel ligands and co-activator mimetics. Detailed binding equilibria will be determined through Core C. NMR dynamics studies will be complemented by theoretical calculations to understand correlated motions and to predict ligand affinities.