title: How computational methods try to disclose the estrogen receptor secrecy--modeling the flexibility.
abstract: The Estrogen Receptor (ER) is a ligand activated transcription factor involved in numerous fundamental biological processes as in many important diseases and malfunctions. Since 1998, when the first structure of the ER ligand binding domain complexed with 17 beta-estradiol (E2) was released, the number of ER alpha and ER beta crystallographic structures constantly increased. Nevertheless, little is still known about several fundamental events that govern the regular biological activity, or that modulate the transcription response following the interaction of the receptor with xenobiotic compounds. Moreover, the peculiar flexibility of the receptor characterized by two levels of conformational changes, i.e slight adjustments of binding pocket residues side chains, and more significant displacement of helix 12, moving from a close/agonist-like to an open/antagonist-like position, makes experimental approaches unable to properly describe and predict the receptor conformational equilibrium. Which is the most probable structure of the unbound receptor? How do biological ligands enter the receptor? How does the tissue-related pull of coactivators and corepressors affect the puzzling conformational equilibrium of the receptor? Since most of these questions still do not have an answer. A proper description of the structure-activity relationship and of the pharmacophoric properties of the binding pocket would be of paramount importance in order to design new agonist and antagonist molecules, and to understand how diverse xenobiotic compounds can alter the conformational equilibrium of the receptor, inducing estrogenic or anti-estrogenic effects. In this review we report the most relevant computational approaches, both theoretical and applicative, and the latest proposed models.
authors.affiliation: Laboratory of Molecular Modeling, Department of General and Inorganic Chemistry, University of Parma, Parma, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Spyrakis
authors.forename: Pietro
authors.initials: P
authors.lastname: Cozzini
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D015195:Drug Design; D006801:Humans; D008024:Ligands; D021281:Quantitative Structure-Activity Relationship; D011960:Receptors, Estrogen / Q000737:chemistry* / Q000378:metabolism
chemical_list: D008024:Ligands; D011960:Receptors, Estrogen