Literature DB >> 19689279

How computational methods try to disclose the estrogen receptor secrecy--modeling the flexibility.

Francesca Spyrakis1, Pietro Cozzini.   

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.

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Year:  2009        PMID: 19689279     DOI: 10.2174/092986709788803123

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  2 in total

1.  Characterization of ligand type of estrogen receptor by MD simulation and mm-PBSA free energy analysis.

Authors:  Jing-Yuan Liu; Sean D Mooney
Journal:  Int J Biochem Mol Biol       Date:  2011-04-23

Review 2.  Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective.

Authors:  Luca Dellafiora; Chiara Dall'Asta; Gianni Galaverna
Journal:  Toxins (Basel)       Date:  2018-01-23       Impact factor: 4.546

  2 in total

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