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MD simulations of estrogen receptors (ER) and docking analysis of DPN analogues reveal insights about subtype-receptor selectivity | Abstract
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Journal of Computational Methods in Molecular Design

Abstract

MD simulations of estrogen receptors (ER) and docking analysis of DPN analogues reveal insights about subtype-receptor selectivity

Author(s): Marlet Martinez

Estrogen (17-estradiol) is essential for normal growth and differentiation in the mammary gland. In the last three decades previous investigations have revealed that estrogen receptor alpha (ERα) plays a critical role in breast cancer. More recently, observations regarding the widespread expression of ERβ-like proteins in normal and neoplastic mammary tissues have suggested that ERβ is involved in the mentioned pathology. Therefore, design of new drugs both steroidal and nonsteroidal that target ERβ represents a therapeutical promise to treat several diseases. In this work, we have proposed a new set of compounds that target effectively the estrogen receptors, and particularly the ERβ. They were designed based on the chemical structure of the ERβ-selective agonist diarylpropionitrile (DPN), then, these potential ligands were submitted in silico ADMET (absorption, distribution, metabolism, excretion, toxicity), from such analysis we could select the ones that showed better properties and they were used for docking studies on ERα and ERβ, employing snapshots at 0 ns and 100 ns retrieved from Molecular Dynamics (MD) Simulations.