Rational Design of Multi-Target Estrogen Receptors ER_α and ER_β by QSAR Approaches

Title:Rational Design of Multi-Target Estrogen Receptors ER_α and ER_β by QSAR Approaches

Volume: 18 Issue: 5

Author(s): Qi Zhao, Yuxi Lu, Yan Zhao, Rongchao Li, Feng Luan and M. Natalia D.S. Cordeiro

Affiliation:

Keywords: Estrogen receptor, QSAR modeling, virtual screening, multi-task learning, ER_α, ER_β.

Abstract: Estrogens play a crucial role in the growth, development, and homeostasis of various target tissues, their biological effects being mediated by the estrogen receptor (ER). In order to get a better understanding of the structural features of the modulators associated with the binding to ER, this paper provides an overview of the Quantitative Structure–Activity (QSAR) studies performed so far for estimating or predicting the activity of different ligands towards its two known subtypes (ER_α and ER_β). Recent progresses in the application of these modeling studies are additionally pointed out. Finally, ongoing challenges that may lead to new and exciting directions for QSAR modeling studies in this field are discussed.

Cite this article as:

Zhao Qi, Lu Yuxi, Zhao Yan, Li Rongchao, Luan Feng and Cordeiro Natalia D.S. M., Rational Design of Multi-Target Estrogen Receptors ER_α and ER_β by QSAR Approaches, Current Drug Targets 2017; 18 (5) . https://dx.doi.org/10.2174/1389450117666160401125542