Rational Design of Multi-Target Estrogen Receptors ERα and ERβ by QSAR Approaches

Qi Zhao; Yuxi Lu; Yan Zhao; Rongchao Li; Feng Luan; M Natalia D S Cordeiro

doi:10.2174/1389450117666160401125542

Rational Design of Multi-Target Estrogen Receptors ERα and ERβ by QSAR Approaches

Curr Drug Targets. 2017;18(5):576-591. doi: 10.2174/1389450117666160401125542.

Authors

Qi Zhao¹, Yuxi Lu¹, Yan Zhao¹, Rongchao Li¹, Feng Luan¹, M Natalia D S Cordeiro²

Affiliations

¹ Chemistry & Chemistry Engineering College, Yantai University, Yantai 264005, China.
² LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal.

PMID: 27033186
DOI: 10.2174/1389450117666160401125542

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 (ERα and ERβ). 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.

Keywords: ERα; ERβ; Estrogen receptor; QSAR modeling; multi-task learning; virtual screening.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Animals
Computational Biology / methods*
Computer-Aided Design
Drug Design
Estrogen Receptor alpha / antagonists & inhibitors*
Estrogen Receptor beta / antagonists & inhibitors*
Humans
Quantitative Structure-Activity Relationship

Substances

Estrogen Receptor alpha
Estrogen Receptor beta