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2000
Volume 18, Issue 5
  • ISSN: 1389-4501
  • E-ISSN: 1873-5592

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 and ER). 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.

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/content/journals/cdt/10.2174/1389450117666160401125542
2017-04-01
2025-05-28
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/content/journals/cdt/10.2174/1389450117666160401125542
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  • Article Type:
    Research Article
Keyword(s): ERα; ERβ; Estrogen receptor; multi-task learning; QSAR modeling; virtual screening
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