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Updated: Aug 11, 2026

Screening for Phytoestrogens using a Cell-based Estrogen Receptor β Reporter Assay
Published on: June 7, 2020
Estrogen receptors: molecular interactions, virtual screening and future prospects
Andrew J S Knox1, Mary J Meegan, David G Lloyd
1School of Pharmacy & Pharmaceutical Sciences, Trinity College Dublin, Dublin 2, Ireland. knoxas@tcd.ie
Abstract:
Identification of the Estrogen Receptor (ER) as a key mediator of the proliferation of breast cancer, and its involvement in pathways leading to osteoporosis and coronary heart disease, has resulted in a surge to discover and design compounds with the ability to modulate its actions (SERMs). Concurrently, a dramatic increase in the number of crystal structures of the ER has led to a more in depth understanding of the governing mechanisms involved in ER modulation. Entwining computational techniques with the availability of 3D structural data, has allowed not only the rational design of potent inhibitors of the ER, but also its incorporation in Virtual Screening (VS) in the search for novel chemotypes that can modulate the ER. An important initial step in the VS process is to filter towards molecules that occupy similar chemical space to a set of known actives prior to docking. We illustrate through Principal Component Analysis (PCA) of 145 descriptors the region of chemical space antiestrogens occupy compared with 'drug-like' space. We also review all available studies involving validation of several docking algorithms utilizing the ER, ultimately focusing on analysis of Enrichment (E) rates and False Positive (FP) rates to illustrate the successes attributed to each docking algorithm. Finally, we relate the recent discovery of non-genomic mechanisms of the ER and subsequently present a model involving a recently identified alternative, second binding-pocket of the ER in our laboratory through cavity analysis that suggests how the same receptor can invoke these, 'classical' and rapid responses concurrently.
Insights
Researchers are using computational methods and 3D structural data to discover new drugs that target the Estrogen Receptor (ER). This approach aids in designing potent inhibitors and identifying novel compounds for breast cancer and other diseases.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Pharmacology
Background:
- The Estrogen Receptor (ER) is crucial in breast cancer proliferation, osteoporosis, and coronary heart disease.
- Advances in ER crystal structures enhance understanding of its modulation mechanisms.
- Selective Estrogen Receptor Modulators (SERMs) are key therapeutic agents.
Purpose of the Study:
- To explore computational techniques for rational drug design targeting the ER.
- To investigate the chemical space of antiestrogens using Principal Component Analysis (PCA).
- To validate docking algorithms for Virtual Screening (VS) of ER modulators.
Main Methods:
- Principal Component Analysis (PCA) of 145 molecular descriptors.
- Review and validation of docking algorithms using ER structural data.
- Cavity analysis to identify alternative ER binding pockets.
Main Results:
- PCA differentiated antiestrogen chemical space from general 'drug-like' space.
- Enrichment (E) and False Positive (FP) rates were used to assess docking algorithm performance.
- A model for concurrent genomic and non-genomic ER signaling via a second binding pocket was proposed.
Conclusions:
- Computational methods combined with structural data enable rational design and VS of ER modulators.
- Docking algorithms show varying success rates in ER-targeted VS.
- A novel binding pocket model explains dual ER signaling pathways.
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