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Updated: May 21, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Discovery and structure-activity analysis of selective estrogen receptor modulators via similarity-based virtual
Jie Shen1, Jing Jiang, Guanglin Kuang
1Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
Abstract:
A number of selective estrogen receptor modulators (SERMs) were discovered from the SPECS database via a simple protocol. Based on two reference SERMs we identified via structure-based virtual screening previously, ligand-based similarity search and molecular docking filtering were conducted to identify novel SERMs from SPECS library. Among the 36 purchased compounds, 21 were confirmed to be active by in vitro assays, and 10 showed dual profile properties, namely as antagonists of ERα and agonists of ERβ. The anti-proliferative potency of these ligands was also evaluated against MCF-7 cell lines. Further investigation of the anti-proliferative mechanism of compound 3a suggested that it induced a G1 cell cycle arrest in ERα positive MCF-7 cell through ERα mediated cyclin D1 down-regulation.
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