ArticleJournal of computer-aided molecular design2026
Identification of new ER-targeted anticancer hits active against MCF-7 breast cancer cells in the marine fungal secondary metabolite library using computative and experimental approaches.
Article in Journal of computer-aided molecular design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The identification of novel estrogen receptor (ER)-targeted anticancer compounds from marine fungal secondary metabolites was performed using a combined computational and experimental approach. A library of 461 marine fungal metabolites was analyzed using chemical space visualization, structural similarity assessment using Tanimoto indices, and target-prediction tools to identify potential ER ligands. Scaffold analysis of predicted hits suggested decalin/bicyclic terpenoid (6-6), tricyclic 6-6-6 terpenoid, bicyclic 5-6 system and several polycyclic system chemotypes as novel for ER ligands. The ER-dependence of the proposed hits cytotoxicity was tested in vitro against ER-positive human breast cancer MCF-7 cells using a 4-hydroxytamoxifen (4-OHT)-competitive viability assay. The compounds virescenoside M, cladosporin, zosteropenilline S, and griseofulvin exhibited ER-dependent cytotoxic effects on MCF-7 cells, confirming the in silico predictions. In 48 h experiments, cladosporin, zosteropenilline S, and griseofulvin at 100 µM decreased the MCF-7 cell viability by 73.6%, 33.2%, and 45.8%, respectively, but statistically significant cytotoxic effect of griseofulvin also was observed at its concentration of 1 µM. Surface plasmon resonance (SPR) experiments confirmed the direct binding of griseofulvin to ERα, with a dissociation constant (Kd) of 8.00 µM. These findings highlight marine fungi as a valuable source of novel ER-targeted anticancer agents and suggest a novel ER-dependent mechanism for the antifungal drug griseofulvin, providing a basis for its potential repositioning in ER-positive breast cancer therapy. This integrated computational-experimental strategy provides a framework for discovering new lead compounds for breast cancer treatment.
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