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<p>This study investigated the molecular targets and pathways modulated by pterostilbene in breast cancer using network pharmacology and in vitro analysis. The structure of chemicals of pterostilbene was retrieved from PubChem, and gene targets were predicted through Swiss Target Prediction. Human-specific targets were validated using UniProtKB and breast cancer-related targets were identified using GeneCards and BioVenn. Protein–protein interaction (PPI) networks were created using STRING and visualized using Cytoscape, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to elucidate biological functions. Molecular docking studies using AutoDock Vina were used to assess the binding interactions of pterostilbene with key nuclear receptors (PTGS2, ESR1, EGFR, and BCL2). Molecular dynamics (MD) simulations over 200&#xa0;ns in GROMACS confirmed the stability of the ESR1-pterostilbene complex and highlighted significant hydrogen bonding. ADME/T was assessed using the Protox software. In vitro cytotoxicity was assessed using the MTT assay in MCF-7 cells. Sixteen key genes, including PTGS2, ESR1, EGFR, and BCL2, were identified as key targets connecting pterostilbene to breast cancer. PPI analysis identified ESR1, EGFR, and BCL2 as central nodes in the network. Molecular docking revealed robust binding of pterostilbene (below − 8.1&#xa0;kcal/mol), suggesting potential modulation of estrogen receptor signaling. MD simulations confirmed the stability of the complex with favorable structural dynamics. Toxicity analysis suggested a low risk, and MTT assays revealed selective cytotoxicity of pterostilbene toward MCF-7 breast cancer cells (IC<sub>50</sub> = 14.8&#xa0;µM) with a Selectivity Index of 2.85 compared to normal HEL 299 cells. These findings highlight the potential of pterostilbene as a treatment option for breast cancer, which merits additional exploration in experimental models and human studies.</p>

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Pterostilbene as a potent ESR-1 in breast cancer therapy: insights from network pharmacology, molecular docking, dynamics simulations, ADMET, and in vitro analysis

  • 期刊论文

  • 发表日期：

    2025年2月24日

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  • Harneet Marwah,
  • Hitesh Kumar Dewangan

摘要

This study investigated the molecular targets and pathways modulated by pterostilbene in breast cancer using network pharmacology and in vitro analysis. The structure of chemicals of pterostilbene was retrieved from PubChem, and gene targets were predicted through Swiss Target Prediction. Human-specific targets were validated using UniProtKB and breast cancer-related targets were identified using GeneCards and BioVenn. Protein–protein interaction (PPI) networks were created using STRING and visualized using Cytoscape, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to elucidate biological functions. Molecular docking studies using AutoDock Vina were used to assess the binding interactions of pterostilbene with key nuclear receptors (PTGS2, ESR1, EGFR, and BCL2). Molecular dynamics (MD) simulations over 200 ns in GROMACS confirmed the stability of the ESR1-pterostilbene complex and highlighted significant hydrogen bonding. ADME/T was assessed using the Protox software. In vitro cytotoxicity was assessed using the MTT assay in MCF-7 cells. Sixteen key genes, including PTGS2, ESR1, EGFR, and BCL2, were identified as key targets connecting pterostilbene to breast cancer. PPI analysis identified ESR1, EGFR, and BCL2 as central nodes in the network. Molecular docking revealed robust binding of pterostilbene (below − 8.1 kcal/mol), suggesting potential modulation of estrogen receptor signaling. MD simulations confirmed the stability of the complex with favorable structural dynamics. Toxicity analysis suggested a low risk, and MTT assays revealed selective cytotoxicity of pterostilbene toward MCF-7 breast cancer cells (IC50 = 14.8 µM) with a Selectivity Index of 2.85 compared to normal HEL 299 cells. These findings highlight the potential of pterostilbene as a treatment option for breast cancer, which merits additional exploration in experimental models and human studies.