{"title":"Pterostilbene as a potent ESR-1 in breast cancer therapy: insights from network pharmacology, molecular docking, dynamics simulations, ADMET, and in vitro analysis.","authors":"Harneet Marwah, Hitesh Kumar Dewangan","doi":"10.1007/s11030-025-11144-3","DOIUrl":null,"url":null,"abstract":"<p><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 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 (IC<sub>50</sub> = 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.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Diversity","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s11030-025-11144-3","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
Pterostilbene as a potent ESR-1 in breast cancer therapy: insights from network pharmacology, molecular docking, dynamics simulations, ADMET, and in vitro analysis.
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.
期刊介绍:
Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including:
combinatorial chemistry and parallel synthesis;
small molecule libraries;
microwave synthesis;
flow synthesis;
fluorous synthesis;
diversity oriented synthesis (DOS);
nanoreactors;
click chemistry;
multiplex technologies;
fragment- and ligand-based design;
structure/function/SAR;
computational chemistry and molecular design;
chemoinformatics;
screening techniques and screening interfaces;
analytical and purification methods;
robotics, automation and miniaturization;
targeted libraries;
display libraries;
peptides and peptoids;
proteins;
oligonucleotides;
carbohydrates;
natural diversity;
new methods of library formulation and deconvolution;
directed evolution, origin of life and recombination;
search techniques, landscapes, random chemistry and more;