Exploring the Underlying Molecular Mechanisms of Chaetomugilin Q in Breast Cancer Using Network Pharmacology, Molecular Docking, and Bioinformatics
- 1Department of Life Science, Yuncheng University, Yuncheng 044000, China
- 2College of Plant Science, Jilin University, Changchun 130062, China
- 3Featured Fruit Quality Control and Application Laboratory, Department of Food and Health, Yuncheng University, Yuncheng 044000, China
Abstract
Chaetomugilin Q has demonstrated anti-tumor effects in preclinical models. However, the potential mechanisms of chaetomugilin Q in treating breast cancer remain unclear. This study used network pharmacology and molecular docking prediction to explore these mechanisms and prioritize candidate targets of chaetomugilin Q in breast cancer. PharmMapper, SuperPred, and GalaxySagittarius-AF were utilized to obtain targets associated with chaetomugilin Q, while GeneCards, CTD, DrugBank, OMIM, and TTD were used to collect breast cancer-related targets. A total of 299 overlapping candidate targets were obtained using Venny 2.1.0. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the DAVID tool. These candidate targets were input into the STRING database and Cytoscape 3.10.1 software to construct a protein–protein interaction (PPI) network and prioritize candidate core targets. Molecular docking prediction was performed using the CB-Dock2 server. The candidate core targets were further analyzed using GEPIA, HPA, cBioPortal, Kaplan–Meier Plotter, and TIMER. After GO and KEGG enrichment analyses, 1174 relevant terms and 169 signaling pathways were identified, respectively. PIK3R1, HSP90AA1, SRC, AKT1, STAT3, PIK3CD, PIK3CB, EGFR, GRB2, and ESR1 were prioritized as candidate core targets. Molecular docking results showed that the predicted docking scores of chaetomugilin Q to the candidate core targets were lower than −5 kcal/mol. Bioinformatics analyses based on independent public databases indicated that these candidate core targets exhibited differential expression at the mRNA and protein levels and were associated with patient prognosis, mutation status, and immune cell infiltration, providing clinical and biological context. This study provides a computational prediction of the potential mechanisms of chaetomugilin Q against breast cancer and a theoretical basis for subsequent experimental validation.
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BibTeX
@article{he2026exploring,
title = {{Exploring the Underlying Molecular Mechanisms of Chaetomugilin Q in Breast Cancer Using Network Pharmacology, Molecular Docking, and Bioinformatics}},
author = {Qiurui He and Weibing Li and Jiaxuan Xiang and Jingjing Mu and Yuying Miao and Zhirong Su and Jianchun Qin and Feng Wang},
journal = {Molecules},
year = {2026},
month = oct,
doi = {10.3390/molecules31203661},
url = {https://www.mdpi.com/1420-3049/31/20/3661},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Exploring the Underlying Molecular Mechanisms of Chaetomugilin Q in Breast Cancer Using Network Pharmacology, Molecular Docking, and Bioinformatics
AU - Qiurui He
AU - Weibing Li
AU - Jiaxuan Xiang
AU - Jingjing Mu
AU - Yuying Miao
AU - Zhirong Su
AU - Jianchun Qin
AU - Feng Wang
PY - 2026
DA - 2026/10/01
JO - Molecules
DO - 10.3390/molecules31203661
UR - https://www.mdpi.com/1420-3049/31/20/3661
AB - Chaetomugilin Q has demonstrated anti-tumor effects in preclinical models. However, the potential mechanisms of chaetomugilin Q in treating breast cancer remain unclear. This study used network pharmacology and molecular docking prediction to explore these mechanisms and prioritize candidate targets of chaetomugilin Q in breast cancer. PharmMapper, SuperPred, and GalaxySagittarius-AF were utilized to obtain targets associated with chaetomugilin Q, while GeneCards, CTD, DrugBank, OMIM, and TTD were used to collect breast cancer-related targets. A total of 299 overlapping candidate targets were obtained using Venny 2.1.0. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the DAVID tool. These candidate targets were input into the STRING database and Cytoscape 3.10.1 software to construct a protein–protein interaction (PPI) network and prioritize candidate core targets. Molecular docking prediction was performed using the CB-Dock2 server. The candidate core targets were further analyzed using GEPIA, HPA, cBioPortal, Kaplan–Meier Plotter, and TIMER. After GO and KEGG enrichment analyses, 1174 relevant terms and 169 signaling pathways were identified, respectively. PIK3R1, HSP90AA1, SRC, AKT1, STAT3, PIK3CD, PIK3CB, EGFR, GRB2, and ESR1 were prioritized as candidate core targets. Molecular docking results showed that the predicted docking scores of chaetomugilin Q to the candidate core targets were lower than −5 kcal/mol. Bioinformatics analyses based on independent public databases indicated that these candidate core targets exhibited differential expression at the mRNA and protein levels and were associated with patient prognosis, mutation status, and immune cell infiltration, providing clinical and biological context. This study provides a computational prediction of the potential mechanisms of chaetomugilin Q against breast cancer and a theoretical basis for subsequent experimental validation.
SN - 1420-3049
ER -