ArticleMolecular diversity2024
Identification of molecular targets of Trigonelline for treating breast cancer through network pharmacology and bioinformatics-based prediction.
Article in Molecular diversity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Integrative Transcriptomic and Machine Learning Analysis of ecDNA-Associated Features for Studying Chemotherapy Resistance in TNBC.bioRxiv : the preprint server for biology · 2026Article
- Novel explainable deep learning based drug sensitivity prediction for early treatment of breast cancer.Scientific reports · 2026Article
- Trigonelline activates NRF2 and awakens dormant ovarian follicles to promote pregnancy in aging mice.iScience · 2025Article
- Maturity related metabolomic analysis of Balanites aegyptiaca fruits with in vitro and in silico cytotoxicity evaluation.Scientific reports · 2025Article
- Bioinformatics and Omics-based Perspectives on Breast Cancer: Advancing Target Gene Identification for the Development of Anticancer Agents.Asian Pacific journal of cancer prevention : APJCP · 2025Review
- Towards interpretable drug interaction predictionPeerJ. Computer science · 2025Article
- Medicinal effects of Ephedra foeminea aqueous extracts: Metabolomic characterization, biological evaluation, and molecular docking.PloS one · 2025Article
- Unveiling the Therapeutic Potential of Trigonelline: A Promising Approach in Cancer Prevention and Treatment.Anti-cancer agents in medicinal chemistry · 2025Review
- Mechanisms of QiShenYiQi in Inhibiting Blood-Brain Barrier Damage Following Stroke: A Network Pharmacology and Experimental Study.Combinatorial chemistry & high throughput screening · 2025Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer, a highly prevalent and fatal cancer that affects the female population worldwide, stands as a significant health challenge. Despite the abundance of chemotherapy drugs, the adverse side effects associated with them have initiated an investigation into natural plant-based compounds. Trigonelline, an alkaloid found in Trigonella foenum-graecum, was previously reported for its anticancer properties by the researchers. In this present study, we have identified the molecular targets of Trigonelline in breast cancer and predicted its drug-like properties and toxicity. By analyzing breast cancer targets from databases including TTD, TCGA, Gene cards, and Trigonelline targets obtained from CTD, we identified 14 specific targets of Trigonelline in the context of breast cancer. The protein-protein interaction (PPI) network of the 14 Trigonelline targets provided insights into the complex relationships between different genes and targets. Heatmap analysis demonstrated the expression patterns of these 14 genes at the protein and RNA levels in breast cancer cells and breast tissues. Notably, four genes, namely EGF, BAX, EGFR, and MTOR, were enriched in the breast cancer pathway. At the same time, PARP1, DDIT3, BAX, and TNF were associated with the apoptosis pathway according to KEGG pathway enrichment analyses. Molecular docking studies between Trigonelline and target proteins from the Protein Data Bank (PDB) revealed favorable binding affinity. Furthermore, mutation analysis of target genes within a dataset of 1918 samples from cBioPortal revealed the absence of mutations. Remarkably, Trigonelline also exhibited binding affinity towards two mutant proteins, and based on these findings, we predicted that Trigonelline could be utilized to target breast cancer genes and their mutants through network pharmacology. Additionally, this was supported by molecular dynamic simulation studies. As our study is preliminary, further validation through in vitro and in vivo studies is essential to confirm the efficacy of Trigonelline in breast cancer treatment.
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