ArticleApplied biochemistry and biotechnology2025
Prediction of Multi-targeting Pharmacological Activity of Bioactive Compounds from Medicinal Plants Against Hepatocellular Carcinoma Through Advanced Network Pharmacology and Bioinformatics-Based Investigation.
Article in Applied biochemistry and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Integrated Metabolomics and Multilevel Validation of the Anti-Inflammatory and Skin-Soothing Effects of Bioactive Components fromInternational journal of molecular sciences · 2026Article
- In silico analysis of gene expression signatures and drug repurposing associated with metastatic progression in melanoma (skin cancer).Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Anti-Inflammatory Potential of Key Phytochemicals From Humboldtia sanjappae: In Vivo Studies and Molecular Docking With MM-GBSA Analysis.Chemistry & biodiversity · 2026Article
- Multi-omics profiling and cellular validation reveal distinct lipid networks of krill oil and its predicted mechanisms against insulin resistance.Frontiers in nutrition · 2026Article
- Targeting Chemical-induced Hepatocellular Carcinoma: Ameliorative Potential of Natural Compounds with Focus on Beta-carbolines.Mini reviews in medicinal chemistry · 2026Review
- Integrating in-silico and experimental validation approaches to unveil the therapeutic mechanism of naringenin against breast cancer.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The primary objective of this study was to identify bioactive compounds from four medicinal plants with multi-targeting activity against hepatocellular carcinoma (HCC). A comprehensive analysis led to the identification of a subset of compounds possessing favorable drug-likeness, pharmacokinetics, and absence of toxicity profiles. Target analysis for 42 phytochemicals revealed 210 potential targets associated with HCC. Protein-protein interaction (PPI) analysis of these targets uncovered five critical hub genes, STAT3, SRC, AKT1, MAPK3, and EGFR, in our study. Correlation analysis of these hub genes indicated a strong positive correlation between EGFR, MAPK3, and SRC expression highlighting their interconnected roles in HCC. Survival analysis underscored the significant prognostic role of these hub genes in HCC underscoring their potential as biomarkers. The co-expression analysis unveiled an intricate network of interactions among the hub genes, while the enrichment analysis demonstrated their enrichment in diverse biological and signaling pathways related to HCC. Molecular docking analysis between the seven phytochemicals and five identified targets revealed that bauerenol exhibited good affinity towards all the targets. Subsequent molecular dynamics (MD) simulations demonstrated that bauerenol formed stable complexes with STAT3, AKT1, EGFR, and MAPK3, suggesting its potential as a multi-targeted inhibitor. Our research suggests that bauerenol shows promise as an inhibitor for HCC targets and stands out as a notable lead compound. However, further experimental studies are necessary to confirm its activity and to evaluate its potential as a therapeutic agent for HCC.
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Registered trials
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