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<p>Magnolol, a bioactive principle from <i>Magnolia officinalis</i>, has demonstrated potential anticancer properties. This study investigates the anticancer effects of magnolol on liver cancer cells under in vitro conditions, expounding its molecular mechanisms, target interactions, and therapeutic potential. SwissADME evaluated drug-like physicochemical properties of magnolol while as SwissTargetPrediction, SuperPred, and GeneCards identified potential biological targets of magnolol and disease targets (liver cancer) respectively. Protein-protein interaction (PPI) networks were generated by using STRING database and Cytoscape software with identification of hub genes by using Cytohubba plugin. Functional enrichment analysis, such as gene ontology (GO) and KEGG pathway analyses of the common biological targets was performed in order to identify main biological processes, molecular functions, cellular components and signalling pathways. Hub genes were differentially expressed, staged, and prognosed using GEPIA2. Using CB-Dock2, binding affinities of magnolol with NFKB1, EGFR, and ERBB2 were examined, while MD simulations was performed using Desmond Software. MTT, clonogenic, Transwell, EDU, and flow cytometry assays were implemented to evaluate the therapeutic efficacy of magnolol on HepG2 cell proliferation, cellular morphology, cell migration, DNA synthesis, and cellular apoptosis. Magnolol demonstrated favorable drug-like physicochemical properties, including high GI absorption and BBB permeability. A total of 44 overlapping targets between magnolol and liver cancer were identified, forming a dense PPI network with 10 hub genes, including NFKB1, EGFR, and ERBB2. GO and KEGG analyses revealed enrichment in critical pathways such as PI3K-Akt, MAPK, and ErbB signaling, emphasizing the potential of magnolol in cancer treatment. Hub gene analysis showed differential expression patterns, with NFKB1 and ERBB2 overexpressed in tumors, correlating with advanced stages and poor survival, while EGFR downregulation indicated a favorable prognosis. Docking studies revealed strong binding affinities, particularly for ERBB2 (Vina score − 10.1), with MD simulations confirming stable interactions. Functional assays in HepG2 cells demonstrated dose-dependent inhibition of proliferation, colony formation, migration, and DNA synthesis, alongside significant apoptosis induction. This study highlights magnolol as a possible lead molecule candidate for liver cancer, targeting key molecular pathways and hub genes associated with disease progression. Its ability to modulate critical cellular functions and induce apoptosis, coupled with its strong binding affinity and stability with pivotal proteins, underscores its therapeutic potential.</p>

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Uncovering the antiproliferative effects of magnolol in liver cancer: a multi-omics study integrating computational chemistry, network pharmacology, bioinformatics and in vitro experimental validations

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Yu Cai,
  • Yutong Liu,
  • Chang Tian,
  • Fende Liu,
  • Xiaojun Wang

摘要

Magnolol, a bioactive principle from Magnolia officinalis, has demonstrated potential anticancer properties. This study investigates the anticancer effects of magnolol on liver cancer cells under in vitro conditions, expounding its molecular mechanisms, target interactions, and therapeutic potential. SwissADME evaluated drug-like physicochemical properties of magnolol while as SwissTargetPrediction, SuperPred, and GeneCards identified potential biological targets of magnolol and disease targets (liver cancer) respectively. Protein-protein interaction (PPI) networks were generated by using STRING database and Cytoscape software with identification of hub genes by using Cytohubba plugin. Functional enrichment analysis, such as gene ontology (GO) and KEGG pathway analyses of the common biological targets was performed in order to identify main biological processes, molecular functions, cellular components and signalling pathways. Hub genes were differentially expressed, staged, and prognosed using GEPIA2. Using CB-Dock2, binding affinities of magnolol with NFKB1, EGFR, and ERBB2 were examined, while MD simulations was performed using Desmond Software. MTT, clonogenic, Transwell, EDU, and flow cytometry assays were implemented to evaluate the therapeutic efficacy of magnolol on HepG2 cell proliferation, cellular morphology, cell migration, DNA synthesis, and cellular apoptosis. Magnolol demonstrated favorable drug-like physicochemical properties, including high GI absorption and BBB permeability. A total of 44 overlapping targets between magnolol and liver cancer were identified, forming a dense PPI network with 10 hub genes, including NFKB1, EGFR, and ERBB2. GO and KEGG analyses revealed enrichment in critical pathways such as PI3K-Akt, MAPK, and ErbB signaling, emphasizing the potential of magnolol in cancer treatment. Hub gene analysis showed differential expression patterns, with NFKB1 and ERBB2 overexpressed in tumors, correlating with advanced stages and poor survival, while EGFR downregulation indicated a favorable prognosis. Docking studies revealed strong binding affinities, particularly for ERBB2 (Vina score − 10.1), with MD simulations confirming stable interactions. Functional assays in HepG2 cells demonstrated dose-dependent inhibition of proliferation, colony formation, migration, and DNA synthesis, alongside significant apoptosis induction. This study highlights magnolol as a possible lead molecule candidate for liver cancer, targeting key molecular pathways and hub genes associated with disease progression. Its ability to modulate critical cellular functions and induce apoptosis, coupled with its strong binding affinity and stability with pivotal proteins, underscores its therapeutic potential.