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<p>Liver cancer remains a smajor cause of mortality worldwide, underscoring the urgent need for novel natural therapeutics. <i>Polygonatum kingianum</i> var. grandifolium (PK) and <i>Polygonatum sibiricum</i> Redouté (PS) are rice in terpenoids, yet their anti-liver cancer mechanisms remain poorly understood. This study used metabolism, network analysis, molecular docking, and molecular dynamics simulations to investigate their therapeutic potential. Metabolomic analysis identified nine differential terpenoid metabolites, with Maslinic acid and Alphitolic acid being species-specific. Network analysis revealed 23 liver cancer-related targets, including five key proteins: HMGCR, PTGS2, ESR1, PPARG, and PGR. Functional enrichment analysis identified 126 GO terms and 11 KEGG pathways (<i>P</i> &lt; 0.05). Molecular docking suggested strong binding affinities between core compounds and targets, while molecular dynamics simulations confirmed the stability of maslinic acid and alphitolic acid with their respective targets. This study enhances the pharmacological understanding of <i>Polygonatum</i> species and offers promising insights for the development of novel liver cancer treatments.</p>

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Metabolomics combined with network pharmacology reveals the anti-hepatoma effects of terpenoids from Polygonatum kingianum var. grandifolium and Polygonatum sibiricum Redouté as well as differences in their terpenoid metabolites

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月5日

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  • Xiuzhi Wang,
  • Xiaolin Wan,
  • Tianrun Zhu,
  • Lingjun Cui,
  • Qiang Xiao

摘要

Liver cancer remains a smajor cause of mortality worldwide, underscoring the urgent need for novel natural therapeutics. Polygonatum kingianum var. grandifolium (PK) and Polygonatum sibiricum Redouté (PS) are rice in terpenoids, yet their anti-liver cancer mechanisms remain poorly understood. This study used metabolism, network analysis, molecular docking, and molecular dynamics simulations to investigate their therapeutic potential. Metabolomic analysis identified nine differential terpenoid metabolites, with Maslinic acid and Alphitolic acid being species-specific. Network analysis revealed 23 liver cancer-related targets, including five key proteins: HMGCR, PTGS2, ESR1, PPARG, and PGR. Functional enrichment analysis identified 126 GO terms and 11 KEGG pathways (P < 0.05). Molecular docking suggested strong binding affinities between core compounds and targets, while molecular dynamics simulations confirmed the stability of maslinic acid and alphitolic acid with their respective targets. This study enhances the pharmacological understanding of Polygonatum species and offers promising insights for the development of novel liver cancer treatments.