Scholarlink

Background <p>Gut microbiota metabolites are increasingly recognized for their role in modulating chronic disease progression. However, their potential impact on vein graft restenosis (VGR) remains unexplored. This study aimed to elucidate the mechanisms by which gut microbiota and its metabolites attenuate VGR using an integrated approach of network pharmacology, molecular docking, and molecular dynamics (MD) simulations.</p> Methods <p>Gut microbiota, metabolites, and human gut targets were obtained from the gutMGene database. Metabolite targets were predicted using SwissTargetPrediction and Similarity Ensemble Approach, while disease targets were collected from GeneCards, Online Mendelian Inheritance in Man (OMIM), and DrugBank. Overlapping targets were used to construct both a protein-protein interaction (PPI) network and a gut microbiota–metabolites–targets–VGR (GM-M-T-V) network to identify key microbiota, core metabolites, and hub targets. Enrichment analysis investigated associated biological processes, cellular components, molecular functions, and signaling pathways. Drug-likeness and toxicity were evaluated with SwissADME and ADMETlab 2.0. Molecular docking and MD simulations assessed the binding affinity and dynamic characteristics of target-metabolite complexes.</p> Results <p>Integrated data from relevant databases identified 260 gut microbiota, 251 metabolites, 404 metabolite targets, 238 human gut targets, and 741 VGR-related targets. Among these, 16 overlapping targets were identified for further analysis. Enrichment analysis highlighted significant involvement of the relaxin signaling pathway, while PPI topology analysis pinpointed AKT1, NFKB1, EGFR, PTGS2, and PPARG as hub targets. Quercetin was prioritized as the core metabolite based on its top network connectivity, favorable drug-likeness prediction, and manageable in silico-predicted hepatotoxicity/genotoxicity risks in light of its absent clinical toxicity. Molecular docking revealed that quercetin bound to four hub targets (AKT1, NFKB1, EGFR, PPARG) with affinities (ranging from−6.0 to−8.9&#xa0;kcal/mol) comparable or superior to positive controls. MD simulations further suggested favorable structural stability and binding affinity of the EGFR–quercetin complex.</p> Conclusion <p>This integrative study elucidates the role of gut microbiota metabolites against VGR, identifying the microbial metabolite quercetin as a promising multi-target therapeutic agent primarily via the relaxin signaling pathway, which provides a mechanistic groundwork for a novel potential treatment strategy.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Role of gut microbiota metabolites against vein graft restenosis: insights from network pharmacology, molecular docking and molecular dynamic simulation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月8日

查看全文
  • Zi’ang Li,
  • Xiankun Liu,
  • Yiming Bai,
  • Yunpeng Bai,
  • Zhigang Guo

摘要

Background

Gut microbiota metabolites are increasingly recognized for their role in modulating chronic disease progression. However, their potential impact on vein graft restenosis (VGR) remains unexplored. This study aimed to elucidate the mechanisms by which gut microbiota and its metabolites attenuate VGR using an integrated approach of network pharmacology, molecular docking, and molecular dynamics (MD) simulations.

Methods

Gut microbiota, metabolites, and human gut targets were obtained from the gutMGene database. Metabolite targets were predicted using SwissTargetPrediction and Similarity Ensemble Approach, while disease targets were collected from GeneCards, Online Mendelian Inheritance in Man (OMIM), and DrugBank. Overlapping targets were used to construct both a protein-protein interaction (PPI) network and a gut microbiota–metabolites–targets–VGR (GM-M-T-V) network to identify key microbiota, core metabolites, and hub targets. Enrichment analysis investigated associated biological processes, cellular components, molecular functions, and signaling pathways. Drug-likeness and toxicity were evaluated with SwissADME and ADMETlab 2.0. Molecular docking and MD simulations assessed the binding affinity and dynamic characteristics of target-metabolite complexes.

Results

Integrated data from relevant databases identified 260 gut microbiota, 251 metabolites, 404 metabolite targets, 238 human gut targets, and 741 VGR-related targets. Among these, 16 overlapping targets were identified for further analysis. Enrichment analysis highlighted significant involvement of the relaxin signaling pathway, while PPI topology analysis pinpointed AKT1, NFKB1, EGFR, PTGS2, and PPARG as hub targets. Quercetin was prioritized as the core metabolite based on its top network connectivity, favorable drug-likeness prediction, and manageable in silico-predicted hepatotoxicity/genotoxicity risks in light of its absent clinical toxicity. Molecular docking revealed that quercetin bound to four hub targets (AKT1, NFKB1, EGFR, PPARG) with affinities (ranging from−6.0 to−8.9 kcal/mol) comparable or superior to positive controls. MD simulations further suggested favorable structural stability and binding affinity of the EGFR–quercetin complex.

Conclusion

This integrative study elucidates the role of gut microbiota metabolites against VGR, identifying the microbial metabolite quercetin as a promising multi-target therapeutic agent primarily via the relaxin signaling pathway, which provides a mechanistic groundwork for a novel potential treatment strategy.