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Background <p><i>Zanthoxylum simulans</i>, traditionally used for diabetes, lacks molecular mechanistic insights. This study integrates network pharmacology, molecular docking, ADMET profiling, 200-ns molecular dynamics, PCA, and FEL analyses to identify anti-diabetic phytochemicals from its fruit and bark.</p> Methods <p>From 120 literature-identified phytochemicals, five leads were screened (MolSoft DL ≥ 0.18): magnocurarine (1.45), N-methyltetrahydrocolumbamine (1.30), reticuline (1.13), β-sitostenone (0.91), menisperine (0.87). SwissTargetPrediction yielded 500 targets overlapping 27 diabetes genes (DisGeNET), identifying hub proteins PPARG, IL6, TNF, STAT3 via Cytoscape/STRING. Docking used AutoDock Vina; ADMET via SwissADME/pkCSM; Molecular Dynamics (200&#xa0;ns GROMACS) with RMSD/RMSF/Rg/SASA/H-bond analysis; PCA/FEL via Bio3D/OriginPro.</p> Results <p>β-Sitostenone showed the highest docking affinities (-8.5&#xa0;kcal/mol STAT3, -8.2&#xa0;kcal/mol PPARG); menisperine -8.1&#xa0;kcal/mol STAT3. All leads had optimal ADMET (no hepatotoxicity/hERG inhibition; LD50 2.356–2.531&#xa0;mol/kg). Magnocurarine-PPARG exhibited superior stability vs pioglitazone: stable RMSD (&lt; 0.30&#xa0;nm), low RMSF (0.05–0.15&#xa0;nm), compact Rg (1.92–1.98&#xa0;nm), reduced SASA (142–150 nm<sup>2</sup>), consistent H-bonds (2–4), and broader FEL basic indicating entropic flexibility.</p> Conclusion <p>Magnocurarine emerges as a superior anti-diabetic lead from <i>Zanthoxylum simulans</i>, demonstrating exceptional PPARG binding, pharmacokinetic safety, and dynamic stability over 200&#xa0;ns validating its therapeutic potential.</p>

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Integrated network pharmacology and molecular modeling approaches to reveal the anti-diabetic potential of phytochemicals from Zanthoxylum simulans

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Sowmiya Palanivel,
  • Anguraj Moulishankar,
  • Santhanavel Murugan,
  • Kathiravan Muthu Kumaradoss,
  • Sundarrajan Thirugnanasambandam

摘要

Background

Zanthoxylum simulans, traditionally used for diabetes, lacks molecular mechanistic insights. This study integrates network pharmacology, molecular docking, ADMET profiling, 200-ns molecular dynamics, PCA, and FEL analyses to identify anti-diabetic phytochemicals from its fruit and bark.

Methods

From 120 literature-identified phytochemicals, five leads were screened (MolSoft DL ≥ 0.18): magnocurarine (1.45), N-methyltetrahydrocolumbamine (1.30), reticuline (1.13), β-sitostenone (0.91), menisperine (0.87). SwissTargetPrediction yielded 500 targets overlapping 27 diabetes genes (DisGeNET), identifying hub proteins PPARG, IL6, TNF, STAT3 via Cytoscape/STRING. Docking used AutoDock Vina; ADMET via SwissADME/pkCSM; Molecular Dynamics (200 ns GROMACS) with RMSD/RMSF/Rg/SASA/H-bond analysis; PCA/FEL via Bio3D/OriginPro.

Results

β-Sitostenone showed the highest docking affinities (-8.5 kcal/mol STAT3, -8.2 kcal/mol PPARG); menisperine -8.1 kcal/mol STAT3. All leads had optimal ADMET (no hepatotoxicity/hERG inhibition; LD50 2.356–2.531 mol/kg). Magnocurarine-PPARG exhibited superior stability vs pioglitazone: stable RMSD (< 0.30 nm), low RMSF (0.05–0.15 nm), compact Rg (1.92–1.98 nm), reduced SASA (142–150 nm2), consistent H-bonds (2–4), and broader FEL basic indicating entropic flexibility.

Conclusion

Magnocurarine emerges as a superior anti-diabetic lead from Zanthoxylum simulans, demonstrating exceptional PPARG binding, pharmacokinetic safety, and dynamic stability over 200 ns validating its therapeutic potential.