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<p><i>Datura metel</i> L., a well-known herb in traditional Ayurvedic medicine, has shown promising anti-cancer activity in prior studies, though the specific active compounds and their mechanisms remain unclear. This study investigates the molecular basis of its therapeutic potential against lung cancer using an integrated in silico approach. We firstly employed compound-target interaction networks using network pharmacology, identifying AKT1 and EGFR as key targets via the Cyto-Hubba plugin in Cytoscape. Molecular docking was then performed, which revealed strong binding of two compounds to AKT1 and fourteen to EGFR. Rigorous filtering based on molecular interactions and ADMET profiles narrowed the candidates to four promising phytochemicals. These were subjected to further validation through 100&#xa0;ns molecular dynamics simulations, MMPBSA binding free energy calculations, and DFT (HOMO–LUMO) analyses. The computational analyses consistently indicate that 12-Deoxywithastramonolide, Withametelin E, Withametelin D, and Withametelin C demonstrate stable binding, favorable energetics, and optimal chemical properties as potential EGFR inhibitors. These findings shed light on the molecular mechanisms underlying <i>D. metel</i>’s anti-lung cancer potential and identify several promising phytochemical candidates. However, these conclusions are based on computational data; in vitro and in vivo studies are essential next steps to validate their therapeutic efficacy.</p>

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Identification of Datura metel phytochemicals as potential EGFR inhibitors in lung cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月17日

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  • Pankaja Pandey,
  • Priyanka Joshi,
  • Shilpi Rawat,
  • Aamal A. Al-Mutairi,
  • Gizachew Alene Alem,
  • Emad Rashad Sindi,
  • Subhash Chandra,
  • Magdi E. A. Zaki

摘要

Datura metel L., a well-known herb in traditional Ayurvedic medicine, has shown promising anti-cancer activity in prior studies, though the specific active compounds and their mechanisms remain unclear. This study investigates the molecular basis of its therapeutic potential against lung cancer using an integrated in silico approach. We firstly employed compound-target interaction networks using network pharmacology, identifying AKT1 and EGFR as key targets via the Cyto-Hubba plugin in Cytoscape. Molecular docking was then performed, which revealed strong binding of two compounds to AKT1 and fourteen to EGFR. Rigorous filtering based on molecular interactions and ADMET profiles narrowed the candidates to four promising phytochemicals. These were subjected to further validation through 100 ns molecular dynamics simulations, MMPBSA binding free energy calculations, and DFT (HOMO–LUMO) analyses. The computational analyses consistently indicate that 12-Deoxywithastramonolide, Withametelin E, Withametelin D, and Withametelin C demonstrate stable binding, favorable energetics, and optimal chemical properties as potential EGFR inhibitors. These findings shed light on the molecular mechanisms underlying D. metel’s anti-lung cancer potential and identify several promising phytochemical candidates. However, these conclusions are based on computational data; in vitro and in vivo studies are essential next steps to validate their therapeutic efficacy.