In Silico Study of Micheliolide Derivatives as Potential Non-Small Cell Lung Cancer Drugs Targeting the Epidermal Growth Factor Receptor.
To identify Micheliolide-based derivatives with favorable drug-like properties and inhibitory potential against the epidermal growth factor receptor (EGFR) using an integrated in silico approach.
Micheliolide derivatives were evaluated for pharmacokinetic and toxicity profiles using SwissADME and ADMET-AI, and anticancer-related activity was predicted using PASS Online. Molecular docking was performed with AutoDock Vina using erlotinib as a reference ligand. The top-ranked compounds were further examined through 50 ns molecular dynamics simulations to assess complex stability.
All derivatives fulfilled Lipinski's criteria. Several compounds demonstrated favorable predicted bioavailability and anticancer probability. Docking analysis identified compound 10 as having the strongest binding affinity, followed by compounds 19 and 3, with all three occupying the same EGFR binding pocket as erlotinib. Molecular dynamics simulations showed that compounds 3 and 19 formed more stable complexes, maintaining root-mean-square deviation values of approximately 1-3 Å throughout the trajectory, whereas compound 10 displayed greater fluctuations and reduced stability.
Compounds 3 and 19 exhibited the most favorable combination of binding affinity, dynamic stability, and predicted safety profiles, highlighting their potential as lead candidates for further development as EGFR inhibitors in NSCLC.
Micheliolide derivatives were evaluated for pharmacokinetic and toxicity profiles using SwissADME and ADMET-AI, and anticancer-related activity was predicted using PASS Online. Molecular docking was performed with AutoDock Vina using erlotinib as a reference ligand. The top-ranked compounds were further examined through 50 ns molecular dynamics simulations to assess complex stability.
All derivatives fulfilled Lipinski's criteria. Several compounds demonstrated favorable predicted bioavailability and anticancer probability. Docking analysis identified compound 10 as having the strongest binding affinity, followed by compounds 19 and 3, with all three occupying the same EGFR binding pocket as erlotinib. Molecular dynamics simulations showed that compounds 3 and 19 formed more stable complexes, maintaining root-mean-square deviation values of approximately 1-3 Å throughout the trajectory, whereas compound 10 displayed greater fluctuations and reduced stability.
Compounds 3 and 19 exhibited the most favorable combination of binding affinity, dynamic stability, and predicted safety profiles, highlighting their potential as lead candidates for further development as EGFR inhibitors in NSCLC.
Authors
Halim Halim, Harris Harris, Nata Nata, Muchlis Muchlis, Darmadi Darmadi, Herikurniawan Herikurniawan, Rumende Rumende
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