<![CDATA[Lung cancer is one of the leading causes of cancer-related death worldwide and is often associated with overexpression of the Epidermal Growth Factor Receptor (EGFR), making the development of EGFR inhibitors an important therapeutic strategy. This study aims to evaluate the potential of coumarin derivatives from Daphne mezereum as EGFR inhibitor candidates in lung cancer therapy using an in silico approach. This study used computational methods, including molecular docking to analyze binding affinity and ligand–protein interactions, drug-likeness evaluation based on Lipinski’s rule, and ADMET analysis to predict pharmacokinetic properties and toxicity. The results show that all compounds had RMSD values ≤ 2 Å, with a re-docking value of 1.1614 Å, indicating the validity of the method. Compound 2 showed the highest binding affinity and optimal interaction with the Met769 residue in EGFR, which plays a role in lung cancer cell proliferation, but it did not meet Lipinski’s criteria and had a less optimal ADMET profile. Conversely, compound 3 (umbelliferone) showed a balance between affinity, drug-likeness, and a good ADMET profile, including high absorption and non-toxic properties. The conclusion of this study emphasizes that compound 3 is more prospective as a lung cancer drug candidate, while compound 2 (7-hydroxycoumarin-5,8-di-β-D-glucopyranoside) has potential as a lead compound for further optimization. These findings contribute to the development of EGFR-targeted therapy based on coumarin derivatives and emphasize the importance of computational approaches in efficient and rational drug design.]]>
