Computational Screening of Indole Metabolites Targeting EGFR Wild‐Type and Mutant Proteins Using Molecular Docking and Molecular Dynamics Simulations

The development of novel anticancer agents with improved efficacy and minimized side effects remains a key challenge in modern drug discovery. With the aim of finding new anticancer leads, five indole metabolites were selected through a multi‐level screening procedure from the KNApSAcK core database and were analyzed through a computational framework. Density functional theory calculations at B3LYP/6‐311++G(d,p) level were performed. Molecular docking studies were carried out against epidermal growth factor receptor targets, including wild‐type (PDB: 2J6M), T790M mutant (PDB: 5XGM & 5XDK), and L858R mutant (PDB: 2ITT). Among the selected compounds, 1‐DL‐(indole‐3‐acetyl)‐myo‐inositol (M1) showed strong binding affinity toward all selected proteins. The obtained binding affinity values of M1 are −8.0, −6.9, −7.1, and −7.7 kcal/mol with proteins 2J6M, 5XGM, 5XDK, and 2ITT, respectively. A 200 ns molecular dynamics simulation was performed to evaluate the stability of the docked complexes. The results show that the M1‐2J6M complex outperformed the other complexes and maintained structural stability throughout the simulation. The formation of hydrogen bonds indicates the stability of the protein‐ligand complex. Further, ADMET screening was also conducted. The results indicate that the selected indole metabolites, particularly M1, possess favorable outcomes, supporting their potential as lead compounds for further development in anticancer therapy.