In silico identification of benzamide-based aryl halides as EGFR inhibitors: multi-ligand ADMET, pharmacophore mapping, and target prediction

Cancer is one of the greatest global health challenges, with specific costs of US$25 trillion by 2050, including treatment and socioeconomic impacts. The epidermal growth factor receptor (EGFR), a central tyrosine kinase, is a key target for anticancer therapies. The halogenated-benzamides scaffold was chosen due to its reported action among clinical EGFR inhibitors, favoring its binding in hydrophobic pockets in the protein. To characterize the pharmacokinetics of 24 halogenated-benzamides, a multiparametric optimization was performed using the open-source software DataWarrior for absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, while EGFR inhibitory activity was conducted through ligand-based target prediction, which was supported by molecular docking simulations using AutoDockVina software, and Normal Mode Analysis (NMA)-based molecular dynamics simulation. AB1 and AB4 stand out as lead compounds due to high intestinal absorption (>95%) and apparent permeability (P app > 1.0 × 10 -5 cm/s) compatible with high pharmacological potential. Target prediction revealed a strong association with EGFR (392 and 395 similar compounds). Molecular docking simulations identified van der Waals interactions with residues PHE-723 and VAL-726, strongly influenced by the halogen-substituted ring of the ligands, with affinity energies close to clinical drugs (–6.7 to –6.75 kcal/mol). Molecular dynamics showed that AB1 can cause a conformational deformation in EGFR similarly to Gefitinib, indicating a promising antiproliferative effect. The results positioning them as promising candidates for anticancer therapies and highlighting the practicality of in silico approaches in the early screening of new drugs.