Introduction: Cancer ranks among the leading causes of death globally. Dysregulation of growth factor receptors like EGFR, through oncogene activation or tumor suppressor loss, underlies aggressive, therapy-resistant malignancies, making EGFR a prime therapeutic target. Method: Computational methods such as molecular docking, molecular dynamics simulations, Density Functional Theory (DFT) calculations, and in silico pharmacokinetic profiling to investigate ligand-target binding interactions were utilized in this study. Drug-like-ness properties were also evaluated based on Lipinski's rule of five. Results: All designed quinazoline derivatives were subjected to in-silico evaluation involving molecular docking, molecular dynamics, DFT, and the (absorption, distribution, metabolism, excretion, and toxicity) ADMET study as EGFR inhibitors. In addition, drug-likeness was determined using the Lipinski rule of five. Among all proposed 4-amino quinazoline derivatives, it was found that all ligands showed binding energy scores in the range of -7.5 to -7.8 kcal/mol. Lower water solubility (logS), which ranged from -3.652 log mol/L to -3.463 log mol/L Discussion: The current study focuses on the in-silico evaluation and molecular prediction of some quinazoline derivatives as EGFR inhibitors. Ligands A1, A3, A4, and A5 showed relatively favorable bioactivity, likeness with one violation as compared to standard drugs included in this computational study, which indicated that A1, A3, A4, and A5 ligands were excellent EGFR inhibitors. Conclusion: These parameters enable the selection of the most promising candidates for synthesis to address EGFR-TK gene mutations and resistance.
Shinde et al. (Tue,) studied this question.