Integrated Molecular Docking, Molecular Dynamics Simulation, and MM-PBSA Free Energy Analysis of Novel Small-Molecule Inhibitors Targeting Epidermal Growth Factor Receptor (EGFR) in Non-Small Cell Lung Cancer

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Authors: Rathnayaka Mudiyanselage Isuru Gayashan Wijiesinghe
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Abstract

Non-small cell lung cancer (NSCLC) accounts for approximately 85% of lung cancer cases worldwide and remains a leading cause of cancer-related mortality. Epidermal Growth Factor Receptor (EGFR) plays a central role in tumor proliferation, survival, angiogenesis, and metastasis, making it a critical therapeutic target. Although several EGFR tyrosine kinase inhibitors (TKIs) are clinically available, acquired resistance and dose-limiting toxicities continue to challenge long-term treatment efficacy. This doctoral study employed an integrated computational drug discovery pipeline combining molecular docking, molecular dynamics (MD) simulation, and MM-PBSA binding free energy calculations to identify novel small-molecule EGFR inhibitors with improved stability and pharmacological profiles. Selected compounds were docked into the EGFR ATP-binding domain using AutoDock Vina. Top-ranked complexes were subjected to 100 ns MD simulations using GROMACS to evaluate conformational stability. Binding free energies were calculated via MM-PBSA, and pharmacokinetic properties were assessed using SwissADME and pkCSM. Docking results identified multiple compounds with binding affinities ranging from -9.2 to -11.0 kcal/mol. MD simulations demonstrated stable protein?ligand complexes, supported by low RMSD fluctuations and consistent hydrogen bonding within the catalytic pocket. MM-PBSA analysis confirmed favorable binding energies, correlating with persistent interactions involving Met793, Leu718, and Asp855. ADMET profiling revealed acceptable oral bioavailability and low predicted toxicity for prioritized leads. The integrated approach identified promising EGFR inhibitors exhibiting enhanced binding stability and drug-like characteristics. These findings provide valuable insight for lead optimization and support further experimental validation toward targeted NSCLC therapy development.

Fields of Study & Subjects

Computational Drug Discovery Methods Lung Cancer Treatments and Mutations Synthesis and Characterization of Heterocyclic Compounds

Publication details

Journal / source
International Journal of Science and Research (IJSR)
Pages
223–226
Publication date
7 February 2026