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Computational Evaluation of Carbazole–Chalcone Urea and Thiourea Derivatives Against EGFR: Molecular Docking, Pharmacokinetic Profiling, Target Prediction, and Molecular Dynamics Simulation

Sep 2026 · Molecules · Vol 31 · 0 citations · 60 references
Medicine

TL;DR

Overall, 5f was computationally prioritized based on its favorable predicted EGFR interactions and sustained association over the investigated simulation timescale, while its physicochemical and pharmacokinetic limitations indicate the need for further structural optimization and experimental validation.

Abstract

A series of previously synthesized carbazole-based urea and thiourea derivatives (5a–5i) was subjected to an integrated computational investigation of their predicted interactions with epidermal growth factor receptor (EGFR) (PDB ID: 1M17) and their pharmacokinetic and dynamic behavior. Molecular docking yielded scores of −9.0 to −13.5 kcal/mol, with 5f showing the most favorable value (−13.5 kcal/mol). Redocking of the co-crystallized ligand AQ4 yielded an RMSD of 1.65 Å, supporting the docking protocol. SwissADME analysis revealed high lipophilicity, low predicted gastrointestinal absorption, and poor aqueous solubility across the series. Compound 5f showed a Consensus LogP of 7.05, two Lipinski violations, a bioavailability score of 0.17, and predicted P-glycoprotein substrate behavior. SwissTargetPrediction identified EGFR among the predicted targets of 5f, providing complementary computational rationale for its investigation. Three independent 100 ns molecular dynamics simulations of the EGFR–5f complex showed limited protein backbone deviations (mean RMSD: 0.217–0.282 nm), maintained overall compactness (mean Rg: 2.005–2.040 nm), and continued protein–ligand association despite replicate-dependent conformational sampling. Overall, 5f was computationally prioritized based on its favorable predicted EGFR interactions and sustained association over the investigated simulation timescale, while its physicochemical and pharmacokinetic limitations indicate the need for further structural optimization and experimental validation.

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