ArticleFrontiers in pharmacology2024
Deciphering quinazoline derivatives' interactions with EGFR: a computational quest for advanced cancer therapy through 3D-QSAR, virtual screening, and MD simulations.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Novel pyridine-heterocycle hybrids: synthesisRSC advances · 2026Article
- A case study of the application of AI to early stage drug discovery.Scientific reports · 2025Article
- Synthesis, Molecular Docking, and Biological Studies of New Naphthalene-1,4-Dione-Linked Phenylpiperazine and Thioether.Chemistry & biodiversity · 2025Article
- Conceptual density functional theory in drug discovery: an overview.Journal of molecular modeling · 2025Review
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Authors and funding
6 authors.
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Abstract
Introduction: The epidermal growth factor receptor (EGFR) presents a crucial target for combatting cancer mortality. Methods: This study employs a suite of computational techniques, including 3D-QSAR, ligand-based virtual screening, molecular docking, fingerprinting analysis, ADME, and DFT-based analyses (MESP, HOMO, LUMO), supplemented by molecular dynamics simulations and MMGB/PBSA free energy calculations, to explore the binding dynamics of quinazoline derivatives with EGFR. With strong q2 and r2 values from CoMFA and CoMSIA models, our 3D- QSAR models reliably predict EGFR inhibitors' efficacy. Results and Discussion: Utilizing a potent model compound as a reference, an E-pharmacophore model was developed to sift through the eMolecules database, identifying 19 virtual screening hits based on ShapeTanimoto, ColourTanimoto, and TanimotoCombo scores. These hits, assessed via 3D- QSAR, showed pIC
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