Compounds Consisting of Quinazoline, Ibuprofen, and Amino Acids with Cytotoxic and Anti-Inflammatory Effects.
Luis Roberto Garduño-VillavicencioUlises Martínez-OrtegaElizabeth Ortiz-SánchezJosé Manuel Tinajero-RodríguezFrancisco Hernández-LuisPublished in: ChemMedChem (2024)
In this research work, a series of 16 quinazoline derivatives bearing ibuprofen and an amino acid were designed as inhibitors of epidermal growth factor receptor tyrosine kinase domain (EGFR-TKD) and cyclooxygenase-2 (COX-2) with the intention of presenting dual action in their biological behavior. The designed compounds were synthesized and assessed for cytotoxicity on epithelial cancer cells lines (AGS, A-431, MCF-7, MDA-MB-231) and epithelial non-tumorigenic cell line (HaCaT). From this evaluation, derivative 6 was observed to exhibit higher cytotoxic potency (IC 50 ) than gefitinib (reference drug) on three cancer cell lines (0.034 μM in A-431, 2.67 μM in MCF-7, and 3.64 μM in AGS) without showing activity on the non-tumorigenic cell line (>100 μM). Furthermore, assessment of EGFR-TKD inhibition by 6 showed a discreet difference compared to gefitinib. Additionally, 6 was used to conduct an in vivo anti-inflammatory assay using the 12-O-tetradecanoylphorbol-3-acetate (TPA) method, and it was shown to be 5 times more potent than ibuprofen. Molecular dynamics studies of EGFR-TKD revealed interactions between compound 6 and M793. On the other hand, one significant interaction was observed for COX-2, involving S531. The RMSD graph indicated that the ligand remained stable in 50 ns.
Keyphrases
- epidermal growth factor receptor
- tyrosine kinase
- amino acid
- molecular dynamics
- breast cancer cells
- advanced non small cell lung cancer
- anti inflammatory
- density functional theory
- postoperative pain
- papillary thyroid
- high throughput
- small cell lung cancer
- single cell
- squamous cell
- squamous cell carcinoma
- case report
- emergency department
- convolutional neural network
- cell proliferation
- signaling pathway
- young adults
- deep learning
- case control