Computational Exploration and Optimization of 6-Aryl-5-Cyano Thiouracil Scaffolds as Type-II VEGFR-2 Tyrosine Kinase Inhibitors: Insights from Docking, Molecular Dynamics, DFT, and ADMET Studies

Background: This study presents the rationale for the in silico design and computational assessment of a novel set of six aryl 5-cyanothiouracil-based vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors as prospective anticancer agents. The compounds strategically integrate a hinge-binding pyrimidine core, a piperazine linker for alignment with the aspartate-phenylalanine-glycine (DFG) motif, and an oxadiazole–amide pharmacophore to mimic sorafenib’s critical hydrogen bonding within the adenosine triphosphate (ATP) pocket. Methods: Computational evaluation was conducted via molecular docking against VEGFR-2. The structural stability of the leading complex was validated through a 100 ns molecular dynamics (MD) simulation and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding free energy calculations. Density functional theory (DFT) evaluated electronic properties, while absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles were predicted. Results: Docking revealed multiple candidates achieving canonical type II binding modes with scores superior to sorafenib, maintaining essential contacts with Cys919, Glu885, and Asp1046. The MD simulation of the VEGFR-2/compound 10d complex confirmed high structural stability, minimal Root-Mean-Square Deviation (RMSD) fluctuations, and favorable MM-GBSA energies driven by lipophilic interactions. DFT calculations confirmed electronic suitability, with compound 10d showing the narrowest frontier orbital gaps. Predicted ADMET profiles indicated adequate oral absorption, though showing class-wide liabilities for cytochrome P450 (CYP), human Ether-à-go-go-Related Gene (hERG), and hepatotoxicity. Compound 10a displayed the most favorable pharmacokinetic profile. Conclusion: Compounds 10a and 10d were successfully identified as promising lead scaffolds targeting VEGFR-2, providing a robust computational foundation for further experimental validation and optimization.