3D-QSAR-Assisted Drug Design: Identification of a Potent Quinazoline-Based Aurora Kinase Inhibitor

We describe the 3D-QSAR-assisted design of an Aurora kinaseA inhibitor with improved physicochemical properties, invitro activity, and invivo pharmacokinetic profiles over those of the initial lead. Three different 3D-QSAR models were built and validated by using a set of 66 pyrazole (ModelI) and furanopyrimidine (ModelII) compounds with IC₅₀ values toward Aurora kinaseA ranging from 33nM to 10.5μM. The best 3D-QSAR model, ModelIII, constructed with 24 training set compounds from both series, showed robustness (r²_CV=0.54 and 0.52 for CoMFA and CoMSIA, respectively) and superior predictive capacity for 42 test set compounds (R²_pred=0.52 and 0.67, CoMFA and CoMSIA). Superimposition of CoMFA and CoMSIA ModelIII over the crystal structure of Aurora kinaseA suggests the potential to improve the activity of the ligands by decreasing the steric clash with Val147 and Leu139 and by increasing hydrophobic contact with Leu139 and Gly216 residues in the solvent-exposed region of the enzyme. Based on these suggestions, the rational redesign of furanopyrimidine 24 (clogP=7.41; AuroraA IC₅₀=43nM; HCT-116 IC₅₀=400nM) led to the identification of quinazoline 67 (clogP=5.28; AuroraA IC₅₀=25nM; HCT-116 IC₅₀=23nM). Rat invivo pharmacokinetic studies showed that 67 has better systemic exposure after i.v. administration than 24, and holds potential for further development.