The discovery of potential cyclin A/CDK2 inhibitors: a combination of 3D QSAR pharmacophore modeling, virtual screening, and molecular docking studies

Abstract

Cyclin-dependent kinases are a family of enzymes that regulates the cell cycle process. They have been found to be novel targets for potential anti-cancer drugs. In the present study, a 3D pharmacophore model has been developed for cyclin A/CDK2 from its known inhibitors. The most reliable quantitative HypoGen model (Hypo1) consists of two hydrogen bond acceptors, one hydrogen bond donor and one hydrophobic feature. Hypo1, with a correlation coefficient of 0.98, a root mean square deviation of 0.84, a configuration cost of 16.25 and a cost difference of 102.93, showed a remarkable predictive power and has >90 % probability of representing a true correlation in the activity data. The model was validated using Fisher’s test at 95 % confidence level and test set prediction (r = 0.96). Hypo1 was then employed for virtual screening of Life Chemicals and NCI2003 databases of which multiple conformations were generated for each compound (596,030 compounds, 45,603,414 conformers). Hits were filtered according to the Lipinski, Ghose, and Veber’s rules. Following docking simulations, consensus scoring was used to determine the ligand poses that interact best with the protein binding site and to reduce number of false positives. 11 hits were ultimately selected as potent candidate leads. This work may help in the identification or design of novel anti-cancer drugs based on hits determined. The pharmacophore model obtained and validated in this study can be used as a three-dimensional query in searches for CDK2 inhibitors in additional compound databases.