An efficient tool for identifying inhibitors based on 3D-QSAR and docking using feature-shape pharmacophore of biologically active conformation--a case study with CDK2/cyclinA.

This study proposes a fast and efficient approach for identifying novel inhibitors when the biologically active conformation of an inhibitor is known. The present study was carried out with CDK2/CyclinA inhibitors. The co-crystal structure of the most active ligand with CDK2/CyclinA was converted into a feature-shape query. This query served three purposes (i) alignment of molecules to generate 3D-QSAR model, (ii) rigid docking to the active site using GOLD, (iii) extracting hits from databases. A statistically valid 3D-QSAR (r(2)=0.867, q(2)=0.887) with good external set prediction (r(pred)(2)=0.890) was obtained. The docked poses were analyzed based on their interaction with hinge region (Glu81-Leu83) of CDK2. A reasonably good consensus score was generated using 11 scoring functions. The developed model was then successfully used to identify potential leads for CDK2/CyclinA inhibitors.