Book of Abstracts: Albany 2011
June 14-18 2011
©Adenine Press (2010)
Virtual Screening and Theoretical Activity Prediction of Idenopyrazole Derivatives of CDK2 Inhibitors: A QPLD and MM-GBSA Approach
Cyclin-dependent kinases (CDKs) are core components of the cell cycle machinery that govern the transition between phases during cell cycle progression. Genes involved in cell cycle are frequently mutated in human cancer and deregulated CDK activity represents a characteristic of malignancy. Among them CDK2 is essential in the mammalian cell cycle and is required to complete G1 and to activate the S phase (1). Lately there have been successful implementation of computer-aided drug design to develop new therapeutics (2-5), and we have employed these designs to develop anticancer drugs targetting CDK2. In this study we have taken 119 compounds of idenopyrazole derivatives, with in vitro biological activity data for CDK2 inhibition (6). Here, we used Virtual screening protocol to obtain effective idenopyrazole derivatives of CDK2 via VS workflow of Schrodinger package, ADME and Lipinski- filter options. 17 top-ranked molecules obtained from this screening were subjected for Molecular docking with GLIDE module and Quantam Polarized Ligand Docking (QPLD) using QPLD module of Schrodinger package (7, 8).
The top-ranked 17 compounds were post-scored using molecular mechanics and continuum solvation (MM-GBSA) (9, 10). The validity of the virtual screening protocol was supported by (i) Testing of the MM-GBSA procedure (ii) Agreement between predicted and crystallographic binding poses (iii) Recovery and identification of top-scoring potent idenopyrazole derivatives. With these combined approach of ADME, Docking, QPLD and MM-GBSA, we found that compound 13, 24, 25 and 46 having properties essential for effective drugs so biological activity testing can be carried out on selected leads, for getting effective and potent anticancer drug.
Figure: Compound 48 showing interaction with Glu12, Asn132 and Asp145 of CDK2.
Sanjeev Kumar Singh
Department of Bioinformatics