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Book of Abstracts: Albany 2009

category image Albany 2009
Conversation 16
June 16-20 2009
© Adenine Press (2008)

CoMFA and CoMSIA ? A 3D Quantitative Structure Activity Relationship Prediction on Benzodipyrazoles Series as Cyclin Dependent Kinase 2 (CDK2) Inhibitors

Protein phosphorylation and dephosphorylation are important processes in the control of protein functions. Phosphorylation occurs on serine, threonine, and tyrosine residues and is catalyzed by protein kinases whose number transcends 800 in the human genome. Because of the importance of protein phosphorylation as a main post-translational mechanism used by cells to regulate enzymes and other proteins and the association of many maladies with its aberrations, kinases have increasingly become important targets and the hunt for kinase inhibitors has been intensified and attracted a great attention in drug discovery over the years. Cyclin dependent kinases have appeared as important drug target over the years with a multitude of therapeutic potentials. Cyclin dependent kinase 2 (CDK2) belongs to this class of protein kinases and plays a key role in the cell cycle regulation. With the intention of designing compounds with enhanced inhibitory potencies against CDK2, the 3D-QSAR CoMFA and CoMSIA study on benzodipyrazoles series is presented here.

Sanjeev K. Singh1,*
Sunil Tripathi1
Nigus Dessalew2

1Center of Excellence in Bioinformatics
School of Biotechnology
Madurai Kamaraj University
Madurai 625 021, Tamil Nadu, India
2Department of Pharmaceutical Chemistry
School of Pharmacy Addis Ababa University
P.O.Box 1176
Addis Ababa, Ethiopia
*Phone (Office): 91-452-2459141
Fax: 91-452-2459105
EMail: sanjeev@mrna.tn.nic.in
skysanjeev@gmail.com


The developed models showed a strong correlative and predictive capability having a cross validated correlation co-efficient of (r2cv) 0.699 for CoMFA and 0.794 for CoMSIA models. A very good conventional and predicted correlation co-efficient were also obtained: CoMFA (r2ncv, r2pred: 0.883, 0.754), CoMSIA (0.937, 0.815). The models were found to be statistically robust and are expected to be of an aid to design and/or prioritize drug likes for synthesis.

References and Footnotes
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  2. M. Rarey, B. Kramer, T. Lengauer, G. Klebe. J Mol Biol 261, 470-489 (1996).
  3. M. J. S. Dewar, E. G. Zoebisch, E. F. Healy, J. J. P Stewart. J Am Chem Soc 107, 3902-3909 (1985).
  4. R. D'Alessio, A. Bargiotti, S. Metz, M. G. Brasca, A. Cameron, A. Ermoli, A. Marsiglio, P. Polucci, F. Roletto, M. Tibolla, M. L. Vazquez, A. Vulpetti, P. Pevarello. Bioorg Med Chem Lett 15, 1315-1319 (2005).