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Book of Abstracts: Albany 2011

category image Albany 2011
Conversation 17
June 14-18 2011
©Adenine Press (2010)

Integrating CADD Methodologies for the Design of Novel COMT Inhibitors

Catechol-O-methyltransferase (COMT) catalyzes the methylation of catecholamines, including neurotransmitters like dopamine, epinephrine and norepinephrine, leading to their degradation. COMT has been a subject of study as it has implications in numerous neurological disorders like Parkinson's disease (PD), depression, schizophrenia and several mood disorders (1).

Availability of crystal structure of human soluble-COMT (S-COMT) (2) has helped us in modeling of membrane-bound COMT (MB-COMT) and thus paved the way for the discovery of a novel lead molecule using integrated computer aided drug design (CADD) methodologies (3-8). Combination of both structure-based (molecular docking, de novo ligand design) and ligand-based (QSAR, pharmacophore modeling) approaches that models separate facets of the natural system, will allow us to use all available information to screen a chemical database in a more objective and meaningful way.

In this study, we examine the structure of MB-COMT refined by molecular dynamics simulations. We have also conducted detailed computational modeling studies to understand the molecular mechanisms for the catalytic behavior of human MB-COMT with respect to AdoMet (the methyl donor) and various substrates. We have also carried out docking studies with known COMT inhibitors (5 ,9) to understand physico-chemical interactions in the protein-ligand complex in order to identify the optimal binding geometry. The virtual screening procedure has been implemented in a docking pipeline that performs a step-by-step, target specific, filtering approach for data reduction to discover inhibitors with novel scaffolds. We hope that the combination of energy terms from structure-based docking studies with the chemical knowledge of a ligand-based pharmacophore search will leverage the strengths of both approaches to produce a good diversity of active molecules. Results of these studies will be discussed and presented.

References

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  4. S. Y. Yang, Drug Discov. Today 15, 444-50 (2010).
  5. H. C. Guldberg, C. A. Marsden, Pharmacol. Rev. 27, 135–206 (1975).
  6. A. Kaur Kahlon, S. Roy, A. Sharma, J Biomol Struct Dyn 28, 201-210 (2010).
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  8. T. T. Chang, H. J. Huang, K. J. Lee, H. W. Yu, H. Y. Chen, F. J. Tsai, M. F. Sun, C. Y. C. Chen, J Biomol Struct Dyn 26, 309-321 (2009).
  9. M. J. Bonifacio, P. N. Palma, L. Almeida, P. S, da Silva, CNS Drug Rev. 13, 352-379 (2007).

Nidhi Jatana
Aditya Sharma
N. Latha*

Bioinformatics Infrastructure Facility,
Sri Venkateswara College
University of Delhi,
Benito Juarez Road,
Dhaula Kuan,
New Delhi 110021, India.


ph: +91 11 24111742,
fx: +91 11 24118535
Email: lata@bic-svc.ac.in