International Journal of Chemical Studies
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P-ISSN: 2349-8528, E-ISSN: 2321-4902   |   Impact Factor: GIF: 0.565

Vol. 4, Issue 1 (2016)

Molecular modeling studies and structure based virtual screening for identification of potent ligands for Cb2 receptor


Author(s): Shikha Rajput, Rajesh Kumari, B. N. Mishra

Abstract: The CB2 receptor is an attractive drug target for treatment of pain and inflammation. CB2 receptor is member of rhodopsin-like family of seven-transmembrane G-protein-coupled receptor. In this work, three dimensional structure model of CB2 receptor in Homo sapiens was determined based on template sequence (PDB code: 2KS9) by comparative homology modeling program MODELLER9v10. Selection of template was done through mGenTHREADER tool in MODELLER, which has 13.1% sequence identity with CB2 receptor. The computed model’s energy was minimized and validated using PROCHECK and ERRAT to obtain a stable model structure. Stable model was further used for virtual screening against N-1 alkyl chain length of cannabimimetic indoles through molecular docking studies using AutoDock 3.05. The docked complexes were validated and enumerated based on the AutoDock Scoring function to pick out the best agonist based on docked Energy. Thus from the entire 30 compounds which were Docked, we got best 3 of them with optimal docked energy as JHW-156 (Docking Energy -13.26 kcal/mol), JWH-122(Docking Energy:-12.53 kcal/mol) and JWH-146 (Docking Energy: -12.46 kcal/mol). Further the three best-docked complexes were analyzed through Python Molecular Viewer software for their interaction studies. Thus from the Complex scoring and binding ability its deciphered that these ligands could be used as interesting leads for the development of new active CB2 ligands. QSAR Properties of all these compounds were calculated, which shows these compounds could be used as interesting leads for development of new active CB2 ligands

Pages: 24-36  |  1703 Views  68 Downloads

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How to cite this article:
Shikha Rajput, Rajesh Kumari, B. N. Mishra. Molecular modeling studies and structure based virtual screening for identification of potent ligands for Cb2 receptor. Int J Chem Stud 2016;4(1):24-36.
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