Title: 3D QSAR CoMFA/CoMSIA and docking studies on azole dione derivatives, as anti-cancer inhibitors

Authors: Rohith Kumar Anugolu; Shravan Kumar Gunda; Shaik Mahmood

Addresses: Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India ' Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India ' Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India

Abstract: Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on a series of 103 azole dione derivatives, as selective anti-cancer inhibitors. The atom and shape based root mean square alignment yielded the best predictive CoMFA model q² = 0.923, r² = 0.980, when compared with the CoMSIA model. Docking studies were employed to position the inhibitors into active site of Crystal Structure of Delta (4)-3-ketosteroid 5-beta-reductase (PDB id: 3BUR). Results that indicate steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor substituents play a significant role in design novel, potent and selective anti-cancer activity of the compounds.

Keywords: CoMFA; comparative molecular field analysis; CoMSIA; comparative molecular similarity indices analysis; 3D-QSAR; azole dione; FlexX; docking; anti-cancer inhibitors; cancer cells; cell proliferation; cell growth.

DOI: 10.1504/IJCBDD.2012.048280

International Journal of Computational Biology and Drug Design, 2012 Vol.5 No.2, pp.111 - 136

Received: 25 Aug 2011
Accepted: 29 Jan 2012

Published online: 30 Jul 2012 *

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