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http://dx.doi.org/10.5012/bkcs.2010.31.10.2761

Ligand Based CoMFA, CoMSIA and HQSAR Analysis of CCR5 Antagonists  

Gadhe, Changdev G. (Department of Bio-New Drug Development, College of Medicine, Chosun University)
Lee, Sung-Haeng (Department of Bio-New Drug Development, College of Medicine, Chosun University)
Madhavan, Thirumurthy (Department of Bio-New Drug Development, College of Medicine, Chosun University)
Kothandan, Gugan (Department of Bio-New Drug Development, College of Medicine, Chosun University)
Choi, Du-Bok (Biotechnology Lab, BK Company R&D Center)
Cho, Seung-Joo (Department of Bio-New Drug Development, College of Medicine, Chosun University)
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Abstract
In this study, we have developed QSAR models for a series of 38 piperidine-4-carboxamide CCR5 antagonists using CoMFA, CoMSIA and HQSAR methods. Developed models showed good statistics in terms of $q^2$ and $r^2$ values. Best predictions obtained with standard CoMFA model ($r^2$ = 0.888, $q^2$ = 0.651) and combined CoMSIA model ($r^2$ = 0.892, $q^2$ = 0.665) with electrostatics and H-bond acceptor parameter. The validity of developed models was assessed by test set of 9 compounds, which showed good predictive correlation coefficient for CoMFA (0.804) and CoMSIA (0.844). Bootstrapped analysis showed statistically significant and robust CoMFA (0.968) and CoMSIA (0.936) models. Best HQSAR model was obtained with a $q^2$ of 0.662 and $r^2$ of 0.936 using atom, connection, hydrogen, donor and acceptor as parameters and fragment size (7-10) with optimum number of 6 components. Predictive power of developed HQSAR model was proved by test set and it was found to be 0.728.
Keywords
CCR5; QSAR; CoMFA; CoMSIA; HQSAR;
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