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Molecular modelling and QSAR analysis of some structurally diverse N-type calcium channel blockers

Publication Type : Journal Article

Thematic Areas : Nanosciences and Molecular Medicine

Publisher : Journal of Molecular Modeling

Source : Journal of Molecular Modeling, Volume 16, Number 4, p.629–644 (2010)

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Campus : Kochi

School : Center for Nanosciences

Center : Amrita Center for Nanosciences and Molecular Medicine Move, Nanosciences

Department : Nanosciences and Molecular Medicine

Year : 2010

Abstract : A quantitative structure–activity relationship (QSAR) analysis was performed on a data set of 104 molecules showing N-type calcium channel blocking activity. Several types of descriptors, including electrotopological, structural, thermodynamics and ADMET, were used to derive a quantitative relationship between N-type calcium channel blocking activity and structural properties. The genetic algorithm-based genetic function approximation (GFA) method of variable selection was used to generate the 2D-QSAR model. The model was established on a training set of 83 molecules, and validated by a test set of 21 molecules. The model was developed using five information-rich descriptors–-Atype{_}C{_}24, Atype{_}N{_}68, Rotlbonds, S{_}sssN, and ADME{_}Solubility–-playing an important role in determining N-type calcium channel blocking activity. For the best QSAR model (model 4), the statistics were r 2þinspace}=þinspace}0.798; q 2þinspace}=þinspace}0.769; nþinspace}=þinspace}83 for the training set. This model was further validated using the leave-one-out (LOO) cross-validation approach, Fischer statistics (F), Y-randomisation test, and predictions based on the test data set. The resulting descriptors produced by QSAR model 4 were used to identify physico-chemical features relevant to N-type calcium channel blocking activity.

Cite this Research Publication : J. Mungalpara, Pandey, A., Jain, V., and Dr. Gopi Mohan C., “Molecular modelling and QSAR analysis of some structurally diverse N-type calcium channel blockers”, Journal of Molecular Modeling, vol. 16, pp. 629–644, 2010.

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