Bulletin of the Korean Chemical Society

Korean Chemical Society (대한화학회)
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Nonlinear QSAR Study of Xanthone and Curcuminoid Derivatives as α-Glucosidase Inhibitors

  • Saihi, Youcef (Department of Chemistry, Faculty of Sciences, University of Badji Mokhtar) ;
  • Kraim, Khairedine (Department of Chemistry, Faculty of Sciences, University of Badji Mokhtar) ;
  • Ferkous, Fouad (Department of Chemistry, Faculty of Sciences, University of Badji Mokhtar) ;
  • Djeghaba, Zeineddine (Department of Chemistry, Faculty of Sciences, University of Badji Mokhtar) ;
  • Azzouzi, Abdelkader (Department of Chemistry, Faculty of Sciences, University of Djelfa) ;
  • Benouis, Sabrina (Department of Chemistry, Faculty of Sciences, University of Badji Mokhtar)
  • Received : 2012.11.26
  • Accepted : 2013.03.06
  • Published : 2013.06.20
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Abstract

A non linear QSAR model was constructed on a series of 57 xanthone and curcuminoide derivatives as ${\alpha}$-glucosidase inhibitors by back-propagation neural network method. The neural network architecture was optimized to obtain a three-layer neural network, composed of five descriptors, nine hidden neurons and one output neuron. A good predictive determination coefficient was obtained (${R^2}_{Pset}$ = 86.7%), the statistical results being better than those obtained with the same data set using a multiple regression analysis (MLR). As in the MLR model, the descriptor MATS7v weighted by Van der Waals volume was found as the most important independent variable on the ${\alpha}$-glucosidase inhibitory.

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References

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