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Bulletin of the Korean Chemical Society (BKCS)

ISSN 0253-2964(Print)
ISSN 1229-5949(Online)
Volume 34, Number 6
BKCSDE 34(6)
June 20, 2013 

Nonlinear QSAR Study of Xanthone and Curcuminoid Derivatives as α-Glucosidase Inhibitors
Youcef Saihi*, Khairedine Kraim, Fouad Ferkous, Zeineddine Djeghaba, Abdelkader Azzouzi, Sabrina Benouis
α-Glucosidase, Inhibitors, Xanthone-curcuminoide derivatives, QSAR, Artificial neural networks
A non linear QSAR model was constructed on a series of 57 xanthone and curcuminoide derivatives as α- 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 (R2 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 α-glucosidase inhibitory.
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