@article{Zahouily:2006aa,
	Abstract = {Quantitative structure-activity antimalarial relationships have been studied for 63 analogues of 2-aziridinyl and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives by means of multiple linear regression (MLR) and artificial neural networks (ANN). The antimalarial activity [-log(IC(50)x10(6))] of the compounds studied were well correlated with descriptors encoding the chemical structure. Using the pertinent descriptors revealed by a stepwise procedure in the multiple linear regression technique, a correlation coefficient of 0.9394 (s=0.2121) for the training set was obtained for the ANN model in a [3-5-1] configuration. The results show that the antimalarial activity of 2-aziridinyl and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives is strongly dependent on hydrophobic character, hydrogen-bond acceptors and also steric factors of the substituents.},
	Author = {Zahouily, M and Lazar, M and Elmakssoudi, A and Rakik, J and Elaychi, S and Rayadh, A},
	Date-Added = {2008-04-28 11:56:59 -0400},
	Date-Modified = {2009-04-06 16:12:34 -0400},
	Doi = {10.1007/s00894-005-0059-x},
	Journal = {J.~Mol.~Model.},
	Keywords = {2d; qsar; antimalarial; pertinent descriptors; MLR; neural network regression},
	Pages = {398--405},
	Timescited = {0},
	Title = {{QSAR} for Anti-Malarial Activity of 2-Aziridinyl and 2,3-Bis(Aziridinyl)-1,4-Naphthoquinonyl Sulfonate and Acylate Derivatives},
	Volume = {12},
	Year = {2006},
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	Bdsk-Url-1 = {http://dx.doi.org/10.1007/s00894-005-0059-x}}