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Current Topics in Biochemical Research   Volumes    Volume 17 
Modeling of fungicide activity of trifluoromethyl-substituted 1,2,4-triazoles using PLS, ANN and SVM
Simona Funar-Timofei, Daniela Ionescu, Takahiro Suzuki
Pages: 45 - 55
Number of pages: 11
Current Topics in Biochemical Research
Volume 17 

Copyright © 2016 Research Trends. All rights reserved

1,2,4-triazole derivatives have a wide spectrum of biological activities, including anti-inflammatory, antiviral, analgesic, antimicrobial, anticonvulsant, anticancer, antioxidant and antidepressant. In this study, quantitative structure-activity relationships (QSAR) of trifluoromethyl-substituted 1,2,4-triazole derivatives with fungicidal activity against Fusarium oxysporum f. sp. cucumerinum were investigated by employing modern modeling approaches. In a previous work two types of E and Z isomers were found and several molecular descriptors were calculated from their minimum energy conformations. In this study, these descriptors were correlated with the experimental fungicide relative inhibition rate using artificial neural networks (ANNs) and support vector machine (SVM) methods. Partial least squares (PLS) calculations were also performed for the same sets. The predictive ability of these models was validated by several criteria using an external set of five out of eighteen compounds. Best results were obtained by means of the SVM model for Z isomers, which could be used for the prediction of new fungicides with higher activity.
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