Effect of the electronic and physicochemical parameters on the carcinogenesis activity of some sulfa drugs using QSAR analysis based on genetic-MLR and genetic-PLS [An article from: Chemosphere]
Book Details
PublisherElsevier
ISBN / ASINB000PDYP7G
ISBN-13978B000PDYP71
MarketplaceUnited Kingdom 🇬🇧
Description
This digital document is a journal article from Chemosphere, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
A quantitative structure activity relationship study has been applied to a data set of 18 sulfa drugs with carcinogenesis activity. Semi-empirical quantum chemical calculation (AM1 method) was used to find the optimum 3D geometry of the studied molecules. Two types of molecular descriptors including chemical and electronic was used to derive a quantitative relation between the carcinogenesis activity and structural properties. Two multi-parametric equations with good statistical qualities were obtained using genetic algorithms multiple linear regression (GA-MLR) methods. In addition, genetic algorithm-partial least squares (GA-PLS) regression was used to model the structure-activity relationships, more accurately. The results confirmed the superiority of the results obtained by GA-PLS relative to GA-MLR. The significant effect of the HOMO energy on the carcinogenic activity was explained in the context of the shape of this orbital.
Description:
A quantitative structure activity relationship study has been applied to a data set of 18 sulfa drugs with carcinogenesis activity. Semi-empirical quantum chemical calculation (AM1 method) was used to find the optimum 3D geometry of the studied molecules. Two types of molecular descriptors including chemical and electronic was used to derive a quantitative relation between the carcinogenesis activity and structural properties. Two multi-parametric equations with good statistical qualities were obtained using genetic algorithms multiple linear regression (GA-MLR) methods. In addition, genetic algorithm-partial least squares (GA-PLS) regression was used to model the structure-activity relationships, more accurately. The results confirmed the superiority of the results obtained by GA-PLS relative to GA-MLR. The significant effect of the HOMO energy on the carcinogenic activity was explained in the context of the shape of this orbital.
