QSAR modeling of antimalarial activity of urea derivatives using genetic algorithm–multiple linear regressions
نویسندگان
چکیده
منابع مشابه
QSAR models to predict physico-chemical Properties of some barbiturate derivatives using molecular descriptors and genetic algorithm- multiple linear regressions
In this study the relationship between choosing appropriate descriptors by genetic algorithm to the Polarizability (POL), Molar Refractivity (MR) and Octanol/water Partition Coefficient (LogP) of barbiturates is studied. The chemical structures of the molecules were optimized using ab initio 6-31G basis set method and Polak-Ribiere algorithm with conjugated gradient within HyperChem 8.0 environ...
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Quantitative structure-activity relationship (QSAR) models were employed for prediction the activity of P2X7 receptor antagonists. A data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. A suitable group of calculated molecular descriptors was selected by employing stepwise multiple ...
متن کاملQSAR Modeling of COX-2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method
COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure–activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R2) of 0.972 and 0.531 for training and test groups, respectively. The quality of the mod...
متن کاملQSAR Modeling of COX-2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method
COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure–activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R2) of 0.972 and 0.531 for training and test groups, respectively. The quality of the mod...
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A quantitative structure-activity relationship (QSAR) modeling of the antimalarial activity of two diverse sets of compounds for each of two strains D6 and NF54 of Plasmodium falciparum is presented. The molecular structural features of compounds are presented by molecular descriptors (geometrical, topological, quantum mechanical, and electronic) calculated using the CODESSA PRO software. Satis...
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ژورنال
عنوان ژورنال: Journal of Saudi Chemical Society
سال: 2016
ISSN: 1319-6103
DOI: 10.1016/j.jscs.2012.07.019