A quantitative structure-melting point relationship was developed to predict the melting point of some pyridinum bromides. A set of 1497 zero- to three-dimensional descriptors were used for each molecule in the data set. Multivariate adaptive regression spline (MARS) was successfully used as a descriptor selection method and also for mapping model. The root mean square error and coefficient of determination were obtained as 17.36 and 0.8750, respectively. The results were compared with those obtained from other model, which after selection of descriptors by MARS, multiple linear regression (MLR) was applied for modeling. The results showed MARS can be used as a powerful model for prediction of melting point of pyridinum bromides.
The H-point standard addition method was applied to kinetic data for simultaneous determination of V(IV) and V(V) or selective determination of V(IV) in presence of V(V). The method is based on the difference in the rate of complex formation between V(IV) and V(V) with methyl thymol blue. The linear dynamic ranges for the two analytes of V(IV) and V(V) are 0.18-3.15 and 0.25-4.00 μg mL-1, respectively. The proposed method was successfully applied for the determination of vanadium in two different oxidation states in several synthetic mixtures and also in blood serum and water samples.
The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.
AUTHOR KEYWORDS: Benzodiazepine receptor; Binding affinity; CART; Imidazobenzodiazepines; QSAR INDEX KEYWORDS: 3D structures; Binding affinities; Classification and regression tree; Classification and regression tree analysis; Cross-validation methods; Data sets; Dependent variables; Descriptors; Mean relative error; Molecular descriptors; Optimization method; Predictive power; Quantitative structure-activity relationship studies; Quantitative structure-activity relationships; Receptor binding; Semi-empirical; Tree models; Tree structures, Classification (of information); Optimization; Sulfur compounds; Three dimensional, Binding energy
A quantitative structure activity relationship analysis (QSAR) has been applied to a data set of 23 derivatives of l-2-[(hydroxyethoxy)methyl]-6- (phenylthio)thymine (HEPT) with their anti-HIV activities. Semi-empirical quantum chemical calculations at the AMI level were used to find the 3D geometry of the studied molecules. Whole numbers of descriptors were calculated with Dragon software, and a subset of calculated descriptors was selected from 1481 Dragon descriptors with the forward stepwise multiple linear regression (MLR) method. Then anti-HIV activities against HIV-1 and four HIV-1 mutant strains containing single mutations in their reverse transcriptases (RTs) were studied, and five equations with excellent statistical qualities were obtained using multiple linear regression. The activities of these compounds were also calculated in predictions, and good correlation coefficients were obtained.
AUTHOR KEYWORDS: Anti-HIV; HEPT derivatives; HIV-1; Mutant strains; QSAR PUBLISHER: Chinese Chemical Society Taiwan
A quantitative structure-property relationship (QSPR) study based on the wavelet neural network (WNN) technique was performed for the prediction of gas chromatography retention indexes of methyl-substituted alkanes produced by insects. In addition to the simple structural descriptors, semi-empirical quantum chemical calculations at the AMI (Austin Model 1) level were used to find the optimum 3D geometry of the studied molecules and a numbers of descriptors were calculated with HyperChem and Dragon software. A stepwise MLR (Multiple Linear Regression) method was used to select the best descriptors, and the selected descriptors were used as input neurons in a wavelet neural network model. The average relative error was 2.2%.
AUTHOR KEYWORDS: Gas chromatography; Insect; Methyl-substituted alkanes; QSPR; Wavelet neural network PUBLISHER: Chinese Chemical Society Taiwan
A very sensitive, simple and selective spectrophotometric method for simultaneous determination of phosphate and silicate based on formation of phospho- and silicomolybdenum blue complexes in the presence of ascorbic acid is described. Although the complexes of phosphate and silicate with reagent in the presence of ascorbic acid show a spectral overlap, they have been simultaneously determined by principal component artificial neural network (PC-ANN). The PC-ANN architectures were different for phosphate and silicate. The output of phosphate PC-ANN architecture was used as an input for silicate PC-ANN architecture. This modification improves the capability of silicate PC-ANN model for prediction of silicate concentrations. The linear range was 0.01-3.00 μg mL-1 for phosphate and 0.01-5.00 μg mL -1 for silicate. Interference effects of common anions and cations were studied and the proposed method was also applied satisfactorily to the determination of phosphate and silicate in detergents.
INDEX KEYWORDS: detergent; molybdenum; phosphate; silicate, article; artificial neural network; chemistry; evaluation; methodology; principal component analysis; sensitivity and specificity; ultraviolet spectrophotometry, Detergents; Molybdenum; Neural Networks (Computer); Phosphates; Principal Component Analysis; Sensitivity and Specificity; Silicates; Spectrophotometry, Ultraviolet
The H-point standard addition method was applied to kinetic data for simultaneous determination of citric and ascorbic acid or selective determination of ascorbic acid in presence of citric acid. The method is based on the difference in the rate of reaction of citric and ascorbic acid with copper(II)-ammonia complex. The linear dynamic ranges for the two analytes of citric and ascorbic acid are 0.80-1.15 × 102 and 0.70-10.00 mM, respectively. The proposed method was successfully applied for the determination of citric and ascorbic acid in some powdered drink mixtures and vitamin C tablet.
A very simple spectrophotometric method for simultaneous determination of aluminum(III) and iron(III) based on formation of their complexes with pyrocatechol violet (PCV) in micellar media, using the H-point standard addition method (HPSAM), is described. In micellar media, the metal complexes of Al-PCV and Fe-PCV are formed very fast. Formation of both of the complexes was complete within 5 min at pH 8.5. The linear ranges for aluminum and iron were 0.05-2.50 and 0.10-4.00 μg mL-1, respectively. The relative standard deviation (R.S.D.) for the simultaneous determination 0.40 μg mL-1 of Al(III) and 0.20 μg mL-1 of Fe(III) were 3.24% and 4.22%, respectively. Interference effects of common anions and cations were studied. Themethod was applied to simultaneous determination of Al(III) and Fe(III) in standard reference material and alloy samples.
AUTHOR KEYWORDS: Aluminum; H-point standard addition method; Iron; PCV PUBLISHER: Chinese Chemical Society Taiwan
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