125 resultados para Quantitative structure-activity relationship

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Five variables for phenol derivatives were calculated by molecular projection in three-dimensional space which were combined with eight quantum-chemical parameters and three Am indices. These variables were selected by using leaps-and-bounds regression analysis. Multiple linear regression analysis and artificial neural networks' were performed, and the results obtained by using. artificial neural networks are superior than that obtained by using multiple linear regression.

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In this article, generalized torsion angles of derivatives of 1-[(2-hydroxyethoxy)methy1]-6(phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps-and-Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.

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In this research. we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter. such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results Were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method-the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA Were achieved. Besides the CoMFA analysis. multiregression analysis and neural network methods for building the models were used in this paper.

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A series of 3,4-dimethyl-4-(3-hydroxyphenyl) piperidine opioid antagonists with varying substituents on the nitrogen were evaluated for their effect on food consumption in obese Zucker rats. In developing three-dimensional quantitative structure-activity relationship (3D-QSAR) studies for this series of opioid antagonists, different structure alignments have been tested to predict the anorectant activities. The interaction energies between molecules and the probe atom were then correlated with anorectant activity using partial least squares (PLS) method. The steric and electrostatic features of the 3D-QSAR were presented in the form of standard deviation coefficient contour maps of steric and electrostatic fields. The results showed that 3D-QSAR results are much better than the results obtained by 2D-QSAR.

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Molecular connectivity index and comparative molecular field analysis (CoMFA) have been applied to the studies of the correlation of the derivatives of benzamide and their antiallergic activities. The results achieved by using CoMFA based on 3D factors are much better than that obtained by using multiple regression analysis based on majorly 2D structural information. The CoMFA results show that the dominant factor which affects activity is steric, whereas electrostatic effect only plays an unimportant role.

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In recent years there has been a resurgence of interest in inhibitors of cyclic nucleotide phosphodiesterases (PDE) and enzymes responsible for the intracellular hydrolysis of the second messenger cAMP and cGMP. In this study, a series of 2-substituted phenyllimidazo[4,5-b]pyridines have been made to investigate 3D-QSAR of PDE activity using CoMFA. CoMFA resulted in a quantitative description of the major steric and electrostatic field effects, and gave significant new insights to factors governing PDE inhibition activity. The model was used to predict the PDE inhibition activity of imidazopyridines with satisfactory results.

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In this paper, the comparison of orthogonal descriptors and Leaps-and-Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps-and-Bounds regression for the data set of nitrobenzenes used in this study. Leaps-and-Bounds regression can be used effectively for selection of variables in quantitative structure-activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.

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In this study, by the use of partial least squares (PLS) method and 26 quantum chemical descriptors computed by PM3 Hamiltonian, a quantitative structure-property relationship (QSPR) model was developed for reductive dehalogenation rate constants of 13 halogenated aliphatic compounds in sediment slurry under anaerobic conditions. The model can be used to explain the dehalogenation mechanism. Halogenated aliphatic compounds with great energy of the lowest unoccupied molecular orbital (E-lumo), total energy (TE), electronic energy (EE), the smallest bond order of the carbon-halogen bonds (BO) and the most positive net atomic charges on an atom of the molecule (q(+)) values tend to be reductively dehalogenated slow, whereas halogenated aliphatic compounds with high values of molecular weight (Mw), average molecular polarizability (a) and core-core repulsion energy (CCR) values tend to be reductively dehalogenated fastest. (C) 2001 Published by Elsevier Science Ltd.

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Based on some fundamental quantum chemical descriptors computed by PM3 Hamiltonian, by the use of partial least-squares (PLS) analysis, a significant quantitative structure-property relationship (QSPR) model for logK(ow) of polychlorinated dibenzo-p-dioxins and dibenzo-p-furans (PCDD/Fs) was obtained. The QSPR can be used for prediction. The intermolecular dispersive interactions and thus the bulkness of the PCDD/Fs are the main factors affecting the logK(ow). The more chlorines in the PCDD/F molecule, the greater the logK(ow) values. (C) 2001 Elsevier Science Ltd. All rights reserved.

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A new index, i.e., the periphery representation of the projection of a molecule from 3D space to a 2D plane is described. The results, correlation with toxicity of substituted nitrobenzenes, obtained by using periphery descriptors are much better than that obtained by using the areas (i.e., shadows) of projections of the compounds. Even better results were achieved by using the combination of periphery descriptors and the projections areas as well as the indicated variable K reflecting the action of group NO position on the benzene ring.

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Three kinds of surfactants as stabilizer were applied to the preparation of electrocatalysts for direct methanol fuel cell (DMFC). The catalysts have been characterized by examining their catalytic activities, morphologies and particle sizes by means of cyclic voltammetry, chronoamperometry, X-ray diffraction and transmission electron microscopy (TEM). It is found that the surfactants with different structures have a significantly influence on the catalyst shape and activity. The catalysts prepared with non-ionic surfactants as the stabilizer show higher activity for direct oxidation of methanol. The structure-activity relationship (SAR) analysis has been explored and the effect of hydrophile-lipophile balance (HLB value) has also been discussed.

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The A(m) index and molecular connectivity index were used for studying the photoionization sensitivity of some organic compounds in gas chromatography. The analysis of structure-property relationship between the photoionization sensitivity of the compounds and the A(m) indices or molecular connectivity indices has been carried out. The genetic algorighm was used to build the correlation model in this field. The results demonstrate that the property of compounds can be described by both A(m) indices and molecular connectivity indices, and the mathematical model obtained by the genetic algorithm was better than that by multivariate regression analysis.

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Comparative molecular fiels analysis (CoMFA) has been applied to the studies of the correlation of the N-nitroso compounds and their carcinogenic activities, The comparison of CoMFA results with different lattice spacing and different atom probes was investigated, CoMFA resulted in a quantitative description of the major steric and electrostatic field effects and gave significant new insights to factors governing potency.