Structure-activity relationship of surfactant for preparing DMFC anodic catalyst

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.

Applications of the method of three-dimensional projection of a molecule in quantitative structure-activity relationship of phenol derivatives

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.

Applications of generalized torsion angles in studies on quantitative structure-activity relationship

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.

Effective descriptions of molecular structures and the quantitative structure - Activity relationship studies

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.

Three-dimensional quantitative structure-activity relationship of the opioid antagonist with potent anorectant activity of 3,4-dimethyl-4-(3-hydroxyphenyl) piperidine

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.

Studies on quantitative structure-activity relationship between the structures of derivatives of benzamide and their antiallergic activities

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.

Studies on three-dimensional quantitative structure-activity relationship of PDE inhibitory activity of imidazopyridines

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.

STUDY ON STRUCTURE-ACTIVITY-RELATIONSHIPS OF ORGANIC-COMPOUNDS - 3 NEW TOPOLOGICAL INDEXES AND THEIR APPLICATIONS

In this paper, three new topological indices, A(x1), A(x2), and A(x3), have been developed for use in multivariate analysis in structure-property relationship (SPR) and structure-activity relationship (SAR) studies. Good results have been obtained by using them to predict the physical and chemical properties and biological activities of some organic compounds.

Selection for variables in quantitative structure-activity/property relationship studies - Comparison between methods of orthogonal descriptors and leaps-and-bounds regression analysis

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.

STUDIES ON STRUCTURE-CARCINOGENIC ACTIVITY RELATIONSHIP OF N-NITROSO COMPOUNDS

The electronic parameters of 12 N-nitroso compounds have been computated with semiempirical quantum chemical calculation, and the study on the relationships between the structures of these compounds and the carcinogenic activities have been performed by using multivariate regression analysis and neural network with satisfactory results.

Structure-activity relationships for antiplasmodial activity among aminoquinolines

The extended gravitational index G(Q) and quantum-chemical descriptors were calculated for the relationship analysis of aminoquinolines. An evolutionary algorithm was described for variable selection and building QSAR models. And the quasi-newton neural networks were employed with better results.

Structure-function relationship of three neurotoxins from the venom of Naja kaouthia: a comparison between the NMR-derived structure of NT2 with its homologues, NT1 and NT3

Three homologous short-chain neurotoxins, named NT1, NT2 and NT3, were purified from the venom of Naja kaouthia. NT1 has an identical amino acid sequence to cobrotoxin from Naja naja atra [Biochemistry 32 (1993) 2131]. NT3 shares the same sequence with cobrotoxin b [J. Biochem. (Tokyo) 122 (1997) 1252], whereas NT2 is a novel 6 1 -residue neurotoxin. Tests of their physiological functions indicate that NT1 shows a greater inhibition of muscle contraction induced by electrical stimulation of the nerve than do NT2 and NT3. Homonuclear proton two-dimensional NMR methods were utilized to study the solution tertiary structure of NT2. A homology model-building method was employed to predict the structure of NT3. Comparison of the structures of these three toxins shows that the surface conformation of NT1 facilitates the substituted base residues, Arg28, Arg30, and Arg36, to occupy the favorable spatial location in the central region of loop 11, and the cation groups of all three arginines face out of the molecular surface of NT1 This may contribute greatly to the higher binding of NT1 with AchR compared to NT2 and NT3. (C) 2002 Elsevier Science B,V. All rights reserved.

Quantitative structure-property relationship study on reductive dehalogenation of selected halogenated aliphatic hydrocarbons in sediment slurries

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.

Quantitative structure-property relationship studies on n-octanol/water partitioning coefficients of PCDD/Fs

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.