Expert system for elucidation of structures of organic compounds (ESESOC) - Algorithm on stereoisomer generation

An algorithm for enumeration of stereoisomers due to asymmetric carbon, C=C double bond and so on has been developed. It consists of three steps. The output of stereoisomers can be represented by 2.5-dimensional connection table.

Automorphism group algorithm in computer-aided structure elucidation

It is necessary to generate automorphism group of chemical graph in computer-aided structure eluciation. In this paper, an algorithm is developed by all-path topological symmetry algorithm to build automorphism group of chemical graph. A comparison of several topological symmetry algorithm reveals that all-path algorthm can yield correct of class of chemical graph. It lays a foundation for ESESOC system for computer-aided structure elucidation.

Correlation analysis of the structures and gas-liquid chromatographic retention indices of amines

Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.

Quantitative structure-property relationship research to the analysis of photoionization sensitivity of organic compounds in gas chromatography

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.

Comparison of different methods for variable selection

In chemistry for chemical analysis of a multi-component sample or quantitative structure-activity/property relationship (QSAR/QSPR) studies, variable selection is a key step. In this study, comparisons between different methods were performed. These methods include three classical methods such as forward selection, backward elimination and stepwise regression; orthogonal descriptors; leaps-and-bounds regression and genetic algorithm. Thirty-five nitrobenzenes were taken as the data set. From these structures quantum chemical parameters, topological indices and indicator variable were extracted as the descriptors for the comparisons of variable selections. The interesting results have been obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

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.

The algorithm on ring perception of molecule

It's important to identify ring in the process of structure elucidation. In this paper, all rings and the smallest set of smallest ring(SSSR) of structure are obtained from two-dimensional connection table. The results are satisfactory by using this algorithm in ESESOC expert system as constraint.

A double logarithmic method in thin-layer spectroelectrochemistry for distinction among mechanisms of an irreversible electrochemical process

A simple double logarithmic method in potential-controlled thin-layer spectroelectrochemistry for an irreversible electrochemical process has been studied by numerical analysis and examined by experimental examples. This simple algorithm has a novel function offering some important information about the mechanism of a complex electrochemical process directly from a limited amount of potential-spectrum data, and can be used to distinguish different reaction mechanisms such as E, EC, EE, as well as to determine the electron-transfer coefficient, a, and the kinetically modified E-0'. Combination of the double logarithmic method with nonlinear regression provides a powerful tool to examine the proposed mechanism and also to estimate other thermodynamic and kinetic parameters. (C) 1999 The Electrochemical Society. S0013-4651(98)06-090-X. All rights reserved.

Computer perception of topological symmetry by all-paths algorithm

During the development of our ESESOC system (Expert System for the Elucidation of the Structures of Organic Compounds), computer perception of topological symmetry is essential in searching for the canonical description of a molecular structure, removing the irredundant connections in the structure generation process, and specifying the number of peaks in C-13- and H-1-NMR spectra in the structure evaluation process. In the present paper, a new path identifier is introduced and an algorithm for detection of topological symmetry from a connection table is developed by the all-paths method. (C) 1999 Elsevier Science B.V. All rights reserved.

Studies on the method of leaps and bounds regression

In this paper, we introduce the method of leaps and bounds regression which can be used to select variables quickly and obtain the best regression models. These models contain one variable, two variables, three variables and so on. The results obtained by using leaps and bounds regression were compared with those achieved by using stepwise regression to lead to the conclusion that leaps and bounds regression is an effective method.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

Study on Phenol Compounds Using Multiple Regression and Neural Network Methods

In this paper, the molecular connectivity indices and the electronic charge parameters of forty-eight phenol compounds nave been calculated. and applied for studying the relationship between partition coefficients and structure of phenol compounds. The results demonstrate that the properties of compounds can be described better with selective parameters, and the results obtained by neural network are superior to that by multiplle regression.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.

ALGORITHM FOR COMPUTER PERCEPTION OF TOPOLOGICAL SYMMETRY

For the exhaustive and irredundant generation of candidate structures in ESESOC (Expert System for the Elucidation of the Structures of Organic Compounds), a new algorithm for computer perception of topological equivalence classes of the nodes (non-hydrog

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor