摘要:

A quantitative structure-activity relationship (QSAR) investigation was done for the acute oral mammalian toxicity (LD50) of a set of 54 organophosphorus pesticide compounds. The compounds were represented with calculated molecular structure descriptors, which encoded their topological, electronic, and geometrical features. Feature selection was done with a genetic algorithm to find subsets of descriptors that would support a high quality computational neural network (CNN) model to link the structural descriptors to the - log(mmol/kg) values for the compounds. The best seven-descriptor non-linear CNN model found had an rms error of 0.22 log units for the training set compounds and 0.25 log units for the prediction set compounds.

ISSN:1062-936X    

DOI:10.1080/10629369908039170

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

The problem of the relationship between the structure of a molecule and its physical, chemical, and biological properties is one of the most fundamental in chemistry. Three molecular structure-property studies are discussed as illustrations of different approaches to this problem. In the first study the carcinogenic activities of polycyclic aromatic hydrocarbons and their derivatives are examined. Molecular orbital calculations of the presumptive activation steps and species for these compounds (based on the “bay region” theory of activation) are seen to yield a surprisingly good guide to the observed carcinogenic activities. Both activation and deactivation steps are considered. The second study reviews structure-property work on the tissue solubilities of halogenated hydrocarbons. Relatively simple structural descriptors give a good account of the solubilities of these compounds in blood, muscle, fat, and liver tissue. With the aid of principal components analysis it is shown that there are two dominant dimensions to this problem, which can be interpreted in terms of solubilities of the compounds in lipid and saline environments. The final study, which examines the boiling points of aliphatic alcohols, illustrates the value of using more than one descriptor set. The (perhaps surprising) conclusion is that a theoretical model can sometimes be more accurate than the data upon which it is based. Moreover, two models are better than one.

ISSN:1062-936X    

DOI:10.1080/10629369908039171

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

A hierarchical approach has been used in this paper in predicting the mutagenicity/non-mutagenicity of a set of 127 chemicals from their molecular descriptors. The set of descriptors consisted of topostructural and topochemical parameters, experimental properties like logP, and quantum chemical indices calculated using a semi-empirical method. The results show that a combination of topostructural and topochemical molecular descriptors explain most of the variance in the experimental data. The addition of physical properties or quantum chemical parameters did not make any significant improvement in the predictive power of the models.

ISSN:1062-936X    

DOI:10.1080/10629369908039172

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

The correlation of different molecular sub-structures with various molecular properties has a long history, of over a century. And currently such structural characterizations still remain of central interest in chemistry. Thus a general formalism to analyze a property or activity in terms of sub-structural contributions is of interest, and is pursued here. The approach may indeed be viewed as a formalization and extension of standard bond-energy ideas as arise even in introductory chemistry courses. The present formalism allows for:

ISSN:1062-936X    

DOI:10.1080/10629369908039173

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

A novel method of pharmacophore identification and activity prediction in structure-activity (structure-property) relationships is worked out as an essential extension and improvement of previous publications. In this method each conformation of the molecular systems in the training set of the SAR problem is presented by both electronic structure and geometry parameters arranged in a matrix form. Multiple comparisons of these matrices for the active and inactive compounds allows one to separate a smaller number of matrix elements that are common for all the active compounds and are not present in the same arrangement in the inactive ones. This submatrix of activity represents the pharmacophore (Pha).

ISSN:1062-936X    

DOI:10.1080/10629369908039174

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Quantitative structure-activity relationships (QSAR) were developed for nucleoside analogs with anti-HIV activity. These compounds were investigated to determine the correlation of structure and toxicity/activity using molecular similarity analysis and structure-activity maps. A multiple-formula approach was used to perform quantitative molecular similarity analysis (QMSA) and QSAR study. Molecular descriptors such as number of atoms and bonds of a molecule (NAB), maximum common substructure (MaCS), and molecular similarity index (MSI) were used in our structure-activity relationship study. The MaCS of two molecules is defined as the substructure with the greatest NAB value common to both molecules. The MSI of two moleculesXandYis defined as MSI(X,Y)= [MaCS(X,Y)/NAB(X)] X [MaCS(X,Y)/NAB(Y)]. MaCS and MSI quantify the similarity between two molecular structures. Structure-activity maps (structure-toxicity map and structure-antiviral map) and QMSA were used to determine the site and type of modification for reduced toxicity and improved activity of new compounds.

ISSN:1062-936X    

DOI:10.1080/10629369908039175

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Semiempirical quantum calculations were performed on a series of organophosphorus fluoridates to determine the relative reactivity for hydrolysis. This value was determined by subtracting the energy of the metastable intermediate from the energy of the stable molecule. Plotting this relative reactivity for each compoundvs.its toxicity resulted in a parabolic curve with nerve agents and other similarly toxic compounds in the center. The more reactive phosphinates and less reactive phosphates were at the edges of the graph in the region of lower toxicity. The results indicate that for compounds meeting minimal structural requirements, chemical reactivity is the principal determinant of cholinesterase inhibition.

ISSN:1062-936X    

DOI:10.1080/10629369908039176

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

A substantial body of evidence indicates that both humans and wildlife suffer adverse health effects from exposure to environmental chemicals that are capable of interacting with the endocrine system. The recent cloning of the estrogen receptorβsubtype (ER-β) suggests that the selective effects of estrogenic compounds may arise in part by the control of different subsets of estrogen-responsive promoters by the two ER subtypes, ER-α and ER-β. In order to identify the structural prerequisites for ligand-ER binding and to discriminate ER-αand ER-3 in terms of their ligand-binding specificities, Comparative Molecular Field Analysis (CoMFA) was employed to construct a three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) model on a data set of 31 structurally-diverse compounds for which competitive binding affinities have been measured against both ER-α and ER-β. Structural alignment of the molecules in CoMFA was achieved by maximizing overlap of their steric and electrostatic fields using the Steric and Electrostatic ALignment (SEAL) algorithm. The final CoMFA models, generated by correlating the calculated 3D steric and electrostatic fields with the experimentally observed binding affinities using partial least-squares (PLS) regression, exhibited excellent self-consistency (r2> 0.99) as well as high internal predictive ability (q2> 0.65) based on cross-validation. CoMFA-predicted values of RBA for a test set of compounds outside of the training set were consistent with experimental observations. These CoMFA models can serve as guides for the rational design of ER ligands that possess preferential binding affinities for either ER-α or ER-β. These models can also prove useful in risk assessment programs to identify real or suspected EDCs.

ISSN:1062-936X    

DOI:10.1080/10629369908039177

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

An outline is provided on the development and use of correlative and mechanistic approaches to predictive toxicology, with particular emphasis on the experience at the U.S. EPA as applied to assessing the potential hazard posed by new industrial chemicals for which little or no test data are provided under the Toxic Substances Control Act. This information is presented with a historical perspective.

ISSN:1062-936X    

DOI:10.1080/10629369908039178

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

On the basis of a set of 593 experimental octanol/water partition coefficients (logP) for pesticides, the simulation performances of two models using computable descriptors are compared. The back propagation neural network model designed from autocorrelation descriptors (SAR QSAR Environ. Res.(1997),7, 151–172) compares favorably with the AFC model (J. Pharm. Sci.(1995),84, 83–92) using atom/fragment contributions and correction factors.

ISSN:1062-936X    

DOI:10.1080/10629369908039179

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor