0000000000591765
AUTHOR
Miguel Murcia-soler
Artificial Neural Networks and Linear Discriminant Analysis: A Valuable Combination in the Selection of New Antibacterial Compounds
A set of topological descriptors has been used to discriminate between antibacterial and nonantibacterial drugs. Topological descriptors are simple integers calculated from the molecular structure represented in SMILES format. The methods used for antibacterial activity discrimination were linear discriminant analysis (LDA) and artificial neural networks of a multilayer perceptron (MLP) type. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval of the discriminant function and the output value of the neural network versus these values. Pharmacological distribution diagrams (PDD) were used as a visualizing technique for the i…
New Hypolipaemic Agents Designed by Molecular Topology: Pharmacological Studies of 2,6-Di-tert-butyl-4-methylpyridine and 2,6-Di-tert-butylpyridine
New compounds showing hypolipaemic activity have been designed using a computer-aided method based on molecular topology and QSAR analysis. Linear discriminant analysis and connectivity functions were used to design three potentially suitable drugs which were tested for hypolipaemic properties by the Triton WR-1339 test in rats. The pharmacological tests carried out on the newly designed compounds demonstrated the existence of notable activity in phase I for two of them. namely 2,6-Di-tert-butyl-4-methylpyridine (C.A.S. 38222-83-2) and 2,6-Di-tert-butylpyridine (C.A.S. 585-48-8), with respect to the level of total cholesterol. Both substances decrease the lipaemia to lower levels than clofi…
QSAR Analysis of Hypoglycemic Agents Using the Topological Indices
The molecular topology model and discriminant analysis have been applied to the prediction of some pharmacological properties of hypoglycemic drugs using multiple regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies performed on the selected prediction models confirmed the goodness of the fits. The method used for hypoglycemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new hypoglycemic agents, and we …
Discrimination and selection of new potential antibacterial compounds using simple topological descriptors.
Abstract The aim of the work was to discriminate between antibacterial and non-antibacterial drugs by topological methods and to select new potential antibacterial agents from among new structures. The method used for antibacterial activity selection was a linear discriminant analysis (LDA). It is possible to obtain a QSAR interpretation of the information contained in the discriminant function. We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new antibacterial agents.
Drugs and Nondrugs: An Effective Discrimination with Topological Methods and Artificial Neural Networks
A set of topological and structural descriptors has been used to discriminate general pharmacological activity. To that end, we selected a group of molecules with proven pharmacological activity including different therapeutic categories, and another molecule group without any activity. As a method for pharmacological activity discrimination, an artificial neural network was used, dividing molecules into active and inactive, to train the network and externally validate it. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval, and the output value of the neural network versus these values. Pharmacological distribution diagram…