Artificial neural network applied to prediction of fluorquinolone antibacterial activity by topological methods.

A new topological method that makes it possible to predict the properties of molecules on the basis of their chemical structures is applied in the present study to quinolone antimicrobial agents. This method uses neural networks in which training algorithms are used as well as different concepts and methods of artificial intelligence with a suitable set of topological descriptors. This makes it possible to determine the minimal inhibitory concentration (MIC) of quinolones. Analysis of the results shows that the experimental and calculated values are highly similar. It is possible to obtain a QSAR interpretation of the information contained in the network after the training has been carried out.

Correlation of pharmacological properties of a group of beta-blocker agents by molecular topology.

The molecular connectivity method has been applied to the study of pharmacological properties, among which are found the angor treatment dose, alpha-distribution half-life and intravenous LD50 in mouse, of a group of beta-blocker agents, verifying its application in the prediction of theoretic values for said pharmacological properties. To do this, the obtained multiple regression functions of the corresponding connectivity indices were used in relation with the experimental values of the properties, which are accompanied by the statistical parameters used in their selection criteria, as well as the corresponding random and cross-validation studies of said functions, which corroborate the good correlation of the selected equations.

Correlation of pharmacological properties of a group of hypolipaemic drugs by molecular topology.

This investigation was undertaken to test the ability of the molecular connectivity model to predict the percentage of plasma protein binding, the percentage of total cholesterol reduction and oral LD50 in rats of a group of hypolipaemic drugs using multi-variable regression equations with multiple correlation coefficients, standard error of estimate, degrees of freedom, F-Snedecor function values, Mallow's CP and Student's t-test as criteria of fit. Regression analyses showed that the molecular connectivity model predicts these properties. Corresponding stability (cross validation) studies were made on the selected prediction models which confirmed their goodness of fit. The results also demonstrated that the presence of substituents and molecular volume, determine the value of these properties in hypolipaemic drugs.

Pharmacological studies of 1-(p-chlorophenyl)propanol and 2-(1-hydroxy-3-butenyl)phenol: two new non-narcotic analgesics designed by molecular connectivity.

Molecular topology has been applied to the design of new analgesic drugs. Linear discriminant analysis and connectivity functions were used to design two potentially suitable drugs which were synthesized and tested for analgesic properties by the acetic acid-induced abdominal constriction test in mice and the tail-flick test in rats. In mice, the compound 1-(p-chlorophenyl)propanol showed higher analgesic activity, both intraperitoneally and orally, than acetylsalicylic acid. 2-(1-Hydroxy-3-butenyl)phenol exhibited a lesser protective effect (70% of that shown by acetylsalicylic acid). In rats, acetylsalicylic acid gave the greatest protection against pain when administered intraperitoneally, while 1-(p-chlorophenyl)propanol was the most active orally. The 2-(1-hydroxy-3-butenyl)phenol, both intraperitoneally and orally, showed the least protective effect. These results demonstrated the peripheral analgesic properties of the selected compounds, thus confirming the validity of the molecular design method.

Pharmacological studies of the two new hypoglycaemic compounds 4-(3-methyl-5-oxo-2-pyrazolin-1-yl)benzoic acid and 1-(mesitylen-2-sulfonyl)-1H-1,2,4-triazole.

New compounds showing hypoglycaemic activity have been designed through a computer-aided method based on QSAR (quantitative structure activity relationship) and molecular connectivity. The pharmacological tests carried out on the newly designed compounds demonstrated the existence of notable activity for two of them, namely: 4-(3-methyl-5-oxo-2-pyrazolin-1-yl) benzoic acid (CAS 60875-16-3) and 1-(mesitylen-2-sulfonyl)-1H-1,2,4-triazole, (CAS 54230-59-0). Both substances mainly follow a mechanism based on the response to the oral glucose overcharge, decreasing the glycemia to lower levels as compared with tolbutamide, which is used as a standard drug, and reaching normal glycaemia at a similar time.

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 tested on rats the predictive ability of the model.