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.
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.
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