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.

SummaryA study is reported of the relationship between the RF values for a group of organophosphorus insecticides obtained by thin layer chromatography and a series of topological descriptors. By using multivariate regression, the corresponding connectivity functions were obtained, which had been selected on the basis of their respective statistical parameters: multiple correlation coefficient (r), standard error of estimate (s), F-Snedecor values and statistical significance (Student's t). Regression analysis of the connectivity functions can predict the elution behaviour of any structurally similar derivative of this group of compounds with different stationary and mobile phases. Stability studies of the prediction models selected were carried out and yielded good stability in all cases. These results demonstrate the ability of Molecular Topology to identify and predict different structural features that determine the RF values of organophosphorus insecticides obtained by TLC.