Zupan's descriptors in QSAR applied to the study of a new class of cardiotonic agents.

Recently a new class of molecular descriptors has been proposed and used in QSAR with simulated data and with regression performed by neural networks. In the present paper these descriptors (Zups, from the name of their author, Juri Zupan) have been slightly modified and then applied to a real data set with the aim of studying the structure-activity relationships of a new class of cardiotonics. Forty-one molecules (thirty-seven milrinone analogues, the two lead compounds amrinone and milrinone, and two commercial products) have been studied using classical chemometrical techniques such as PCA (Principal Components Analysis) and PLS (Partial Least Squares regression). Zups describe essentially the local geometry of the molecules. They show promising performances, as compared with other classical geometrical descriptors (as molecular volume, etc.), both in that regards the overall performances, measured by the C.V. Explained variance and in the interpretability of the regression equation. However they have not all the requirements of a good structure representation. Moreover some selectable parameters seem to have a great importance, so that the refinement of the regression model requires time and the evaluation step must be performed in condition of full-validation, because predictive optimisation is used in the selection of parameters, and the final model must be checked on molecules never used to refine the model or, in this case, the parameters of the structure representation.