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Application of desirability analysis for finding the optimal levels of the molecular descriptors in QSAR models

Desirability analysis was performed in order to find a set of levels of the predictor variables (molecular descriptors) that maximizes the desirability of the responses on the dependent variable (studied inhibitory activities). The best QSAR models for the inhibition of α-glucosidase by polyphenols and anti-malarial activity of synthetic tri-pyrrole derivatives (prodiginines) were used for analysis. Predicting responses on the dependent variable were obtained by fitting the observed responses using an equation based on the levels of the independent variables (descriptors). Subsequently, the levels of the independent variables that simultaneously produce the most desirable predicted responses on the dependent variable were found. Overall desirability was computed as the geometric mean of the individual desirability. Desirability profiles consist of a series of graphs, one for each independent variable, of overall desirability scores at different levels of one independent variable, holding the levels of the other independent variables constant at specified values. Inspection of the desirability profiles shows which levels of the predictor variables produce the most desirable predicted responses on the dependent variable. Spline method was selected for fitting the desirability function and contours maps. The contour plots show the levels of overall response desirability produced in different regions of the plane defined by pairs of independent variables. Each region of the plane represents a different combination of the levels of the two variables. Desirability analysis was carried out with STATISTICA 7.0.

Desirability analysis ; inhibition ; antimalarial activity ; QSAR

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