Quantitative structure−activity relationships (QSAR) studies were performed on the radical scavenging activities of a set of compounds consisting of various types of antioxidant families. The predicting five parameter models correlating selected descriptors, derived from the 2D and 3D representations of molecules and antioxidant activity, were set up using multiple linear regressions (MLR) and a multilayer perceptron neural network (MLP-NN), separately. The best obtained model had statistics of R2 = 0.968 and q2 = 0.898 for the MLP-NN model and R2 = 0.902 and q2 = 0.862 for the MLR model. The chemical applicability domains of these models were determined via a leverage approach. The obtained result indicated that the proposed models can be successfully used for predictions of radical scavenging activities of new antioxidants.
