Exploring QSAR of antiamoebic agents of isolated natural products by MLR, ANN, and RTO

A QSAR study of antiamoebic agents isolated from natural products was performed by multi linear regression (MLR), artificial neuron network (ANN), and regression through origin (RTO). After several procedures to reduce the number of descriptors, 11 descriptors were selected from the descriptor pool by a complete MLR methodology. The best proportion between training:predicted:validation sets is 100:43:16 molecules. The Mor23m descriptor is a 3D-MoRSE descriptor and it is the main descriptor in the models studied. This result suggests that the three-dimensional structure and atomic properties like masses are very important in the models. The best quantitative structure–activity relationship model was proved to be independent of chance correlation.