Using a combination of theoretical descriptors and a neural network to predict the activity of a set of N-alkyl-n-acyl- -aminoamide derivatives

A back -propagation artificial neural net has been trained to estimate the activity values of a set of 18 N-alkyl-N-acyl- -aminoamide derivatives from the results of molecular mechanics and RHF/PM3/SCF MO semi-empirical calculations. The input descriptors include molecular properties such as the partition coefficient P, 3d structure dependent parameters, charge dependent parameters, and topological descriptors.