Artificial neural network prediction of the psychometric activities of phenylalkylamines using DFT-calculated molecular descriptors

Abstract

In the present work, a quantitative structure-activity relationship (QSAR) method was used to predict the psychometric activity values (as mescaline unit, log MU) of 48 phenylalkylamine derivatives from their density functional theory (DFT) calculated molecular descriptors and an artificial neural network (ANN). In the first step, the molecular descriptors were obtained by DFT calculation at the 6-311G