NEURAL NETWORKS IN QSAR STUDIES:ESTIMATION AND PREDICTION OF BIOLOGICAL ACTIVITY FOR N-(SUBSTITUTED PHENOXYETHYL)-CYCLOPROPYLAMINES

Neural networks(NN)methods were applied to quantitative structure-activity relationship(QSAR)studies.The relationship between biological activity(pC=pIC₅₀)and electronic,hydrophobic and steric parameters and dumming index(sigma,pi,Es,was investigated by usingmodified backpropagation(MBP)neural networks.The biological activity of N-(substitutedphenoxyethyl)-cyclopropylamines derivative regression was estimated and predicted with relative errorless than 16%and with correct classification ratio being 94.4%,The results obtained by thedeveloped NN(MBP)method seem to be better than those by multivariate regression(MR)and step-wise regression(SR).The NN(MBP)method was,therefore,regarded as an excellent chemometricmedeling technique for estimating and predicting biological activity on basis of chemical structure forQSAR studies。