Prediction of Partition Coefficients (LOGPoct) Using Autocorrelation Descriptors

Abstract

A backpropagation neural network model, implemented in AUTOLOGP (Version 4.0), was developed for estimating the n-octanol/water partition coefficient of organic molecules from their structure described by means of a modified autocorrelation method. The advantages of the autocorrelation method, which allows the description of any kind of molecules by means of computerized molecular descriptors presenting a physicochemical meaning, were emphasized through the simulation performances obtained with AUTOLOGP (Version 4.0) and from a comparative study involving two regression models derived from various topological indices.