Quantitative structure-property relationship study of alcohols water solubility based on a new model combined modified autocorrelation method and electro-topological indices

Abstract

In this study, structure water solubility modeling was performed to describe a set of 50 of aliphatic alcohols in a Quantitative Structure-Property Relationship model by developing of two descriptors types based on multifunctional autocorrelation method, which gives a general description of whole molecule; and electro-topological descriptors. The index combines the topological nature with electronic state of the atom. The Modified Autocorrelation Method was used in structure–property relationships to describe the local environment of the hydroxyl group. For the statistical studies, Multiple Linear Regression, Artificial Neural Networks and Principal Components Analysis were used. The approach efficiency approach was evaluated through the predictive ability of models by leave-p-Out cross-validation method. The coefficient of determination and errors of descriptors combination calculated respectively by multiple linear regression and artificial neural networks were r= 0.99, s = 0.18 and r = 0.99, s = 0.32. In order to simplify components computation, the molecules were coded by means of SMILES system and stored as input files. The results showed that aliphatic alcohols solubility is dominated by the shape and molecule branching, also the electro-topological descriptors had a considered model effect.