prediction of aqueous solubility of alcohols by molecular approach

In this work, two new models by group contribution method (gc) and quantitative structure-property relationship (qspr) were developed to prediction the aqueous solubility of alcohols based on theoretically derived molecular parameters# to develop the gc model a total of 53 substructures or functional groups was used# an efficient approach combining modified particle swarm optimization (mpso) and multiple linear regression (mlr) was used for selecting a subset of relevant descriptors and building the optimal qspr model# the proposed models were assessed by external validation method# the squared correlation coefficient values of 0#900 for the gc model and 0#897 for the qspr model show good predictive ability of both models# the selected descriptors by mpso-mlr suggest that size and hydrophobicity of alcohols are the most important factors affecting their aqueous solubility#