Prediction of immobilised artificial membrane chromatography retention factors using theoretical molecular fragments and structural features

Abstract

Many in silico alternatives to aquatic toxicity tests rely on hydrophobicity-based quantitative structure–activity relationships (QSARs). Hydrophobicity is often estimated as log P, where P is the octanol–water partition coefficient. Immobilised artificial membrane (IAM) high performance liquid chromatography (HPLC) may be a more biologically relevant alternative to log P. The aim of this study was to investigate the applicability of a theoretical structural fragment and feature-based method to predict log k IAM (the logarithm of the retention index determined by IAM–HPLC) values. This will allow the prediction of log k IAM based on chemical structure alone. The use of structural fragment values to predict log P was first proposed in the 1970s. The application of a similar method using fragment values to predict log k IAM is a novel approach. Values of log k IAM were determined for 22 aliphatic and 42 aromatic compounds using an optimised and robust IAM–HPLC assay. The method developed shows good predictive performance using leave-one-out cross validation and application to an external validation set not seen a priori by the training set also generated good predictive values. The ability to predict log k IAM without the need for practical measurement will allow for the increased use of QSARs based on this descriptor.