Computational prediction of solubilizers' effect on partitioning.

A computational model for the prediction of solubilizers' effect on drug partitioning has been developed. Membrane/water partitioning was evaluated by means of immobilized artificial membrane (IAM) chromatography. Four solubilizers were used to alter the partitioning in the IAM column. Two types of molecular descriptors were calculated: 2D descriptors using the MOE software and 3D descriptors using the Volsurf software. Structure-property relationships between each of the two types of descriptors and partitioning were established using partial least squares, projection to latent structures (PLS) statistics. Statistically significant relationships between the molecular descriptors and the IAM data were identified. Based on the 2D descriptors structure-property relationships R(2)Y=0. 99 and Q(2)=0.82-0.83 were obtained for some of the solubilizers. The most important descriptor was related to logP. For the Volsurf 3D descriptors models with R(2)Y=0.53-0.64 and Q(2)=0.40-0.54 were obtained using five descriptors. The present study showed that it is possible to predict partitioning of substances in an artificial phospholipid membrane, with or without the use of solubilizers.