Parameterization of an empirical model for the prediction of n-octanol, alkane and cyclohexane/water as well as brain/blood partition coefficients.

Quantitative information of solvation and transfer free energies is often needed for the understanding of many physicochemical processes, e.g the molecular recognition phenomena, the transport and diffusion processes through biological membranes and the tertiary structure of proteins. Recently, a concept for the localization and quantification of hydrophobicity has been introduced (Jäger et al. J Chem Inf Comput Sci 43:237-247, 2003). This model is based on the assumptions that the overall hydrophobicity can be obtained as a superposition of fragment contributions. To date, all predictive models for the logP have been parameterized for n-octanol/water (logP(oct)) solvent while very few models with poor predictive abilities are available for other solvents. In this work, we propose a parameterization of an empirical model for n-octanol/water, alkane/water (logP(alk)) and cyclohexane/water (logP(cyc)) systems. Comparison of both logP(alk) and logP(cyc) with the logarithms of brain/blood ratios (logBB) for a set of structurally diverse compounds revealed a high correlation showing their superiority over the logP(oct) measure in this context.