High-Throughput Prediction of Blood−Brain Partitioning: A Thermodynamic Approach

Abstract

A high-throughput in silico screening tool for potentially CNS active compounds was developed on the basis of the correlation of solvation free energies and blood−brain partitioning (log(c_brain/c_blood) = log BB) data available from experimental sources. Utilizing a thermodynamic approach, solvation free energies were calculated by the fast and efficient generalized Born/surface area continuum solvation model, which enabled us to evaluate more than 10 compounds/min. Our training set involved a structurally diverse set of 55 compounds and yielded a function of log BB = 0.035G_solv + 0.2592 (r = 0.85, standard error 0.37). Calculation of solvation free energies for 8700 CNS active compounds (CIPSLINE database) revealed that G_solv is higher than −50 kJ/mol for the 96% of these compounds which can be used as suitable criteria for the identification of compounds preferable for CNS penetration.