Prediction of blood-brain distribution: effect of ionization

Two simple multiple linear regression models were proposed to calculate the logarithm of the blood to brain concentration ratio (log BB) of drugs or drug-like compounds. The drugs were classified into two groups according to their ionization state in blood, and the significant parameters were selected using the train sets for each group. For un-ionizable compounds, the logarithm of distribution coefficient in octanol-water in pH 7.4 (log D(7.4)) and molecular weight are the significant parameters, whereas for ionizable compounds, log D(7.4) and number of hydrogen bond acceptor are significant parameters. The developed models were validated and their prediction capabilities checked using an external dataset of 25 compounds. In addition to the acceptable prediction errors, comparison of the external data analysis results with previously proposed models confirmed superior prediction capability of newly developed models.