A simple predictive model for blood-brain barrier penetration.

A simple two-descriptor model to predict blood-brain barrier penetration is derived from a training set of 79 compounds: log BB = - 13.31V2 + 9.601V - 2.231PSA - 0.5290 (n = 79, r2 = 0.83) where log BB is the logarithm of the ratio of the steady-state concentration of the compound in the brain to in the blood, V (nm3) is the molecular volume, PSA (nm2) is the polar surface area which is defined as the sum of the van der Waals surface areas of oxygen atoms, nitrogen atoms, and attached hydrogen atoms in a molecule, n is the number of compounds, and r is the correlation coefficient. The model is validated by a leave-one-out procedure and an external test set (25 compounds). The results indicate that the model developed is statistically sound and is sufficiently reliable and robust for predictive use. The descriptors in the model can be easily computed and it is suitable for the rapid prediction of the blood-brain barrier penetration for a wide range of drug candidates.