Predicting blood-brain barrier penetration from molecular weight and number of polar atoms

Abstract

A simple three-descriptor model to predict blood-brain barrier is derived from a training set of 78 compounds: logBB=-9.880 x 10(-6)M(W)(2)+7.339 x 10(-3)M(W)-0.2268n(pol)-0.1143 (n=78, r(2)=0.74), where logBB is the logarithm of the ratio of the steady-state concentration of the compound in the brain to concentration in the blood, M(W) is the molecular weight, n(pol) is the number of polar atoms (oxygen, nitrogen, and attached hydrogen), n is the number of compounds, and r is the correlation coefficient. The model is validated through use of leave-one-out procedure and an external test set (25 compounds). The model is suitable for the rapid prediction of the blood-brain barrier penetration of drug candidates because of its predictive ability and simplicity.