Blood-brain barrier permeation models: discriminating between potential CNS and non-CNS drugs including P-glycoprotein substrates

Abstract

The aim of this article is to present the design of a large heterogeneous CNS library (approximately 1700 compounds) from WDI and mapping CNS drugs using QSAR models of blood-brain barrier (BBB) permeation and P-gp substrates. The CNS library finally includes 1336 BBB-crossing drugs (BBB+), 259 molecules non-BBB-crossing (BBB-), and 91 P-gp substrates (either BBB+ or BBB-). Discriminant analysis and PLS-DA have been used to model the passive diffusion component of BBB permeation and potential physicochemical requirement of P-gp substrates. Three categories of explanatory variables (Cdiff, BBBpred, PGPpred) have been suggested to express the level of permeation within a continuous scale, starting from two classes data (BBB+/BBB-), allowing that the degree to which each compound belongs to an activity class is given using a membership score. Finally, statistical data analyses have shown that some very simple descriptors are sufficient to evaluate BBB permeation in most cases, with a high rate of well-classified drugs. Moreover, a "CNS drugs" map, including P-gp substrates and accurately reflecting the in vivo behavior of drugs, is proposed as a tool for CNS drug virtual screening.