The
blood–brain barrier (BBB) protects the brain from the
toxic side effects of drugs and exogenous molecules. However, it is crucial that medications
developed for neurological disorders cross into the brain in therapeutic
concentrations. Understanding the BBB interaction with drug molecules
based on physicochemical property space can guide effective and efficient
drug design. An algorithm, designated “BBB Score”, composed
of stepwise and polynomial piecewise functions, is herein proposed
for predicting BBB penetration based on five physicochemical descriptors:
number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising
molecular weight, hydrogen bond donor, and hydrogen bond acceptors),
topological polar surface area, and pKa. On the basis of statistical
analyses of our results, the BBB Score outperformed (AUC = 0.86) currently
employed MPO approaches (MPO, AUC = 0.61; MPO_V2, AUC = 0.67). Initial
evaluation of physicochemical property space using the BBB Score is
a valuable addition to currently available drug design algorithms.
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