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Predicting efflux ratios and blood-brain barrier penetration from chemical structure: combining passive permeability with active efflux by P-glycoprotein.

ABSTRACT: In order to reach their pharmacologic targets, successful central nervous system (CNS) drug candidates have to cross a complex protective barrier separating brain from the blood. Being able to predict a priori which molecules can successfully penetrate this barrier could be of significant value in CNS drug discovery. Herein we report a new computational approach that combines two mechanism-based models, for passive permeation and for active efflux by P-glycoprotein, to provide insight into the multiparameter optimization problem of designing small molecules able to access the CNS. Our results indicate that this approach is capable of distinguishing compounds with high/low efflux ratios as well as CNS+/CNS- compounds and provides advantage over estimating P-glycoprotein efflux or passive permeability alone when trying to predict these emergent properties. We also demonstrate that this method could be useful for rank-ordering chemically similar compounds and that it can provide detailed mechanistic insight into the relationship between chemical structure and efflux ratios and/or CNS penetration, offering guidance as to how compounds could be modified to improve their access into the brain.

SUBMITTER: Dolghih E

PROVIDER: S-EPMC3582291 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Predicting efflux ratios and blood-brain barrier penetration from chemical structure: combining passive permeability with active efflux by P-glycoprotein.

Dolghih Elena E Jacobson Matthew P MP

ACS chemical neuroscience 20121211 2

In order to reach their pharmacologic targets, successful central nervous system (CNS) drug candidates have to cross a complex protective barrier separating brain from the blood. Being able to predict a priori which molecules can successfully penetrate this barrier could be of significant value in CNS drug discovery. Herein we report a new computational approach that combines two mechanism-based models, for passive permeation and for active efflux by P-glycoprotein, to provide insight into the m ...[more]

PMID: 23421687

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Project description:Drug permeability is often a limiting step in drug action, requiring chemical optimization of a drug candidate to improve this property. Such optimization is typically performed in the context of a congeneric series, where substituents are varied to optimize the target property. Motivated by this need the present work examines the influence of chemical substituents on passive permeability (log P pass) across parallel artificial membranes (PAMPA) undertaken for three congeneric series of compounds; benzoic acids, pyridines and quinolines. PAMPA showed pyridine and quinoline to have high permeability and chemical substituents to typically reduce the permeability. On the contrary, benzoic acid showed poor permeability and chemical substituents typically increased the permeability. To quantitate these effects with respect to physical properties, models were built to explain and predict the permeability of these classes of compounds based on computed molecular descriptors. Models for the benzoic acid series in the ionized state indicated the solvent accessible surface area, cavity dispersion and the free energy of solvation in hexane as well as in water to dominate permeability. However, when the acid group is treated as neutral, the free energy of solvation in water, the fraction polar surface area, the polar surface area and difference in the free energy of solvation between hexane and water were important; these terms, among others, were also important for the neutral pyridine-quinoline series. Considering that the permeability of the benzoic acid series is about 2 orders of magnitude lower than the pyridines and quinolines and that a shift of approximately two pH units in the p K a of the acid group of benzoic acid will allow for the neutral species of the molecule to dominate under experimental conditions (pH = 6.5), these results suggest that the additional energy barrier associated with permeation of the benzoic acid series is associated with the need to protonate the acidic group, thereby forming the neutral species which may then cross the hydrophobic region of the membrane.

Dataset Information

Predicting efflux ratios and blood-brain barrier penetration from chemical structure: combining passive permeability with active efflux by P-glycoprotein.

Publications

Predicting efflux ratios and blood-brain barrier penetration from chemical structure: combining passive permeability with active efflux by P-glycoprotein.

Similar Datasets

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