Development of a Computational Approach to Predict Blood-Brain Barrier Permeability

Abstract

This article is available online at http://dmd.aspetjournals.org ABSTRACT:The objectives of this study were to generate a data set of bloodbrain barrier (BBB) permeability values for drug-like compounds and to develop a computational model to predict BBB permeability from structure. The BBB permeability, expressed as permeabilitysurface area product (PS, quantified as logPS), was determined for 28 structurally diverse drug-like compounds using the in situ rat brain perfusion technique. A linear model containing three descriptors, logD, van der Waals surface area of basic atoms, and polar surface area, was developed based on 23 compounds in our data set, where the penetration across the BBB was assumed to occur primarily by passive diffusion The blood-brain barrier (BBB 1 ) consists of a continuous layer of endothelial cells joined by tight junctions at the cerebral vasculature. It represents a physical and enzymatic barrier to restrict and regulate the penetration of compounds into and out of the brain and maintain the homeostasis of the brain microenvironment (Davson and Segal, 1995). Brain penetration is essential for compounds where the site of action is within the central nervous system, whereas BBB penetration needs to be minimized for compounds that target peripheral sites to reduce potential central nervous system-related side effects. Therefore, it is critical during the drug discovery phase to select compounds that have appropriate brain penetration properties. Brain penetration is commonly assessed by two experimental approaches, namely equilibrium distribution between brain and blood and BBB permeability. The equilibrium distribution is defined as the ratio of concentrations in brain and blood (BB, quantified as logBB). LogBB is determined at

Efavirenz Is Predicted To Accumulate in Brain Tissue: an In Silico , In Vitro , and In Vivo Investigation

“…Limitations of this work include the following: the presented model does not take genetic variability (i.e., CYP2B6 variants) into account, the brain f u values were generated for rodent brains rather than human brains, the current model is not able to estimate local concentrations in individual brain regions, and the permeation of efavirenz was calculated using a quantitative structure-activity relationship (QSAR) model of passive permeability, which often relies on extrapolated data obtained from animals with important differences from humans (28,29). The CSF concentrations predicted by the model were approximately 3-fold greater than those observed in human patients.…”

A Biomathematical Modeling Approach to Central Nervous System Radioligand Discovery and Development

“…However, it is known that the endothelial membranes of the BBB contain several transport proteins that can actively transport compounds into the brain (e.g., transporters for amino acids and monocarboxylic acids) or efflux compounds from the brain (e.g., P-glycoprotein). Although several permeability models have been developed over the past few decades (10,(32)(33)(34), none was able to accurately predict permeability for all the transport mechanisms because of the complexity of these active and facilitated transport systems in the BBB. We are aware that in our validation dataset there exist several compounds that are likely to cross the BBB actively, and these have been identified in a recent study combining equilibrium dialysis assays with in vivo PET data (31).…”

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“…The BBB PS product is a better index of BBB permeability as it predicts the level of free drug in the brain, since the level of free drug is determined by the total drug concentration in plasma, the PS product, and the fraction of drug in plasma that is available for transport into the brain (Pardridge 2004b). However, most in-silico models are based on logBB value determinations (Ecker & Noe 2004), and the lack of logPS data has limited the development and validation of models that predict BBB permeability (Liu et al 2004). Table 2 is a summary of some of the in-silico models developed on the basis of logBB data.…”

“…One such model has been developed by Pfizer, which compares the logPS (determined by in-situ brain perfusions) with various parameters using 23 passively permeating drug-like compounds, and drugs that are thought to undergo active uptake and efflux (Liu et al 2004). This model included a data set of compounds that were considered representative of those that might be encountered in a drug discovery programme.…”