Perspectives in Pharmacology In Silico Predictions of Blood-Brain Barrier Penetration: Considerations to “Keep in Mind”

Within drug discovery, it is desirable to determine whether a compound will penetrate and distribute within the central nervous system (CNS) with the requisite pharmacokinetic and pharmacodynamic performance required for a CNS target or if it will be excluded from the CNS, wherein potential toxicities would mitigate its applicability. A variety of in vivo and in vitro methods for assessing CNS penetration have therefore been developed and applied to advancing drug candidates with the desired properties. In silico methods to predict CNS penetration from chemical structures have been developed to address virtual screening and prospective design. In silico predictive methods are impacted by the quality, quantity, sources, and generation of the measured data available for model development. Key considerations for predictions of CNS penetration include the comparison of local (in chemistry space) versus global (more structurally diverse) models and where in the drug discovery process such models may be best deployed. Preference should also be given to in vitro and in vivo measurements of greater mechanistic clarity that better support the development of structure-property relationships. Although there are numerous statistical methods that have been brought to bear on the prediction of CNS penetration, a greater concern is that such models are appropriate for the quality of measured data available and are statistically validated. In addition, the assessment of prediction uncertainty and relevance of predictive models to structures of interest are critical. This article will address these key considerations for the development and application of in silico methods in drug discovery. The main interfaces between the central nervous system (CNS) and the peripheral circulation are the blood-brain barrier (BBB) and the blood-cerebrospinal fluid barrier. The surface area of the former (approximately 20 m) is several thousand times larger than the latter; thus, the BBB represents the most important barrier between the CNS and the systemic circulation (Pardridge, 2002; Graff and Pollack, 2004). There are at least two aspects of the BBB that make it a formidable barrier to candidate CNS drugs. First, in terms of its morphology, the endothelial cells of which the BBB is composed are connected by complex tight junctions, which severely limit any paracellular transport. Furthermore, a minimal level of pinocytosis and lack of significant membrane fenestrae affords an additional hindrance to the transport of hydrophilic molecules. Second, the BBB includes an array of metabolic enzyme systems and efflux transporters that constitutes a biochemical barrier to the majority of xenobiotics (de Boer et al., 2003). This combination of physical and biochemical barriers establishes the BBB endothelium as quite distinct from other endothelia, and it has been estimated to prevent the brain uptake of more than 98% of potential neurotherapeutics (Pardridge, 2002). Determinants of BBB Penetration The generally accepted biophysical/physicochemical models of BBB permeability have as their primary determinants for passive transport the solute’s lipophilicity, hydrogen-bond desolvation potential, pKa/charge, and molecular size (Levin, 1980; Young et al., 1988; Jezequel, 1992; Chikhale et al., 1994; Atkinson et al., 2002; Abraham, 2004). Such models must, however, also acknowledge the potential for active mechanisms, which generally depend upon some specificity of molecular recognition and solute concentration at the Article, publication date, and citation information can be found at http://jpet.aspetjournals.org. doi:10.1124/jpet.104.075705. ABBREVIATIONS: CNS, central nervous system; BBB, blood-brain barrier; BB, blood (plasma)-brain partitioning; PS, permeability-surface area; ADMET, absorption, distribution, metabolism, excretion, toxicity; PSA, polar surface area. 0022-3565/05/3152-477–483$20.00 THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS Vol. 315, No. 2 Copyright © 2005 by The American Society for Pharmacology and Experimental Therapeutics 75705/3045525 JPET 315:477–483, 2005 Printed in U.S.A. 477 at A PE T Jornals on Jauary 3, 2016 jpet.asjournals.org D ow nladed from transporter. BBB permeability is therefore impacted by other factors that determine solute concentration at the brain capillary surface, including plasma protein binding, blood flow through and partitioning into capillary membranes, and distribution into brain parenchyma (Kalvass and Maurer, 2002). These and other pharmacokinetic parameters such as absorption, first-pass metabolism, distribution into other tissues, and elimination pathways are in turn complex functions of physicochemical, biochemical, and physiological determinants, not all of which are directly related to the chemical structure of the drug (Burton et al., 2002). The question then becomes whether, and how well, these determinants are captured by current in silico methods and which determinants can be related directly to solute chemical structure. Qualitative, expert-based rules such as those proposed by Lipinski [Raub, 2004 (http://www.aapspharmaceutica. com/meetings/files/36/Raub.revised.092804.PPT); Raub et al., 2005] or simple molecular polar surface metrics are considered grossly reflective of the major determinants of passive cellular membrane permeability (Clark, 1999). These simplified rule-based approaches have utility because they approximate our understanding of the underlying mechanisms that contribute to CNS penetration; however, they are unlikely to accurately reflect the complexity of the interactions and combination of these physicochemical and biochemical determinants. Now that predictions of CNS penetration are playing a greater role in discovery decision making, an examination of the primary endpoints that are measured and modeled is warranted. How Is BBB Permeation Measured? Log blood (plasma)-brain partitioning (BB) is a measure of the partitioning between blood (plasma) and brain tissue, quantified by the ratio of the solute concentrations in brain and plasma. Log BB is generally obtained by methods such as the brain uptake index (Ohlendorf, 1981), which measures first-pass extraction from a single intravenous injection to yield log BB. Log BB can also be determined from the bolus carotid intravenous method (Ohno et al., 1978) with area under the curve plasma quantitation and single-point brain concentration determination. In this case, a permeabilitysurface area coefficient is determined, and log BB can be calculated from log PS with certain assumptions regarding the endothelial surface area. It is an apparent value because the perfusate contains serum protein and other blood components to which the compound of interest may bind. Note that BBB permeability is implicitly captured in this measure and that it does not distinguish free and plasma-bound solute (Pardridge, 2004). It also does not address intracerebral distribution, differentiating between intracellular and extracellular concentrations. As a consequence, log BB is but a crude assessment of the likely concentrations at the targeted site of CNS activity, whether extracellular or cytosolic. Results from log BB measurements also depend upon experimental conditions, particularly dosing regimen (single bolus dose versus multiple doses versus continuous infusion) as well as sampling time from dose. Ideally, brain concentrations are measured at the plasma tmax for the solute; however, differences in brain and systemic clearance can lead to variations in the measured log BB for a given compound depending upon sampling time. It is appropriate to consider the various contributions to experimental uncertainty when employing such data in model development, particularly when attempting to infer improved performance of a given method or set of computational descriptors relative to others. When considering CNS penetration, perhaps the most appropriate in vivo measure is the log of the permeabilitysurface area coefficient (log PS) (Martin, 2004; Pardridge, 2004), which represents the permeability of a given solute across the brain capillary endothelium (the anatomical representation of the BBB). This measure reflects the free (unbound) extracellular solute concentrations and is most often performed following the perfusion method established by Takasato et al. (1984). This method eliminates serum binding and provides a direct measure of trans-BBB apparent permeability; however, it is a resource-intensive measure that requires microsurgical expertise and therefore is of relatively low throughput. Solubility of the solute of interest in the perfusate can also be a limiting factor. As with log BB, this measure does not address specific intracerebral solute tissue distribution and represents the potential combination of passive and active transport mechanisms [deconvolution requires additional experiments, perhaps in combination with in vitro methods (as addressed in Current Issues and Future Directions)]. Considering the greater mechanistic clarity of log PS compared with log BB, the former property is likely to be more informative as a measure of CNS penetration for use in lead optimization. Its value will be greatly enhanced in combination with measures of other determinants of CNS penetration, including plasma protein binding and susceptibility to active transport (Mahar-Doan et al., 2002; Raub et al., 2005). There have been numerous efforts recently to classify chemical structures as CNS or CNS , where these predictions are derived from available data for marketed compounds (for examples, see Ajay et al., 1999). These data represent pharmacological activity, which is the activity of the compound at the receptor/targeted site of action, and are indirect and implicit measures of BBB permeability and intracerebral concentration and distribution. It should be understood that if a given compound does not show CNS pharmacological activity, the compound may yet access the CNS but without the targeted or modeled pharmacological potency—“the absence of evidence is not the evidence of absence.” Such predictions may be best suited for combinatorial library design, in which a general bias for chemistries more likely to manifest CNS potency is desired, to select from among a much larger virtual or existing compound library and to reduce the burden on compound acquisition, library synthesis, or high-throughput screening resources. Another critical consideration is the utility of such classification methods (e.g., CNS versus CNS ) in prioritization and selection of potential candidates. What is the error in such classification, particularly at the boundaries separating the classes? What is the associate risk of advancing poor candidates or excluding viable candidates as a result of such classification error? Practitioners should also be cognizant of the risks in assuming that marketed drugs and existing compounds for which such pharmacological data exist represent the breadth and diversity of all chemistries likely to demonstrate favorable CNS activities. 478 Goodwin and Clark at A PE T Jornals on Jauary 3, 2016 jpet.asjournals.org D ow nladed from Why Predict BBB Permeation? What are the decisions that are made in drug discovery with respect to CNS penetration? Certainly, in the simplest terms, it is desirable to determine whether a compound will penetrate and distribute within the CNS with the requisite pharmacokinetic and pharmacodynamic performance required for a CNS target or if it will be excluded from the CNS, wherein potential toxicities would mitigate its applicability. As a result, a variety of in vivo and in vitro methods for assessing CNS penetration have been developed and applied to advancing drug candidates with the desired properties. However, such methods are inevitably resource-intensive in terms of skilled personnel, animals, cell culturing, and bioanalytical support, and they are of course retrospective in their application, requiring the existence of synthesized compound. In silico prediction methods address this limitation, supporting the prospective design and selection of candidate structures prior to synthesis.