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

Abstract

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 2 ) 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).

Drug metabolism and pharmacokinetics, the blood-brain barrier, and central nervous system drug discovery

“…Other studies have correlated brain uptake with lipophobicity, hydrogen donors/acceptors, and the number of rotatable bonds. 90,91 In silico prediction methods offer the prospect of screening libraries of actual or virtual compounds on the basis of BBB permeation. A number of such models are available.…”

“…They have evolved from simple regression models based on calculation of lipophilicity and polar surface area, to grid-based approaches; the use of artificial neural networks is also becoming very popular. 91,95 An in silico model of the BBB is clearly not going to have any construct validity, so its utility rests entirely with its power of prediction. However, because of the paucity consistent brain permeation data, effective modeling is difficult and the utility of the models questionable.…”

Gyógyszertranszporterek szerepe a központi idegrendszerben

“…Így a molekulasúly, az in vitro meghatározott passzív permeabilitás, a P-gp transzporter külcsönhatások, hidrogéndonor, illetve akceptor tulajdonság, az aromás gyűrűk száma a molekulában, a lipofilicitást jelző logPés logD-értékek, a poláros felszín aránya, a flexibilitás és a pozitív és negatív töltések száma alapján számítógépes kalkulációkat végezhetünk a barriereken való átjutás predikciójára vonatkozóan [39][40][41][42][43]. A meglévő in vitro és in vivo modellekből származó kísérletes adatokat megfelelő algoritmus segítségével használják fel ezek a mód-szerek molekulakönyvtárak vizsgálatára.…”

Impact of protein binding on receptor occupancy: A two-compartment model

“…Goodwin et al (2005)) -then from equation (9.2) it can be calculated that even drugs with low values of permeability (e.g. 10 −6 cm/s, which translates into a P S value of 0.7 L/h) and typical lipid and protein binding should achieve equilibrium within a time frame of days.…”