Search

In vitro transporter kinetics are typically analyzed by steady-state Michaelis-Menten approximations. However, no clear evidence exists that these approximations, applied to multiple transporters in biological membranes, yield system-independent mechanistic parameters needed for reliable in vivo hypothesis generation and testing. Areas covered: The classical mass action model has been developed for P-glycoprotein (P-gp) mediated transport across confluent polarized cell monolayers. Numerical integration of the mass action equations for transport using a stable global optimization program yields fitted elementary rate constants that are system-independent. The efflux active P-gp was defined by the rate at which P-gp delivers drugs to the apical chamber, since as much as 90% of drugs effluxed by P-gp partition back into nearby microvilli prior to reaching the apical chamber. The efflux active P-gp concentration was 10-fold smaller than the total expressed P-gp for Caco-2 cells, due to their microvilli membrane morphology. The mechanistic insights from this analysis are readily extrapolated to P-gp mediated transport in vivo. Expert opinion: In vitro system-independent elementary rate constants for transporters are essential for the generation and validation of robust mechanistic PBPK models. Our modeling approach and programs have broad application potential. They can be used for any drug transporter with minor adaptations.

It has been previously demonstrated that IC50 values for inhibition of digoxin transport across confluent polarized cell monolayers are system-dependent. Digoxin IC50 data from five laboratories participating in the P-glycoprotein (P-gp) IC50 Initiative, using Caco-2, MDCKII-hMDR1 or LLC-PK1-hMDR1 cells, were fitted by the structural mass action kinetic model for P-gp-mediated transport across confluent cell monolayers. We determined their efflux-active P-gp concentration [T(0)], inhibitor elementary dissociation rate constant from P-gp (krQ), digoxin basolateral uptake clearance (kB), and inhibitor binding affinity to the digoxin basolateral uptake transporter (KQB). We also fitted the IC50 data for inhibition of digoxin transport through monolayers of primary human proximal tubule cells (HPTCs). All cell systems kinetically required a basolateral uptake transporter for digoxin, which also bound to all inhibitors. The inhibitor krQ was cell system-independent, thereby allowing calculation of a system-independent Ki. The variability in efflux-active P-gp concentrations and basolateral uptake clearances in the five laboratories was about an order of magnitude. These laboratory-to-laboratory variabilities can explain more than 60% of the IC50 variability found in the principal component analysis plot in a previous study, supporting the hypothesis that the observed IC50 variability is primarily due to differences in expression levels of efflux-active P-gp and the basolateral digoxin uptake transporter. HPTCs had 10- to 100-fold lower efflux-active P-gp concentrations than the overexpressing cell lines, whereas their digoxin basolateral uptake clearances were similar. HPTC basolateral uptake of digoxin was inhibited 50% by 10 μM ouabain, suggesting involvement of OATP4C1.

From fits of drug transport kinetics across confluent MDCKII-hMDR1-NKI and Caco-2 cell monolayers we estimated the levels of efflux active P-glycoprotein (P-gp) in these two cell lines (companion paper). In the present work, we compared the efflux active P-gp number to the total P-gp level, using liquid chromatography-tandem mass spectrometry, and showed that in Caco-2 cells total P-gp is about 10-fold greater than efflux active P-gp, whereas in MDCKII-hMDR1-NKI cells these values are within twofold. We further visualized the microvilli in MDCKII-hMDR1-NKI and Caco-2 cells using three-dimensional structured illumination super-resolution microscopy and found that the microvilli in Caco-2 cells are taller and more densely packed than those in MDCK-hMDR1-NKI cells. We hypothesized over 10 years ago that only P-gp at the tips of the microvilli contribute significantly to efflux activity, whereas the remaining P-gp are involved in a futile cycle of efflux of amphipathic drugs from the microvillus membrane, followed by their reabsorption into the same or nearby microvillous membranes. The difference between the levels of total and efflux active P-gp in Caco-2 cells can be explained by the more densely packed microvilli in Caco-2 cells, which would lead to a substantial fraction of P-gp not contributing to final release of drug into the apical chamber. Our results suggest that the effect of microvilli morphology differences between in vitro and in vivo systems must be considered when scaling transporter activity for efflux transporters of amphipathic compounds, for example, P-gp.

Rosuvastatin is a widely prescribed antihyperlipidemic which undergoes limited metabolism, but is an in vitro substrate of multiple transporters [organic anion transporting polypeptide 1B1 (OATP1B1), OATP1B3, OATP1A2, OATP2B1, sodium-taurocholate cotransporting polypeptide, breast cancer resistance protein (BCRP), multidrug resistance protein 2 (MRP2), MRP4, organic anion transporter 3]. It is therefore frequently used as a probe substrate in clinical drug-drug interaction (DDI) studies to investigate transporter inhibition. Although each of these transporters is believed to play a role in rosuvastatin disposition, multiple pharmacogenetic studies confirm that OATP1B1 and BCRP play an important role in vivo. Ronacaleret, a drug-development candidate for treatment of osteoporosis (now terminated), was shown to inhibit OATP1B1 in vitro (IC50 = 11 µM), whereas it did not inhibit BCRP. Since a DDI risk through inhibition of OATP1B1 could not be discharged, a clinical DDI study was performed with rosuvastatin before initiation of phase II trials. Unexpectedly, coadministration with ronacaleret decreased rosuvastatin exposure by approximately 50%, whereas time of maximal plasma concentration and terminal half-life remained unchanged, suggesting decreased absorption and/or enhanced first-pass elimination of rosuvastatin. Of the potential in vivo rosuvastatin transporter pathways, two might explain the observed results: intestinal OATP2B1 and hepatic MRP4. Further investigations revealed that ronacaleret inhibited OATP2B1 (in vitro IC50 = 12 µM), indicating a DDI risk through inhibition of absorption. Ronacaleret did not inhibit MRP4, discharging the possibility of enhanced first-pass elimination of rosuvastatin (reduced basolateral secretion from hepatocytes into blood). Therefore, a likely mechanism of the observed DDI is inhibition of intestinal OATP2B1, demonstrating the in vivo importance of this transporter in rosuvastatin absorption in humans.

A P-glycoprotein (P-gp) IC₅₀ working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC₅₀ determinations. Each laboratory followed its in-house protocol to determine in vitro IC₅₀ values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells--Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLC-PK1-MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC₅₀ values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC₅₀ values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC₅₀ values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratio-based equation generally resulted in severalfold lower IC₅₀ values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC₅₀ values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC₅₀ determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided.

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter-knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter-mediated pharmacokinetics and drug–drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science.

The best parameters for incorporation into mechanistic physiologically based pharmacokinetic models for transporters are system-independent kinetic parameters and active (not total) transporter levels. Previously, we determined the elementary rate constants for P-glycoprotein (P-gp)-mediated transport (on- and off-rate constants from membrane to P-gp binding pocket and efflux rate constant into the apical chamber) using the structural mass action kinetic model in confluent MDCKII-hMDR1-NKI cell monolayers. In the present work, we extended the kinetic analysis to Caco-2 cells for the first time and showed that the elementary rate constants are very similar compared with MDCKII-hMDR1-NKI cells, suggesting they primarily depend on the interaction of the compound with P-gp and are therefore mostly independent of the in vitro system used. The level of efflux active (not total) P-gp is also fitted by our model. The estimated level of efflux active P-gp was 5.0 ± 1.4-fold lower in Caco-2 cells than in MDCKII-hMDR1-NKI cells. We also kinetically identified the involvement of a basolateral uptake transporter for both digoxin and loperamide in Caco-2 cells, as found previously in MDCKII-hMDR1-NKI cells, due to their low passive permeability. This demonstrates the value of our P-gp structural model as a diagnostic tool in detecting the importance of other transporters, which cannot be unambiguously done by the Michaelis-Menten approach. The system-independent elementary rate constants for P-gp obtained in vitro are more fundamental parameters than those obtained using Michaelis-Menten steady-state equations. This suggests they will be more robust mechanistic parameters for incorporation into physiologically based pharmacokinetic models for transporters.

Digoxin, an orally administered cardiac glycoside cardiovascular drug, has a narrow therapeutic window. Circulating digoxin levels (maximal concentration of ∼1.5 ng/ml) require careful monitoring, and the potential for drug-drug interactions (DDI) is a concern. Increases in digoxin plasma exposure caused by inhibition of P-glycoprotein (P-gp) have been reported. Digoxin has also been described as a substrate of various organic anion-transporting polypeptide (OATP) transporters, posing a risk that inhibition of OATPs may result in a clinically relevant DDI similar to what has been observed for P-gp. Although studies in rats have shown that Oatps contribute to the disposition of digoxin, the role of OATPs in the disposition of digoxin in humans has not been clearly defined. Using two methods, Boehringer Ingelheim, GlaxoSmithKline, Pfizer, and Solvo observed that digoxin is not a substrate of OATP1A2, OATP1B1, OATP1B3, and OATP2B1. However, digoxin inhibited the uptake of probe substrates of OATP1B1 (IC(50) of 47 μM), OATP1B3 (IC(50)8.1 μM), and OATP2B1 (IC(50)300 μM), but not OATP1A2 in transfected cell lines. It is interesting to note that digoxin is a substrate of a sodium-dependent transporter endogenously expressed in HEK293 cells because uptake of digoxin was significantly greater in cells incubated with sodium-fortified media compared with incubations conducted in media in which sodium was absent. Thus, although digoxin is not a substrate for the human OATP transporters evaluated in this study, in addition to P-gp-mediated efflux, its uptake and pharmacokinetic disposition may be partially facilitated by a sodium-dependent transporter.

The human multi-drug resistance membrane transporter, P-glycoprotein, or P-gp, has been extensively studied due to its importance to human health and disease. Thus far, the kinetic analysis of P-gp transport has been limited to steady-state Michaelis-Menten approaches or to compartmental models, neither of which can prove molecular mechanisms. Determination of the elementary kinetic rate constants of transport will be essential to understanding how P-gp works. The experimental system we use is a confluent monolayer of MDCKII-hMDR1 cells that overexpress P-gp. It is a physiologically relevant model system, and transport is measured without biochemical manipulations of P-gp. The Michaelis-Menten mass action reaction is used to model P-gp transport. Without imposing the steady-state assumptions, this reaction depends upon several parameters that must be simultaneously fitted. An exhaustive fitting of transport data to find all possible parameter vectors that best fit the data was accomplished with a reasonable computation time using a hierarchical algorithm. For three P-gp substrates (amprenavir, loperamide, and quinidine), we have successfully fitted the elementary rate constants, i.e., drug association to P-gp from the apical membrane inner monolayer, drug dissociation back into the apical membrane inner monolayer, and drug efflux from P-gp into the apical chamber, as well as the density of efflux active P-gp. All three drugs had overlapping ranges for the efflux active P-gp, which was a benchmark for the validity of the fitting process. One novel finding was that the association to P-gp appears to be rate-limited solely by drug lateral diffusion within the inner monolayer of the plasma membrane for all three drugs. This would be expected if P-gp structure were open to the lipids of the apical membrane inner monolayer, as has been suggested by recent structural studies. The fitted kinetic parameters show how P-gp efflux of a wide range of xenobiotics has been maximized.

Purpose. Three new computational strategies have been evaluated for their ability to predict intestinal membrane permeability to a series of endothelin receptor antagonists.

The gastrointestinal tract provides a variety of morphological (e.g. epithelial cells, mucus) and physiological (e.g. enzymes, pH, transporters) barriers to the absorption of peptides and proteins. Approaches to overcome these barriers have included the use of particulates which are taken up by specialized mechanisms present in M cells of the gastrointestinal tract. Due to its limited capacity, this approach has found particular application in the delivery of vaccines. In this review, morphological and physiological characteristics of the gastrointestinal tract which influence the design of particulates for oral delivery will be presented. Particulates have been designed to resist luminal factors responsible for limiting absorption and to target a specialized cell population, the M cells, within the gastrointestinal tract employing both physical and biological approaches (e.g. charge, size, hydrophobicity, surface ligands such as lectins). For vaccines, this approach may have `particular' attraction due to the signal magnification which can be accomplished in the gut associated lymphoid tissue (GALT). Recent studies have demonstrated that epithelial cells can be converted to M cells following exposure to Peyer's patch lymphocytes. Future studies designed to identify the factor(s) responsible for transient conversion of epithelial cells to M cells could provide an approach to enhance efficiency of vaccine delivery.

We have reported that the P-gp substrate digoxin required basolateral and apical uptake transport in excess of that allowed by digoxin passive permeability (as measured in the presence of GF120918) to achieve the observed efflux kinetics across MDCK-MDR1-NKI (The Netherlands Cancer Institute) confluent cell monolayers. That is, GF120918 inhibitable uptake transport was kinetically required. Therefore, IC50 measurements using digoxin as a probe substrate in this cell line could be due to inhibition of P-gp, of digoxin uptake transport, or both. This kinetic analysis is now extended to include three additional cell lines: MDCK-MDR1-NIH (National Institute of Health), Caco-2 and CPT-B2 (Caco-2 cells with BCRP knockdown). These cells similarly exhibit GF120918 inhibitable uptake transport of digoxin. We demonstrate that inhibition of digoxin transport across these cell lines by GF120918, cyclosporine, ketoconazole and verapamil is greater than can be explained by inhibition of P-gp alone. We examined three hypotheses for this non-P-gp inhibition. The inhibitors can: (1) bind to a basolateral digoxin uptake transporter, thereby inhibiting digoxin's cellular uptake; (2) partition into the basolateral membrane and directly reduce membrane permeability; (3) aggregate with digoxin in the donor chamber, thereby reducing the free concentration of digoxin, with concomitant reduction in digoxin uptake. Data and simulations show that hypothesis 1 was found to be uniformly acceptable. Hypothesis 2 was found to be uniformly unlikely. Hypothesis 3 was unlikely for GF120918 and cyclosporine, but further studies are needed to completely adjudicate whether hetero-dimerization contributes to the non-P-gp inhibition for ketoconazole and verapamil. We also find that P-gp substrates with relatively low passive permeability such as digoxin, loperamide and vinblastine kinetically require basolateral uptake transport over that allowed by +GF120918 passive permeability, while highly permeable P-gp substrates such as amprenavir, quinidine, ketoconazole and verapamil do not, regardless of whether they actually use the basolateral transporter.

In the 2012 Food and Drug Administration (FDA) draft guidance on drug-drug interactions (DDIs), a new molecular entity that inhibits Pglycoprotein (P-gp) may need a clinical DDI study with a P-gp substrate such as digoxin when themaximumconcentration of inhibitor at steady state divided by IC50 ([I1]/IC50) is0.1 or concentration of inhibitor based on highest approved dose dissolved in 250 ml divide by IC50 ([I2]/IC 50) is10. In this article, refined criteria are presented, determined by receiver operating characteristic analysis, using IC50 values generated by 23 laboratories. P-gp probe substrates were digoxin for polarized cell-lines and N-methyl quinidine or vinblastine for P-gp overexpressed vesicles. Inhibition of probe substrate transport was evaluated using 15 known P-gp inhibitors. Importantly, the criteria derived in this article take into account variability in IC50 values. Moreover, they are statistically derived based on the highest degree of accuracy in predicting true positive and true negative digoxin DDI results. The refined criteria of [I1]/IC50 0.03 and [I2]/IC50 45 and FDA criteria were applied to a test set of 101 in vitro-in vivo digoxin DDI pairs collated from the literature. The number of false negatives (none predicted but DDI observed) were similar, 10 and 12%, whereas the number of false positives (DDI predicted but not observed) substantially decreased from 51 to 40%, relative to the FDA criteria. On the basis of estimated overall variability in IC50 values, a theoretical 95%confidence interval calculation was developed for single laboratory IC 50 values, translating into a range of [I1]/IC50 and [I2]/IC50 values. The extent by which this range falls above the criteria is a measure of risk associated with the decision, attributable to variability in IC50 values. © 2013 by The American Society for Pharmacology.

Existing PBPK models incorporating intestinal first-pass metabolism account for effect of drug permeability on accessible absorption surface area by use of “effective” permeability, P eff , without adjusting number of enterocytes involved in absorption or proportion of intestinal CYP3A involved in metabolism. The current model expands on existing models by accounting for these factors. The PBPK model was developed using SAAM II. Midazolam clinical data was generated at GlaxoSmithKline. The model simultaneously captures human midazolam blood concentration profile and previously reported intestinal availability, using values for CYP3A CLu int , permeability and accessible surface area comparable to literature data. Simulations show: (1) failure to distinguish absorbing from non-absorbing enterocytes results in overestimation of intestinal metabolism of highly permeable drugs absorbed across the top portion of the villous surface only; (2) first-pass extraction of poorly permeable drugs occurs primarily in enterocytes, drugs with higher permeability are extracted by enterocytes and hepatocytes; (3) CYP3A distribution along crypt-villous axes does not significantly impact intestinal metabolism; (4) differences in permeability of perpetrator and victim drugs results in their spatial separation along the villous axis and intestinal length, diminishing drug-drug interaction magnitude. The model provides a useful tool to interrogate intestinal absorption/metabolism of candidate drugs.

We have monitored the fusion of intact A/PR/8/34 influenza virus with glycophorin-bearing liposomes and with ganglioside- (GD1a-) containing liposomes. The lipid bilayers of the glycophorin-bearing liposomes had several compositions, including pure dioleoylphosphatidylethanolamine (DOPE), pure egg phosphatidylethanolamine (EPE), and pure dioleoylphosphatidylcholine (DOPC). Examination of the temperature dependence of fusion for these and other compositions showed that even if the lipids are competent to form inverted hexagonal phases (HII), there is no enhancement of the fusion rate constant at the L alpha-HII phase transition temperature of the lipids, TH. Thus, the HII phase transition is not involved in the HA-mediated fusion mechanism. However, this mechanism is sensitive to lipid composition, in that PC bilayers fused more slowly than PE-containing bilayers above 20 degrees C. These results show that the HA-mediated fusion mechanism depends primarily upon specific lipid-protein interactions, although the fundamental parameters of lipid phase stability (interstice stabilization and monolayer spontaneous radius of curvature) may also be important. The fact that HII phase-component lipid bilayers in the glycophorin liposomes do not enhance the HA-mediated fusion rate strongly suggests that substantial bilayer-bilayer contact is not involved in HA-mediated fusion. Previously, we have shown that glycoprotein-bearing liposomes bind to HA-expressing cells specifically through HA-glycophorin interactions and that fusion is mediated by HAs not bound to glycophorin. Thus, with respect to the target membrane, the fusion site involves just the lipid bilayer. Our results with GD1a-containing liposomes strongly suggest that HAs bound to this sialic acid-bearing molecule are likewise incapable of participating in the fusion site. This could be due to a diminished lateral mobility of the HAs simultaneously bound to both closely apposed membranes. Finally, we find that the low-pH-induced viral inactivation is inhibited by binding to either glycophorin- or GD1a-containing target membranes.

β-Naphthoflavone (BNF) is a synthetic flavone that selectively and potently induces CYP1A enzymes via aryl hydrocarbon receptor activation. Mechanism-based mathematical models of CYP1A enzyme induction were developed to predict the time course of enzyme induction and quantitatively evaluate the interrelationship between BNF plasma concentrations, hepatic CYP1A1 and CYP1A2 mRNA levels, and CYP1A enzyme activity in rats in vivo. Male Sprague-Dawley rats received a continuous intravenous infusion of vehicle or 1.5 or 6 mg · kg(-1) · h(-1) BNF for 6 h, with blood and liver sampling. Plasma BNF concentrations were determined by liquid chromatography-tandem mass spectrometry. Hepatic mRNA levels of CYP1A1 and CYP1A2 were determined by TaqMan. Ethoxyresorufin O-deethylation was used to measure the increase in CYP1A enzyme activity as a result of induction. The induction of hepatic CYP1A1/CYP1A2 mRNA and CYP1A activity occurred within 2 h after BNF administration. This caused a rapid increase in metabolic clearance of BNF, resulting in plasma concentrations declining during the infusion. Overall, the enzyme induction models developed in this study adequately captured the time course of BNF pharmacokinetics, CYP1A1/CYP1A2 mRNA levels, and increases in CYP1A enzyme activity data for both dose groups simultaneously. The model-predicted degradation half-life of CYP1A enzyme activity is comparable with previously reported values. The present results also confirm a previous in vitro finding that CYP1A1 is the predominant contributor to CYP1A induction. These physiologically based models provide a basis for predicting drug-induced toxicity in humans from in vitro and preclinical data and can be a valuable tool in drug development.

From previous fits of drug transport kinetics across confluent Madin-Darby canine kidney II cell line overexpressing human multidrug resistance 1 cell monolayers, we found that a drug's binding constant to P-glycoprotein (P-gp) was significantly smaller than its IC(50) when that drug was used as an inhibitor against another P-gp substrate. We tested several IC(50) candidate functions, including the standard function, the Kalvass-Pollack function, and the efflux ratio, to determine whether any of them yielded an IC(50) = K(I), as would be expected for water-soluble enzymes. For the confluent cell monolayer, the IC(50)/K(I) ratio is greater than 1 for all candidate functions tested. From the mass action kinetic model, we have derived a simple approximate equation that shows how the IC(50)/K(I) ratio depends on the elementary rate constants from our mass action model. Thus, the IC(50) will differ between cell lines and tissues, for the same probe substrate and inhibitor, if there are different membrane concentrations of P-gp, or the probe substrate's elementary rate constants, partition coefficient, binding constant to P-gp, passive permeability, and ability to access the other transporters (if any) in the two cell lines. The mass action model and the approximate equation for the IC(50)/K(I) ratio derived here can be used to estimate the elementary rate constants needed to extrapolate in vitro drug-drug interactions for compounds to the in vivo environment.

The recent finding that more than one Influenza hemagglutinin (HA) is required at the fusion site for HA-expressing fibroblasts [1], together with the crystal structure of HA at neutral pH [2], provide the basic elements of a plausible model for this fusion site. Within an aggregate of HA trimers at low pH, we propose fusion intermediates which are based upon a minimal alteration to the known neutral pH structure of HA and which should have reasonable activation energies. This is the first model of a glycoprotein-mediated fusion site which explicitly accounts for the disposition of the lipids within these intermediates. While the fusion site created by HA will not be the same as that of eukaryotic fusion complexes [3], general characteristics could be shared.

A robust screen for compound interaction with P-glycoprotein (P-gp) has some obvious requirements, such as a cell line expressing P-gp and a probe substrate that is transported solely by P-gp and passive permeability. It is actually difficult to prove that a particular probe substrate interacts only with P-gp in the chosen cell line. Using a confluent monolayer of MDCKII-hMDR1 cells, we have determined the elementary rate constants for the P-gp efflux of amprenavir, digoxin, loperamide, and quinidine. For amprenavir and quinidine, transport was fitted with just P-gp and passive permeability. For digoxin and loperamide, fitting required a basolateral transporter (p0.01), which was inhibited by the P-gp inhibitor N-(4-[2-(1,2,3,4-tetrahydro-6,7-dimethoxy-2-isoquinolinyl)ethyl]-phenyl)-9,10-dihydro-5-methoxy-9-oxo-4-acridine carboxamide (GF120918). This means that when digoxin is used as a probe substrate and a compound is shown to inhibit digoxin flux, it could be that the inhibition occurs at the basolateral transporter rather than at P-gp. Digoxin basolateralapical efflux also required an apical importer (p0.05). We propose that amprenavir and quinidine are robust probe substrates for assessing P-gp interactions using the MDCKII-hMDR1 confluent cell monolayer. Usage of another cell line, e.g., LLC-hMDR1 or Caco-2, would require the same kinetic validation to ensure that the probe substrate interacts only with P-gp. Attempts to identify the additional digoxin and loperamide transporters using a wide range of substrates/inhibitors of known epithelial transporters (organic cation transporters, organic anion transporters, organic ion-transporting polypeptide, uric acid transporter, or multidrug resistance-associated protein) failed to inhibit the digoxin or loperamide transport through their basolateral transporter.

The multidrug resistance transporter P-glycoprotein (P-gp) effluxes a wide range of substrates and can be affected by a wide range of inhibitors or modulators. Many studies have presented classifications for these binding interactions, within either the context of equilibrium binding or the Michaelis-Menten enzyme analysis of the ATPase activity of P-gp. Our approach is to study P-gp transport and its inhibition using a physiologically relevant confluent monolayer of hMDR1-MDCKII cells. We measure the elementary rate constants for P-gp efflux of substrates and study inhibition using pairwise combinations with a different unlabeled substrate acting as the inhibitor. Our current kinetic model for P-gp has only a single binding site, because a previous study proved that the mass-action kinetics of efflux of a single substrate were not sensitive to whether there are one or more substrate-binding and efflux sites. In this study, using this one-site model, we found that, with "high" concentrations of either a substrate or an inhibitor, the elementary rate constants fitted independently for each of the substrates alone quantitatively predicted the efflux curves, simply applying the assumption that binding at the "one site" was competitive. On the other hand, at "low" concentrations of both the substrate and inhibitor, we found no inhibition of the substrate efflux, despite the fact that both the substrate and inhibitor were being well-effluxed. This was not an effect of excess "empty" P-gp molecules, because the competitive efflux model takes site occupancy into account. Rather, it is quantitative evidence that the substrate and inhibitor are being effluxed by multiple pathways within P-gp. Remarkably, increasing the substrate concentration above the "low" concentration, caused the inhibition to become competitive; i.e., the inhibitor became effective. These data and their analysis show that the binding of these substrates must be cooperative, either positive or negative.

P-glycoprotein, a human multidrug resistance transporter, has been extensively studied due to its importance to human health and disease. In order to understand transport kinetics via P-gp, confluent cell monolayers overexpressing P-gp are widely used. The purpose of this study is to obtain the mass action elementary rate constants for P-gp's transport and to functionally characterize members of P-gp's network, i.e., other transporters that transport P-gp substrates in hMDR1-MDCKII confluent cell monolayers and are essential to the net substrate flux. Transport of a range of concentrations of amprenavir, loperamide, quinidine and digoxin across the confluent monolayer of cells was measured in both directions, apical to basolateral and basolateral to apical. We developed a global optimization algorithm using the Particle Swarm method that can simultaneously fit all datasets to yield accurate and exhaustive fits of these elementary rate constants. The statistical sensitivity of the fitted values was determined by using 24 identical replicate fits, yielding simple averages and standard deviations for all of the kinetic parameters, including the efflux active P-gp surface density. Digoxin required additional basolateral and apical transporters, while loperamide required just a basolateral tranporter. The data were better fit by assuming bidirectional transporters, rather than active importers, suggesting that they are not MRP or active OATP transporters. The P-gp efflux rate constants for quinidine and digoxin were about 3-fold smaller than reported ATP hydrolysis rate constants from P-gp proteoliposomes. This suggests a roughly 3∶1 stoichiometry between ATP hydrolysis and P-gp transport for these two drugs. The fitted values of the elementary rate constants for these P-gp substrates support the hypotheses that the selective pressures on P-gp are to maintain a broad substrate range and to keep xenobiotics out of the cytosol, but not out of the apical membrane.

Publisher Summary This chapter focuses on the delivery of liposome encapsulated RNA to cells expressing influenza virus hemagglutinin. The virus binds to sialic acid-containing receptors on the target cell surface and fuses when it encounters low pH in the endosome. In this manner, the influenza virus RNA genome gains access to the cell interior for replication. In the RNA delivery scheme, HA is expressed on the target cell surface and RNA-containing liposomes are prepared with the red blood cell sialoglycoprotein, glycophorin, which provides a specific attachment site for the HA. After binding the liposomes to HA-expressing cells, fusion is induced (at the cell surface) by a brief drop in medium pH. The result is synchronous delivery of RNA into the cells. The method has been used in the laboratory for studying the replication of hepatitis delta virus, a virus with an RNA genome. This chapter also expect the method to be helpful in investigating other aspects of viral life cycles, such as packaging of the viral genome and budding of virus particles. The HA-mediated liposome delivery technique may be particularly well suited for studying the intracellular effects of antisense RNA and ribozymes, agents designed to destroy specific RNA molecules.

Human immunodeficiency virus (HIV) infects cells after binding of the viral envelope glycoprotein gp120 to the cell surface recognition marker CD4. gp120 is noncovalently associated with the HIV transmembrane envelope glycoprotein gp41, and this complex is believed responsible for the initial stages of HIV infection and cytopathic events in infected cells. Soluble constructs of CD4 that contain the gp120 binding site inhibit HIV infection in vitro. This is believed to occur by competitive inhibition of viral binding to cellular CD4. Here we suggest an alternative mechanism of viral inhibition by soluble CD4 proteins. We demonstrate biochemically and morphologically that following binding, the soluble CD4 proteins sT4, V1V2,DT, and V1[106] (amino acids 1-369, 1-183, and -2 to 106 of mature CD4) induced the release of gp120 from HIV-1 and HIV-1-infected cells. gp120 release was concentration-, time-, and temperature-dependent. The reaction was biphasic at 37 degrees C and did not take place at 4 degrees C, indicating that binding of soluble CD4 was not sufficient to release gp120. The appearance of free gp120 in the medium after incubation with sT4 correlated with a decrease in envelope glycoprotein spikes on virions and exposure of a previously cryptic epitope near the amino terminus of gp41 on virions and infected cells. The concentration of soluble CD4 proteins needed to induce the release of gp120 from virally infected cells also correlated with those required to inhibit HIV-mediated syncytium formation. These results suggest that soluble CD4 constructs may inactivate HIV by inducing the release of gp120. We propose that HIV envelope-mediated fusion is initiated following rearrangement and/or dissociation of gp120 from the gp120-gp41 complex upon binding to cellular CD4, thus exposing the fusion domain of gp41.

Influenza virus gains access to the cytoplasm of its host cell by means of a fusion event between viral and host cell membrane. Fusion is mediated by the envelope glycoprotein hemagglutinin (HA) and is triggered by low pH. To learn how many hemagglutinin trimers are necessary to cause membrane fusion, we have used two NIH 3T3 fibroblast cell lines that express HA protein at different surface densities. On the basis of quantitations of the number of HA trimers per cell and the relative surface areas of the two cell lines, the HAb-2 cells have a 1.9-fold higher plasma membrane surface density than the GP4F cells. The membrane lateral diffusion coefficient and the mobile fraction for HA is the same for both cell lines. A Scatchard analysis of the binding of glycophorin-bearing liposomes to the cells showed 1700 binding sites for the GP4F cells and 3750 binding sites for the HAb-2 cells, with effectively the same liposome-cell binding constant, about 7 x 10(10) M-1. Binding was specific for glycophorin on the liposomes and HA expressed on the cells. A competition experiment employing toxin-containing and empty liposomes allowed us to quantitate the number of liposomes that fused per cell, which was a small constant fraction of the number of bound liposomes. For the HAb-2 cells, about 1 in every 70 bound liposomes fused and for the GP4F cells about 1 in every 300 bound liposomes fused. Hence, the HAb-2 cells showed 4.4 times more fusion per bound liposome, even though the surface density of HA was only 1.9 times greater. We conclude the following: (i) One HA trimer is not sufficient to induce fusion. (ii) The HA bound to glycophorin is not the HA that induces fusion. That is, even though each HA has a binding and a fusion function, those functions are not performed by the same HA trimer.

The results indicate that sT4 (CD4) can modify mature and budding HIV virions, possibly influencing infectivity, by enhancing the removal of gp120 from the viral membrane