Fitting the Elementary Rate Constants of the P-gp Transporter Network in the hMDR1-MDCK Confluent Cell Monolayer Using a Particle Swarm Algorithm

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

Prediction of Promiscuous P-Glycoprotein Inhibition Using a Novel Machine Learning Scheme

BACKGROUND: P-glycoprotein (P-gp) is an ATP-dependent membrane transporter that plays a pivotal role in eliminating xenobiotics by active extrusion of xenobiotics from the cell. Multidrug resistance (MDR) is highly associated with the over-expression of P-gp by cells, resulting in increased efflux of chemotherapeutical agents and reduction of intracellular drug accumulation. It is of clinical importance to develop a P-gp inhibition predictive model in the process of drug discovery and development. METHODOLOGY/PRINCIPAL FINDINGS: An in silico model was derived to predict the inhibition of P-gp using the newly invented pharmacophore ensemble/support vector machine (PhE/SVM) scheme based on the data compiled from the literature. The predictions by the PhE/SVM model were found to be in good agreement with the observed values for those structurally diverse molecules in the training set (n = 31, r(2) = 0.89, q(2) = 0.86, RMSE = 0.40, s = 0.28), the test set (n = 88, r(2) = 0.87, RMSE = 0.39, s = 0.25) and the outlier set (n = 11, r(2) = 0.96, RMSE = 0.10, s = 0.05). The generated PhE/SVM model also showed high accuracy when subjected to those validation criteria generally adopted to gauge the predictivity of a theoretical model. CONCLUSIONS/SIGNIFICANCE: This accurate, fast and robust PhE/SVM model that can take into account the promiscuous nature of P-gp can be applied to predict the P-gp inhibition of structurally diverse compounds that otherwise cannot be done by any other methods in a high-throughput fashion to facilitate drug discovery and development by designing drug candidates with better metabolism profile

Effect of P-Glycoprotein on the Rat Intestinal Permeability and Metabolism of the BDDCS Class 1 Drug Verapamil

The Biopharmaceutics Drug Disposition Classification System (BDDCS) predicts intestinal transporter effects to be clinically insignificant following oral dosing for highly soluble and highly permeable/metabolized drugs (class 1 drugs). We investigated the effect of inhibiting P-glycoprotein (P-gp) on the in vitro rat intestinal permeability (Papp) and metabolism of the class 1 drug verapamil. Jejunal segments from Sprague-Dawley rats fasted overnight were mounted in Ussing chambers filled with 10 mL of Krebs-Ringer buffer (KRB). For P-gp inhibition studies, GG918 0.5 μM was added to the KRB solution. The experiment started by the addition of verapamil (1 or 10 μM) to either apical or basolateral sides. Samples from verapamil donor and receiver compartments were collected at 30 s and 0.166, 0.5, 1, 1.83 and 3 h after the start of the experiment. Analysis of verapamil and its major metabolite, norverapamil, in the samples and intracellularly at 3 h was performed by HPLC. The same experiment was repeated with norverapamil 10 μM (verapamil metabolite), digoxin 100 nM (positive control for P-gp activity) and atorvastatin 1 and 10 μM (example of a class 2 drug). For 1 μM verapamil, efflux ratio (B to A Papp/A to B Papp) was 4.6 and markedly decreased by GG918 (efflux ratio = 1.1). For 10 μM verapamil efflux ratio was 4.1 (control) vs 1.8 (GG918), comparable to the change seen for digoxin 100 nM with an efflux ratio of 3.6 (control) vs 1.6 (with GG918) and atorvastatin (efflux ratio of 5.2 and 3.0 for atorvastatin 1.0 and 10 μM, respectively, changed to 1.0 and 0.65 with GG918). The changes observed in the norverapamil 10 μM experiment were also significant, where efflux ratio decreased from 13.5 (control) to 1.5 (GG918). The extraction ratio (ER) of 10 μM verapamil to norverapamil decreased from 0.41 after an apical dose to 0.21 after a basolateral dose, but was unaffected by the incubation with GG918. The results suggest that P-gp inhibition has an effect on class 1 drug verapamil and class 2 drug atorvastatin Papp in the rat intestine. Moreover, a stronger P-gp effect on the Papp of the more polar norverapamil metabolite was observed. Papp changes caused by the P-gp inhibitor GG918 do not affect the extent of verapamil metabolism