Computational Models for Identifying Potential P-Glycoprotein Substrates and Inhibitors

Effect of Oregon grape root extracts on P-glycoprotein mediated transport in in vitro cell lines

Purpose: This study aims to investigate the potential of Oregon grape root extracts to modulate the activity of P-glycoprotein. Methods: We performed 3H-CsA or 3H-digoxin transport experiments in the absence or presence of two sources of Oregon grape root extracts (E1 and E2), berberine or berbamine in Caco-2 and MDCKII-MDR1 cells. In addition, real time quantitative polymerase chain reaction (RT-PCR) was performed in Caco-2 and LS-180 cells to investigate the mechanism of modulating P-glycoprotein. Results: Our results showed that in Caco-2 cells, Oregon grape root extracts (E1 and E2) (0.1-1 mg/mL) inhibited the efflux of CsA and digoxin in a dose-dependent manner. However, 0.05 mg/mL E1 significantly increased the absorption of digoxin. Ten µM berberine and 30 µM berbamine significantly reduced the efflux of CsA, while no measurable effect of berberine was observed with digoxin. In the MDCKII-MDR1 cells, 10 µM berberine and 30 µM berbamine inhibited the efflux of CsA and digoxin. Lastly, in real time RT-PCR study, Oregon grape root extract (0.1 mg/mL) up-regulated mRNA levels of human MDR1 in Caco-2 and LS-180 cells at 24 h. Conclusion: Our study showed that Oregon grape root extracts modulated P-glycoprotein, thereby may affect the bioavailability of drugs that are substrates of P-glycoprotein.

Comparative in silico prediction of P-glycoprotein-mediated transport for 2010-2020 US FDA-approved drugs using six Web-tools

P-glycoprotein (P-gp) is an efflux pump implicated in pharmacokinetics and drug-drug interactions. The identification of its substrates is consequently an important issue, notably for drugs under development. For such a purpose, various in silico methods have been developed, but their relevance remains to be fully established. The present study was designed to get insight about this point, through determining the performance values of six freely accessible Web-tools (ADMETlab, AdmetSAR2.0, PgpRules, pkCSM, SwissADME and vNN-ADMET), computationally predicting P-gp-mediated transport. Using an external test set of 231 marketed drugs, approved over the 2010-2020 period by the US Food and Drug Administration and fully in vitro characterized for their P-gp substrate status, various performance parameters (including sensitivity, specificity, accuracy, Matthews correlation coefficient and area under the receiver operating characteristics curve) were determined. They were found to rather poorly meet criteria commonly required for acceptable prediction, whatever the Web-tools were used alone or in combination. Predictions of being P-gp substrate or non-substrate by these online in silico methods may therefore be considered with caution.

Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design

The objective of this study was to obtain the indicators of physicochemical parameters and structurally active sites to design new chemical entities with desirable pharmacokinetic profiles by investigating the process by which machine learning prediction models arrive at their decisions, which are called explainable artificial intelligence. First, we developed the prediction models for metabolic stability, CYP inhibition, and P-gp and BCRP substrate recognition using 265 physicochemical parameters for designing the molecular structures. Four important parameters, including the well-known indicator h_logD, are common in some in vitro studies; as such, these can be used to optimize compounds simultaneously to address multiple pharmacokinetic concerns. Next, we developed machine learning models that had been programmed to show structurally active sites. Many types of machine learning models were developed using the results of in vitro metabolic stability study of around 30000 in-house compounds. The metabolic sites of in-house compounds predicted using some prediction models matched experimentally identified metabolically active sites, with a ratio of number of metabolic sites (predicted/actual) of over 90%. These models can be applied to several screening projects. These two approaches can be employed for obtaining lead compounds with desirable pharmacokinetic profiles efficiently.

Mastering the Gram-negative bacterial barrier - Chemical approaches to increase bacterial bioavailability of antibiotics

To win the battle against resistant, pathogenic bacteria, novel classes of anti-infectives and targets are urgently needed. Bacterial uptake, distribution, metabolic and efflux pathways of antibiotics in Gram-negative bacteria determine what we here refer to as bacterial bioavailability. Understanding these mechanisms from a chemical perspective is essential for anti-infective activity and hence, drug discovery as well as drug delivery. A systematic and critical discussion of in bacterio, in vitro and in silico assays reveals that a sufficiently accurate holistic approach is still missing. We expect new findings based on Gram-negative bacterial bioavailability to guide future anti-infective research.

Expanding the Efflux In Vitro Assay Toolbox: A CRISPR-Cas9 Edited MDCK Cell Line with Human BCRP and Completely Lacking Canine MDR1

The Breast Cancer Resistance Protein (BCRP) is a key transporter in drug efflux and drug-drug interactions. However, endogenous expression of Multidrug Resistance Protein 1 (MDR1) confounds the interpretation of BCRP-mediated transport in in vitro models. Here we used a CRISPR-Cas9 edited Madin-Darby canine kidney (MDCK) II cell line (MDCK^cMDR1-KO) for stable expression of human BCRP (hBCRP) with no endogenous canine MDR1 (cMDR1) expression (MDCK-hBCRP^cMDR1-KO). Targeted quantitative proteomics verified expression of hBCRP, and global analysis of the entire proteome corroborated no or very low background expression of other drug transport proteins or metabolizing enzymes. This new cell line, had similar proteome like MDCK^cMDR1-KO and a previously established, corresponding cell line overexpressing human MDR1 (hMDR1), MDCK-hMDR1^cMDR1-KO. Functional studies with MDCK-hBCRP^cMDR1-KO confirmed high hBCRP activity. The MDCK-hBCRP^cMDR1-KO cell line together with the MDCK-hMDR1^cMDR1-KO easily and accurately identified shared or specific substrates of the hBCRP and the hMDR1 transporters. These cell lines offer new, improved in vitro tools for the assessment of drug efflux and drug-drug interactions in drug development.

P-Glycoprotein-Mediated Efflux Using a Rapidly Maturing Caco2 Clone (CLEFF4) in Only 5 Days without Requiring Modified Growth Medium

In drug discovery it is essential that one of the parameters tested for any new chemical entity is its affinity for human efflux systems, most notably P-glycoprotein (P-gp). These efflux systems affect not only rates of oral absorption but also rates of excretion through the liver, blood-brain barrier, and accumulation in potential target cells that upregulate efflux systems. Current methods to determine drugs' P-gp transport potential include in vitro bidirectional transport studies, and the two most common cell lines used are Caco2 and MDR1-transfected MDCK models. Caco2 cells are human but slow growing and require more than 3 weeks to mature, while MDCK cells are canine, but when transfected with human P-gp become a rapid model of P-gp affinity. Our laboratory has generated a Caco2 subclone called CLEFF4 that is fully human, yet now approaches the rapid nature of the MDCK model. No special medium is required. We have shown, in as little as 5 days postseeding, high transepithelial electrical resistance values of more than 1000 Ω·cm² plus P-gp expression more than threefold higher than that of 21-day-old cells. Currently tested drugs included rhodamine 123 (Rh123), vinblastine, and doxorubicin, and all drugs exhibited P-gp-mediated efflux that was inhibited by PSC833. By day 6, bidirectional transport of Rh123 was as potent as that of mature Caco2 cells, for use in comparative P-gp affinity studies. We now have a human P-gp model that is rapid and works without any need for special accelerating medium. We believe this could be a welcome addition to the testing regime of new chemical entities.

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from non-inhibitors using molecular solvation theory with excellent accuracy and precision. The excess chemical potential and partial molar volume in various solvents are calculated for PgP± (PgP inhibitors and non-inhibitors) compounds with the statistical-mechanical based three-dimensional reference interaction site model with the Kovalenko-Hirata closure approximation (3D-RISM-KH molecular theory of solvation). The statistical importance analysis of descriptors identified the 3D-RISM-KH based descriptors as top molecular descriptors for classification. Among the constructed classification models, the support vector machine predicted the test set of Pgp± compounds with highest accuracy and precision of ~ 97% for test set. The validation of models confirms the robustness of state-of-the-art molecular solvation theory based descriptors in identification of the Pgp± compounds.

Using Caffeine and Free Amino Acids To Enhance the Transepithelial Transport of Catechins in Caco-2 Cells

Catechins are well-known to possess health-promoting functions. The interaction of the catechins with other components in tea could alter their absorption and efflux. This study investigated whether the absorption of catechins is affected by caffeine and amino acids using the Caco-2 monolayer cell model. We found that (-)-epigallocatechin gallate (EGCG), (-)-epicatechin gallate (ECG), and (-)-epicatechin (EC) were all actively effluxed. Co-transportation of EGCG, ECG, or EC with caffeine, theanine, serine, or glycine increased their apparent permeability coefficient [ P_app(AP-BL)] value by 3.42-5.40- fold, 1.19-5.75-fold, and 1.55-8.01-fold, respectively. Meanwhile, their efflux ratio values were significantly decreased. Moreover, the expression of multi-drug resistance protein 2 (MRP2) after 3 h of incubation with either 50 μM EGCG or 50 μM EC was elevated by 1.58- and 2.98-fold, respectively, while 50 μM ECG had no significantly effects. In addition, the expression of P-glycoprotein (P-gp) after treatment with either 50 μM EGCG, 50 μM ECG, or 50 μM EC was enhanced by 1.53-, 1.63-, and 1.80-fold, respectively. The addition of either caffeine or any one of the three amino acids decreased the expression of both MRP2 and P-gp induced by EGCG, and the expression of P-gp induced by ECG or EC also decreased. In contrast, only glycine decreased the expression of MRP2 induced by EC. Taken together, our data indicated that caffeine and theanine, glycine, or serine in tea might increase the absorption of catechins by the selectively suppressed expression of the efflux transporters induced by catechins.

Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico Prediction Models To Evaluate Transport Potential of P-Glycoprotein

For efficient drug discovery and screening, it is necessary to simplify P-glycoprotein (P-gp) substrate assays and to provide in silico models that predict the transport potential of P-gp. In this study, we developed a simplified in vitro screening method to evaluate P-gp substrates by unidirectional membrane transport in P-gp-overexpressing cells. The unidirectional flux ratio positively correlated with parameters of the conventional bidirectional P-gp substrate assay ( R² = 0.941) and in vivo K_p,brain ratio (mdr1a/1b KO/WT) in mice ( R² = 0.800). Our in vitro P-gp substrate assay had high reproducibility and required approximately half the labor of the conventional method. We also constructed regression models to predict the value of P-gp-mediated flux and three-class classification models to predict P-gp substrate potential (low-, medium-, and high-potential) using 2397 data entries with the largest data set collected under the same experimental conditions. Most compounds in the test set fell within two- and three-fold errors in the random forest regression model (71.3 and 88.5%, respectively). Furthermore, the random forest three-class classification model showed a high balanced accuracy of 0.821 and precision of 0.761 for the low-potential classes in the test set. We concluded that the simplified in vitro P-gp substrate assay was suitable for compound screening in the early stages of drug discovery and that the in silico regression model and three-class classification model using only chemical structure information could identify the transport potential of compounds including P-gp-mediated flux ratios. Our proposed method is expected to be a practical tool to optimize effective central nervous system (CNS) drugs, to avoid CNS side effects, and to improve intestinal absorption.

Excess glutamate secreted from astrocytes drives upregulation of P-glycoprotein in endothelial cells in amyotrophic lateral sclerosis

In amyotrophic lateral sclerosis (ALS), upregulation in expression and activity of the ABC transporter P-glycoprotein (P-gp) driven by disease advancement progressively reduces CNS penetration and efficacy of the ALS drug, riluzole. Post-mortem spinal cord tissues from ALS patients revealed elevated P-gp expression levels in endothelial cells of the blood-spinal cord barrier compared to levels measured in control, non-diseased individuals. We recently found that astrocytes expressing familial ALS-linked SOD1 mutations regulate expression levels of P-gp in endothelial cells, which also exhibit a concomitant, significant increase in reactive oxygen species production and NFκB nuclear translocation when exposed to mutant SOD1 astrocyte conditioned media. In this study, we found that glutamate, which is abnormally secreted by mutant SOD1 and sporadic ALS astrocytes, drives upregulation of P-gp expression and activity levels in endothelial cells via activation of N-Methyl-D-Aspartic acid (NMDA) receptors. Surprisingly, astrocyte-secreted glutamate regulation of endothelial P-gp levels is not a mechanism shared by all forms of ALS. C9orf72-ALS astrocytes had no effect on endothelial cell P-gp expression and did not display increased glutamate secretion. Utilizing an optimized in vitro human BBB model consisting of patient-derived induced pluripotent stem cells, we showed that co-culture of endothelial cells with patient-derived astrocytes increased P-gp expression levels and transport activity, which was significantly reduced when endothelial cells were incubated with the NMDAR antagonist, MK801. Overall, our findings unraveled a complex molecular interplay between astrocytes of different ALS genotypes and endothelial cells potentially occurring in disease that could differentially impact ALS prognosis and efficacy of pharmacotherapies.

Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates

Feature selection is commonly used as a preprocessing step to machine learning for improving learning performance, lowering computational complexity and facilitating model interpretation. This paper proposes the application of boosting feature selection to improve the classification performance of standard feature selection algorithms evaluated for the prediction of P-gp inhibitors and substrates. Two well-known classification algorithms, decision trees and support vector machines, were used to classify the chemical compounds. The experimental results showed better performance for boosting feature selection with respect to the standard feature selection algorithms while maintaining the capability for feature reduction.

Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression Scheme

P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood⁻brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorption and disposition of a wide range of substrates. Nevertheless, the mechanism of P-gp substrate efflux is rather complex since it can take place through active transport and passive permeability in addition to multiple P-gp substrate binding sites. A nonlinear quantitative structure⁻activity relationship (QSAR) model was developed in this study using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to explore the perplexing relationships between descriptors and efflux ratio. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (n = 50, r² = 0.96, qCV2 = 0.94, RMSE = 0.10, s = 0.10) and test set (n = 13, q² = 0.80⁻0.87, RMSE = 0.21, s = 0.22). When subjected to a variety of statistical validations, the developed HSVR model consistently met the most stringent criteria. A mock test also asserted the predictivity of HSVR. Consequently, this HSVR model can be adopted to facilitate drug discovery and development.

Inhibition of P-Glycoprotein Mediated Efflux in Caco-2 Cells by Phytic Acid

Phytic acid (IP6) is a natural phosphorylated inositol, which is abundantly present in most cereal grains and seeds. This study investigated the effects of IP6 regulation on P-glycoprotein (P-gp) and its potential mechanisms using in situ and in vitro models. The effective permeability of the typical P-gp substrate rhodamine 123 (R123) in colon was significantly increased from (1.69 ± 0.22) × 10^-5 cm/s in the control group to (3.39 ± 0.417) × 10^-5 cm/s (p < 0.01) in the 3.5 mM IP6 group. Additionally, IP6 can concentration-dependently decrease the R123 efflux ratio in both Caco-2 and MDCK II-MDR1 cell monolayers and increase intracellular R123 accumulation in Caco-2 cells. Furthermore, IP6 noncompetitively inhibited P-gp by impacting R123 efflux kinetics. The noncompetitive inhibition of P-gp by IP6 was likely due to decreases in P-gp ATPase activity and P-gp molecular conformational changes induced by IP6. In summary, IP6 is a promising P-gp inhibitor candidate.

Comprehensive Synthesis of Amino Acid-Derived Thiazole Peptidomimetic Analogues to Understand the Enigmatic Drug/Substrate-Binding Site of P-Glycoprotein

A novel set of 64 analogues based on our lead compound 1 was designed and synthesized with an initial objective of understanding the structural requirements of ligands binding to a highly perplexing substrate-binding site of P-glycoprotein (P-gp) and their effect on modulating the ATPase function of the efflux pump. Compound 1, a stimulator of P-gp ATPase activity, was transformed to ATPase inhibitory compounds 39, 53, and 109. The ATPase inhibition by these compounds was predominantly contributed by the presence of a cyclohexyl group in lieu of the 2-aminobenzophenone moiety of 1. The 4,4-difluorocyclohexyl analogues, 53 and 109, inhibited the photolabeling by [¹²⁵I]-IAAP, with IC₅₀ values of 0.1 and 0.76 μM, respectively. Selected compounds were shown to reverse paclitaxel resistance in HEK293 cells overexpressing P-gp and were selective toward P-gp over CYP3A4. Induced-fit docking highlighted a plausible binding pattern of inhibitory compounds in the putative-binding pocket of P-gp. The current study underscores the stringent requirement by P-gp to bind to chemically similar molecules.

A novel adaptive ensemble classification framework for ADME prediction

AECF is a GA based ensemble method. It includes four components which are (1) data balancing, (2) generating individual models, (3) combining individual models, and (4) optimizing the ensemble.

Study of Structure and Permeability Relationship of Flavonoids in Caco-2 Cells

Flavonoids exhibit a broad range of biological activities. However, poor absorption of some flavonoids is a major limitation for use of flavonoids as nutraceuticals. To investigate the structure requirements for flavonoids intestinal absorption, transepithelial transport and cellular accumulation (CA) of 30 flavonoids were determined using the Caco-2 cell monolayer. The bilateral permeation of five types of flavonoids followed the order: flavanones ≥ isoflavones > flavones ≥ chalcones > flavonols. The concentration of flavonoids accumulated in cells did not correlate with cell penetration since the correlation coefficient between the apparent permeability coefficient (P_app) and their corresponding CA was poor (R² < 0.3). Most flavonoids exhibited a ratio of 0.8–1.5 for P_{app A to B}/P_{app B to A}, suggesting passive diffusion pathways. However, luteolin, morin and taxifolin may involve the efflux mechanisms. The quantitative structure-permeability relationship (QSPR) study demonstrated that the intestinal absorption of flavonoids can be related to atomic charges on carbon 3′ (Q_C3′), molecule surface area (SlogP_V3), balance between the center of mass and position of hydrophobic region (vsurf_ID1) and solvation energy of flavonoids (E_sol). These results provide useful information for initially screening of flavonoids with high intestinal absorption.

Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA

The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

Semi-synthetic ocotillol analogues as selective ABCB1-mediated drug resistance reversal agents

Overexpression of ATP-Binding Cassette transporters leads to multidrug resistance in cancer cells and results in the failure of chemotherapy. In this in-vitro study, we investigated whether or not (20S, 24R/S)-epoxy-12β, 25-dihydroxy-dommarane-3β-amine (ORA and OSA), a pair of semi-synthetic ocotillol analogue epimers, could inhibit the ABCB1 transporter. ORA (1 μM and 3 μM) significantly reversed the resistance to paclitaxel and vincristine in ABCB1-overexpressing SW620/Ad300 and HEK/ABCB1 cells, whereas OSA had no significant effects. In addition, ORA (3 μM) significantly increased the intracellular accumulation of [3H]-paclitaxel by suppressing the efflux function of ABCB1. Meanwhile, both ORA (3 μM) and OSA (3 μM) did not significantly alter the expression level or the subcellular location of ABCB1 protein. Moreover, the ABCB1 ATPase study suggested that ORA had a stronger stimulatory effect on the ATPase activity than OSA. ORA also exhibited a higher docking score as compared with OSA inside transmembrane domain of ABCB1. Overall, we concluded that ORA reverse ABCB1-mediated MDR by competitively inhibiting the ABCB1 drug efflux function.

[Classification models of structure - P-glycoprotein activity of drugs]

Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1÷5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation. In the second case forward selection procedure up to 5 descriptors, starting from the best single descriptor was used. This strategy was applied to a set of 387 DRAGON descriptors. It was found that only one of 33 models has necessary statistical parameters. This model was designed by means of the linear discriminant analysis on the basis of a single descriptor of H-bond (ΣC(ad)). The model has good statistical characteristics as evidenced by results to both internal cross-validation, and external validation with application of 44 new chemicals. This confirms an important role of hydrogen bond in the processes connected with penetration of chemical compounds through a blood-brain barrier.

The Interactions of P-Glycoprotein with Antimalarial Drugs, Including Substrate Affinity, Inhibition and Regulation

The combination of passive drug permeability, affinity for uptake and efflux transporters as well as gastrointestinal metabolism defines net drug absorption. Efflux mechanisms are often overlooked when examining the absorption phase of drug bioavailability. Knowing the affinity of antimalarials for efflux transporters such as P-glycoprotein (P-gp) may assist in the determination of drug absorption and pharmacokinetic drug interactions during oral absorption in drug combination therapies. Concurrent administration of P-gp inhibitors and P-gp substrate drugs may also result in alterations in the bioavailability of some antimalarials. In-vitro Caco-2 cell monolayers were used here as a model for potential drug absorption related problems and P-gp mediated transport of drugs. Artemisone had the highest permeability at around 50 x 10(-6) cm/sec, followed by amodiaquine around 20 x 10(-6) cm/sec; both mefloquine and artesunate were around 10 x 10(-6) cm/sec. Methylene blue was between 2 and 6 x 10(-6) cm/sec depending on the direction of transport. This 3 fold difference was able to be halved by use of P-gp inhibition. MRP inhibition also assisted the consolidation of the methylene blue transport. Mefloquine was shown to be a P-gp inhibitor affecting our P-gp substrate, Rhodamine 123, although none of the other drugs impacted upon rhodamine123 transport rates. In conclusion, mefloquine is a P-gp inhibitor and methylene blue is a partial substrate; methylene blue may have increased absorption if co-administered with such P-gp inhibitors. An upregulation of P-gp was observed when artemisone and dihydroartemisinin were co-incubated with mefloquine and amodiaquine.

Discovery of 4-acetyl-3-(4-fluorophenyl)-1-(p-tolyl)-5-methylpyrrole as a dual inhibitor of human P-glycoprotein and Staphylococcus aureus Nor A efflux pump

Polysubstituted pyrrole natural products, lamellarins, are known to overcome multi-drug resistance in cancer via the inhibition of p-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) efflux pumps. Herein, a series of simplified polysubstituted pyrroles, prepared via a one-pot domino protocol, were screened for P-gp inhibition in P-gp overexpressing human adenocarcinoma LS-180 cells using a rhodamine 123 efflux assay. Several compounds showed the significant inhibition of P-gp at 50 μM, as indicated by increase in the intracellular accumulation of Rh123 in LS-180 cells. Furthermore, pyrrole 5i decreased the efflux of digoxin, a FDA approved P-gp substrate in MDCK-MDR1 cells with an IC50 of 11.2 μM. In in vivo studies, following the oral administration of a P-gp substrate drug, rifampicin, along with compound , the Cmax and AUC0-∞ of rifampicin was enhanced by 31% and 46%, respectively. All the compounds were then screened for their ability to potentiate ciprofloxacin activity via the inhibition of Staphylococcus aureus Nor A efflux pump. Pyrrole showed the significant inhibition of S. aureus Nor A efflux pump with 8- and 4-fold reductions in the MIC of ciprofloxacin at 50 and 6.25 μM, respectively. The molecular docking studies of compound with the human P-gp and S. aureus Nor A efflux pump identified its plausible binding site and key interactions. Thus, the results presented herein strongly indicate the potential of this scaffold for its use as multi-drug resistance reversal agent or bioavailability enhancer.

Development of in Silico Models for Predicting P-Glycoprotein Inhibitors Based on a Two-Step Approach for Feature Selection and Its Application to Chinese Herbal Medicine Screening

P-glycoprotein (P-gp) is regarded as an important factor in determining the ADMET (absorption, distribution, metabolism, elimination, and toxicity) characteristics of drugs and drug candidates. Successful prediction of P-gp inhibitors can thus lead to an improved understanding of the underlying mechanisms of both changes in the pharmacokinetics of drugs and drug-drug interactions. Therefore, there has been considerable interest in the development of in silico modeling of P-gp inhibitors in recent years. Considering that a large number of molecular descriptors are used to characterize diverse structural moleculars, efficient feature selection methods are required to extract the most informative predictors. In this work, we constructed an extensive available data set of 2428 molecules that includes 1518 P-gp inhibitors and 910 P-gp noninhibitors from multiple resources. Importantly, a two-step feature selection approach based on a genetic algorithm and a greedy forward-searching algorithm was employed to select the minimum set of the most informative descriptors that contribute to the prediction of P-gp inhibitors. To determine the best machine learning algorithm, 18 classifiers coupled with the feature selection method were compared. The top three best-performing models (flexible discriminant analysis, support vector machine, and random forest) and their ensemble model using respectively only 3, 9, 7, and 14 descriptors achieve an overall accuracy of 83.2%-86.7% for the training set containing 1040 compounds, an overall accuracy of 82.3%-85.5% for the test set containing 1039 compounds, and a prediction accuracy of 77.4%-79.9% for the external validation set containing 349 compounds. The models were further extensively validated by DrugBank database (1890 compounds). The proposed models are competitive with and in some cases better than other published models in terms of prediction accuracy and minimum number of descriptors. Applicability domain then was addressed by developing an ensemble classification model to obtain more reliable predictions. Finally, we employed these models as a virtual screening tool for identifying potential P-gp inhibitors in Traditional Chinese Medicine Systems Pharmacology (TCMSP) database containing a total of 13 051 unique compounds from 498 herbs, resulting in 875 potential P-gp inhibitors and 15 inhibitor-rich herbs. These predictions were partly supported by a literature search and are valuable not only to develop novel P-gp inhibitors from TCM in the early stages of drug development, but also to optimize the use of herbal remedies.

In silico ADME/T modelling for rational drug design

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

A high throughput flow cytometric assay platform targeting transporter inhibition

This review highlights the concepts, recent applications and limitations of High Throughput Screening (HTS) flow cytometry-based efflux inhibitory assays. This platform has been employed in mammalian and yeast efflux systems leading to the identification of small molecules with transporter inhibitory capabilities. This technology offers the possibility of substrate multiplexing and may promote novel strategies targeting microbial efflux systems. This platform can generate a comprehensive dataset that may support efforts to map the interface between chemistry and transporter biology in a variety of pathogenic systems.

Homology modelling and molecular docking of MDR1 with chemotherapeutic agents in non-small cell lung cancer

MDR1, a protein commonly involved in drug transport, has been linked to multi drug resistance and disease progression in cancers such as non-small cell lung cancer. Hence, targeting this protein is essential for improving drug design and preventing adverse drug-drug interactions. The aim of the study was to examine chemotherapeutic drug binding to MDR1 and the interactions therein. We have used Schrödinger suite 2014, to perform homology modelling of human MDR1 based on Mouse MDR1, followed by Induced Fit Docking with Paclitaxel, Docetaxel, Gemcitabine, Carboplatin and Cisplatin drugs. Finally, we evaluated drug binding affinities using Prime/MMGBSA and using these scores we compared the affinities of combination therapies against MDR1. Analysis of the docking results showed Paclitaxel>Docetaxel>Gemcitabine>Carboplatin>Cisplatin as the order of binding affinities, with Paclitaxel having the best docking score. The combination drug binding affinity analysis showed Paclitaxel+Gemcitabine to have the best docking score and hence, efficacy. Through our investigation we have identified the residues Gln 195 and Gln 946 to be more frequently involved in drug binding interactions with MDR1. Our results suggest that, Paclitaxel or combination of Paclitaxel+Gemcitabine could serve as a suitable therapy against MDR1 in NSCLC patients. Thus, our study provides new insight into the possible repurposing of chemotherapeutic drugs in targeting elevated MDR1 levels in NSCLC patients, thereby ensuring better overall outcome. Further our study highlights the use of in silico methodologies in understanding drug binding to protein targets and its relevance to advancing lung cancer therapy.

Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks

P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approach in the fight against cancer. Therefore, the discovery of P-gp inhibitors is considered one of the most popular strategies to reverse MDR in tumour cells and to improve therapeutic efficacy of commonly used cytotoxic drugs. Until now, several generations of P-gp inhibitors have been developed but they have largely failed in preclinical and clinical studies due to lack of selectivity, poor solubility and severe pharmacokinetic interactions. In this study, three models (SION, SIO, SIN) to classify specific 'true' P-gp inhibitors as well as three other models (CPBN, CPB1, CPN) to distinguish between P-gp inhibitors, CYP 3A inhibitors and co-inhibitors of these proteins with rather high accuracy values for the test set and the external set were generated based on counter-propagation neural networks (CPG-NN). Such three and four-class classification models helped provide more information about the bioactivities of compounds not only on one target (P-gp), but also on a combination of multiple targets (P-gp, CYP 3A).

Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein

P-glycoprotein (P-gp/ABCB1) and breast cancer resistance protein (BCRP/ABCG2) are two members of the adenosine triphosphate (ATP) binding cassette (ABC) family of transporters which function as membrane efflux transporters and display considerable substrate promiscuity. Both are known to significantly influence the absorption, distribution and elimination of drugs, mediate drug-drug interactions and contribute to multiple drug resistance (MDR) of cancer cells. Correspondingly, timely characterization of the interaction of novel leads and drug candidates with these two transporters is of great importance. In this study, several computational classification models for prediction of transport and inhibition of P-gp and BCRP, respectively, were developed based on newly compiled and critically evaluated experimental data. Artificial neural network (ANN) and support vector machine (SVM) ensemble based models were explored, as well as knowledge-based approaches to descriptor selection. The average overall classification accuracy of best performing models was 82% for P-gp transport, 88% for BCRP transport, 89% for P-gp inhibition and 87% for BCRP inhibition, determined across an array of different test sets. An analysis of substrate overlap between P-gp and BCRP was also performed. The accuracy, simplicity and interpretability of the proposed models suggest that they could be of significant utility in the drug discovery and development settings.

Modulation of P-glycoprotein efflux pump: induction and activation as a therapeutic strategy

P-glycoprotein (P-gp) is an ATP-dependent efflux pump encoded by the MDR1 gene in humans, known to mediate multidrug resistance of neoplastic cells to cancer therapy. For several decades, P-gp inhibition has drawn many significant research efforts in an attempt to overcome this phenomenon. However, P-gp is also constitutively expressed in normal human epithelial tissues and, due to its broad substrate specificity, to its cellular polarized expression in many excretory and barrier tissues, and to its great efflux capacity, it can play a crucial role in limiting the absorption and distribution of harmful xenobiotics, by decreasing their intracellular accumulation. Such a defense mechanism can be of particular relevance at the intestinal level, by significantly reducing the intestinal absorption of the xenobiotic and, consequently, avoiding its access to the target organs. In this review, the current knowledge on this important efflux pump is summarized, and a new focus is brought on the therapeutic interest of inducing and/or activating P-gp for limiting the toxicity caused by its substrates. Several in vivo and in vitro studies validating the use of such a therapeutic strategy are discussed. An extensive literature search for reported P-gp inducers/activators and for the experimental models used in their characterization was conducted. Those studies demonstrate that effective antidotal pathways can be achieved by efficiently promoting the P-gp-mediated efflux of deleterious xenobiotics, resulting in a significant reduction in their intracellular levels and, consequently, in a significant reduction of their toxicity.

Repositioning of Tyrosine Kinase Inhibitors as Antagonists of ATP-Binding Cassette Transporters in Anticancer Drug Resistance

The phenomenon of multidrug resistance (MDR) has attenuated the efficacy of anticancer drugs and the possibility of successful cancer chemotherapy. ATP-binding cassette (ABC) transporters play an essential role in mediating MDR in cancer cells by increasing efflux of drugs from cancer cells, hence reducing the intracellular accumulation of chemotherapeutic drugs. Interestingly, small-molecule tyrosine kinase inhibitors (TKIs), such as AST1306, lapatinib, linsitinib, masitinib, motesanib, nilotinib, telatinib and WHI-P154, have been found to have the capability to overcome anticancer drug resistance by inhibiting ABC transporters in recent years. This review will focus on some of the latest and clinical developments with ABC transporters, TKIs and anticancer drug resistance.

Design and synthesis of human ABCB1 (P-glycoprotein) inhibitors by peptide coupling of diverse chemical scaffolds on carboxyl and amino termini of (S)-valine-derived thiazole amino acid

P-glycoprotein (P-gp) serves as a therapeutic target for the development of multidrug resistance reversal agents. In this study, we synthesized 21 novel compounds by peptide coupling at corresponding carboxyl and amino termini of (S)-valine-based bis-thiazole and monothiazole derivatives with diverse chemical scaffolds. Using calcein-AM efflux assay, we identified compound 28 (IC₅₀ = 1.0 μM) carrying 3,4,5-trimethoxybenzoyl and 2-aminobenzophenone groups, respectively, at the amino and carboxyl termini of the monothiazole zwitter-ion. Compound 28 inhibited the photolabeling of P-gp with [¹²⁵I]-iodoarylazidoprazosin with IC₅₀ = 0.75 μM and stimulated the basal ATP hydrolysis of P-gp in a concentration-dependent manner (EC₅₀ ATPase = 0.027 μM). Compound 28 at 3 μM reduced resistance in cytotoxicity assay to paclitaxel in P-gp-expressing SW620/Ad300 and HEK/ABCB1 cell lines. Biochemical and docking studies showed site-1 to be the preferable binding site for 28 within the drug-binding pocket of human P-gp.

Synthesis, biological evaluation and 3D-QSAR studies of new chalcone derivatives as inhibitors of human P-glycoprotein

P-glycoprotein (P-gp) is an ATP-dependent multidrug resistance efflux transporter that plays an important role in anticancer drug resistance and in pharmacokinetics of medicines. Despite a large number of structurally and functionally diverse compounds, also flavonoids and chalcones have been reported as inhibitors of P-gp. The latter share some similarity with the well studied class of propafenones, but do not contain a basic nitrogen atom. Furthermore, due to their rigidity, they are suitable candidates for 3D-QSAR studies. In this study, a set of 22 new chalcone derivatives were synthesized and evaluated in a daunomycin efflux inhibition assay using the CCRF.CEM.VCR1000 cell line. The compound 10 showed the highest activity (IC50=42nM), which is one order of magnitude higher than the activity for an equilipohillic propafenone analogue. 2D- and 3D-QSAR studies indicate the importance of H-bond acceptors, methoxy groups, hydrophobic groups as well as the number of rotatable bonds as pharmacophoric features influencing P-gp inhibitory activity.

Design, synthesis, and biological evaluation of (S)-valine thiazole-derived cyclic and noncyclic peptidomimetic oligomers as modulators of human P-glycoprotein (ABCB1)

Multidrug resistance caused by ATP binding cassette transporter P-glycoprotein (P-gp) through extrusion of anticancer drugs from the cells is a major cause of failure in cancer chemotherapy. Previously, selenazole-containing cyclic peptides were reported as P-gp inhibitors and were also used for co-crystallization with mouse P-gp, which has 87 % homology to human P-gp. It has been reported that human P-gp can simultaneously accommodate two to three moderately sized molecules at the drug binding pocket. Our in silico analysis, based on the homology model of human P-gp, spurred our efforts to investigate the optimal size of (S)-valine-derived thiazole units that can be accommodated at the drug binding pocket. Towards this goal, we synthesized varying lengths of linear and cyclic derivatives of (S)-valine-derived thiazole units to investigate the optimal size, lipophilicity, and structural form (linear or cyclic) of valine-derived thiazole peptides that can be accommodated in the P-gp binding pocket and affects its activity, previously an unexplored concept. Among these oligomers, lipophilic linear (13) and cyclic trimer (17) derivatives of QZ59S-SSS were found to be the most and equally potent inhibitors of human P-gp (IC50 =1.5 μM). As the cyclic trimer and linear trimer compounds are equipotent, future studies should focus on noncyclic counterparts of cyclic peptides maintaining linear trimer length. A binding model of the linear trimer 13 within the drug binding site on the homology model of human P-gp represents an opportunity for future optimization, specifically replacing valine and thiazole groups in the noncyclic form.

Computer modeling of blood brain barrier permeability of physiologically active compounds

At present work discusses the current level of computer modeling the relationship structure of organic compounds and drugs and their ability to penetrate the BBB. All descriptors that influence to this permeability within classification and regression QSAR models are generalized and analyzed. The crucial role of H-bond in processes both passive, and active transport across BBB is observed. It is concluded that further research should be focused on interpretation the spatial structure of a full-size P-glycoprotein molecule with high resolution and the creation of QSAR models describing the quantitative relationship between structure and active transport of substances across BBB.

Osthol and curcumin as inhibitors of human Pgp and multidrug efflux pumps of Staphylococcus aureus: reversing the resistance against frontline antibacterial drugs

Curcumin and osthol are identified as NorA pump inhibitors.

Fluorescent probes of the isoxazole-dihydropyridine scaffold: MDR-1 binding and homology model

Isoxazole-1,4-dihydropyridines (IDHPs) were tethered to fluorescent moieties using double activation via a lanthanide assisted Weinreb amidation. IDHP-fluorophore conjugate 3c exhibits the highest binding to date for IDHPs at the multidrug-resistance transporter (MDR-1), and IDHP-fluorophore conjugates 3c and 7 distribute selectively in SH-SY5Y cells. A homology model for IDHP binding at MDR-1 is presented which represents our current working hypothesis.

Accurate models for P-gp drug recognition induced from a cancer cell line cytotoxicity screen

P-glycoprotein (P-gp, MDR1) is a promiscuous drug efflux pump of substantial pharmacological importance. Taking advantage of large-scale cytotoxicity screening data involving 60 cancer cell lines, we correlated the differential biological activities of ∼13,000 compounds against cellular P-gp levels. We created a large set of 934 high-confidence P-gp substrates or nonsubstrates by enforcing agreement with an orthogonal criterion involving P-gp overexpressing ADR-RES cells. A support vector machine (SVM) was 86.7% accurate in discriminating P-gp substrates on independent test data, exceeding previous models. Two molecular features had an overarching influence: nearly all P-gp substrates were large (>35 atoms including H) and dense (specific volume of <7.3 Å(3)/atom) molecules. Seven other descriptors and 24 molecular fragments ("effluxophores") were found enriched in the (non)substrates and incorporated into interpretable rule-based models. Biological experiments on an independent P-gp overexpressing cell line, the vincristine-resistant VK2, allowed us to reclassify six compounds previously annotated as substrates, validating our method's predictive ability. Models are freely available at http://pgp.biozyne.com .

2D- and 3D-QSAR studies of a series of benzopyranes and benzopyrano[3,4b][1,4]-oxazines as inhibitors of the multidrug transporter P-glycoprotein

The ATP-binding cassette efflux transporter P-glycoprotein (P-gp) is notorious for contributing to multidrug resistance in antitumor therapy. Due to its expression in many blood-organ barriers, it also influences the pharmacokinetics of drugs and drug candidates and is involved in drug/drug- and drug/nutrient interactions. However, due to lack of structural information the molecular basis of ligand/transporter interaction still needs to be elucidated. Towards this goal, a series of Benzopyranes and Benzopyrano[3,4b][1,4]oxazines have been synthesized and pharmacologically tested for their ability to inhibit P-gp mediated daunomycin efflux. Both quantitative structure–activity relationship (QSAR) models using simple physicochemical and novel GRID-independent molecular descriptors (GRIND) were established to shed light on the structural requirements for high P-gp inhibitory activity. The results from 2D-QSAR showed a linear correlation of vdW surface area (Ų) of hydrophobic atoms with the pharmacological activity. GRIND (3D-QSAR) studies allowed to identify important mutual distances between pharmacophoric features, which include one H-bond donor, two H-bond acceptors and two hydrophobic groups as well as their distances from different steric hot spots of the molecules. Activity of the compounds particularly increases with increase of the distance of an H-bond donor or a hydrophobic feature from a particular steric hot spot of the benzopyrane analogs.

BIRB796, the inhibitor of p38 mitogen-activated protein kinase, enhances the efficacy of chemotherapeutic agents in ABCB1 overexpression cells

ATP-binding-cassette family membrane proteins play an important role in multidrug resistance. In this study, we investigated BIRB796, an orally active inhibitor of p38 mitogen-activated protein kinase, reversed MDR induced by ABCB1, ABCG2 and ABCC1. Our results showed that BIRB796 could reverse ABCB1-mediated MDR in both the drug selected and transfected ABCB1-overexpressing cell models, but did not enhance the efficacy of substrate-chemotherapeutical agents in ABCC1 or ABCG2 overexpression cells and their parental sensitive cells. Furthermore, BIRB796 increased the intracellular accumulation of the ABCB1 substrates, such as rhodamine 123 and doxorubicin. Moreover, BIRB796 bidirectionally mediated the ATPase activity of ABCB1, stimulating at low concentration, inhibiting at high concentration. However, BIRB796 did not alter the expression of ABCB1 both at protein and mRNA level. The down-regulation of p38 by siRNA neither affected the expression of ABCB1 nor the cytotoxic effect of paclitaxel on KBV200. The binding model of BIRB796 within the large cavity of the transmembrane region of ABCB1 may form the basis for future lead optimization studies. Importantly, BIRB796 also enhanced the effect of paclitaxel on the inhibition of growth of the ABCB1-overexpressing KBV200 cell xenografts in nude mice. Overall, we conclude that BIRB796 reverses ABCB1-mediated MDR by directly inhibiting its transport function. These findings may be useful for cancer combinational therapy with BIRB796 in the clinic.

4-Isoxazolyl-1,4-dihydropyridines exhibit binding at the multidrug-resistance transporter

The 4-isoxazolyl-dihydropyridines (IDHPs) exhibit inhibition of the multidrug-resistance transporter (MDR-1), and exhibit an SAR distinct from their activity at voltage gated calcium channels (VGCC). Among the four most active IDHPs, three were branched at C-5 of the isoxazole, including the most active analog, 1k.

Saracatinib (AZD0530) is a potent modulator of ABCB1-mediated multidrug resistance in vitro and in vivo

Saracatinib, a highly selective, dual Src/Abl kinase inhibitor, is currently in a Phase II clinical trial for the treatment of ovarian cancer. In our study, we investigated the effect of saracatinib on the reversal of multidrug resistance (MDR) induced by ATP-binding cassette (ABC) transporters in vitro and in vivo. Our results showed that saracatinib significantly enhanced the cytotoxicity of ABCB1 substrate drugs in ABCB1 overexpressing HeLa/v200, MCF-7/adr and HEK293/ABCB1 cells, an effect that was stronger than that of gefitinib, whereas it had no effect on the cytotoxicity of the substrates in ABCC1 overexpressing HL-60/adr cells and its parental sensitive cells. Additionally, saracatinib significantly increased the doxorubicin (Dox) and Rho 123 accumulation in HeLa/v200 and MCF-7/adr cells, whereas it had no effect on HeLa and MCF-7 cells. Furthermore, saracatinib stimulated the ATPase activity and inhibited photolabeling of ABCB1 with [(125)I]-iodoarylazidoprazosin in a concentration-dependent manner. In addition, the homology modeling predicted the binding conformation of saracatinib within the large hydrophobic drug-binding cavity of human ABCB1. However, neither the expression level of ABCB1 nor the phosphorylation level of Akt was altered at the reversal concentrations of saracatinib. Importantly, saracatinib significantly enhanced the effect of paclitaxel against ABCB1-overexpressing HeLa/v200 cancer cell xenografts in nude mice. In conclusion, saracatinib reverses ABCB1-mediated MDR in vitro and in vivo by directly inhibiting ABCB1 transport function, without altering ABCB1 expression or AKT phosphorylation. These findings may be helpful to attenuate the effect of MDR by combining saracatinib with other chemotherapeutic drugs in the clinic.