Molecular determinants of ligand selectivity for the human multidrug and toxin extruder proteins MATE1 and MATE2-K

Interactions of bosutinib with drug transporters: In vitro and In vivo inhibition of organic cation transporter 2, multidrug and toxin extrusion protein 1, and breast cancer resistance protein by bosutinib

Bosutinib has been approved for use in patients with chronic myeloid leukemia. Information regarding the effects of bosutinib on clinically important drug transporters is limited, particularly regarding its inhibitory potency on transporters and in vivo effects. Therefore, we conducted a study investigating the in vitro and in vivo effects of bosutinib on drug transporters. Bosutinib showed moderate or strong inhibitory effects on organic cation transporter 2, multidrug and toxin extrusion protein 1, and breast cancer resistance protein with IC50 values of 0.0894, 0.598, and 10.8 µM, respectively. In vivo experiments in rats showed that bosutinib significantly inhibited organic cation transporter 2 and multidrug and toxin extrusion protein 1, leading to a marked reduction in the renal clearance of metformin and an increase in systemic exposure to metformin. Bosutinib increased systemic exposure to sulfasalazine, a probe substrate of breast cancer resistance protein, by 75 % in rats, highlighting its potential to significantly affect intestinal drug efflux. These quantitative changes suggest that bosutinib may alter the in vivo pharmacokinetics of drugs that are substrates of these transporters, potentially leading to increased drug exposure and enhanced or unexpected pharmacological effects.

How PBPK Can Help to Understand Old Drugs and Inform their Dosing in Elderly: Amantadine Case Study

Amantadine, despite being on the market for 55 years, has several unknown aspects of its pharmacokinetics especially related to the influence of covariates such as age, disease, or interactions linked to amantadine's renal elimination. As amantadine is used in Parkinson's disease and is considered a potential candidate in COVID treatment and other diseases, there is an unmet need for thorough understanding of its pharmacokinetic in special populations, such as the elderly. We aimed to mechanistically describe amantadine pharmacokinetics in healthy subjects and shed some light on the differences in drug behavior between healthy volunteers (18-65 years) and an elderly/geriatric population (65-98 years) using PBPK modeling and simulation. The middle-out PBPK model includes mechanistic description of drug renal elimination, specifically an organic cation transporter (OCT)2-mediated electrogenic bidirectional transport (basolateral) and multidrug and toxic compound extrusion (MATE)1-mediated efflux (apical). The model performance was verified against plasma and urine data reported after single and multiple dose administration in healthy volunteers and elderly patients from 18 independent studies. The ratios of predicted vs. observed maximal plasma concentration and area under the concentration-time curve values were within 1.25-fold. The model illustrates that renal transporter activity is expected to decrease in healthy elderly compared to healthy volunteers, which is in line with literature proteomic data for OCT2. The model was applied to assess the potential of reaching toxicity-related plasma concentrations in different age groups of geriatric subjects.

Survey of Pharmaceutical Industry's Best Practices around In Vitro Transporter Assessment and Implications for Drug Development: Considerations from the International Consortium for Innovation and Quality for Pharmaceutical Development Transporter Working Group

The International Consortium for Innovation and Quality in Pharmaceutical Development Transporter Working Group had a rare opportunity to analyze a crosspharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of preincubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of crosstransport inhibition (P-gp, BCRP, OATP1B, and OCT1), with high molecular weight (MW ≥500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1, and MATE1, suggesting that prediction of DDIs for these transporters will be common. In contrast, inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates, whereas compounds with MW <500 Da tended to be OAT3 substrates. Interestingly, the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whereas those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing, with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified, supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. SIGNIFICANCE STATEMENT: A diverse dataset showed that transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1, and MATE1 was frequent if the compound inhibited other transporters. In contrast, inhibition of OAT1 did not correlate with the other drug transporters tested.

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

Novel drug transporter substrates identification: An innovative approach based on metabolomic profiling, in silico ligand screening and biological validation

Solute carrier (SLC) transport proteins are fundamental for the translocation of endogenous compounds and drugs across membranes, thus playing a critical role in disease susceptibility and drug response. Because only a limited number of transporter substrates are currently known, the function of a large number of SLC transporters is elusive. Here, we describe the proof-of-concept of a novel strategy to identify SLC transporter substrates exemplarily for the proton-coupled peptide transporter (PEPT) 2 (SLC15A2) and multidrug and toxin extrusion (MATE) 1 transporter (SLC47A1), which are important renal transporters of drug reabsorption and excretion, respectively. By combining metabolomic profiling of mice with genetically-disrupted transporters, in silico ligand screening and in vitro transport studies for experimental validation, we identified nucleobases and nucleoside-derived anticancer and antiviral agents (flucytosine, cytarabine, gemcitabine, capecitabine) as novel drug substrates of the MATE1 transporter. Our data confirms the successful applicability of this new approach for the identification of transporter substrates in general, which may prove particularly relevant in drug research.

Deciphering the role of fucoidan from brown macroalgae in inhibiting SARS-CoV-2 by targeting its main protease and receptor binding domain: Invitro and insilico approach

The current study investigated the role of fucoidan from Padina tetrastromatica and Turbinaria conoides against 3-chymotrypsin like protease (3CLpro) and receptor binding domain (RBD) spike protein of SARS-CoV-2 using an invitro and computational approach. The 3CLpro and RBD genes were successfully cloned in pET28a vector, expressed in BL-21DE3 E. coli rosetta cells and purified by ion exchange affinity and size exclusion chromatography. Fucoidan extracted from both biomass using green approach, subcritical water, was found to inhibit 3CLpro of SARS-CoV-2 with an IC50 value of up to 0.35 mg mL-1. However, fucoidan was found to be inactive against the RBD protein. Molecular docking studies demonstrated that fucoidan binds to the active sites of 3CLpro with an affinity of -5.0 kcal mol-1. In addition, molecular dynamic simulations recorded stabilized interactions of protein-ligand complexes in terms of root mean square deviation, root mean square fluctuation, the radius of gyration, solvent accessible surface area and hydrogen bond interaction. The binding energy of fucoidan with 3CLpro was determined to be -101.821 ± 12.966 kJ mol-1 using Molecular Mechanic/Poisson-Bolt-Boltzmann Surface Area analysis. Fucoidan satisfies the Absorption, Distribution, Metabolism, and Excretion (ADME) properties, including Lipinski's rule of five, which play an essential role in drug design. According to the toxicity parameters, fucoidan does not exhibit skin sensitivity, hepatotoxicity, or AMES toxicity. Therefore, this work reveals that fucoidan from brown macroalgae could act as possible inhibitors in regulating the function of the 3CLpro protein, hence inhibiting viral replication and being effective against COVID-19.

Machine Learning Models Identify New Inhibitors for Human OATP1B1

The uptake transporter OATP1B1 (SLC01B1) is largely localized to the sinusoidal membrane of hepatocytes and is a known victim of unwanted drug-drug interactions. Computational models are useful for identifying potential substrates and/or inhibitors of clinically relevant transporters. Our goal was to generate OATP1B1 in vitro inhibition data for [3H] estrone-3-sulfate (E3S) transport in CHO cells and use it to build machine learning models to facilitate a comparison of seven different classification models (Deep learning, Adaboosted decision trees, Bernoulli naïve bayes, k-nearest neighbors (knn), random forest, support vector classifier (SVC), logistic regression (lreg), and XGBoost (xgb)] using ECFP6 fingerprints to perform 5-fold, nested cross validation. In addition, we compared models using 3D pharmacophores, simple chemical descriptors alone or plus ECFP6, as well as ECFP4 and ECFP8 fingerprints. Several machine learning algorithms (SVC, lreg, xgb, and knn) had excellent nested cross validation statistics, particularly for accuracy, AUC, and specificity. An external test set containing 207 unique compounds not in the training set demonstrated that at every threshold SVC outperformed the other algorithms based on a rank normalized score. A prospective validation test set was chosen using prediction scores from the SVC models with ECFP fingerprints and were tested in vitro with 15 of 19 compounds (84% accuracy) predicted as active (≥20% inhibition) showed inhibition. Of these compounds, six (abamectin, asiaticoside, berbamine, doramectin, mobocertinib, and umbralisib) appear to be novel inhibitors of OATP1B1 not previously reported. These validated machine learning models can now be used to make predictions for drug-drug interactions for human OATP1B1 alongside other machine learning models for important drug transporters in our MegaTrans software.

Transport Turnover Rates for Human OCT2 and MATE1 Expressed in Chinese Hamster Ovary Cells

MATE1 (multidrug and toxin extruder 1) and OCT2 (organic cation transporter 2) play critical roles in organic cation excretion by the human kidney. The transporter turnover rate (TOR) is relevant to understanding both their transport mechanisms and interpreting the in vitro-in vivo extrapolation (IVIVE) required for physiologically-based pharmacokinetic (PBPK) modeling. Here, we use a quantitative western blot method to determine TORs for MATE1 and OCT2 proteins expressed in CHO cells. MATE1 and OCT2, each with a C-terminal V-5 epitope tag, were cell surface biotinylated and the amount of cell surface MATE1 and OCT2 protein was quantified by western analysis, using standard curves for the V5 epitope. Cell surface MATE1 and OCT2 protein represented 25% and 24%, respectively, of the total expression of these proteins in CHO cells. The number of cell surface transporters was ~55 fmol cm^-2 for MATE1 and ~510 fmol cm^-2 for OCT2. Dividing these values into the different J_max values for transport of MPP, metformin, and atenolol mediated by MATE1 and OCT2 resulted in calculated TOR values (±SE, n = 4) of 84.0 ± 22.0 s^-1 and 2.9 ± 0.6 s^-1; metformin, 461.0 ± 121.0 s^-1 and 12.6 ± 2.4 s^-1; atenolol, 118.0 ± 31.0 s^-1, respectively. These values are consistent with the TOR values determined for a variety of exchangers (NHEs), cotransporters (SGLTs, Lac permease), and uniporters (GLUTs, ENTs).

Importance of the Azole Moiety of Cimetidine Derivatives for the Inhibition of Human Multidrug and Toxin Extrusion Transporter 1 (hMATE1)

Herein, we describe the design and synthesis of cimetidine analogs, as well as their inhibitory activity toward the human multidrug and toxin extrusion transporter 1 (hMATE1), which is related to nephrotoxicity of drugs. Cimetidine is the histamine H₂-receptor antagonist, but also inhibits hMATE1, which is known to cause renal impairment. We designed and synthesized cimetidine analogs to evaluate hMATE1 inhibitory activity to reveal whether the analogs could reduce the inhibition of hMATE1. The results showed that all analogs with an unsubstituted guanidino group exhibited hMATE1 inhibitory activity. On the other hand, there was a clear difference in the hMATE1 inhibitory activity for the other compounds. That is, compounds with a methylimidazole ring exhibited hMATE1 inhibition, while compounds with a phenyl ring did not. The results suggest that the ability to form hydrogen bonds at the azole moiety is strongly involved in the hMATE1 inhibition.

Multiple Computational Approaches for Predicting Drug Interactions with Human Equilibrative Nucleoside Transporter 1

Equilibrativenucleoside transporters (ENTs) participate in the pharmacokinetics and disposition of nucleoside analog drugs. Understanding drug interactions with the ENTs may inform and facilitate the development of new drugs, including chemotherapeutics and antivirals that require access to sanctuary sites such as the male genital tract. This study created three-dimensional pharmacophores for ENT1 and ENT2 substrates and inhibitors using K_t and IC₅₀ data curated from the literature. Substrate pharmacophores for ENT1 and ENT2 are distinct, with partial overlap of hydrogen bond donors, whereas the inhibitor pharmacophores predominantly feature hydrogen bond acceptors. Mizoribine and ribavirin mapped to the ENT1 substrate pharmacophore and proved to be substrates of the ENTs. The presence of the ENT-specific inhibitor 6-S-[(4-nitrophenyl)methyl]-6-thioinosine (NBMPR) decreased mizoribine accumulation in ENT1 and ENT2 cells (ENT1, ∼70% decrease, P = 0.0046; ENT2, ∼50% decrease, P = 0.0012). NBMPR also decreased ribavirin accumulation in ENT1 and ENT2 cells (ENT1: ∼50% decrease, P = 0.0498; ENT2: ∼30% decrease, P = 0.0125). Darunavir mapped to the ENT1 inhibitor pharmacophore and NBMPR did not significantly influence darunavir accumulation in either ENT1 or ENT2 cells (ENT1: P = 0.28; ENT2: P = 0.53), indicating that darunavir's interaction with the ENTs is limited to inhibition. These computational and in vitro models can inform compound selection in the drug discovery and development process, thereby reducing time and expense of identification and optimization of ENT-interacting compounds. SIGNIFICANCE STATEMENT: This study developed computational models of human equilibrative nucleoside transporters (ENTs) to predict drug interactions and validated these models with two compounds in vitro. Identification and prediction of ENT1 and ENT2 substrates allows for the determination of drugs that can penetrate tissues expressing these transporters.

Organic Cation Transporter Expression and Function in the CNS

The blood-brain barrier (BBB) and blood-cerebrospinal fluid barrier (BCSFB) represent major control checkpoints protecting the CNS, by exerting selective control over the movement of organic cations and anions into and out of the CNS compartment. In addition, multiple CNS cell types, e.g., astrocytes, ependymal cells, microglia, contribute to processes that maintain the status quo of the CNS milieu. To fulfill their roles, these barriers and cell types express a multitude of transporter proteins from dozens of different transporter families. Fundamental advances over the past few decades in our knowledge of transporter substrates, expression profiles, and consequences of loss of function are beginning to change basic theories regarding the contribution of various cell types and clearance networks to coordinated neuronal signaling, complex organismal behaviors, and overall CNS homeostasis. In particular, transporters belonging to the Solute Carrier (SLC) superfamily are emerging as major contributors, including the SLC22 organic cation/anion/zwitterion family of transporters (includes OCT1-3 and OCTN1-3), the SLC29 facilitative nucleoside family of transporters (includes PMAT), and the SLC47 multidrug and toxin extrusion family of transporters (includes MATE1-2). These transporters are known to interact with neurotransmitters, antidepressant and anxiolytic agents, and drugs of abuse. Clarifying their contributions to the underlying mechanisms regulating CNS permeation and clearance, as well as the health status of astrocyte, microglial and neuronal cell populations, will drive new levels of understanding as to maintenance of the CNS milieu and approaches to new therapeutics and therapeutic strategies in the treatment of CNS disorders. This chapter highlights organic cation transporters belonging to the SLC superfamily known to be expressed in the CNS, providing an overview of their identification, mechanism of action, CNS expression profile, interaction with neurotransmitters and antidepressant/antipsychotic drugs, and results from behavioral studies conducted in loss of function models (knockout/knockdown).

Involvement of Human Multidrug and Toxic Compound Extrusion (MATE) Transporters in Testosterone Transport

Multidrug and toxic compound extrusion (MATE) transporters are primarily expressed in the kidneys and liver, where they contribute to the excretion of organic cations. Our previous study suggested that pig MATE2 (class III) participates in testosterone secretion from Leydig cells. In humans, it is unclear which MATE class is involved in testosterone transport. In this study, we aimed to clarify whether human MATE1 (hMATE1) or human MATE2K (hMATE2K) mediates testosterone transport. To confirm that testosterone inhibits transporter-mediated tetraethylammonium (TEA) uptake, a cis-inhibition assay was performed using cells that stably expressed hMATE1 or hMATE2K. Docking simulations were performed to characterize differences in the binding of hMATE1 and hMATE2K to testosterone. Transport experiments in LLC-PK1 cells that stably expressed hMATE1 were used to test whether hMATE1 mediates testosterone transport. We detected differences between the amino acid sequences of the substrate-binding sites of hMATE1 and hMATE2K that could potentially be involved in testosterone binding. Testosterone and estradiol inhibited TEA uptake mediated by hMATE1 but not that mediated by hMATE2K. Transport experiments in LLC-PK1 cells indicated that testosterone might be transported via hMATE1. This study suggested that hMATE1, but not hMATE2K, is involved in human testosterone transport.

Organic Cation Transporters in Health and Disease

The organic cation transporters (OCTs) OCT1, OCT2, OCT3, novel OCT (OCTN)1, OCTN2, multidrug and toxin exclusion (MATE)1, and MATE kidney-specific 2 are polyspecific transporters exhibiting broadly overlapping substrate selectivities. They transport organic cations, zwitterions, and some uncharged compounds and operate as facilitated diffusion systems and/or antiporters. OCTs are critically involved in intestinal absorption, hepatic uptake, and renal excretion of hydrophilic drugs. They modulate the distribution of endogenous compounds such as thiamine, L-carnitine, and neurotransmitters. Sites of expression and functions of OCTs have important impact on energy metabolism, pharmacokinetics, and toxicity of drugs, and on drug-drug interactions. In this work, an overview about the human OCTs is presented. Functional properties of human OCTs, including identified substrates and inhibitors of the individual transporters, are described. Sites of expression are compiled, and data on regulation of OCTs are presented. In addition, genetic variations of OCTs are listed, and data on their impact on transport, drug treatment, and diseases are reported. Moreover, recent data are summarized that indicate complex drug-drug interaction at OCTs, such as allosteric high-affinity inhibition of transport and substrate dependence of inhibitor efficacies. A hypothesis about the molecular mechanism of polyspecific substrate recognition by OCTs is presented that is based on functional studies and mutagenesis experiments in OCT1 and OCT2. This hypothesis provides a framework to imagine how observed complex drug-drug interactions at OCTs arise. Finally, preclinical in vitro tests that are performed by pharmaceutical companies to identify interaction of novel drugs with OCTs are discussed. Optimized experimental procedures are proposed that allow a gapless detection of inhibitory and transported drugs.

Molecular dynamics simulations of the interactions between triose phosphate isomerase and sulfonamides

Malaria is a disease with debilitating health and negative economic impacts in regions at high risk of infection. Parasitic resistance and side effects of current antimalarial drugs are major setbacks to the successful campaigns that have reduced malaria incidence by 40% in the last decade. The parasite’s dependence on glycolysis for energy requirements makes pathway enzymes suitable targets for drug development. Specifically, triose phosphate isomerase (TPI) from Plasmodium falciparum (pTPI) and human (hTPI) cells show striking structural features that can be used in development of new antimalarial agents. In this study MD simulations were used to characterize binding sites on hTPI and pTPI interactions with sulfonamides. The molecular mechanics Poisson–Boltzmann surface area (MM–PBSA) method was used to estimate the interaction energies of four sulfonamide-TPI docked complexes. A unique combination of key residues at the dimer interface of pTPI is responsible for the observed selective affinity to pTPI compared to hTPI. The representative sulfonamide; 4-amino-N-(3,5-dimethylphenyl)-3-fluorbenzenesulfonamide (sulfaE) shows a strong affinity with pTPI (dimer interface, −42.91 kJ/mol and active site region, −71.62 kJ/mol), hTPI (dimer interface, −41.32 kJ/mol and active site region, −84.40 kJ/mol). Strong and favorable Van der Waals interactions and increases in non-polar solvation energies explain the difference in affinity between pTPI with sulfaE compared to hTPI at the dimer interface. This is an indication that the dimer interface of TPI glycolytic enzyme is vital for development of sulfonamide based antimalarial drugs.

High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of Staphylococcus aureus

One potential source of new antibacterials is through probing existing chemical libraries for copper-dependent inhibitors (CDIs), i.e., molecules with antibiotic activity only in the presence of copper. Recently, our group demonstrated that previously unknown staphylococcal CDIs were frequently present in a small pilot screen. Here, we report the outcome of a larger industrial anti-staphylococcal screen consisting of 40 771 compounds assayed in parallel, both in standard and in copper-supplemented media. Ultimately, 483 had confirmed copper-dependent IC50 values under 50 μM. Sphere-exclusion clustering revealed that these hits were largely dominated by sulfur-containing motifs, including benzimidazole-2-thiones, thiadiazines, thiazoline formamides, triazino-benzimidazoles, and pyridinyl thieno-pyrimidines. Structure-activity relationship analysis of the pyridinyl thieno-pyrimidines generated multiple improved CDIs, with activity likely dependent on ligand/ion coordination. Molecular fingerprint-based Bayesian classification models were built using Discovery Studio and Assay Central, a new platform for sharing and distributing cheminformatic models in a portable format, based on open-source tools. Finally, we used the latter model to evaluate a library of FDA-approved drugs for copper-dependent activity in silico. Two anti-helminths, albendazole and thiabendazole, scored highly and are known to coordinate copper ions, further validating the model's applicability.

Renal Excretion of Dabigatran: The Potential Role of Multidrug and Toxin Extrusion (MATE) Proteins

Following oral administration, dabigatran etexilate (DABE) is rapidly hydrolyzed to its active form, dabigatran. DABE, but not dabigatran, presents as a P-glycoprotein (P-gp) substrate and has increasingly been used as a probe drug. Therefore, although dosed as DABE, a P-gp drug-drug interaction (DDI) is reported as a dabigatran plasma concentration ratio (perpetrator versus placebo). Because the majority of a DABE dose (80 to 85%) is recovered in urine as unchanged dabigatran (renal active secretion is ∼25% of total clearance), dabigatran was evaluated in vitro as a substrate of various human renal transporters. Active (pyrimethamine-sensitive) dabigatran uptake was observed with human embryonic kidney (HEK) 293 cells expressing multidrug and toxin extrusion protein 1 (MATE1) and 2K (MATE2K), with Michaelis-Menten constant (K_m) values of 4.0 and 8.0 μM, respectively. By comparison, no uptake of 2 μM dabigatran (versus mock-transfected HEK293 cells) was evident with HEK293 cells transfected with organic cation transporters (OCT1 and OCT2) and organic anion transporters (OAT1, 2, 3, and 4). The efflux ratios of dabigatran across P-gp- and BCRP (breast cancer resistance protein)-MDCK (Madin-Darby canine kidney) cell monolayers were 1.5 and 2.0 (versus mock-MDCK cell monolayers), suggesting dabigatran is a relatively poor P-gp and BCRP substrate. Three of five drugs (verapamil, ketoconazole, and quinidine) known to interact clinically with dabigatran, as P-gp inhibitors, presented as MATE inhibitors in vitro (IC₅₀ = 1.0 to 25.2 μM). Taken together, although no basolateral transporter was identified for dabigatran, the results suggest that apical MATE1 and MATE2K could play an important role in its renal clearance. MATE-mediated renal secretion of dabigatran needs to be considered when interpreting the results of P-gp DDI studies following DABE administration.

Repurposing Approved Drugs as Inhibitors of Kv7.1 and Nav1.8 to Treat Pitt Hopkins Syndrome

PURPOSE

Pitt Hopkins Syndrome (PTHS) is a rare genetic disorder caused by mutations of a specific gene, transcription factor 4 (TCF4), located on chromosome 18. PTHS results in individuals that have moderate to severe intellectual disability, with most exhibiting psychomotor delay. PTHS also exhibits features of autistic spectrum disorders, which are characterized by the impaired ability to communicate and socialize. PTHS is comorbid with a higher prevalence of epileptic seizures which can be present from birth or which commonly develop in childhood. Attenuated or absent TCF4 expression results in increased translation of peripheral ion channels K_v7.1 and Na_v1.8 which triggers an increase in after-hyperpolarization and altered firing properties.

METHODS

We now describe a high throughput screen (HTS) of 1280 approved drugs and machine learning models developed from this data. The ion channels were expressed in either CHO (K_V7.1) or HEK293 (Na_v1.8) cells and the HTS used either ⁸⁶Rb⁺ efflux (K_V7.1) or a FLIPR assay (Na_v1.8).

RESULTS

The HTS delivered 55 inhibitors of K_v7.1 (4.2% hit rate) and 93 inhibitors of Na_v1.8 (7.2% hit rate) at a screening concentration of 10 μM. These datasets also enabled us to generate and validate Bayesian machine learning models for these ion channels. We also describe a structure activity relationship for several dihydropyridine compounds as inhibitors of Na_v1.8.

CONCLUSIONS

This work could lead to the potential repurposing of nicardipine or other dihydropyridine calcium channel antagonists as potential treatments for PTHS acting via Na_v1.8, as there are currently no approved treatments for this rare disorder.

Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science

Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.

Interaction of environmental contaminants with zebrafish (Danio rerio) multidrug and toxin extrusion protein 7 (Mate7/Slc47a7)

Zebrafish Mate7 belongs to solute carrier protein superfamily and specifically to subfamily of multidrug and toxin extruders. It is co-orthologous to mammalian Mates, and is ubiquitously expressed in zebrafish tissues with the highest expression in kidney. It has been shown to interact with both endogenous (steroid hormones) and xenobiotic compounds (pharmaceuticals), implying a role in efflux of toxic compounds. The objective of our study was to analyse interaction of environmental contaminants with zebrafish Mate7 using a newly developed high throughput screening (HTS) Mate7 assay. A full-length zebrafish mate7 sequence was obtained from zebrafish cDNA originating from male kidney, and a stable expression of Mate7 in genetically engineered HEK293 Flp-In cells was achieved. Stable Mate7 transfectants were then used for development and optimization of a new HTS cellular uptake protocol, with DAPI and ASP + as model fluorescent substrates. The developed assay was used for identifying zebrafish Mate 7 interactors and discerning the type of interaction. A series of 89 diverse environmental contaminants, including industrial chemicals, pesticides, and pharmaceuticals, was tested and highly effective Mate7 interactors were identified in all of the aforementioned groups. Some of the inhibitors identified could be of environmental concern because they may potentially impair Mate7 efflux function, lowering the fish defence capacity against environmental contaminants, or interfering with transport of yet unidentified physiological substrates. In addition, we found significant differences between zebrafish Mate7 and mammalian Mates' substrate preferences, a finding that should be taken into consideration when using zebrafish as a model organism in toxicokinetic studies.

Interaction of the New Monofunctional Anticancer Agent Phenanthriplatin With Transporters for Organic Cations

Cancer treatment with platinum compounds is an important achievement of modern chemotherapy. However, despite the beneficial effects, the clinical impact of these agents is hampered by the development of drug resistance as well as dose-limiting side effects. The efficacy but also side effects of platinum complexes can be mediated by uptake through plasma membrane transporters. In the kidneys, plasma membrane transporters are involved in their secretion into the urine. Renal secretion is accomplished by uptake from the blood into the proximal tubules cells, followed by excretion into the urine. The uptake process is mediated mainly by organic cation transporters (OCT), which are expressed in the basolateral domain of the plasma membrane facing the blood. The excretion of platinum into the urine is mediated by exchange with protons via multidrug and toxin extrusion proteins (MATE) expressed in the apical domain of plasma membrane. Recently, the monofunctional, cationic platinum agent phenanthriplatin, which is able to escape common cellular resistance mechanisms, has been synthesized and investigated. In the present study, the interaction of phenanthriplatin with transporters for organic cations has been evaluated. Phenanthriplatin is a high affinity substrate for OCT2, but has a lower apparent affinity for MATEs. The presence of these transporters increased cytotoxicity of phenanthriplatin. Therefore, phenanthriplatin may be especially effective in the treatment of cancers that express OCTs, such as colon cancer cells. However, the interaction of phenanthriplatin with OCTs suggests that its use as chemotherapeutic agent may be complicated by OCT-mediated toxicity. Unlike cisplatin, phenanthriplatin interacts with high specificity with hMATE1 and hMATE2K in addition to hOCT2. This interaction may facilitate its efflux from the cells and thereby decrease overall efficacy and/or toxicity.

Contribution of multidrug and toxin extrusion protein 1 (MATE1) to renal secretion of trimethylamine-N-oxide (TMAO)

Trimethylamine-N-oxide (TMAO) gained considerable attention because of its role as a cardiovascular risk biomarker. Organic cation transporter 2 (OCT2) mediates TMAO uptake into renal proximal tubular cells. Here we investigated the potential role of multidrug and toxin extrusion protein 1 (MATE1) for translocation of TMAO across the luminal membrane of proximal tubular cells. HEK293 cells stably expressing OCT2 (HEK-OCT2) or MATE1 (HEK-MATE1) were used for uptake studies. Transcellular transport of TMAO was investigated using monolayers of MDCK control cells (MDCK-Co) as well as single- (MDCK-OCT2, MDCK-MATE1) and double-transfected cells (MDCK-OCT2-MATE1). In line with previous studies, HEK-OCT2 cells revealed a 2.4-fold uptake of TMAO compared to control cells (p < 0.001), whereas no significant uptake was observed in HEK-MATE1. In monolayers of MDCK cells, polarised TMAO transcellular transport was not significantly different between MDCK-Co and MDCK-OCT2 cells, but significantly increased in MDCK-MATE1 (p < 0.05) and MDCK-OCT2-MATE1 cells (p < 0.001). The OCT/MATE inhibitor trimethoprim abolished TMAO translocation in MDCK-OCT2-MATE1 cells (p < 0.05). The present data suggest that MATE1 contributes to renal elimination of TMAO. For selected MATE substrates, such as TMAO, uptake studies using non-polarised MATE-expressing cells can reveal false negative results compared to studies using polarised monolayers.

Renal Drug Transporters and Drug Interactions

Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.

The effects of dietary and herbal phytochemicals on drug transporters

Membrane transporter proteins (the ABC transporters and SLC transporters) play pivotal roles in drug absorption and disposition, and thus determine their efficacy and safety. Accumulating evidence suggests that the expression and activity of these transporters may be modulated by various phytochemicals (PCs) found in diets rich in plants and herbs. PC absorption and disposition are also subject to the function of membrane transporter and drug metabolizing enzymes. PC-drug interactions may involve multiple major drug transporters (and metabolizing enzymes) in the body, leading to alterations in the pharmacokinetics of substrate drugs, and thus their efficacy and toxicity. This review summarizes the reported in vitro and in vivo interactions between common dietary PCs and the major drug transporters. The oral absorption, distribution into pharmacological sanctuaries and excretion of substrate drugs and PCs are considered, along with their possible interactions with the ABC and SLC transporters which influence these processes.

Moxifloxacin Is a Potent In Vitro Inhibitor of OCT- and MATE-Mediated Transport of Metformin and Ethambutol

It is largely unknown if simultaneous administration of tuberculosis (TB) drugs and metformin leads to drug-drug interactions (DDIs). Disposition of metformin is determined by organic cation transporters (OCTs) and multidrug and toxin extrusion proteins (MATEs). Thus, any DDIs would primarily be mediated via these transporters. This study aimed to assess the in vitro inhibitory effects of TB drugs (rifampin, isoniazid, pyrazinamide, ethambutol, amikacin, moxifloxacin, and linezolid) on metformin transport and whether TB drugs are also substrates themselves of OCTs and MATEs. HEK293 cells overexpressing OCT1, OCT2, OCT3, MATE1, and MATE2K were used to study TB drug-mediated inhibition of [¹⁴C]metformin uptake and to test if TB drugs are transporter substrates. Metformin uptake was determined by quantifying [¹⁴C]metformin radioactivity, and TB drug uptake was analyzed using liquid chromatography-tandem mass spectrometry. DDI indices were calculated (plasma maximum concentrations [C_max]/50% inhibitory concentrations [IC₅₀]), and based on the literature, a cutoff of >0.1 was assumed to warrant further in vivo investigation. Moxifloxacin was the only TB drug identified as a potent inhibitor (DDI index of >0.1) of MATE1- and MATE2K-mediated metformin transport, with IC₅₀s of 12 μM (95% confidence intervals [CI], 5.1 to 29 μM) and 7.6 μM (95% CI, 0.2 to 242 μM), respectively. Of all TB drugs, only ethambutol appeared to be a substrate of OCT1, OCT2, OCT3, MATE1, and MATE2K. MATE1-mediated ethambutol uptake was inhibited strongly (DDI index of >0.1) by moxifloxacin (IC₅₀, 12 μM [95% CI, 3.4 to 43 μM]). Our findings provide a mechanistic basis for DDI predictions concerning ethambutol. According to international guidelines, an in vivo interaction study is warranted for the observed in vitro interaction between ethambutol and moxifloxacin.

Species specificity profiling of rat and human organic cation/carnitine transporter Slc22a5/SLC22A5 (Octn2/OCTN2)

The purpose of this study was to characterize the uptake of carnitine, the physiological substrate, and the uptake of 3-(2,2,2-trimethylhydrazinium)propionate, a consensus substrate by rat Octn2 and human OCTN2 transporters as well as to characterize drug-mediated inhibition of l-carnitine uptake by the rat and human orthologs overexpressed in CHO-K1 cells. l-carnitine and 3-(2,2,2-trimethylhydrazinium)propionate were found to be a lower affinity substrate for rat Octn2 (K_M = 32.66 ± 5.11 μM and 23.62 ± 4.99 μM respectively) than for human OCTN2 (K_M = 3.08 ± 0.74 μM and 7.98 ± 0.63 μM). The intrinsic clearance (CL_int) value for carnitine was higher for the human than for the rat transporter (22.82 ± 5.57 ml/min*mg vs 4.008 ± 0.675 ml/min*mg). For 3-(2,2,2-trimethylhydrazinium)propionate, in contrast, the CL_int value for rat Octn2 was higher than for human OCTN2 (323.9 ± 72.8 ml/min*mg vs 65.11 ± 5.33 ml/min*mg). Furthermore, many pharmacologically important drugs were shown to affect l-carnitine transport by Octn2/OCTN2. The correlation between the IC₅₀ datasets for the rat and human transporter resulted in an r value of 0.47 (p > 0.05). However, the greatest difference was less than seven-fold and 13 of 15 compounds yielded a difference less than 3-fold. Thus, the transporters from these two species showed an overlapping but somewhat different substrate and inhibitor specificity.

Role of ABC and Solute Carrier Transporters in the Placental Transport of Lamivudine

Lamivudine is one of the antiretroviral drugs of choice for the prevention of mother-to-child transmission (MTCT) in HIV-positive women. In this study, we investigated the relevance of drug efflux transporters P-glycoprotein (P-gp) (MDR1 [ABCB1]), BCRP (ABCG2), MRP2 (ABCC2), and MATE1 (SLC47A1) for the transmembrane transport and transplacental transfer of lamivudine. We employed in vitro accumulation and transport experiments on MDCK cells overexpressing drug efflux transporters, in situ-perfused rat term placenta, and vesicular uptake in microvillous plasma membrane (MVM) vesicles isolated from human term placenta. MATE1 significantly accelerated lamivudine transport in MATE1-expressing MDCK cells, whereas no transporter-driven efflux of lamivudine was observed in MDCK-MDR1, MDCK-MRP2, and MDCK-BCRP monolayers. MATE1-mediated efflux of lamivudine appeared to be a low-affinity process (apparent Km of 4.21 mM and Vmax of 5.18 nmol/mg protein/min in MDCK-MATE1 cells). Consistent with in vitro transport studies, the transplacental clearance of lamivudine was not affected by P-gp, BCRP, or MRP2. However, lamivudine transfer across dually perfused rat placenta and the uptake of lamivudine into human placental MVM vesicles revealed pH dependency, indicating possible involvement of MATE1 in the fetal-to-maternal efflux of the drug. To conclude, placental transport of lamivudine does not seem to be affected by P-gp, MRP2, or BCRP, but a pH-dependent mechanism mediates transport of lamivudine in the fetal-to-maternal direction. We suggest that MATE1 might be, at least partly, responsible for this transport.

Lack of Influence of Substrate on Ligand Interaction with the Human Multidrug and Toxin Extruder, MATE1

Multidrug and toxin extruder (MATE) 1 plays a central role in mediating renal secretion of organic cations, a structurally diverse collection of compounds that includes ∼40% of prescribed drugs. Because inhibition of transport activity of other multidrug transporters, including the organic cation transporter (OCT) 2, is influenced by the structure of the transported substrate, the present study screened over 400 drugs as inhibitors of the MATE1-mediated transport of four structurally distinct organic cation substrates: the commonly used drugs: 1) metformin and 2) cimetidine; and two prototypic cationic substrates, 3) 1-methyl-4-phenylpyridinium (MPP), and 4) the novel fluorescent probe, N,N,N-trimethyl-2-[methyl(7-nitrobenzo[c][1,2,5]oxadiazol-4-yl)amino]ethanaminium iodide. Transport was measured in Chinese hamster ovary cells that stably expressed the human ortholog of MATE1. Comparison of the resulting inhibition profiles revealed no systematic influence of substrate structure on inhibitory efficacy. Similarly, IC50 values for 26 structurally diverse compounds revealed no significant influence of substrate structure on the kinetic interaction of inhibitor with MATE1. The IC50 data were used to generate three-dimensional quantitative pharmacophores that identified hydrophobic regions, H-bond acceptor sites, and an ionizable (cationic) feature as key determinants for ligand binding to MATE1. In summary, in contrast to the behavior observed with some other multidrug transporters, including OCT2, the results suggest that substrate identity exerts comparatively little influence on ligand interaction with MATE1.

Impact of Experimental Conditions on the Evaluation of Interactions between Multidrug and Toxin Extrusion Proteins and Candidate Drugs

Multidrug and toxin extrusion transporters (MATEs) have a determining influence on the pharmacokinetic profiles of many drugs and are involved in several clinical drug-drug interactions (DDIs). Cellular uptake assays with recombinant cells expressing human MATE1 or MATE2-K are widely used to investigate MATE-mediated transport for DDI assessment; however, the experimental conditions and used test substrates vary among laboratories. We therefore initially examined the impact of three assay conditions that have been applied for MATE substrate and inhibitor profiling in the literature. One of the tested conditions resulted in significantly higher uptake rates of the three test substrates, [(14)C]metformin, [(3)H]thiamine, and [(3)H]1-methyl-4-phenylpyridinium (MPP(+)), but IC50 values of four tested MATE inhibitors varied only slightly among the three conditions (<2.5-fold difference). Subsequently, we investigated the uptake characteristics of the five MATE substrates: [(14)C]metformin, [(3)H]thiamine, [(3)H]MPP(+), [(3)H]estrone-3-sulfate (E3S), and rhodamine 123, as well as the impact of the used test substrate on the inhibition profiles of 10 MATE inhibitors at one selected assay condition. [(3)H]E3S showed atypical uptake characteristics compared with those observed with the other four substrates. IC50 values of the tested inhibitors were in a similar range (<4-fold difference) when [(14)C]metformin, [(3)H]thiamine, [(3)H]MPP(+), or [(3)H]E3S were used as substrates but were considerably higher with rhodamine 123 (9.8-fold and 4.1-fold differences compared with [(14)C]metformin with MATE1 and MATE2-K, respectively). This study demonstrated for the first time that the impact of assay conditions on IC50 determination is negligible, that kinetic characteristics differ among used test substrates, and that substrate-dependent inhibition exists for MATE1 and MATE2-K, giving valuable insight into the assessment of clinically relevant MATE-mediated DDIs in vitro.

Lack of genomic diversity in the SLC47A1 gene within the indigenous Xhosa population

BACKGROUND

Multidrug and toxin extrusion 1 (MATE1) is an organic cation/H+ exchanger, localized in the apical membrane of proximal renal tubules, which mediates the cellular elimination of organic cations into the renal lumen. These organic cations include clinically important drugs such as metformin, oxaliplatin and cimetidine. Moreover, genetic polymorphisms of SLC47A1, the pharmacogenetically relevant gene encoding human MATE1, have been implicated in reduced transport or accumulation to cytotoxic levels of these drugs in vitro. However, little or no information is available on the minor allele frequency distribution of known SLC47A1 coding SNPs in the sub-Saharan African populations.

METHODS

Thus, the aim of this study was to determine the baseline minor allele frequency distribution of 20 known coding SNPs in the SLC47A1 gene of 148 Xhosa individuals residing in Cape Town, South Africa.

RESULTS

This study did not identify any of these known SLC47A1 coding SNPs in the Xhosa individuals who participated in this study.

CONCLUSIONS

It is anticipated that whole genome or exome sequencing may reveal novel SNPs in the Xhosa and other sub-Saharan African populations, which may have been missed with the current genotyping strategy.

Structure and function of multidrug and toxin extrusion proteins (MATEs) and their relevance to drug therapy and personalized medicine

Multidrug and toxin extrusion (MATE; SLC47A) proteins are membrane transporters mediating the excretion of organic cations and zwitterions into bile and urine and thereby contributing to the hepatic and renal elimination of many xenobiotics. Transported substrates include creatinine as endogenous substrate, the vitamin thiamine and a number of drug agents with in part chemically different structures such as the antidiabetic metformin, the antiviral agents acyclovir and ganciclovir as well as the antibiotics cephalexin and cephradine. This review summarizes current knowledge on the structural and molecular features of human MATE transporters including data on expression and localization in different tissues, important aspects on regulation and their functional role in drug transport. The role of genetic variation of MATE proteins for drug pharmacokinetics and drug response will be discussed with consequences for personalized medicine.

Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses

Bayesian models constructed from structure-derived fingerprints have been a popular and useful method for drug discovery research when applied to bioactivity measurements that can be effectively classified as active or inactive. The results can be used to rank candidate structures according to their probability of activity, and this ranking benefits from the high degree of interpretability when structure-based fingerprints are used, making the results chemically intuitive. Besides selecting an activity threshold, building a Bayesian model is fast and requires few or no parameters or user intervention. The method also does not suffer from such acute overtraining problems as quantitative structure–activity relationships or quantitative structure–property relationships (QSAR/QSPR). This makes it an approach highly suitable for automated workflows that are independent of user expertise or prior knowledge of the training data. We now describe a new method for creating a composite group of Bayesian models to extend the method to work with multiple states, rather than just binary. Incoming activities are divided into bins, each covering a mutually exclusive range of activities. For each of these bins, a Bayesian model is created to model whether or not the compound belongs in the bin. Analyzing putative molecules using the composite model involves making a prediction for each bin and examining the relative likelihood for each assignment, for example, highest value wins. The method has been evaluated on a collection of hundreds of data sets extracted from ChEMBL v20 and validated data sets for ADME/Tox and bioactivity.

The multidrug transporter MATE1 sequesters OCs within an intracellular compartment that has no influence on OC secretion in renal proximal tubules

Secretion of organic cations (OCs) across renal proximal tubules (RPTs) involves basolateral OC transporter (OCT)2-mediated uptake from the blood followed by apical multidrug and toxin extruder (MATE)1/2-mediated efflux into the tubule filtrate. Whereas OCT2 supports electrogenic OC uniport, MATE is an OC/H(+) exchanger. As assessed by epifluorescence microscopy, cultured Chinese hamster ovary (CHO) cells that stably expressed human MATE1 accumulated the fluorescent OC N,N,N-trimethyl-2-[methyl(7-nitrobenzo[c][l,2,5]oxadiazol-4-yl)amino]ethanaminium (NBD-MTMA) in the cytoplasm and in a smaller, punctate compartment; accumulation in human OCT2-expressing cells was largely restricted to the cytoplasm. A second intracellular compartment was also evident in the multicompartmental kinetics of efflux of the prototypic OC [(3)H]1-methyl-4-phenylpyridinium (MPP) from MATE1-expressing CHO cells. Punctate accumulation of NBD-MTMA was markedly reduced by coexposure of MATE1-expressing cells with 5 μM bafilomycin (BAF), an inhibitor of V-type H(+)-ATPase, and accumulation of [(3)H]MPP and [(3)H]NBD-MTMA was reduced by >30% by coexposure with 5 μM BAF. BAF had no effect on the initial rate of MATE1-mediated uptake of NBD-MTMA, suggesting that the influence of BAF was a secondary effect involving inhibition of V-type H(+)-ATPase. The accumulation of [(3)H]MPP by isolated single nonperfused rabbit RPTs was also reduced >30% by coexposure to 5 μM BAF, suggesting that the native expression in RPTs of MATE protein within endosomes can increase steady-state OC accumulation. However, the rate of [(3)H]MPP secretion by isolated single perfused rabbit RPTs was not affected by 5 μM BAF, suggesting that vesicles loaded with OCs(+) are not likely to recycle into the apical plasma membrane at a rate sufficient to provide a parallel pathway for OC secretion.

Pharmacophore-based discovery of inhibitors of a novel drug/proton antiporter in human brain endothelial hCMEC/D3 cell line

BACKGROUND AND PURPOSE

An influx drug/proton antiporter of unknown structure has been functionally demonstrated at the blood-brain barrier. This transporter, which handles some psychoactive drugs like diphenhydramine, clonidine, oxycodone, nicotine and cocaine, could represent a new pharmacological target in drug addiction therapy. However, at present there are no known drugs/inhibitors that effectively inhibit/modulate this transporter in vivo.

EXPERIMENTAL APPROACH

The FLAPpharm approach was used to establish a pharmacophore model for inhibitors of this transporter. The inhibitory potency of 44 selected compounds was determined against the specific substrate, [(3)H]-clonidine, in the human cerebral endothelial cell line hCMEC/D3 and ranked as good, medium, weak or non-inhibitor.

KEY RESULTS

The pharmacophore model obtained was used as a template to screen xenobiotic and endogenous compounds from databases [Specs, Recon2, Human Metabolome Database (HMDB), human intestinal transporter database], and hypothetical candidates were tested in vitro to determine their inhibitory capacity with [(3)H]-clonidine. According to the transporter database, 80% of the proton antiporter inhibitor candidates could inhibit P-glycoprotein/MDR1/ABCB1 and specificity is improved by reducing inhibitor size/shape and increasing water solubility. Virtual screening results using HMDB and Recon2 for endogenous compounds appropriately scored tryptamine as an inhibitor.

CONCLUSIONS AND IMPLICATIONS

The pharmacophore model for the proton-antiporter inhibitors was a good predictor of known inhibitors and allowed us to identify new good inhibitors. This model marks a new step towards the discovery of this drug/proton antiporter and will be of great use for the discovery and design of potent inhibitors that could potentially help to assess and validate its pharmacological role in drug addiction in vivo.

Combinatorial Pharmacophore Modeling of Multidrug and Toxin Extrusion Transporter 1 Inhibitors: a Theoretical Perspective for Understanding Multiple Inhibitory Mechanisms

A combinatorial pharmacophore (CP) model for Multidrug and toxin extrusion 1 (MATE1/SLC47A1) inhibitors was developed based on a data set including 881 compounds. The CP model comprises four individual pharmacophore hypotheses, HHR1, DRR, HHR2 and AAAP, which can successfully identify the MATE1 inhibitors with an overall accuracy around 75%. The model emphasizes the importance of aromatic ring and hydrophobicity as two important structural determinants for MATE1 inhibition. Compared with the pharmacophore model of Organic Cation Transporter 2 (OCT2/ SLC22A2), a functional related transporter of MATE1, the hypotheses of AAAP and PRR5 are suggested to be responsible for their ligand selectivity, while HHR a common recognition pattern for their dual inhibition. A series of analysis including molecular sizes of inhibitors matching different hypotheses, matching of representative MATE1 inhibitors and molecular docking indicated that the small inhibitors matching HHR1 and DRR involve in competitive inhibition, while the relatively large inhibitors matching AAAP are responsible for the noncompetitive inhibition by locking the conformation changing of MATE1. In light of the results, a hypothetical model for inhibiting transporting mediated by MATE1 was proposed.

Making Transporter Models for Drug-Drug Interaction Prediction Mobile

The past decade has seen increased numbers of studies publishing ligand-based computational models for drug transporters. Although they generally use small experimental data sets, these models can provide insights into structure-activity relationships for the transporter. In addition, such models have helped to identify new compounds as substrates or inhibitors of transporters of interest. We recently proposed that many transporters are promiscuous and may require profiling of new chemical entities against multiple substrates for a specific transporter. Furthermore, it should be noted that virtually all of the published ligand-based transporter models are only accessible to those involved in creating them and, consequently, are rarely shared effectively. One way to surmount this is to make models shareable or more accessible. The development of mobile apps that can access such models is highlighted here. These apps can be used to predict ligand interactions with transporters using Bayesian algorithms. We used recently published transporter data sets (MATE1, MATE2K, OCT2, OCTN2, ASBT, and NTCP) to build preliminary models in a commercial tool and in open software that can deliver the model in a mobile app. In addition, several transporter data sets extracted from the ChEMBL database were used to illustrate how such public data and models can be shared. Predicting drug-drug interactions for various transporters using computational models is potentially within reach of anyone with an iPhone or iPad. Such tools could help prioritize which substrates should be used for in vivo drug-drug interaction testing and enable open sharing of models.

In silico methods for predicting drug-drug interactions with cytochrome P-450s, transporters and beyond

Drug-drug interactions (DDIs) are associated with severe adverse effects that may lead to the patient requiring alternative therapeutics and could ultimately lead to drug withdrawal from the market if they are severe. To prevent the occurrence of DDI in the clinic, experimental systems to evaluate drug interaction have been integrated into the various stages of the drug discovery and development process. A large body of knowledge about DDI has also accumulated through these studies and pharmacovigillence systems. Much of this work to date has focused on the drug metabolizing enzymes such as cytochrome P-450s as well as drug transporters, ion channels and occasionally other proteins. This combined knowledge provides a foundation for a hypothesis-driven in silico approach, using either cheminformatics or physiologically based pharmacokinetics (PK) modeling methods to assess DDI potential. Here we review recent advances in these approaches with emphasis on hypothesis-driven mechanistic models for important protein targets involved in PK-based DDI. Recent efforts with other informatics approaches to detect DDI are highlighted. Besides DDI, we also briefly introduce drug interactions with other substances, such as Traditional Chinese Medicines to illustrate how in silico modeling can be useful in this domain. We also summarize valuable data sources and web-based tools that are available for DDI prediction. We finally explore the challenges we see faced by in silico approaches for predicting DDI and propose future directions to make these computational models more reliable, accurate, and publically accessible.

Open Source Bayesian Models. 2. Mining a "Big Dataset" To Create and Validate Models with ChEMBL

In an associated paper, we have described a reference implementation of Laplacian-corrected naïve Bayesian model building using extended connectivity (ECFP)- and molecular function class fingerprints of maximum diameter 6 (FCFP)-type fingerprints. As a follow-up, we have now undertaken a large-scale validation study in order to ensure that the technique generalizes to a broad variety of drug discovery datasets. To achieve this, we have used the ChEMBL (version 20) database and split it into more than 2000 separate datasets, each of which consists of compounds and measurements with the same target and activity measurement. In order to test these datasets with the two-state Bayesian classification, we developed an automated algorithm for detecting a suitable threshold for active/inactive designation, which we applied to all collections. With these datasets, we were able to establish that our Bayesian model implementation is effective for the large majority of cases, and we were able to quantify the impact of fingerprint folding on the receiver operator curve cross-validation metrics. We were also able to study the impact that the choice of training/testing set partitioning has on the resulting recall rates. The datasets have been made publicly available to be downloaded, along with the corresponding model data files, which can be used in conjunction with the CDK and several mobile apps. We have also explored some novel visualization methods which leverage the structural origins of the ECFP/FCFP fingerprints to attribute regions of a molecule responsible for positive and negative contributions to activity. The ability to score molecules across thousands of relevant datasets across organisms also may help to access desirable and undesirable off-target effects as well as suggest potential targets for compounds derived from phenotypic screens.

Unstirred Water Layers and the Kinetics of Organic Cation Transport

PURPOSE

Unstirred water layers (UWLs) present an unavoidable complication to the measurement of transport kinetics in cultured cells, and the high rates of transport achieved by overexpressing heterologous transporters exacerbate the UWL effect. This study examined the correlation between measured Jmax and Kt values and the effect of manipulating UWL thickness or transport Jmax on the accuracy of experimentally determined kinetics of the multidrug transporters, OCT2 and MATE1.

METHODS

Transport of TEA and MPP was measured in CHO cells that stably expressed human OCT2 or MATE1. UWL thickness was manipulated by vigorous reciprocal shaking. Several methods were used to manipulate maximal transport rates.

RESULTS

Vigorous stirring stimulated uptake of OCT2-mediated transport by decreasing apparent Kt (Ktapp) values. Systematic reduction in transport rates was correlated with reduction in Ktapp values. The slope of these relationships indicated a 1500 μm UWL in multiwell plates. Reducing the influence of UWLs (by decreasing either their thickness or the Jmax of substrate transport) reduced Ktapp by 2-fold to >10-fold.

CONCLUSIONS

Failure to take into account the presence of UWLs in experiments using cultured cells to measure transport kinetics can result in significant underestimates of the apparent affinity of multidrug transporters for substrates.

Multidrug and toxic compound extrusion protein-1 (MATE1/SLC47A1) is a novel flavonoid transporter

Dietary flavonoids have various biological functions. However, their cellular transport mechanisms are largely unknown. We have determined that the multidrug and toxic compound extrusion transporter-1 (MATE1) is a membrane transporter for flavonoids and has a high affinity for quercetin. HEK293T cells overexpressing MATE1 exhibited increased intracellular quercetin accumulation. This effect disappeared in the presence of a MATE1 inhibitor and after MATE1 gene knockdown. HepG2 cells expressed MATE1 significantly, with the uptake quercetin of which was dramatically reduced with MATE1 inhibition. On the basis of immunofluorescence analysis, MATE1 was highly expressed in peroxisomes and the endoplasmic reticulum (ER) as well as in plasma membranes in the liver and intestine, which suggests potential accumulation of quercetin in peroxisomes and the ER in these tissues. Fluorescent microscopic analysis confirmed selective accumulation of qurcetin in peroxisome. The effects of quercetin on cellular lipid reduction and glucose uptake were exaggerated with MATE1 overexpression. In conclusion, MATE1 is a membrane transporter for quercetin; its overexpression enhances the hypolipidemic activity of quercetin and cellular glucose transport. Considering the low bioavailability of quercetin, appropriate regulation of MATE1 expression may optimize cellular quercetin concentrations and promote health benefits.

Quantitative NTCP pharmacophore and lack of association between DILI and NTCP Inhibition

The human sodium taurocholate cotransporting polypeptide (NTCP) is a hepatic bile acid transporter. Inhibition of NTCP uptake may potentially also prevent hepatitis B virus (HBV) infection. The first objective was to develop a quantitative pharmacophore for NTCP inhibition. Recent studies showed that hepatotoxic drugs could inhibit bile acid uptake into hepatocytes, without inhibiting canalicular efflux, and cause bile acid elevation in plasma. Hence, a second objective was to examine whether NTCP inhibition is associated with drug induced liver injury (DILI). Twenty-seven drugs from our previous study were used as the training set to develop a quantitative pharmacophore. From secondary screening from a drug database, six retrieved drugs and three drugs not retrieved by the model were tested for NTCP inhibition. Tertiary screening involved drugs known to cause DILI and not cause DILI. Overall, ninety-four drugs were assessed for hepatotoxicity and were assessed relative to NTCP inhibition. The quantitative pharmacophore possessed one hydrogen bond acceptor, one hydrogen bond donor, a hydrophobic feature, and excluded volumes. From 94 drugs, NTCP inhibitors and non-inhibitors were approximately equally distributed across the drugs of most DILI concern, less DILI concern, and no DILI concern, indicating no relationship between NTCP inhibition and DILI risk. Hence, an approach to treat HBV via NTCP inhibition is not expected to be associated with DILI.

Molecular modeling and ligand docking for solute carrier (SLC) transporters

Solute Carrier (SLC) transporters are membrane proteins that transport solutes, such as ions, metabolites, peptides, and drugs, across biological membranes, using diverse energy coupling mechanisms. In human, there are 386 SLC transporters, many of which contribute to the absorption, distribution, metabolism, and excretion of drugs and/or can be targeted directly by therapeutics. Recent atomic structures of SLC transporters determined by X-ray crystallography and NMR spectroscopy have significantly expanded the applicability of structure-based prediction of SLC transporter ligands, by enabling both comparative modeling of additional SLC transporters and virtual screening of small molecules libraries against experimental structures as well as comparative models. In this review, we begin by describing computational tools, including sequence analysis, comparative modeling, and virtual screening, that are used to predict the structures and functions of membrane proteins such as SLC transporters. We then illustrate the applications of these tools to predicting ligand specificities of select SLC transporters, followed by experimental validation using uptake kinetic measurements and other assays. We conclude by discussing future directions in the discovery of the SLC transporter ligands.

SLC22, SLC44, and SLC47 transporters--organic anion and cation transporters: molecular and cellular properties

Transporters within the SLC22, SLC44, and SLC47 families of solute carriers mediate transport of a structurally diverse array of organic electrolytes, that is, molecules that are generally charged (cationic, anionic, or zwitterionic) at physiological pH. Transporters in the SLC22 family--all of which are members of the major facilitator superfamily (MFS) of transporters--represent a mechanistically diverse set of processes, including the organic anion transporters (OATs and URAT1) that physiologically operate as organic anion (OA) exchangers, the organic cation transporters (OCTs) that operate as electrogenic uniporters of organic cations (OCs), and the so-called "novel" organic cation transporters (OCTNs) that support Na-cotransport of selected zwitterions. Whereas the OCTNs display a high degree of substrate selectivity, the physiological hallmark of the OATs and OCTs is their multiselectivity--consistent with a principal role in renal and hepatic clearance of a wide array of both endogenous and xenobiotic compounds. SLC47 consists of members of the multidrug and toxin extruder (MATE) family, which are carriers that are obligatory exchangers and that physiologically support electroneutral H⁺ exchange. The MATEs also display a characteristic multiselectivity and are frequently paired with OCTs to mediate transepithelial OC secretion, with the OCTs typically supporting basolateral OC entry and the MATEs supporting apical OC efflux. The SLC44 family contains the choline transporter-like (CTL) transporters. Largely restricted to choline and a limited set of structural congeners, the CTLs appear to support the Na-independent, electrogenic uniport of choline, thereby providing choline for membrane biogenesis. The solution of X-ray crystal structures of representative prokaryotic MFS and MATE transporters has led to the development of homology models of mammalian OAT, OCT, and MATE transporters that, in turn, have supplemented studies of the molecular basis of the complex interactions of ligands with these multiselective proteins.

Fusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation

The search for new tuberculosis treatments continues as we need to find molecules that can act more quickly, be accommodated in multidrug regimens, and overcome ever increasing levels of drug resistance. Multiple large scale phenotypic high-throughput screens against Mycobacterium tuberculosis (Mtb) have generated dose response data, enabling the generation of machine learning models. These models also incorporated cytotoxicity data and were recently validated with a large external data set. A cheminformatics data-fusion approach followed by Bayesian machine learning, Support Vector Machine, or Recursive Partitioning model development (based on publicly available Mtb screening data) was used to compare individual data sets and subsequent combined models. A set of 1924 commercially available molecules with promising antitubercular activity (and lack of relative cytotoxicity to Vero cells) were used to evaluate the predictive nature of the models. We demonstrate that combining three data sets incorporating antitubercular and cytotoxicity data in Vero cells from our previous screens results in external validation receiver operator curve (ROC) of 0.83 (Bayesian or RP Forest). Models that do not have the highest 5-fold cross-validation ROC scores can outperform other models in a test set dependent manner. We demonstrate with predictions for a recently published set of Mtb leads from GlaxoSmithKline that no single machine learning model may be enough to identify compounds of interest. Data set fusion represents a further useful strategy for machine learning construction as illustrated with Mtb. Coverage of chemistry and Mtb target spaces may also be limiting factors for the whole-cell screening data generated to date.