Application of anin vitroOAT assay in drug design and optimization of renal clearance

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.

Effect of OATP-binding on the prediction of biliary excretion

1. Biliary excretion of compounds is dependant on several transporter proteins for the active uptake of compounds from the blood into the hepatocytes. Organic anion-transporting polypeptides (OATPs) are some of the most abundant transporter proteins in the sinusoidal membrane and have been shown to have substrate specificity similar to the structural characteristics of cholephilic compounds. 2. In this study, we sought to use measures of OATP binding as predictors of biliary excretion in conjunction with molecular descriptors in a quantitative structure-activity relationship (QSAR) study. Percentage inhibitions of three subtypes of OATPs were used as surrogate indicators of OATP substrates. Several statistical modelling techniques were incorporated including classification and regression trees, boosted trees, random forest and multivariate adaptive regression splines (MARS) in order to first develop QSARs for the prediction of OATP inhibition of compounds. The predicted OATP percentage inhibition using selected models were then used as features of the QSAR models for the prediction of biliary excretion of compounds in rat. 3. The results indicated that incorporation of predicted OATP inhibition improves accuracy of biliary excretion models. The best result was obtained from a simple regression tree that used predicted OATP1B1 percentage inhibition at the root node of the tree.

Hepatic drug transporters: the journey so far

INTRODUCTION

The key role of transporter biology in both the manifestation and treatment of disease is now firmly established. Experiences of sub-optimal drug exposure due to drug-transporter interplay have supported incorporation of studies aimed at understanding the interactions between compounds and drug transporters much earlier in drug discovery. While drug transporters can impact the most pivotal pharmacokinetic parameter with respect to human dose and exposure projections, clearance, at a renal or hepatobiliary level, the latter will form the focus of this perspective.

AREAS COVERED

A synopsis of guidelines on which transporters to study together with an overview of the currently available toolkit is presented. A perspective on when to conduct studies with various hepatic transporters is also provided together with structural "alerts" which should prompt early investigation.

EXPERT OPINION

Great progress has been made in individual laboratories and via consortia to understand the role of drug transporters in disease, drug disposition, drug-drug interactions and toxicity. A systematic analysis of the value posed by the available approaches and an inter-lab comparison now seems warranted. The emerging ability to use physico-chemical properties to guide future screening cascades promises to revolutionise the efficiency of early drug discovery.

Transmembrane transport of steviol glucuronide and its potential interaction with selected drugs and natural compounds

Steviol glucuronide (SVG) is the major metabolite derived from steviol, the aglycone of stevioside and rebaudioside A. After the ingestion of stevioside and rebaudioside A, SVG is formed and excreted into the urine in humans. In the present study, transporter mediated efflux and uptake of SVG was investigated in order to understand molecular mechanisms underlying its renal clearance. Results showed that SVG was not a substrate of efflux transporters BCRP, MRP2, MATE1 or P-gp. In contrast, OAT3 played a predominant role in the uptake of SVG in comparison to OATP1B1, OATP1B3, or OATP2B1. Quercetin, telmisartan, diclofenac, and mulberrin displayed a relatively strong inhibition against OAT3 mediated uptake of SVG with IC50 values of 1.8, 2.9, 8.0, and 10.0 μM, respectively. Because OAT3 is a major uptake transporter in the kidney, inhibition of OAT3 activity may alter SVG's renal clearance by drugs and natural compounds that are used concomitantly with stevia leaf extracts.

Computational modeling to predict the functions and impact of drug transporters

Transport proteins are important mediators of cellular drug influx and efflux and play crucial roles in drug distribution, disposition and clearance. Drug-drug interactions have increasingly been found to occur at the transporter level and, hence, computational tools for studying drug-transporter interactions have gained in interest. In this short review, we present the most important transport proteins for drug influx and efflux. Computational tools for predicting and understanding the substrate and inhibitor interactions with these membrane-bound proteins are discussed. We have primarily focused on ligand-based and structure-based modeling, for which the state-of-the-art and future challenges are also discussed.