Role of membrane transporters in the safety profile of drugs

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially.

Drug-induced liver injury: the role of drug metabolism and transport

Many studies have pinpointed the significant contribution of liver-mediated drug metabolism and transport to the complexity of drug-induced liver injury (DILI). Phase I cytochrome P450 (CYP450) enzymes can lead to altered drug metabolism and formation of toxic metabolites, whilst Phase II enzymes are also associated with DILI. The emerging role of hepatic transporters in regulating the movement of endogenous and exogenous chemicals (e.g., bile acids and drugs) across cellular and tissue membranes is critical in determining the pathophysiology of liver disease as well as drug toxicity and efficacy. Genetic and environmental factors can have a significant impact on drug metabolism and transporter proteins, consequently increasing the risk of DILI in susceptible individuals. The assessment of these factors therefore represents an important approach for predicting and preventing DILI, by better understanding the pharmacological profile of a specific drug. This review focuses on the mechanisms of DILI associated with drug metabolism and hepatic transport, and how they can be influenced by underlying factors.

Structure-activity relationships, ligand efficiency, and lipophilic efficiency profiles of benzophenone-type inhibitors of the multidrug transporter P-glycoprotein

The drug efflux pump P-glycoprotein (P-gp) has been shown to promote multidrug resistance (MDR) in tumors as well as to influence ADME properties of drug candidates. Here we synthesized and tested a series of benzophenone derivatives structurally analogous to propafenone-type inhibitors of P-gp. Some of the compounds showed ligand efficiency and lipophilic efficiency (LipE) values in the range of compounds which entered clinical trials as MDR modulators. Interestingly, although lipophilicity plays a dominant role for P-gp inhibitors, all compounds investigated showed LipE values below the threshold for promising drug candidates. Docking studies of selected analogues into a homology model of P-glycoprotein suggest that benzophenones show an interaction pattern similar to that previously identified for propafenone-type inhibitors.

Ligand- and structure-based pregnane X receptor models

The human pregnane X receptor (PXR) is a ligand dependent transcription factor that can be activated by structurally diverse agonists including steroid hormones, bile acids, herbal drugs, and prescription medications. PXR regulates the transcription of several genes involved in xenobiotic detoxification and apoptosis. Activation of PXR has the potential to initiate adverse effects by altering drug pharmacokinetics or perturbing physiological processes. Hence, more reliable prediction of PXR activators would be valuable for pharmaceutical drug discovery to avoid potential toxic effects. Ligand- and protein structure-based computational models for PXR activation have been developed in several studies. There has been limited success with structure-based modeling approaches to predict human PXR activators, which can be attributed to the large and promiscuous site of this protein. Slightly better success has been achieved with ligand-based modeling methods including quantitative structure-activity relationship (QSAR) analysis, pharmacophore modeling and machine learning that use appropriate descriptors to account for the diversity of the ligand classes that bind to PXR. These combined computational approaches using molecular shape information may assist scientists to more confidently identify PXR activators. This chapter reviews the various ligand and structure based methods undertaken to date and their results.

Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy.

Pharmaceutical drug transport: the issues and the implications that it is essentially carrier-mediated only

All cells necessarily contain tens, if not hundreds, of carriers for nutrients and intermediary metabolites, and the human genome codes for more than 1000 carriers of various kinds. Here, we illustrate using a typical literature example the widespread but erroneous nature of the assumption that the 'background' or 'passive' permeability to drugs occurs in the absence of carriers. Comparison of the rate of drug transport in natural versus artificial membranes shows discrepancies in absolute magnitudes of 100-fold or more, with the carrier-containing cells showing the greater permeability. Expression profiling data show exactly which carriers are expressed in which tissues. The recognition that drugs necessarily require carriers for uptake into cells provides many opportunities for improving the effectiveness of the drug discovery process.

Toxicokinetic Considerations in Predicting Toxicity

The ability of a compound to elicit a toxic effect within an organism is dependent upon three factors (i) the external exposure of the organism to the toxicant in the environment or via the food chain (ii) the internal uptake of the compound into the organism and its transport to the site of action in sufficient concentration and (iii) the inherent toxicity of the compound. The in silico prediction of toxicity and the role of external exposure have been dealt with in other chapters of this book. This chapter focuses on the importance of ‘internal exposure’ i.e. the absorption, distribution, metabolism and elimination (ADME) properties of compounds which determine their toxicokinetic profile. An introduction to key concepts in toxicokinetics will be provided, along with examples of modelling approaches and software available to predict these properties. A brief introduction will also be given into the theory of physiologically-based toxicokinetic modelling.