Pharmacophore-based discovery of ligands for drug transporters

The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and the challenges encountered with current approaches are discussed.     

In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling

Pharmacology over the past 100 years has had a rich tradition of scientists with the ability to form qualitative or semi-quantitative relations between molecular structure and activity in cerebro. To test these hypotheses they have consistently used traditional pharmacology tools such as in vivo and in vitro models. Increasingly over the last decade however we have seen that computational (in silico) methods have been developed and applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, pharmacophores, homology models and other molecular modeling approaches, machine learning, data mining, network analysis tools and data analysis tools that use a computer. In silico methods are primarily used alongside the generation of in vitro data both to create the model and to test it. Such models have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The aim of this review is to illustrate some of the in silico methods for pharmacology that are used in drug discovery. Further applications of these methods to specific targets and their limitations will be discussed in the second accompanying part of this review.     

Progress in predicting human ADME parameters in silico

Understanding the development of a scientific approach is a valuable exercise in gauging the potential directions the process could take in the future. The relatively short history of applying computational methods to absorption, distribution, metabolism and excretion (ADME) can be split into defined periods. The first began in the 1960s and continued through the 1970s with the work of Corwin Hansch et al. Their models utilized small sets of in vivo ADME data. The second era from the 1980s through 1990s witnessed the widespread incorporation of in vitro approaches as surrogates of in vivo ADME studies. These approaches fostered the initiation and increase in interpretable computational ADME models available in the literature. The third era is the present were there are many literature data sets derived from in vitro data for absorption, drug-drug interactions (DDI), drug transporters and efflux pumps [P-glycoprotein (P-gp), MRP], intrinsic clearance and brain penetration, which can theoretically be used to predict the situation in vivo in humans. Combinatorial synthesis, high throughput screening and computational approaches have emerged as a result of continual pressure on pharmaceutical companies to accelerate drug discovery while decreasing drug development costs. The goal has become to reduce the drop-out rate of drug candidates in the latter, most expensive stages of drug development. This is accomplished by increasing the failure rate of candidate compounds in the preclinical stages and increasing the speed of nomination of likely clinical candidates. The industry now understands the reasons for clinical failure other than efficacy are mainly related to pharmacokinetics and toxicity. The late 1990s saw significant company investment in ADME and drug safety departments to assess properties such as metabolic stability, cytochrome P-450 inhibition, absorption and genotoxicity earlier in the drug discovery paradigm. The next logical step in this process is the evaluation of higher throughput data to determine if computational (in silico) models can be constructed and validated from it. Such models would allow an exponential increase in the number of compounds screened virtually for ADME parameters. A number of researchers have started to utilize in silico, in vitro and in vivo approaches in parallel to address intestinal permeability and cytochrome P-450-mediated DDI. This review will assess how computational approaches for ADME parameters have evolved and how they are likely to progress.     

From in vivo to in vitro/in silico ADME: progress and challenges

High-throughput screening technologies in biological sciences of large libraries of compounds obtained via combinatorial or parallel chemistry approaches, as well as the application of design rules for drug-likeness, have resulted in more hits to be evaluated with respect to their ADME or drug metabolism and pharmacokinetic properties. The traditional in vivo methods using preclinical species, such as rat, dog or monkey, are no longer sufficient to cope with this demand. This editorial discusses the changes towards medium- to high-throughput in vitro and in silico ADME screening. In addition, much more attention is now put on early safety and risk assessment of promising lead series and potential clinical candidates.     

In vitro testing of drug absorption for drug 'developability' assessment: forming an interface between in vitro preclinical data and clinical outcome

Drug 'developability' assessment has become an increasingly important addition to traditional drug efficacy and toxicity evaluations, as pharmaceutical scientists strive to accelerate drug discovery and development processes in a time- and cost-effective manner. The fraction of drug absorbed and the maximum absorbable dose (MAD) can be estimated from in vivo clinical pharmacokinetics, mass balance studies or in vivo drug permeability in humans by different calculation methods. Unfortunately, in vivo data are usually unavailable at the early stages of drug discovery and development, and in vitro screening for the permeability, solubility, activity and toxicity of a drug has become a routine measurement in drug discovery and development. These in vitro data could be used to predict drug 'developability' with different calculation methods before selecting candidates for clinical evaluation. The fraction of drug absorbed in human could be predicted by in vivo human permeability or in vitro Caco2 permeability. For example, if drug permeability in Caco2 cells reaches 13.3 to 18.1 x 10(-6) cm/s, its predicted in vivo permeability in humans would reach 2 x 10(-4) cm/s, and its predicted fraction of drug absorbed would be > 90%, which is defined as highly permeable. The MAD could also be predicted with in vitro permeability, or calculated absorption rate constant. In addition, in vitro solubility and permeability data can also be used for the biopharmaceutics classification system (BCS) and, subsequently, to direct formulation optimization strategies. If drug 'developability' becomes an obstacle for drug delivery based on these in vitro data and predictions at the early stages of drug discovery and development, options such as prodrug approaches could be explored to enhance drug 'developability', in addition to different formulation methods. Therefore, in vitro absorption testing is a highly valuable tool in the decision-making process to select candidates for in vivo clinical studies at early-stage drug discovery and development.     

Focus on success: using a probabilistic approach to achieve an optimal balance of compound properties in drug discovery

The success of any drug will depend on how closely it achieves an ideal combination of potency, selectivity, pharmacokinetics and safety. The key to achieving this success efficiently is to consider the overall balance of molecular properties of compounds against the ideal profile for the therapeutic indication from the earliest stages of a drug discovery project. The use of in silico predictive models of absorption, distribution, metabolism and elimination (ADME) and physicochemical properties is a major aid in this exercise, as it enables virtual molecules to be assessed across a broad range of properties from initial library generation, through to candidate selection. Of course, no measurement, whether in silico, in vitro or in vivo, is perfect and the uncertainties in any data should be explicitly taken into account when basing conclusions on test results. In addition, in the early stages of drug discovery, when designing a library that is lead seeking or building compound structure-activity relationships, the quality of any set of molecules should also be balanced against the chemical diversity covered. Here, a scheme is presented for achieving these goals based on a suite of predictive ADME models, probabilistic scoring and multiobjective optimisation for library design. The use of this platform for applications in lead identification and optimisation is illustrated.     

QSPR in oral bioavailability: specificity or integrality?

During the last decade the technological advances in drug discovery changed the absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles of New Chemical Entities (NCEs). Among ADMET processes, absorption plays an important role in the research and development of more effective orally administered drugs. Although significant progress has been made in in vitro, in situ and in vivo experimental determinations of absorption, the development of in silico methodologies has emerged as a cheaper and fast alternative to predict them. Even though several in silico models have been described in the literature to predict oral bioavailability and related properties, the prediction accuracy and their potential use is still limited. The low precision and high variability of data, the lack of a complete experimental and theoretical validation of in silico approach, and above all, the multi-factorial nature of the oral absorption term, make the development of predictive in silico models a thorny task. The present review discusses several important advances regarding the QSPR approaches used in the development of predictive oral bioavailability models. The importance of fixing the problem associated with data resource, as well as improving the reliability of in silico results is highlighted. Optimization of individual properties along the absorption process must be integrated in a multi-objective scenario for studying oral bioavailability behavior in the early drug discovery and development.     

Permeability--in vitro assays for assessing drug transporter activity

The accumulating evidence has revealed that drug transporters have essential roles in the delivery and excretory processes of drugs and their metabolites. Inhibition or induction of drug transporters can affect pharmacokinetic properties and therapeutic efficacy of a drug. Thus, the characterization of drug-transporter interactions becomes important for the selection of compounds to avoid transporter associated absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) issues. Additionally, the potential use of absorptive transporters for drug delivery has been recognized for drug design. In vitro and in vivo approaches have been developed for studying the transporter activities. In vitro assays can rapidly provide the information for identifying interaction of a compound and a particular transporter and have proved to be amenable to high throughput approaches. Therefore, the studies are conducted in early drug discovery. In this article, in vitro methods are reviewed, including cell free and cell-based assays. Their applications, limitations and impact on drug discovery are discussed.     

In vitro prediction of gastrointestinal absorption and bioavailability: an experts' meeting report

The most convenient route of drug administration is peroral. To reach their target, drug molecules must be absorbed from the gastrointestinal tract and enter the systemic circulation in sufficient quantities. For this reason, understanding and anticipating the mechanisms and factors affecting gastrointestinal absorption and metabolism are of the utmost importance in developing new drugs. In contrast to drugs, which are administered intentionally for therapeutic reasons, chemical residues in food and other matrices enter the body unintentionally. Hence, in this case, a low systemic availability would be advantageous. For many reasons, but particularly because of financial and ethical (reduced used of animals) considerations, in vitro and ex vivo approaches to this problem have been pursued over the last few years. The use of in vitro methods, however, inherently creates questions about the validity of extrapolation to the in vivo situation. The purpose of this report is to review the current status of the field and to identify major gaps in our knowledge. Currently, there are a number of in silico, in vitro, cultured cell-based and ex vivo approaches available to predict the cell permeation, absorption and gastrointestinal metabolism of molecules. Some strengths and weaknesses of these approaches are presented, together with a discussion of genetic, environmental, physiological and pathological factors responsible for interspecies and inter-individual variability in these processes. Recent advances in our understanding of active processes such as gut epithelial transporters, involved in absorption, and drug-metabolising enzymes, responsible for intestinal presystemic metabolism, are highlighted. Some major research priorities are identified, including the need for high-quality, information-rich databases against which testing methods being developed can be prevalidated and validated. Preclinical drug development is changing rapidly, and the role of in vitro and ex vivo approaches in this process is becoming increasingly more important. Methods available now are very useful in the drug discovery and development process, including lead compound selection and optimisation and in the design of very early clinical studies, but whether any of them will eventually obviate the need for clinical trials of bioavailability is still very debatable and will require their full validation. It is clear, however, that the results from such in vitro tests are important in shaping drug discovery and the early preclinical drug development process. For other environmental, industrial and household chemicals to which humans are exposed, in particular new chemicals, results from in vitro studies might be the only source of information concerning systemic availability.     

新药研发过程中毒理学研究方法的进展--毒性的原因和早期毒性筛选

毒性已成为新药开发过程中淘汰的主要原因。近年来制药和生物技术工业的研究人员开发了多种新技术以便在药物发现和开发过程中尽早确定化合物的安全特性。笔者首先对药物毒性产生的原因如药靶的特异性、药物的分子结构、药物代谢和代谢动力学等方面进行了分析，再介绍了近几年早期毒性筛选的新技术，包括预测模型、体外高通量毒性筛选、活性代谢产物的检测、高内涵筛选技术、动物实验。     

Introduction to in vitro estimation of metabolic stability and drug interactions of new chemical entities in drug discovery and development

Determination of metabolic properties of a new chemical entity (NCE) is one of the most important steps during the drug discovery and development process. Nowadays, in vitro methods are used for early estimation and prediction of in vivo metabolism of NCEs. Using in vitro methods, it is possible to determine the metabolic stability of NCEs as well as the risk for drug-drug interactions (DDIs) related to inhibition and induction of drug metabolic enzymes. Metabolic stability is defined as the susceptibility of a chemical compound to biotransformation, and is expressed as in vitro half-life (t(1/2)) and intrinsic clearance (CL(int)). Based on these values, in vivo pharmacokinetic parameters such as bioavailability and in vivo half-life can be calculated. The drug metabolic enzymes possess broad substrate specificity and can metabolize multiple compounds. Therefore, the risk for metabolism-based DDIs is always a potential problem during the drug development process. For this reason, inhibition and induction in vitro screens are used early, before selection of a candidate drug (CD), to estimate the risk for clinically significant DDIs. At present, most pharmaceutical companies perform in vitro drug metabolism studies together with in silico prediction software and automated high-throughput screens (HTS). Available data suggest that in vitro methods are useful tools for identification and elimination of NCEs with unappreciated metabolic properties. However, the quantitative output of the methods has to be improved. The aim of this review is to highlight the practical and theoretical basis of the in vitro metabolic methods and the recent progress in the development of these assays.     

High-throughput screening approaches for investigating drug metabolism and pharmacokinetics

1. High-throughput screening approaches have been adopted throughout the pharmaceutical industry to aid in the rapid discovery of new chemical entities. Because it is now well recognized that the selection of a robust candidate requires a balance of potency, safety and pharmacokinetics, the role of drug metabolism departments has widened from their traditional one of supporting drug development to include the screening of compounds during the discovery process. To put drug metabolism and pharmacokinetic (DMPK) studies in context, the evolving role of DMPK screening in the drug discovery strategy of pharmaceutical companies will be discussed and a generalized approach will be presented. 2. With the increasing numbers of compounds requiring screening, DMPK optimization methods have had to be adapted for high throughput. There have been many developments in this field over the past decade and this review will focus on the high-throughput DMPK screening methodologies used today and in the recent past. 3. In vitro and in silico (computer-based) methods have proven most amenable to high-throughput approaches and these will firm the bulk of the review, but some advances with in vivo methods will also be discussed. As there has been a vast increase in published material on the topic of high-throughput DMPK methodologies in the past 10 years, it would be impossible to cover every method in detail, so this review will concentrate on the key areas and refer the reader to other, more detailed reviews wherever possible. 4. Most high-throughput methods would not be possible without the enabling technologies of computing, automation, new sample preparation technologies, and highly sensitive and selective detection systems, and these will also be reviewed. 5. The advantages and disadvantages of the screening methods will be presented, in particular the issue of handling the false-positives and -negatives that arise. 6. In concluding the review, future developments in this field will be discussed along with key issues that will need to be addressed.     

The role of early in vivo toxicity testing in drug discovery toxicology

The cost impact of late-stage failures of drug candidates has motivated the pharmaceutical industry to develop, validate, and implement a more proactive testing paradigm, including an emphasis on conducting predictive in vitro and in vivo studies earlier. The goal of drug discovery toxicology is not to reduce or eliminate attrition, as is often mis-stated as such, but rather to reprioritize efforts to shift attrition of future failing molecules upstream in discovery. This shift in attrition requires additional studies and investment earlier in the candidate evaluation process in order to avoid spending resources on molecules with soon-to-be-discovered development-limiting liabilities. While in silico and in vitro models will continually be developed and refined, in vivo preclinical safety models remain the gold standard for assessing human risk. For in vivo testing to influence early discovery effectively, it must: i) require low amounts of compound; ii) provide rapid results to drive decision-making and medicinal chemistry efforts; and iii) be flexible and provide results relevant to the development plan tailored to each target, drug class, and/or indication.     

The search for drug leads targeted to the beta-secretase: an example of the roles of computer assisted approaches in drug discovery

The inhibition of beta-secretase has become a very promising approach to control the onset and progression of Alzheimer's disease due to its involvement in the generation of amyloid plaques. The main goal of the many drug discovery projects targeting this enzyme is the identification of highly specific, non-peptidic compounds with low molecular weight, characteristics that are desirable for drug leads with low toxicity that have to transverse the blood brain barrier. We describe the main approaches used in the discovery of novel inhibitors, including substrate specificity, target structure based design, and high throughput screening (HTS), both in vitro and in silico. We place special emphasis in the receptor based design and in silico HTS, two strategies that make wide use of computer assisted tools. To exemplify the usefulness and versatility of computer tools in this endeavor we use the computer generated 'enzyme's binding site cast' to rationalize qualitatively some salient structural features of known beta-secretase second generation inhibitors, and for guiding the review of many of the ligands whose complexes with the enzyme have been studied by X-ray crystallography. We discuss the use made by other authors of molecular modelling for the understanding of the very special characteristics of ligand binding to beta-secretase and for the design of new inhibitors. Finally, we review the quest for non-peptidic inhibitors that has led to the use of HTS in vitro and in silico. The screening of extensive libraries resulted in a few low affinity compounds that do not fit into the key S1/S1' pockets, indicating that this is not an easy target to block.     

Assays to predict drug permeation across the blood-brain barrier, and distribution to brain

Drug discovery programmes to target or avoid the brain need to take into account the properties of the blood-brain barrier (BBB). The importance to CNS PK of the free drug concentration in brain is increasingly recognised, and assays for drug discovery programmes are being adjusted accordingly. In vitro models of the BBB continue to play an important role in this process. Good cell-based models using brain endothelium have been developed and validated for mechanistic studies, and some are suitable for medium to high throughput permeability screening and toxicology. Brain homogenate and brain slice methods allow estimation of drug partition into brain. In combination with in silico and in vivo models, the portfolio of methods establishing and predicting CNS drug PK is now very powerful, allowing much more accurate iterative feedback to chemists to optimise compound profiles through the drug discovery and development programme. The advantage of using models based on real BBB cellular anatomy and physiology is that they have the power to reveal and incorporate previously undiscovered properties, such as new transporters, metabolic enzymes and modulation, to form the basis for models mimicking neurological disorders as well as normal function, and to allow physiologically-based pharmacokinetic (PBPK) extrapolation from animal models to humans.     

Utility of physiologically based pharmacokinetic models to drug development and rational drug discovery candidate selection

The present paper proposes a modeling and simulation strategy for the prediction of pharmacokinetics (PK) of drug candidates by using currently available in silico and in vitro based prediction tools for absorption, distribution, metabolism and excretion (ADME). These methods can be used to estimate specific ADME parameters (such as rate and extent of absorption into portal vein, volume of distribution, metabolic clearance in the liver). They can also be part of a physiologically based pharmacokinetic (PBPK) model to simulate concentration-time profiles in tissues and plasma resulting from the overall PK after intravenous or oral administration. Since the ADME prediction tools are built only on commonly generated in silico and in vitro data, they can be applied already in early drug discovery, prior to any in vivo study. With the suggested methodology, the following advantages of the mechanistic PBPK modeling framework can now be utilized to explore potential clinical candidates already in drug discovery: (i) prediction of plasma (blood) and tissue PK of drug candidates prior to in vivo experiments, (ii) supporting a better mechanistic understanding of PK properties, as well as helping the development of more rationale PK-PD relationships from tissue kinetic data predicted, and hence facilitating a more rational decision during clinical candidate selection, and (iii) the extrapolation across species, routes of administration and dose levels.     

Assessing drug transport across the human placental barrier: from in vivo and in vitro measurements to the ex vivo perfusion method and in silico techniques

Assessing drug transport across the human placental barrier is of vital importance in order to guarantee drug safety during pregnancy. However, due to ethical reasons, in vivo fetal development risk assessment studies related to maternal drugs and chemicals exposure remain extremely limited. To overcome any ethical issues, several in vitro models applying primary trophoblastic cells, immortal cell lines and tissue explants of placental origin have recently been advanced. Alternatively, ex vivo human placental perfusion seems to be a more representative and highly informative method, which offers better insights into the different drug transporters, xenobiotic metabolism and tissue binding. Recently, in silico techniques have further been advanced as complementary tools to validate experimental placental transfer data, offering an attractive alternative for high throughput screening of potential fetotoxicity at the early stages of drug design. The present review scrutinizes, from a critical point of view, the current trends and perspectives in the emerging topic of drug transport across the human placental barrier. The special characteristics of the recently developed biopharmaceuticals on the transplacental transfer process are also discussed.     

In vitro screening techniques for reactive metabolites for minimizing bioactivation potential in drug discovery

Drug induced toxicity remains one of the major reasons for failures of new pharmaceuticals, and for the withdrawal of approved drugs from the market. Efforts are being made to reduce attrition of drug candidates, and to minimize their bioactivation potential in the early stages of drug discovery in order to bring safer compounds to the market. Therefore, in addition to potency and selectivity; drug candidates are now selected on the basis of acceptable metabolism/toxicology profiles in preclinical species. To support this, new approaches have been developed, which include extensive in vitro methods using human and animal hepatic cellular and subcellular systems, recombinant human drug metabolizing enzymes, increased automation for higher-throughput screens, sensitive analytical technologies and in silico computational models to assess the metabolism aspects of the new chemical entities. By using these approaches many compounds that might have serious adverse reactions associated with them are effectively eliminated before reaching clinical trials, however some toxicities such as those caused by idiosyncratic responses, are not detected until a drug is in late stages of clinical trials or has become available to the market. One of the proposed mechanisms for the development of idiosyncratic drug toxicity is the bioactivation of drugs to form reactive metabolites by drug metabolizing enzymes. This review discusses the different approaches to, and benefits of using existing in vitro techniques, for the detection of reactive intermediates in order to minimize bioactivation potential in drug discovery.     

Emerging applications of kinetic biomarkers in preclinical and clinical drug development

The cost of drug discovery and development is increasing, while the rate of new drug approvals is declining. In contrast to major technological advances with in silico and in vitro screening tools, there have been almost no advances in the tools available for establishing the actions of agents in the complex biochemical networks characteristic of fully assembled living systems. The resulting poor capacity to predict clinical response underlies the high attrition rate of leads at every step of drug development. A potential solution would be provided by kinetic biomarkers (in vivo measurement of fluxes though the key pathways that drive disease processes and therapeutic response). Novel approaches using stable isotope labeling with mass spectrometric analysis have recently emerged for measuring molecular kinetics relevant to drug targets with some applications to drug development. This review discusses the general principles of kinetic biomarkers, providing examples where kinetics have generated meaningful insights into drug activity and highlighting areas where the application of kinetic biomarkers may be particularly useful for future drug discovery and development. Stable isotope mass spectrometric technologies may provide a parallel efficiency for converting molecules into approved drugs with sufficient throughput and reproducibility to maintain pace with the modern engine for generating leads.