Structural alert/reactive metabolite concept as applied in medicinal chemistry to mitigate the risk of idiosyncratic drug toxicity: a perspective based on the critical examination of trends in the top 200 drugs marketed in the United States

Shaping a screening file for maximal lead discovery efficiency and effectiveness: elimination of molecular redundancy

High Throughput Screening (HTS) is a successful strategy for finding hits and leads that have the opportunity to be converted into drugs. In this paper we highlight novel computational methods used to select compounds to build a new screening file at Pfizer and the analytical methods we used to assess their quality. We also introduce the novel concept of molecular redundancy to help decide on the density of compounds required in any region of chemical space in order to be confident of running successful HTS campaigns.

Latest advances in predicting DILI in human subjects: focus on biomarkers

INTRODUCTION

The quest for a biomarker that would reliably identify patients at risk of developing acute drug-induced liver injury (DILI) to a specific agent or class of agents before it occurs, has been underway for years. Historical host factors for DILI, such as older age and female gender, are not considered sufficient to truly predict an individual's inherent risk of DILI. In vitro and animal-based biomarker discoveries, in many instances, have not been considered accurate enough for drug development in human subjects nor for use in clinical practice.

AREAS COVERED

In order to assess the current state of biomarkers to predict idiosyncratic human DILI, the authors utilized the PubMed literature search tool to identify research reports dealing with clinical DILI biomarkers covering the period of 2010 through to June 2012. Studies involving pharmacogenetic, proteomic and toxicogenomic analyses are preferentially reviewed.

EXPERT OPINION

Although acute DILI has been linked to specific genetic associations (e.g., flucloxacillin and HLA-B*5701; and certain polymorphisms seen with anti-TB agent DILI), such predictors have been able to identify only some patients at risk for only a limited number of drugs. Proteomic-based biomarkers from stored sera in the US DILI Network, such as apolipoprotein E, have been identified as potential candidates, but require further study. As it currently stands, the quest for a widely applicable, validated DILI biomarker remains an ongoing clinical challenge.

Preclinical strategy to reduce clinical hepatotoxicity using in vitro bioactivation data for >200 compounds

Drug-induced liver injury is the most common cause of market withdrawal of pharmaceuticals, and thus, there is considerable need for better prediction models for DILI early in drug discovery. We present a study involving 223 marketed drugs (51% associated with clinical hepatotoxicity; 49% non-hepatotoxic) to assess the concordance of in vitro bioactivation data with clinical hepatotoxicity and have used these data to develop a decision tree to help reduce late-stage candidate attrition. Data to assess P450 metabolism-dependent inhibition (MDI) for all common drug-metabolizing P450 enzymes were generated for 179 of these compounds, GSH adduct data generated for 190 compounds, covalent binding data obtained for 53 compounds, and clinical dose data obtained for all compounds. Individual data for all 223 compounds are presented here and interrogated to determine what level of an alert to consider termination of a compound. The analysis showed that 76% of drugs with a daily dose of <100 mg were non-hepatotoxic (p < 0.0001). Drugs with a daily dose of ≥100 mg or with GSH adduct formation, marked P450 MDI, or covalent binding ≥200 pmol eq/mg protein tended to be hepatotoxic (∼ 65% in each case). Combining dose with each bioactivation assay increased this association significantly (80-100%, p < 0.0001). These analyses were then used to develop the decision tree and the tree tested using 196 of the compounds with sufficient data (49% hepatotoxic; 51% non-hepatotoxic). The results of these outcome analyses demonstrated the utility of the tree in selectively terminating hepatotoxic compounds early; 45% of the hepatotoxic compounds evaluated using the tree were recommended for termination before candidate selection, whereas only 10% of the non-hepatotoxic compounds were recommended for termination. An independent set of 10 GSK compounds with known clinical hepatotoxicity status were also assessed using the tree, with similar results.

Molecular conformations, interactions, and properties associated with drug efficiency and clinical performance among VEGFR TK inhibitors

Analyses of compounds in clinical development have shown that ligand efficient-molecules with privileged physical properties and low dose are less likely to fail in the various stages of clinical testing, have fewer postapproval withdrawals, and are less likely to receive black box safety warnings. However, detailed side-by-side examination of molecular interactions and properties within single drug classes are lacking. As a class, VEGF receptor tyrosine kinase inhibitors (VEGFR TKIs) have changed the landscape of how cancer is treated, particularly in clear cell renal cell carcinoma, which is molecularly linked to the VEGF signaling axis. Despite the clear role of the molecular target, member molecules of this validated drug class exhibit distinct clinical efficacy and safety profiles in comparable renal cell carcinoma clinical studies. The first head-to-head randomized phase III comparative study between active VEGFR TKIs has confirmed significant differences in clinical performance [Rini BI, et al. (2011) Lancet 378:193-1939]. To elucidate how fundamental drug potency-efficiency is achieved and impacts differentiation within the VEGFR TKI class, we determined potencies, time dependence, selectivities, and X-ray structures of the drug-kinase complexes using a VEGFR2 TK construct inclusive of the important juxtamembrane domain. Collectively, the studies elucidate unique drug-kinase interactions that are dependent on distinct juxtamembrane domain conformations, resulting in significant potency and ligand efficiency differences. The identified structural trends are consistent with in vitro measurements, which translate well to clinical performance, underscoring a principle that may be broadly applicable to prospective drug design for optimal in vivo performance.

Quantitative risk assessment methods for cancer and noncancer effects

Human health risk assessments have evolved from the more qualitative approaches to more quantitative approaches in the past decade. This has been facilitated by the improvement in computer hardware and software capability and novel computational approaches being slowly recognized by regulatory agencies. These events have helped reduce the reliance on experimental animals as well as better utilization of published animal toxicology data in deriving quantitative toxicity indices that may be useful for risk management purposes. This chapter briefly describes some of the approaches as described in the guidance documents from several of the regulatory agencies as it pertains to hazard identification and dose-response assessment of a chemical. These approaches are contrasted with more novel computational approaches that provide a better grasp of the uncertainty often associated with chemical risk assessments.

Impact of the pharmaceutical sciences on health care: a reflection over the past 50 years

During the last century, particularly the latter half, spectacular progress has been made in improving the health and longevity of people. The reasons are many, but the development of medicines has played a critical role. This report documents and reflects on the impressive contribution that those working in the pharmaceutical sciences have made to healthcare over the past 50 years. It is divided into six sections (drug discovery; absorption, distribution, metabolism, and excretion; pharmacokinetics and pharmacodynamics; drug formulation; drug regulation; and drug utilization), each describing key contributions that have been made in the progression of medicines, from conception to use. A common thread throughout is the application of translational science to the improvement of drug discovery, development, and therapeutic application. Each section has been coordinated by a leading scientist who was asked, after consulting widely with many colleagues across the globe, to identify "The five most influential ideas/concepts/developments introduced by 'pharmaceutical scientists' (in their field) over the past 50 years?" Although one cannot predict where the important breakthroughs will come in the future to meet the unmet medical needs, the evidence presented in this report should leave no doubt that those engaged in the pharmaceutical sciences will continue to make their contributions heavily felt.

Novel bioactivation mechanism of reactive metabolite formation from phenyl methyl-isoxazoles

Recently, we described a series of phenyl methyl-isoxazole derivatives as novel, potent, and selective inhibitors of the voltage-gated sodium channel type 1.7 (Bioorg Med Chem Lett 21:3871-3876, 2011). The lead compound, 2-chloro-6-fluorobenzyl [3-(2,6-dichlorophenyl)-5-methylisoxazol-4-yl]carbamate, showed unprecedented GSH and cysteine reactivity associated with NADPH-dependent metabolism in trapping studies using human liver microsomes. Additional trapping experiments with close analogs and mass spectra and NMR analyses suggested that the conjugates were attached directly to the 5'-methyl on the isoxazole moiety. We propose a mechanism of bioactivation via an initial oxidation of the 5'-methyl generating a stabilized enimine intermediate and a subsequent GSH attack on the 5'-methylene. Efforts to ameliorate reactive metabolite generation were undertaken to minimize the potential risk of toxicity. Formation of reactive metabolites could be significantly reduced or prevented by removing the 5'-methyl, by N-methylation of the carbamate; by replacing the nitrogen with a carbon or removing the nitrogen to obtain a carboxylate; or by inserting an isomeric 5'-methyl isoxazole. The effectiveness of these various chemical modifications in reducing GSH adduct formation is in line with the proposed mechanism. In conclusion, we have identified a novel mechanism of bioactivation of phenyl 5-methyl-isoxazol-4-yl-amines. The reactivity was attenuated by several modifications aimed to prevent the emergence of an enimine intermediate. Whether 5'-methyl isoxazoles should be considered a structural alert for potential formation of reactive metabolites is dependent on their context, i.e., 4'-nitrogen.

ToxAlerts: a Web server of structural alerts for toxic chemicals and compounds with potential adverse reactions

The article presents a Web-based platform for collecting and storing toxicological structural alerts from literature and for virtual screening of chemical libraries to flag potentially toxic chemicals and compounds that can cause adverse side effects. An alert is uniquely identified by a SMARTS template, a toxicological endpoint, and a publication where the alert was described. Additionally, the system allows storing complementary information such as name, comments, and mechanism of action, as well as other data. Most importantly, the platform can be easily used for fast virtual screening of large chemical datasets, focused libraries, or newly designed compounds against the toxicological alerts, providing a detailed profile of the chemicals grouped by structural alerts and endpoints. Such a facility can be used for decision making regarding whether a compound should be tested experimentally, validated with available QSAR models, or eliminated from consideration altogether. The alert-based screening can also be helpful for an easier interpretation of more complex QSAR models. The system is publicly accessible and tightly integrated with the Online Chemical Modeling Environment (OCHEM, http://ochem.eu). The system is open and expandable: any registered OCHEM user can introduce new alerts, browse, edit alerts introduced by other users, and virtually screen his/her data sets against all or selected alerts. The user sets being passed through the structural alerts can be used at OCHEM for other typical tasks: exporting in a wide variety of formats, development of QSAR models, additional filtering by other criteria, etc. The database already contains almost 600 structural alerts for such endpoints as mutagenicity, carcinogenicity, skin sensitization, compounds that undergo metabolic activation, and compounds that form reactive metabolites and, thus, can cause adverse reactions. The ToxAlerts platform is accessible on the Web at http://ochem.eu/alerts, and it is constantly growing.

Strategies for the generation, validation and application of in silico ADMET models in lead generation and optimization

INTRODUCTION

The most desirable chemical starting point in drug discovery is a hit or lead with a good overall profile, and where there may be issues; a clear SAR strategy should be identifiable to minimize the issue. Filtering based on drug-likeness concepts are a first step, but more accurate theoretical methods are needed to i) estimate the biological profile of molecule in question and ii) based on the underlying structure-activity relationships used by the model, estimate whether it is likely that the molecule in question can be altered to remove these liabilities.

AREAS COVERED

In this paper, the authors discuss the generation of ADMET models and their practical use in decision making. They discuss the issues surrounding data collation, experimental errors, the model assessment and validation steps, as well as the different types of descriptors and statistical models that can be used. This is followed by a discussion on how the model accuracy will dictate when and where it can be used in the drug discovery process. The authors also discuss how models can be developed to more effectively enable multiple parameter optimization.

EXPERT OPINION

Models can be applied in lead generation and lead optimization steps to i) rank order a collection of hits, ii) prioritize the experimental assays needed for different hit series, iii) assess the likelihood of resolving a problem that might be present in a particular series in lead optimization and iv) screen a virtual library based on a hit or lead series to assess the impact of diverse structural changes on the predicted properties.

Drug discovery for a new generation of covalent drugs

INTRODUCTION

The design of target-specific covalent inhibitors is conceptually attractive because of increased biochemical efficiency through covalency and increased duration of action that outlasts the pharmacokinetics of the agent. Although many covalent inhibitors have been approved or are in advanced clinical trials to treat indications such as cancer and hepatitis C, there is a general tendency to avoid them as drug candidates because of concerns regarding immune-mediated toxicity that can arise from indiscriminate reactivity with off-target proteins.

AREAS COVERED

The review examines potential reason(s) for the excellent safety record of marketed covalent agents and advanced clinical candidates for emerging therapeutic targets. A significant emphasis is placed on proteomic techniques and chemical/biochemical reactivity assays that aim to provide a systematic rank ordering of pharmacologic selectivity relative to off-target protein reactivity of covalent inhibitors.

EXPERT OPINION

While tactics to examine selective covalent modification of the pharmacologic target are broadly applicable in drug discovery, it is unclear whether the output from such studies can prospectively predict idiosyncratic immune-mediated drug toxicity. Opinions regarding an acceptable threshold of protein reactivity/body burden for a toxic electrophile and a non-toxic electrophilic covalent drug have not been defined. Increasing confidence in proteomic and chemical/biochemical reactivity screens will require a retrospective side-by-side profiling of marketed covalent drugs and electrophiles known to cause deleterious toxic effects via non-selective covalent binding.

Established and emerging trends in computational drug discovery in the structural genomics era

Bioinformatics and chemoinformatics approaches contribute to hit discovery, hit-to-lead optimization, safety profiling, and target identification and enhance our overall understanding of the health and disease states. A vast repertoire of computational methods has been reported and increasingly combined in order to address more and more challenging targets or complex molecular mechanisms in the context of large-scale integration of structure and bioactivity data produced by private and public drug research. This review explores some key computational methods directly linked to drug discovery and chemical biology with a special emphasis on compound collection preparation, virtual screening, protein docking, and systems pharmacology. A list of generally freely available software packages and online resources is provided, and examples of successful applications are briefly commented upon.

Simultaneous screening of glutathione and cyanide adducts using precursor ion and neutral loss scans-dependent product ion spectral acquisition and data mining tools

Drugs can be metabolically activated to soft and hard electrophiles, which are readily trapped by glutathione (GSH) and cyanide (CN), respectively. These adducts are often detected and structurally characterized using separate tandem mass spectrometry methods. We describe a new method for simultaneous screening of GSH and CN adducts using precursor ion (PI) and neutral loss (NL) scans-dependent product ion spectral acquisition and data mining tools on an triple quadrupole linear ion trap mass spectrometry. GSH, potassium cyanide, and their stable isotope labeled analogues were incubated with liver microsomes and a test compound. Negative PI scan of m/z 272 for detection of GSH adducts and positive NL scans of 27 and 29 Da for detection of CN adducts were conducted as survey scans to trigger acquisition of enhanced resolution (ER) spectrum and subsequent enhanced product ion (EPI) spectrum. Post-acquisition data mining of EPI data set using NL filters of 129 and 27 Da was then performed to reveal the GSH adducts and CN adducts, respectively. Isotope patterns and EPI spectra of the detected adducts were utilized for identification of their molecular weights and structures. The effectiveness of this method was evaluated by analyzing reactive metabolites of nefazodone formed from rat liver microsomes. In addition to known GSH- and CN-trapped reactive metabolites, several new CN adducts of nefazodone were identified. The results suggested that current approach is highly effective in the analysis of both soft and hard reactive metabolites and can be used as a high-throughput method in drug discovery.

Finding the sweet spot: the role of nature and nurture in medicinal chemistry

Given its position at the heart of small-molecule drug discovery, medicinal chemistry has an important role in tackling the well-known productivity challenges in pharmaceutical research and development. In recent years, extensive analyses of successful and failed discovery compounds and drug candidates have improved our understanding of the role of physicochemical properties in drug attrition. Based on the clarified challenges in finding the 'sweet spot' in medicinal chemistry programmes, we suggest that this goal can be achieved through a combination of first identifying chemical starting points with appropriate 'nature' and then rigorously 'nurturing' them during lead optimization. Here, we discuss scientific, strategic, organizational and cultural considerations for medicinal chemistry practices, with the aim of promoting more effective use of what is already known, as well as a wider appreciation of the risks of pursuing suboptimal compounds.

Covalent protein binding and tissue distribution of houttuynin in rats after intravenous administration of sodium houttuyfonate

AIM

To investigate the potential of houttuynin to covalently bind to proteins in vitro and in vivo and to identify the adduct structures.

METHODS

Male Sprague-Dawley rats were intravenously injected with sodium houttuyfonate (10 mg/kg). The concentrations of houttuynin in blood, plasma and five tissues tested were determined using an LC/MS/MS method. The covalent binding values of houttuynin with hemoglobin, plasma and tissue proteins were measured in rats after intravenous injection of [1-(14)C]sodium houttuyfonate (10 mg/kg, 150 mCi/kg). Human serum albumin was used as model protein to identify the modification site(s) and structure(s) through enzymatic digestion and LC/MS(n) analysis.

RESULTS

The drug was widely distributed 10 min after intravenous injection. The lungs were the preferred site for disposition, followed by the heart and kidneys with significantly higher concentrations than that in the plasma. The extent of covalent binding was correlated with the respective concentrations in the tissues, ranging from 1137 nmol/g protein in lung to 266 nmol/g protein in liver. Houttuynin reacted primarily with arginine residues in human serum albumin to form a pyrimidine adduct at 1:1 molar ratio. The same adduct was detected in rat lungs digested by pronase E.

CONCLUSION

This study showed that the β-keto aldehyde moiety in houttuynin is strongly electrophilic and readily confers covalent binding to tissue proteins, especially lung proteins, by a Schiff's base mechanism. The findings explain partially the idiosyncratic reactions of houttuyniae injection in clinical use.

QSAR classification of metabolic activation of chemicals into covalently reactive species

Metabolic activation of chemicals into covalently reactive species might lead to toxicological consequences such as tissue necrosis, carcinogenicity, teratogenicity, or immune-mediated toxicities. Early prediction of this undesirable outcome can help in selecting candidates with increased chance of success, thus, reducing attrition at all stages of drug development. The ensemble modelling of mixed features was used for the development of a model to classify the metabolic activation of chemicals into covalently reactive species. The effects of the quality of base classifiers and performance measure for sorting were examined. An ensemble model of 13 naive Bayes classifiers was built from a diverse set of 1,479 compounds. The ensemble model was validated internally with five-fold cross validation and it has achieved sensitivity of 67.4% and specificity of 93.4% when tested on the training set. The final ensemble model was made available for public use.

Hit to lead SAR study on benzoxazole derivatives for an NPY Y5 antagonist

We report a hit to lead study on a novel benzoxazole NPY Y5 antagonist. Starting from HTS hit 1, structure-activity relationships were developed. Compound 12 showed reduction of food intake and a tendency to suppress body weight gain over the 21-day experimental period.

Enhanced screening of glutathione-trapped reactive metabolites by in-source collision-induced dissociation and extraction of product ion using UHPLC-high resolution mass spectrometry

A selective and sensitive approach, called extraction of product ion (XoPI) method, was developed for the detection of l-glutathione (GSH)-trapped reactive metabolites employing an Orbitrap high resolution mass spectrometer. Fragmentation of GSH conjugates in the negative ion mode leads to a product ion, deprotonated γ-glutamyl-dehydroalanyl-glycine (m/z 272.0888). As a means of utilizing this property, negative ion high resolution MS data were collected from in vitro incubations by monitoring ions from m/z 269.5 to 274.5 under in-source collision-induced dissociation. Extraction of product ions at m/z 272.0888 ± 5 ppm from this data resulted in a chromatogram exhibiting deprotonated γ-glutamyl-dehydroalanyl-glycine as the major peaks with no or very few interferences. Therefore, peaks in this extracted product ion chromatogram potentially came from GSH-trapped reactive metabolites. The GSH conjugate parent ions were then confirmed in the corresponding full scan MS data, and their structures were identified from their MS(2) fragmentation patterns. The effectiveness of the approach was assessed with four model compounds, amodiaquine, clozapine, diclofenac, and fipexide, all well-known to form GSH-trapped reactive metabolites, following incubation in human liver microsomes supplemented with β-nicotinamide adenine dinucleotide 2'-phosphate reduced tetrasodium salt (NADPH) and GSH. The results from XoPI method were compared to two other commonly employed liquid chromatography-mass spectrometry (LC-MS) methods: precursor ion scan method and mass defect filter method. Overall, the XoPI method was more selective and sensitive in detecting the GSH conjugates. Many GSH conjugates previously not reported were detected and characterized in this study.

Metabolomic screening and identification of the bioactivation pathways of ritonavir

Ritonavir-boosted protease inhibitor regimens are widely used for HIV chemotherapy. However, ritonavir causes multiple side effects, and the mechanisms are not fully understood. The current study was designed to explore the metabolic pathways of ritonavir that may be related to its toxicity. Metabolomic analysis screened out 26 ritonavir metabolites in mice, and half of them are novel. These novel ritonavir metabolites include two glycine conjugated, two N-acetylcysteine conjugated, and three ring-open products. Accompanied with the generation of ritonavir ring-open metabolites, the formation of methanethioamide and 2-methylpropanethioamide were expected. Upon the basis of the structures of these novel metabolites, five bioactivation pathways are proposed, which may be associated with sulfation and epoxidation. By using Cyp3a-null mice, we confirmed that CYP3A is involved in four pathways of RTV bioactivation. In addition, all these five bioactivation pathways were recapitulated in the incubation of ritonavir in human liver microsomes. Further studies are suggested to determine the role of CYP3A and these bioactivation pathways in ritonavir toxicity.