Metabolic activation of chemicals: in-silico simulation†

The role of metabolism in prioritising chemicals according to their potential adverse health effects is extremely important given the fact that innocuous parents can be transformed into toxic metabolites. Our recent efforts in simulating metabolic activation of chemicals are reviewed in this work. The application of metabolic simulators to predict biodegradation (microbial degradation pathways), bioaccumulation (fish liver metabolism), skin sensitisation (skin metabolism), mutagenicity (rat liver S-9 metabolism) are discussed. The ability of OASIS approach to predict metabolism (toxicokinetics) and toxicity (toxicodynamics) of chemicals resulting from their metabolic activation in a single modelling platform is an important advantage of the method. It allows prioritisation of chemicals due to predicted toxicity of their metabolites.

     

Simulation of chemical metabolism for fate and hazard assessment. V. Mammalian hazard assessment

Animals and humans are exposed to a wide array of xenobiotics and have developed complex enzymatic mechanisms to detoxify these chemicals. Detoxification pathways involve a number of biotransformations, such as oxidation, reduction, hydrolysis and conjugation reactions. The intermediate substances created during the detoxification process can be extremely toxic compared with the original toxins, hence metabolism should be accounted for when hazard effects of chemicals are assessed. Alternatively, metabolic transformations could detoxify chemicals that are toxic as parents. The aim of the present paper is to describe specificity of eukaryotic metabolism and its simulation and incorporation in models for predicting skin sensitization, mutagenicity, chromosomal aberration, micronuclei formation and estrogen receptor binding affinity implemented in the TIMES software platform. The current progress in model refinement, data used to parameterize models, logic of simulating metabolism, applicability domain and interpretation of predictions are discussed. Examples illustrating the model predictions are also provided.     

Metabolic activation of chemicals: in-silico simulation

The role of metabolism in prioritising chemicals according to their potential adverse health effects is extremely important given the fact that innocuous parents can be transformed into toxic metabolites. Our recent efforts in simulating metabolic activation of chemicals are reviewed in this work. The application of metabolic simulators to predict biodegradation (microbial degradation pathways), bioaccumulation (fish liver metabolism), skin sensitisation (skin metabolism), mutagenicity (rat liver S-9 metabolism) are discussed. The ability of OASIS approach to predict metabolism (toxicokinetics) and toxicity (toxicodynamics) of chemicals resulting from their metabolic activation in a single modelling platform is an important advantage of the method. It allows prioritisation of chemicals due to predicted toxicity of their metabolites.     

Simulation of chemical metabolism for fate and hazard assessment. V. Mammalian hazard assessment

Animals and humans are exposed to a wide array of xenobiotics and have developed complex enzymatic mechanisms to detoxify these chemicals. Detoxification pathways involve a number of biotransformations, such as oxidation, reduction, hydrolysis and conjugation reactions. The intermediate substances created during the detoxification process can be extremely toxic compared with the original toxins, hence metabolism should be accounted for when hazard effects of chemicals are assessed. Alternatively, metabolic transformations could detoxify chemicals that are toxic as parents. The aim of the present paper is to describe specificity of eukaryotic metabolism and its simulation and incorporation in models for predicting skin sensitization, mutagenicity, chromosomal aberration, micronuclei formation and estrogen receptor binding affinity implemented in the TIMES software platform. The current progress in model refinement, data used to parameterize models, logic of simulating metabolism, applicability domain and interpretation of predictions are discussed. Examples illustrating the model predictions are also provided.     

Determination of zolpidem, a new sleep-inducing agent, and its metabolites in biological fluids: pharmacokinetics, drug metabolism and overdosing investigations in humans.

For the determination of zolpidem, a new sleep inducer, and its metabolites in human plasma and urine, three methods were developed that are suitable for pharmacokinetics, drug metabolism and overdosing investigations. The methods used for pharmacokinetic and drug metabolism studies are based on column-switching high-performance liquid chromatography; they do not require any sample manipulation because the plasma or diluted urine is injected into a pre-column where clean-up and preconcentration take place. The analytes are transferred by valve-switching to the C18 analytical column for chromatography. To investigate overdose cases, urine samples only are used: the method is simple, because the diluted urine can be injected directly into the analytical column (phenyl type). This allows the identification and quantification of the principal urinary metabolite of zolpidem, the unchanged drug being practically undetectable. All the methods use fluorescence detection, which affords high sensitivity and selectivity. It is necessary to use a method capable of the determination of metabolites even if these are apparently pharmacologically inactive, because in different physiopathological populations the qualitative and quantitative metabolic profiles of zolpidem could be different. The method designed for the investigation of (accidental or deliberate) overdose cases is, as required on such occasions, simple and rapid, with good selectivity with respect to commonly prescribed psychotropic drugs.     

Generation of metabolites by an automated online metabolism method using human liver microsomes with subsequent identification by LC-MS(n), and metabolism of 11 cathinones

Human liver microsomes (HLMs) are used to simulate human xenobiotic metabolism in vitro. In forensic and clinical toxicology, HLMs are popularly used to study the metabolism of new designer drugs for example. In this work, we present an automated online extraction system we developed for HLM experiments, which was compared to a classical offline approach. Furthermore, we present studies on the metabolism of 11 cathinones; for eight of these, the metabolism has not previously been reported. Metabolites were identified based on MS² and MS³ scans. Fifty-three substances encompassing various classes of drugs were employed to compare the established offline and the new online methods. The metabolism of each of the following 11 cathinones was studied using the new method: 3,4-methylenedioxy-N-benzylcathinone, benzedrone, butylone, dimethylcathinone, ethylone, flephedrone, methedrone, methylone, methylethylcathinone, naphyrone, and pentylone. The agreement between the offline and the online methods was good; a total of 158 metabolites were identified. Using only the offline method, 156 (98.7%) metabolites were identified, while 151 (95.6%) were identified using only the online method. The metabolic pathways identified for the 11 cathinones included the reduction of the keto group, desalkylation, hydroxylation, and desmethylenation in cathinones containing a methylenedioxy moiety. Our method provides a straightforward approach to identifying metabolites which can then be added to the library utilized by our clinical toxicological screening method. The performance of our method compares well with that of an established offline HLM procedure, but is as automated as possible.     

Multimodal liquid chromatographic separation methods in the study of ethimizol metabolism in man.

The metabolism of ethimizol in the human body has been investigated. Focus was on the detection and demonstration of the regioselective pathway of metabolic demethylation of ethimizol by determining the presence of the corresponding metabolites in blood, saliva and urine. Isolation, purification and identification of the metabolites present in the biological samples was achieved by applying a combination of the following methods: solid phase extraction, high performance liquid chromatography, high performance thin layer chromatography, nuclear magnetic resonance and mass spectrometry. The suggested chemical structures were definitely established by comparing the physicochemical characteristics of the ethimizol metabolites obtained from the individual biological fluids with the characteristics of synthetized authentic derivatives.     

Incorporation of a nanosplitter interface into an LC-MS-RD system to facilitate drug metabolism studies

In the work reported here, a novel interface, the nanosplitter, is incorporated into the drug metabolism laboratory in order to enhance the analytical capabilities of detecting and identifying drug-related metabolites to support drug metabolism studies during the drug development process. When an existing LC-MS-radiometric detector (RD) system is coupled with this nanosplitter, the system becomes capable of performing dynamic microspray under a typical analytical LC method. With the superior MS sensitivity offered by this system, most of the analytical LC methods developed for metabolite profiling can then be easily adopted for metabolite identification work. The improvement of these analytical capabilities can streamline the entire process of the drug metabolism study. In the experiments presented here, the nanosplitter interface coupled with analytical HPLC systems (e.g. 4.6 x 250 mm column @ 1 ml/min) demonstrated significant increases in MS signal (2x to 40x peak area) when compared to the standard LC-MS interface for both in vitro and in vivo metabolism studies. Furthermore, this signal gain facilitated the MS detection of additional metabolites (observed in the radiometric trace) that were below the MS level of detection when using the standard interface.     

N-Dealkylation of Amines

N-dealkylation, the removal of an N-alkyl group from an amine, is an important chemical transformation which provides routes for the synthesis of a wide range of pharmaceuticals, agrochemicals, bulk and fine chemicals. N-dealkylation of amines is also an important in vivo metabolic pathway in the metabolism of xenobiotics. Identification and synthesis of drug metabolites such as N-dealkylated metabolites are necessary throughout all phases of drug development studies. In this review, different approaches for the N-dealkylation of amines including chemical, catalytic, electrochemical, photochemical and enzymatic methods will be discussed.     

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism

Fumarase catalyzes the interconversion of fumarate and l ‐malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt‐induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC–MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l ‐malic acid, l ‐aspartic acid, glycine and l ‐glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level.     

GC�CTOFMS analysis of metabolites in adherent MDCK cells and a novel strategy for identifying intracellular metabolic markers for use as cell amount indicators in data normalization

Cultured cell lines are useful models in biomedical research that characterize metabolic responses to various stimuli (e.g., pathogens, toxins, or drugs/chemicals) and explore the underlying mechanisms. However, data from cell metabolomic studies must be normalized to the amount of cells, which is dependent on diverse treatments. The currently used methods of cell counting and protein assay involve extra work and delay the quenching of intracellular metabolism. To develop a convenient, alternative approach, in this study, intracellular metabolites were extracted from a series amount of cultured adherent cells and profiled by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS). The GC-TOFMS signal intensities for 11 intracellular markers present in two different cell lines showed good linearity with the protein content, with inositol and pantothenate most promising (correlation coefficient > 0.970). Despite the various amounts of cells, the data normalized to the metabolic markers and protein amounts showed similar effectiveness, resulted in better separation of the two cell lines, closer clustering within each group(cell line) on a principal components analysis scores plot, and had lower relative standard deviations for intracellular metabolites than those of the non-normalized data, suggesting that these markers were effective indicators of cell amounts and independent of cell lines.     

Method for rapid metabolite profiling of drug candidates in fresh hepatocytes using liquid chromatography coupled with a hybrid quadrupole linear ion trap

Rapid information on metabolic profiling is required to evaluate the structural liabilities of drug candidates in early drug discovery. In this study, a sensitive and rapid semi-quantitative method was developed to simultaneously monitor the drug candidate and metabolites as well as collect tandem mass (MS/MS) spectra for subsequent metabolite identification. The simultaneous semi-quantitation and identification of metabolites in fresh hepatocytes is achieved using high-performance liquid chromatography (HPLC) coupled with a hybrid quadrupole linear ion trap. The survey experiment consists of monitoring multiple-reaction monitoring (MRM) transitions for the internal standard, the parent, and 48 MRM transitions designed to cover the most common phase I and II biotransformations. An information-dependent acquisition (IDA) method was employed to trigger product ion scans above the MRM signal threshold. Three biotransformations of a lead compound have been identified through enhanced product ion scans and the respective MRM transitions of those metabolites were selected for semi-quantitation. Parent disappearance and formation of the metabolites as a function of incubation time in five different species were monitored by their respective MRM responses. The method provides the necessary sensitivity to detect minor metabolites in a relevant therapeutic concentration range. Enzymatic turnover of the parent and the metabolites in different species are revealed based on the different initial concentrations of the parent. This methodology integrates the parent disappearance, metabolite identification, and the formation of the metabolites along the time course using a single rapid LC/MS/MS analysis. This method can be used as a complementary tool to the conventional method of metabolic profiling. It provides a rapid and sensitive initial profile of the metabolism of potential structural series at the lead selection stage. The method can also be incorporated into the overall metabolite profiling scheme to evaluate the drug candidates in drug discovery.     

In vivo metabolism study of rhubarb decoction in rat using high-performance liquid chromatography with UV photodiode-array and mass-spectrometric detection: a strategy for systematic analysis of metabolites from traditional Chinese medicines in biological samples

High-performance liquid chromatography with diode-array detection (HPLC-DAD) and tandem mass spectrometry (HPLC-MS/MS) was used for separation and identification of metabolites in rat urine, bile and plasma after oral administration of rhubarb decoction. Based on the proposed strategy, 91 of the 113 potential metabolites were tentatively identified or characterized. Besides anthraquinones metabolites, gallic acid, (-)-epicatechin and (+)-catechin metabolites were also detected and characterized in these biological samples. Our results indicated that glucuronidation and sulfation were the main metabolic pathways of anthraquinones, while methylation, glucuronidation and sulfation were the main metabolic pathways of gallic acid, (-)-epicatechin and (+)-catechin. Phase I reactions (e.g., hydroxylation and reduction) played a relatively minor role compared to phase II reactions in metabolism of phenolic compounds of rhubarb decoction. The identification and structure elucidation of these metabolites provided essential data for further pharmacological and clinical studies of rhubarb and related preparations. Moreover, the results of the present investigations clearly indicated the relevance and usefulness of the combination of chromatographic, spectrophotometric, and mass-spectrometric analysis to detect and identify metabolites.     

Flavonoid metabolism: the synthesis of phenolic glucuronides and sulfates as candidate metabolites for bioactivity studies of dietary flavonoids

Epidemiological studies indicate that flavonoid intake is inversely associated with the risk of coronary heart disease, yet the mechanisms responsible for their bioactivity are still a matter of debate. Based on the rapid and extensive metabolism of most flavonoids, their health effects most likely result from the biological activity of their metabolites. However, a lack of commercially available compounds/standards has prevented the study of metabolite bioactivity and resulted in a focus on non-physiologically relevant precursor/parent structures. This paper details the synthesis of a series of phenolic glucuronide 1a–e and sulfate 2a–e derivates as candidate metabolites for use as reference compounds in metabolic profiling studies and for the exploration of flavonoid bioactivity.     

Urinary exposure marker discovery for toxicants using ultra-high pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry and three untargeted metabolomics approaches

Human biomonitoring is the assessment of actual internal contamination of chemicals by measuring exposure markers, chemicals or their metabolites, in human urine, blood, serum, and other body fluids. However, the metabolism of chemicals within an organism is extremely complex. Therefore, the identification of metabolites is often difficult and laborious. Several untargeted metabolomics methods have been developed to perform objective searching/filtering of accurate-mass-based LC-MS data to facilitate metabolite identification. In this study, three metabolomics data processing approaches were used for chemical exposure marker discovery in urine with an LTQ-Orbitrap high-resolution mass spectrometry (HRMS) dataset; di-isononyl phthalate (DINP) was used as an example. The data processing techniques included the SMAIT, mass defect filtering (MDF), and XCMS Online. Sixteen, 83, and 139 probable DINP metabolite signals were obtained using the SMAIT, MDF, and XCMS procedures, respectively. Fourteen probable metabolite signals mined simultaneously by the three metabolomics approaches were confirmed as DINP metabolites by structural information provided by LC-MS/MS. Among them, 13 probable metabolite signals were validated as exposure-related markers in a rat model. Six (m/z 319.155, 361.127, 373.126, 389.157, 437.112 and 443.130) of the 13 exposure-related DINP metabolite signals have not previously been reported in the literature. Our data indicate that SMAIT provided an efficient method to discover effectively and systematically urinary exposure markers of toxicant. The DINP metabolism information can provide valuable information for further investigations of DINP toxicity, toxicokinetics, exposure assessment, and human health effects.     

POPs: a QSAR system for developing categories for persistent, bioaccumulative and toxic chemicals and their metabolites

This paper presents the framework of a QSAR-based decision support system which provides a rapid screening of potential hazards, classification of chemicals with respect to risk management thresholds, and estimation of missing data for the early stages of risk assessment. At the simplest level, the framework is designed to rank hundreds of chemicals according to their profile of persistence, bioaccumulation potential and toxicity often called the persistent organic pollutant (POP) profile or the PBT (persistent bioaccumulative toxicant) profile. The only input data are the chemical structure. The POPs framework enables decision makers to introduce the risk management thresholds used in the classification of chemicals under various authorities. Finally, the POPs framework advances hazard identification by integrating a metabolic simulator that generates metabolic map for each parent chemical. Both the parent chemicals and plausible metabolites are systematically evaluated for metabolic activation and POPs profile.     

Bioanalytical methods for determination of tamoxifen and its phase I metabolites: a review

The selective estrogen receptor modulator tamoxifen is used in the treatment of early and advanced breast cancer and in selected cases for breast cancer prevention in high-risk subjects. The cytochrome P450 enzyme system and flavin-containing monooxygenase are responsible for the extensive metabolism of tamoxifen into several phase I metabolites that vary in toxicity and potencies towards estrogen receptor (ER) alpha and ER beta.An extensive overview of publications on the determination of tamoxifen and its phase I metabolites in biological samples is presented. In these publications techniques were used such as capillary electrophoresis, liquid, gas and thin layer chromatography coupled with various detection techniques (mass spectrometry, ultraviolet or fluorescence detection, liquid scintillation counting and nuclear magnetic resonance spectroscopy). A trend is seen towards the use of liquid chromatography coupled to mass spectrometry (LC-MS). State-of-the-art LC-MS equipment allowed for identification of unknown metabolites and quantification of known metabolites reaching lower limit of quantification levels in the sub pg mL⁻¹ range. Although tamoxifen is also metabolized into phase II metabolites, the number of publications reporting on phase II metabolism of tamoxifen is scarce. Therefore the focus of this review is on phase I metabolites of tamoxifen.We conclude that in the past decades tamoxifen metabolism has been studied extensively and numerous metabolites have been identified. Assays have been developed for both the identification and quantification of tamoxifen and its metabolites in an array of biological samples. This review can be used as a resource for method transfer and development of analytical methods used to support pharmacokinetic and pharmacodynamic studies of tamoxifen and its phase I metabolites.     

Liquid chromatography/atmospheric pressure ionization-mass spectrometry in drug metabolism studies

The study of the metabolic fate of drugs is an essential and important part of the drug development process. The analysis of metabolites is a challenging task and several different analytical methods have been used in these studies. However, after the introduction of the atmospheric pressure ionization (API) technique, electrospray and atmospheric pressure chemical ionization, liquid chromatography/mass spectrometry (LC/MS) has become an important and widely used method in the analysis of metabolites owing to its superior specificity, sensitivity and efficiency. In this paper the feasibility of LC/API-MS techniques in the identification, structure characterization and quantitation of drug metabolites is reviewed. Sample preparation, LC techniques, isotope labeling, suitability of different MS techniques, such as tandem mass spectrometry, and high-resolution MS in drug metabolite analysis, are summarized and discussed. Automation of data acquisition and interpretation, special techniques and possible future trends are also the topics of the review.     

Evaluation of the metabolism of propranolol by linear ion trap technology in mouse,rat, dog,monkey, and human cryopreserved hepatocytes

Propranolol is a widely used quality control and validation compound for liver microsome and hepatocyte metabolism studies. A multitude of literature reports describing the identification of propranolol metabolites exists today. However, no literature reports currently exist showing hepatocyte metabolism across the five species commonly used during pre‐clinical drug discovery, namely mouse, rat, dog, monkey, and human. Herein, we present full metabolic profiles of propranolol in mouse, rat, dog, monkey and human hepatocytes. As expected, extensive phase I and phase II metabolism was observed across all five species and species‐specific metabolites were detected in monkey and dog hepatocytes. Of particular interest was the detection of an N‐hydroxylamine glucuronide metabolite in monkey and dog hepatocytes. Copyright © 2009 John Wiley & Sons, Ltd.     

Application of restricted access material (RAM) with precolumn-switching and matrix solid-phase dispersion (MSPD) to the study of the metabolism and pharmacokinetics of Verapamil

In the pharmaceutical industry, studies of the metabolism and pharmacokinetics of drugs are important routine applications which require the analysis of the precursor drug and its metabolites in various biological matrices, such as plasma, serum, urine, cell culture media and tissue samples. In this study, two new and simple methods of sample preparation were optimized and validated: on the one hand, a column-switching technique with a restricted access material (RAM) was used to analyze biological fluids, and on the other hand, matrix solid-phase dispersion (MSPD) was applied to the extraction of analytes from tissue samples. Identification of the metabolites was done with a LC-MS system (ion trap in the MS(n)mode) coupled both on-line (RAM) and off-line (MSPD).Using the common calcium antagonist Verapamil, it is shown that these two methods allow rapid identification of phase I and phase II metabolites from biological samples and are suitable for pharmacokinetic and pharmacodynamic studies of pharmaceuticals in biological matrices.