Detection and Structural Characterization of Glutathione-Trapped Reactive Metabolites Using Liquid Chromatography−High-Resolution Mass Spectrometry and Mass Defect Filtering

Screening and identification of reactive metabolic compounds of Cortex Periplocae based on glutathione capture-mass spectrometry

As a traditional Chinese medicine (TCM), Cortex Periplocae (CP) has a wide range of pharmacological effects, as well as toxic side effects. The main toxic components of it are cardiac glycosides, which tend to cause cardiotoxicity. Currently, it has also been reported in studies to cause hepatotoxicity, but it is not clear whether the hepatotoxicity is related to the toxicity caused by the reactive metabolites. This study aims to investigate the target components of CP that generate reactive metabolic toxicity. The fluorescent probe method was used to detect glutathione (GSH)-trapped reactive metabolites in a co-incubation system of CP extract with rat liver microsomes. Identification of GSH conjugates was performed by LC-MS/MS and that of the possible precursor components that produce reactive metabolites was conducted by UPLC-Q-TOF/MS. Cell viability assays were performed on HepG2 and L02 cells to determine the cytotoxicity of the target components. The findings of our study demonstrate that the extract derived from CP has the ability to generate metabolites that exhaust the intracellular GSH levels, resulting in the formation of GSH conjugates and subsequent cytotoxic effects. Through the utilization of the UPLC-Q-TOF/MS technique, we were able to accurately determine the molecular weight of the precursor compound in CP to be 355.1023. The primary evidence to determining the GSH conjugetes relies on the appearance of characteristic product ions resulting from central neutral loss (CNL) scanning of 129 Da and product scanning of m/z 660 in the positive MS/MS spectrum. Through analysis, it was ultimately ascertained that the presence of chlorogenic acid (CGA) and its isomers, namely neochlorogenic acid (NCGA) and cryptochlorogenic acid (CCGA), could lead to the production of GSH conjugates, resulting in cytotoxicity at elevated levels. Taking these findings into consideration, the underlying cause for the potential hepatotoxicity of CP was initially determined.

Development of a fluorous trapping reagent for rapid detection of electrophilic reactive metabolites

A cysteine-based fluorous trapping reagent, Rf8CYS, was developed. Rf8CYS formed adducts with soft and hard electrophilic reactive metabolites. These fluorous-tagged adducts were purified via both fluorous solid-phase extraction and the direct injection method. The highly sensitive mass spectrometric detection of an unprecedented adduct of the ticlopidine metabolite was realized.

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

Machine Learning Enables Accurate Prediction of Quinone Formation during Drug Metabolism

Metabolism helps in the elimination of drugs from the human body by making them more hydrophilic. Sometimes, drugs can be bioactivated to highly reactive metabolites or intermediates during metabolism. These reactive metabolites are often responsible for the toxicities associated with the drugs. Identification of reactive metabolites of drug candidates can be very helpful in the initial stages of drug discovery. Quinones are soft electrophiles that are generated as reactive intermediates during metabolism. Quinones make up more than 40% of the reactive metabolites. In this work, a reliable data set of 510 molecules was used to develop machine learning and deep learning-based predictive models to predict the formation of quinone-type metabolites. For representing molecules, two-dimensional (2D) descriptors, PubChem fingerprints, electro-topological state (E-state) fingerprints, and metabolic reactivity-based descriptors were used. Developed models were compared to the existing Xenosite web server using the untouched test set of 102 molecules. The best model achieved an accuracy of 86.27%, while the Xenosite server could achieve an accuracy of only 52.94% on the test set. Descriptor analysis revealed that the presence of greater numbers of polar moieties in a molecule can prevent the formation of quinone-type metabolites. In addition, the presence of a nitrogen atom in an aromatic ring and the presence of metabolophores V51, V52, and V53 (SMARTCyp descriptors) decrease the probability of quinone formation. Finally, a tool based on the best machine learning models was developed, which is accessible at http://14.139.57.41/quinonepred/.

Feature-Based Molecular Networking Combined with Multivariate Analysis for the Characterization of Glutathione Adducts as a Smoking Gun of Bioactivation

Feature-based molecular networking (FBMN) is a powerful analytical tool for mass spectrometry (MS)-based untargeted metabolomics data analysis. FBMN plays an important role in drug metabolism studies, enabling the visualization of complex metabolomics data to achieve metabolite characterization. In this study, we propose a strategy for the characterization of glutathione (GSH) adducts formed via in vitro metabolic activation using FBMN assisted by multivariate analysis (MVA). Acetaminophen was used as a model substrate for method development, and the practical potential of the method was investigated by its application to 2-aminophenol (2-AP) and 2,4-dinitrochlorobenzene (DNCB). Two 2-AP GSH adducts and one DNCB GSH adduct were successfully characterized by forming networks with GSH even though the mass spectral information obtained for the parent compound was deficient. False positives were effectively filtered out by the variable influence on projection cutoff criteria obtained from orthogonal partial least-squares-discriminant analysis. The GSH adducts formed by enzymatic or nonenzymatic reactions were intuitively distinguished by the pie chart of FBMN results. In summary, our approach effectively characterizes GSH adducts, which serve as compelling evidence of bioactivation. It can be widely utilized to enhance risk assessment in the context of drug metabolism.

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

N-Acylamino Saccharin as an Emerging Cysteine-Directed Covalent Warhead and Its Application in the Identification of Novel FBPase Inhibitors toward Glucose Reduction

With a resurgence of covalent drugs, there is an urgent need for the identification of new moieties capable of cysteine bond formation. Herein, we report on the N-acylamino saccharin moieties capable of novel covalent reactions with cysteine. Their utility as alternative electrophilic warheads was demonstrated through the covalent modification of fructose-1,6-bisphosphatase (FBPase), a promising target associated with cancer and type 2 diabetes. The cocrystal structure of title compound W8 bound with FBPase unexpectedly revealed that the N-acylamino saccharin moiety worked as an electrophile warhead that covalently modified the noncatalytic C128 site in FBPase while releasing saccharin, suggesting a previously undiscovered covalent reaction mechanism of saccharin derivatives with cysteine. Treatment of title compound W8 displayed potent inhibition of glucose production in vitro and in vivo. This newly discovered reactive warhead supplements the current repertoire of cysteine covalent modifiers while avoiding some of the limitations generally associated with established moieties.

Mass Defect Filtering-Oriented Identification of Resin Glycosides from Root of Convolvulus scammonia Based on Quadrupole-Orbitrap Mass Spectrometer

This work aimed to develop and evaluate a post-acquisition data processing strategy, referred to as a mass defect filter (MDF), for rapid target the resin glycosides in root of Convolvulus scammonia by setting mass rang and mass defect range from high-resolution MS data. The full-scan mass data were acquired by high-performance liquid chromatography coupled with Q Exactive Plus hybrid quadrupole-orbitrap mass spectrometer that featured high resolution, mass accuracy, and sensitivity. To screen resin glycosides, three parent filter m/z 871, m/z 853, and m/z 869 combined with diagnostic fragment ions (DFIs) approach were applied to remove the interference from complex herbal extract. The targeted components were characterized based on detailed fragment ions. Using this approach, 80 targeted components, including 22 glycosidic acids and 58 resin glycosides were tentatively identified. The present results suggested that the proposed MDF strategy would be adaptable to the analysis of complex system in relevant filed.

Environmental Sources, Chemistry, Fate, and Transport of Per- and Polyfluoroalkyl Substances: State of the Science, Key Knowledge Gaps, and Recommendations Presented at the August 2019 SETAC Focus Topic Meeting

A Society of Environmental Toxicology and Chemistry (SETAC) Focused Topic Meeting (FTM) on the environmental management of per- and polyfluoroalkyl substances (PFAS) convened during August 2019 in Durham, North Carolina (USA). Experts from around the globe were brought together to critically evaluate new and emerging information on PFAS including chemistry, fate, transport, exposure, and toxicity. After plenary presentations, breakout groups were established and tasked to identify and adjudicate via panel discussions overarching conclusions and relevant data gaps. The present review is one in a series and summarizes outcomes of presentations and breakout discussions related to (1) primary sources and pathways in the environment, (2) sorption and transport in porous media, (3) precursor transformation, (4) practical approaches to the assessment of source zones, (5) standard and novel analytical methods with implications for environmental forensics and site management, and (6) classification and grouping from multiple perspectives. Outcomes illustrate that PFAS classification will continue to be a challenge, and additional pressing needs include increased availability of analytical standards and methods for assessment of PFAS and fate and transport, including precursor transformation. Although the state of the science is sufficient to support a degree of site-specific and flexible risk management, effective source prioritization tools, predictive fate and transport models, and improved and standardized analytical methods are needed to guide broader policies and best management practices. Environ Toxicol Chem 2021;40:3234-3260. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The Fabrication of Amino Acid Incorporated Nanoflowers with Intrinsic Peroxidase-like Activity and Its Application for Efficiently Determining Glutathione with TMB Radical Cation as Indicator

The assessment of glutathione (GSH) levels is associated with early diagnostics and pathological analysis for various disorders. Among all kinds of techniques for detecting GSH, the colorimetric assay relying on the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) catalyzed by many nanomaterials with peroxidase-like activity attracts increasing attention owing to its outstanding merits, such as high sensitivity and high selectivity. However, the aggregation between the nanomaterials severely hinders the entrance of TMB into the “active site” of these peroxidase mimics. To address this problem, the D-amino acid incorporated nanoflowers possessing peroxidase-like activity with a diameter of 10–15 μm, TMB and H₂O₂ were employed to establish the detection system for determining the level of glutathione. The larger diameter size of the hybrid nanoflowers substantially averts the aggregation between them. The results confirm that the hybrid nanoflowers detection system presents a low limit of detection, wide linear range, perfect selectivity, good storage stability and desired operational stability for the detection of GSH relying on the intrinsic peroxidase-like activity and favorable mechanical stability of the hybrid nanoflowers, indicating that the hybrid nanoflowers detection system has tremendous application potential in clinical diagnosis and treatment.

The Application of Mass Spectrometry in Drug Metabolism and Pharmacokinetics

Drug metabolism and pharmacokinetics (DMPK) are fundamental in drug discovery. New chemical entities (NCEs) are typically evaluated with various in vitro and in vivo assays, which are time-consuming and labor intensive. These experiments are essential in identifying potential new drugs. Recently, mass spectrometry (MS) has played a key role in examining the drug-like properties of NCEs. Quantitative and qualitative mass spectrometry approaches are routinely utilized to obtain high-quality data in an efficient, timely, and cost-effective manner. Especially, liquid chromatography (LC) coupled with MS technology has been refined for metabolite identification (Met ID), which is critical for lead optimization. These qualitative and quantitative MS approaches and their specific utility in DMPK characterization will be described in this chapter.

Bio-activation of simeprevir in liver microsomes and characterization of its glutathione conjugates by liquid chromatography coupled to ultrahigh-resolution quadrupole time-of-flight mass spectrometry

Liquid chromatography coupled to a triple quadrupole and, alternatively, to an ultrahigh-resolution quadrupole time-of-flight (UHR-QqTOF) mass spectrometers was used to collect qualitative and quantitative information from incubations of the anti-hepatitis C drug simeprevir with human and rat liver microsomes, respectively, supplemented with NADPH and glutathione. For this, different chromatographic methods using two different chromatographic columns, Kinetex® 2.6 µm C₁₈ (50 × 3 mm) and Atlantis T3 (100 Å, 3 µm, 4.6 mm × 150 mm), have been employed. For determination and structural characterization of the reactive metabolites, we used information obtained from high-resolution mass spectrometry, namely accurate mass data to calculate the elemental composition, accurate MS/MS fragmentation patterns for confirmation of structural proposals, and the high mass spectral resolution to eliminate false-positive peaks. In this study, the use of high-resolution mass spectrometry (HR-MS) enabled the identification of 19 simeprevir metabolites generated by O- respectively N-demethylation, oxidation, dehydrogenation, hydrolysis, and formation of glutathione conjugates. The in silico study provides insights into the sites of simeprevir most amenable to reactions involving cytochrome P₄₅₀. The developed methods have been successfully applied to analyze simeprevir and its metabolites simultaneously; based on this data, potential metabolic pathways of simeprevir are discussed. In general, the obtained results demonstrate that simeprevir is susceptible to form reactive simeprevir-glutathione adducts and cyclopropansulfonamide, which may explain the implication of simeprevir in idiosyncratic adverse drug reactions (IADRs) or hepatotoxicity.

An enhanced strategy integrating offline superimposed two-dimensional separation with mass defect filter and diagnostic ion filter: Comprehensive characterization of steroid alkaloids in Fritillariae Pallidiflorae Bulbus as a case study

The inherent complexity of traditional Chinese medicines necessitates the application of multi-dimensional information to accomplish comprehensive profiling and confirmative identification of their chemical components. In this study, we display an enhanced strategy by integrating offline superimposed two-dimensional separation (S-2D-LC) with mass defect filter and diagnostic ion filter to comprehensively characterize the alkaloid composition of Fritillariae Pallidiflorae Bulbus (FPB). The superimposed HILIC × RP and UPCC × RP offline two-dimensional liquid chromatography system was constructed with superior orthogonality (R²=0.004 and R²=0.001) for chromatographic separation. In total, 70 fractions were collected after the first-dimensional chromatographic separation (HILIC and UPCC) and then analyzed by the second-dimensional reversed phase (RP) liquid chromatography coupled with Q-TOF/MS/MS in FAST DDA acquisition mode. A four-step interpretation strategy combining mass defect filter with diagnostic ion filter was developed to rapidly characterize alkaloids in Fritillaria species. Ultimately, a sum of 529 Fritillaria alkaloids were characterized from two botanical origins of FPB. The integrated strategy is practical to efficiently expose and comprehensively characterize more trace and isomeric components in complex herbal medicines.

Metabolic Forest: Predicting the Diverse Structures of Drug Metabolites

Adverse drug metabolism often severely impacts patient morbidity and mortality. Unfortunately, drug metabolism experimental assays are costly, inefficient, and slow. Instead, computational modeling could rapidly flag potentially toxic molecules across thousands of candidates in the early stages of drug development. Most metabolism models focus on predicting sites of metabolism (SOMs): the specific substrate atoms targeted by metabolic enzymes. However, SOMs are merely a proxy for metabolic structures: knowledge of an SOM does not explicitly provide the actual metabolite structure. Without an explicit metabolite structure, computational systems cannot evaluate the new molecule's properties. For example, the metabolite's reactivity cannot be automatically predicted, a crucial limitation because reactive drug metabolites are a key driver of adverse drug reactions (ADRs). Additionally, further metabolic events cannot be forecast, even though the metabolic path of the majority of substrates includes two or more sequential steps. To overcome the myopia of the SOM paradigm, this study constructs a well-defined system-termed the metabolic forest-for generating exact metabolite structures. We validate the metabolic forest with the substrate and product structures from a large, chemically diverse, literature-derived dataset of 20 736 records. The metabolic forest finds a pathway linking each substrate and product for 79.42% of these records. By performing a breadth-first search of depth two or three, we improve performance to 88.43 and 88.77%, respectively. The metabolic forest includes a specialized algorithm for producing accurate quinone structures, the most common type of reactive metabolite. To our knowledge, this quinone structure algorithm is the first of its kind, as the diverse mechanisms of quinone formation are difficult to systematically reproduce. We validate the metabolic forest on a previously published dataset of 576 quinone reactions, predicting their structures with a depth three performance of 91.84%. The metabolic forest accurately enumerates metabolite structures, enabling promising new directions such as joint metabolism and reactivity modeling.

Application of a fluorous derivatization method for characterization of glutathione-trapped reactive metabolites with liquid chromatography-tandem mass spectrometry analysis

The glutathione (GSH) trapping assay is commonly utilized for the screening and characterization of reactive metabolites produced by drug metabolism. This study describes a fluorous derivatization method for a more sensitive and selective analysis of reactive metabolites trapped by GSH using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In this study, the GSH-trapped reactive metabolites, which were obtained after incubation of the test compounds with human liver microsome (HLM) in the presence of GSH and NADPH, were derivatized using the perfluoroalkylamine reagent through oxazolone chemistry. Since this reaction enabled the selective modification of the α-carboxyl group in GSH, the structural compositions of the metabolites were not affected by the derivatization. Furthermore, the selective analysis of the resulting derivatives could be performed using perfluoroalkyl-modified stationary phase LC separation via the interaction between the perfluoroalkyl-containing compounds, such as fluorous affinity, followed by detection with the precursor ion and/or enhanced product ion scan modes in MS/MS. Finally, we demonstrated the applicability of this method by analyzing perfluoroalkyl derivatives of some drug metabolites trapped by GSH in HLM incubation.

In vitro metabolism of sunscreen compounds by liquid chromatography/high-resolution tandem mass spectrometry

RATIONALE

Exposure to UV light can induce adverse effects on human health, such as photo-aging, immunosuppression, and cancer. Sunscreens are used to prevent the absorption of UV rays, but certain UV-filtering compounds have been shown to disrupt endocrine systems or act as carcinogens. To assess the effects of the exposure to such compounds, it is important to study the pathways by which they are biotransformed in the body.

METHODS

Liquid chromatography coupled to high-resolution tandem mass spectrometry (LC/HRMS/MS) was employed to evaluate the oxidative metabolism and, specifically, the formation of reactive metabolites of six active ingredients commonly used in sunscreen formulations: oxybenzone, avobenzone, homosalate, octisalate, octocrylene, and octinoxate. In vitro incubations were performed with human and rat liver microsomes in the presence of β-nicotinamide adenine dinucleotide phosphate and glutathione. An LC/HRMS/MS method was developed to identify metabolites employing a biphenyl reversed-phase column for separating parent molecules, metabolites, and glutathione (GSH) adducts.

RESULTS

Each tested compound resulted in the formation of several metabolites, including at least one GSH adduct. Compounds containing ester groups were hydrolyzed, and some metabolites of the free acid forms were also detected. High-resolution MS/MS data was crucial for the structural elucidation of metabolites and GSH adducts. Fragmentation pathways were proposed for all parent compounds, as well as each described metabolite and adduct.

CONCLUSIONS

The results of this study will help better understand the metabolism and detoxification pathways of these xenobiotics.

Identification and characterization of in silico, in vivo, in vitro, and reactive metabolites of infigratinib using LC-ITMS: bioactivation pathway elucidation and in silico toxicity studies of its metabolites

Infigratinib (INF) is a novel, small molecule that is orally administered to inhibit human fibroblast growth factor receptors (FGFRs), which are a family of receptor tyrosine kinases that may be upregulated in different tumor cell types. On 6 January 2020, the FDA granted fast track designation to INF for first-line treatment of cholangiocarcinoma. Prediction of susceptible sites of metabolism and reactivity pathways (cyanide and GSH) for INF was performed by the Xenosite web predictor tool. Then, we report the characterization and identification of in vitro, in vivo, and reactive intermediates of INF using liquid chromatography ion trap mass spectrometry (LC-ITMS). Finally, an in silico toxicity assessment of INF metabolites was carried out using the StarDrop DEREK module showing structural alerts. Rat liver microsomes (RLMs) and isolated perfused rat liver hepatocytes were incubated with INF in vitro and the generated metabolites were collected by protein precipitation. In vivo metabolism was evaluated by time-course urine sampling from Sprague-Dawley rats administered a single INF oral dose. A similar volume of acetonitrile was added to each collected urine sample and both organic and aqueous layers were analyzed by LC-ITMS to detect in vivo INF metabolites. N-Ethyl piperazine rings and benzene at part A of the INF structure are metabolized to form iminium and 1,4-benzoquinone, respectively, which are very reactive toward nucleophilic macromolecules. Incubation of INF with RLMs in the presence of 1.0 mM KCN and 1.0 mM glutathione was used to evaluate reactive metabolites potentially responsible for toxicities associated with INF. There were seven in vitro phase I metabolites, three in vitro phase II metabolites, three cyano adducts, and three GSH conjugate metabolites of INF detected by LC-ITMS. In vivo INF metabolites identified included four in vivo phase I and three in vivo phase II metabolites. In vitro and in vivo phase I metabolic pathways included N-dealkylation, N-demethylation, O-demethylation, hydroxylation, and dechlorination, while the in vivo phase II metabolic reaction was a direct conjugation of INF with glucuronic acid and sulphate.

An in silico web designer tool was utilized to guide laboratory work for infigratinib metabolism. Sixteen metabolites of infigratinib and seven reactive intermediates (three iminium ions and four 1,4 benzoquinones) were characterized using LC-ITMS.

In vitro metabolism of triclosan studied by liquid chromatography-high-resolution tandem mass spectrometry

Triclosan (TCS) is an antibacterial and antifungal compound found in many hygiene products, including toothpaste, soap, and detergents. However, this molecule can act as an endocrine disruptor and can induce harmful effects on human health and the environment. In this study, triclosan was biotransformed in vitro using human and rat liver fractions, to evaluate oxidative metabolism, the formation of reactive metabolites via the detection of GSH adducts, as well as glucuronide and sulfate conjugates using liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HRMS/MS). A deuterated analog of triclosan was also employed for better structural elucidation of specific metabolic sites. Several GSH adducts were found, either via oxidative metabolism of triclosan or its cleavage product, 2,4-dichlorophenol. We also detected glucuronide and sulfated conjugates of triclosan and its cleaved product. This study was aimed at understanding the routes of detoxification of this xenobiotic, as well as investigating any potential pathways related to additional toxicity via reactive metabolite formation. Graphical abstract.

A high-throughput glutathione trapping assay with combined high sensitivity and specificity in high-resolution mass spectrometry by applying product ion extraction and data-dependent neutral loss

Reactive metabolites are thought to play a pivotal role in the pathogenesis of some drug-induced liver injury (DILI) and idiosyncratic adverse drug reactions (IADRs), which is of concern to patient safety and has been a cause of drugs being withdrawn from the market place. To identify drugs with a lower propensity for causing DILI and/or IADRs, high-throughput assays to capture reactive metabolites are required in pharmaceutical industry for early drug discovery risk assessment. We describe the development of an assay to detect glutathione adducts with combined high sensitivity, enhanced specificity, and rapid data analysis. In this assay, compounds were incubated with human liver microsomes and a mixture of 1:1 of GSH (γ-GluCysGly): GSX(γ-GluCysGly-¹³ C₂ ¹⁵ N) in a 96-well plate format. UPLC-UV and LTQ Orbitrap XL were employed to detect GSH-adducts using the following mass spectrometry setups: (a) selected ion monitoring (SIM) at m/z of 274 ± 3 Da in negative mode with in-source fragmentation (SCID), which enables simultaneously monitoring two characteristic product ions of m/z 272.0888 (γ-glutamyl-dehydroalanyl-glycine) and 275.0926 (γ-glutamyl-dehydroalanyl-glycine-¹³ C₂ ¹⁵ N); (b) full scan mode for acquisition of exact mass of glutathione adducts; (c) data-dependent MS² scan through isotopic matching (M:M + 3.00375 = 1:1) for monitoring neutral loss fragments (144 Da from dehydroalanyl-glycine) and for structural information of glutathione adducts. This approach was qualified using eight compounds known to form GSH conjugates as reported in the literature. The high sensitivity and specificity were demonstrated in identifying unique CysGly adducts in the case of clozapine, diclofenac, and raloxifene and in identifying GSH-adducts of fragmented parent molecules in the case of amodiaquine and troglitazone. In addition, LC-UV chromatograms in the presence or absence of GSH/GSX allowed for identification of the rearranged glutathione adducts without aforementioned characteristic fragment ions. Implement of this assay in drug discovery small molecule programs has successfully guided drug design.

LC-MS/MS based detection and characterization of covalent glutathione modifications formed by reactive drug of abuse metabolites

Conjugation with the tripeptide glutathione (GSH) is a common mechanism of detoxification of many endogenous and exogenous compounds. This phenomenon typically occurs through the formation of a covalent bond between the nucleophilic free thiol moiety of GSH and an electrophilic site on the compound of interest. While GSH adducts have been identified for many licit drugs, there is a lack of information on the ability of drugs of abuse to adduct GSH. The present study utilized a metabolic assay with GSH as a nucleophilic trapping agent to bind reactive drug metabolites formed in situ. Extracted ion MS spectra were collected via LC-QqQ-MS/MS for all potentially significant ions and examined for fragmentation common to GSH-containing compounds, followed by confirmation of adduction and structural characterization performed by LC-QTOF-MS/MS. In addition to the two positive controls, of the 14 drugs of abuse tested, 10 exhibited GSH adduction, with several forming multiple adducts, resulting in a total of 22 individual identified adducts. A number of these are previously unreported in the literature, including those for diazepam, naltrexone, oxycodone and Δ⁹-THC.

Insight into the Claisen condensation of methyl acetate and dimethyl carbonate to dimethyl malonate

A mechanistic model for the Claisen condensation of methyl acetate and dimethyl carbonate in the presence of sodium methoxide to sodium malonate and further protonation to dimethyl malonate is proposed based on experimental and computational results.

The application of a novel high-resolution mass spectrometry-based analytical strategy to rapid metabolite profiling of a dual drug combination in humans

Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension. First, mass defect filter (MDF), as a targeted data mining tool, worked effectively except for those metabolites with similar MDF values. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, was able to recover all relevant metabolites of VER-IRB from the full-scan MS dataset except for trace metabolites buried in the background noise and/or combined drug-related signals. Third, the novel ring double bond (RDB; valence values of elements in structure) filter, could show rich structural information in more sensitive full-scan MS chromatograms; however, it had a low capability to remove background noise and was difficult to differentiate the metabolites with RDB coverage. Fourth, an integrated strategy, i.e., untargeted BS followed by RDB, was effective for metabolite identification of VER and IRB, which have different RDB values. Majority of matrix signals were firstly removed using BS. Metabolite ions for each parent drug were then isolated from remaining background matrix and combined drug-related signals by imposing of preset RDB values/ranges around the parent drug and selected core substructures. In parallel, MDF was used to recover potential metabolites with similar RDB. As a result, a total of 74 metabolites were found for VER-IRB in human plasma and urine, among which ten metabolites have not been previously reported in human. The results demonstrated that the combination of accurate mass-based multiple data-mining techniques, i.e., untargeted background subtraction followed by ring double bond filtering in parallel with targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drug.

Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism

Many adverse drug reactions are thought to be caused by electrophilically reactive drug metabolites that conjugate to nucleophilic sites within DNA and proteins, causing cancer or toxic immune responses. Quinone species, including quinone-imines, quinone-methides, and imine-methides, are electrophilic Michael acceptors that are often highly reactive and comprise over 40% of all known reactive metabolites. Quinone metabolites are created by cytochromes P450 and peroxidases. For example, cytochromes P450 oxidize acetaminophen to N-acetyl-p-benzoquinone imine, which is electrophilically reactive and covalently binds to nucleophilic sites within proteins. This reactive quinone metabolite elicits a toxic immune response when acetaminophen exceeds a safe dose. Using a deep learning approach, this study reports the first published method for predicting quinone formation: the formation of a quinone species by metabolic oxidation. We model both one- and two-step quinone formation, enabling accurate quinone formation predictions in nonobvious cases. We predict atom pairs that form quinones with an AUC accuracy of 97.6%, and we identify molecules that form quinones with 88.2% AUC. By modeling the formation of quinones, one of the most common types of reactive metabolites, our method provides a rapid screening tool for a key drug toxicity risk. The XenoSite quinone formation model is available at http://swami.wustl.edu/xenosite/p/quinone .

The Opportunities of Metabolomics in Drug Safety Evaluation

Although safety of drug candidates is carefully monitored in preclinical and clinical studies using a variety of approaches, drug toxicity may still occur in clinical practice. Therefore, novel approaches are needed to complement the current drug safety evaluation system. Metabolomics comprehensively analyzes the metabolites altered by drug exposure, which can therefore be used to profile drug metabolism, endobiotic metabolism, and drug-microbiota interactions. The information from metabolomic analysis can be used to determine the off-targets of a drug candidate, and thus provide a mechanistic understanding of drug toxicity. We herein discuss the opportunities of metabolomics in drug safety evaluation.

Strategies to distinguish new synthetic cannabinoid FUBIMINA (BIM-2201) intake from its isomer THJ-2201: metabolism of FUBIMINA in human hepatocytes

Since 2013, a new drugs-of-abuse trend attempts to bypass drug legislation by marketing isomers of scheduled synthetic cannabinoids (SCs), e.g., FUBIMINA (BIM-2201) and THJ-2201. It is much more challenging to confirm a specific isomer’s intake and distinguish it from its structural analog because the isomers and their major metabolites usually have identical molecular weights and display the same product ions. Here, we investigated isomers FUBIMINA and THJ-2201 and propose strategies to distinguish their consumption. THJ-2201 was scheduled in the US, Japan, and Europe; however, FUBIMINA is easily available on the Internet. We previously investigated THJ-2201 metabolism in human hepatocytes, but human FUBIMINA metabolism is unknown. We aim to characterize FUBIMINA metabolism in human hepatocytes, recommend optimal metabolites to confirm its consumption, and propose strategies to distinguish between intakes of FUBIMINA and THJ-2201. FUBIMINA (10 μM) was incubated in human hepatocytes for 3 h, and metabolites were characterized with high-resolution mass spectrometry (HR-MS). We identified 35 metabolites generated by oxidative defluorination, further carboxylation, hydroxylation, dihydrodiol formation, glucuronidation, and their combinations. We recommend 5′-OH-BIM-018 (M34), BIM-018 pentanoic acid (M33), and BIM-018 pentanoic acid dihydrodiol (M7) as FUBIMINA specific metabolites. THJ-2201 produced specific metabolite markers 5′-OH-THJ-018 (F26), THJ-018 pentanoic acid (F25), and hydroxylated THJ-2201 (F13). Optimized chromatographic conditions to achieve different retention times and careful selection of specific product ion spectra enabled differentiation of isomeric metabolites, in this case FUBIMINA from THJ-2201. Our HR-MS approach should be applicable for differentiating future isomeric SCs, which is especially important when different isomers have different legal status.

Characterization of a highly sensitive and selective novel trapping reagent, stable isotope labeled glutathione ethyl ester, for the detection of reactive metabolites

INTRODUCTION

Glutathione (GSH) trapping assays are widely used to predict the post-marketing risk for idiosyncratic drug reactions (IDRs) in the pharmaceutical industry. Although several GSH derivatives have been introduced as trapping reagents for reactive intermediates, more sensitive and selective reagents are desired to prevent the generation of erroneous results. In this study, stable isotope labeled GSH ethyl ester (GSHEE-d5) was designed and its detection capability was evaluated.

METHODS

GSHEE-d5 was synthesized and its detection potential was compared with stable isotope labeled GSH ([(13)C2,(15)N]GSH) as a reference trapping reagent. The trapping reagents were added to human liver microsomes as a 1:1 mixture with GSHEE or GSH, respectively, and incubated with seven IDR positive drugs and three IDR negative drugs. The adducts formed between the reagents and reactive metabolites were analyzed by unit resolution mass spectrometer (MS) using isotope pattern-dependent scan with neutral loss filtering.

RESULTS

A single-step reaction of GSH and ethanol-d6 produced GSHEE-d5 with a yield of 85%. The GSHEE-d5 assay detected adducts with all seven IDR positive drugs, and no adducts were detected with the three IDR negative drugs. In contrast, the [(13)C2,(15)N]GSH assay failed to detect adducts with three of the IDR positive drugs. In the case of diclofenac, the GSHEE-d5 assay showed a 4-times greater signal intensity than the [(13)C2,(15)N]GSH assay.

DISCUSSION

GSHEE-d5 enabled the detection of reactive metabolites with greater sensitivity and selectivity than [(13)C2,(15)N]GSH. These results demonstrate that GSHEE-d5 would be a useful trapping reagent for evaluating the risk of IDRs with unit resolution MS.

Comparison of trapping profiles between d-peptides and glutathione in the identification of reactive metabolites

Qualitative trapping profile of reactive metabolites arising from six structurally different compounds was tested with three different d-peptide isomers (Peptide 1, gly–tyr–pro–cys–pro–his-pro; Peptide 2, gly–tyr–pro–ala–pro–his–pro; Peptide 3, gly–tyr–arg–pro–cys–pro–his–lys–pro) and glutathione (GSH) using mouse and human liver microsomes as the biocatalyst. The test compounds were classified either as clinically “safe” (amlodipine, caffeine, ibuprofen), or clinically as “risky” (clozapine, nimesulide, ticlopidine; i.e., associated with severe clinical toxicity outcomes). Our working hypothesis was as follows: could the use of short different amino acid sequence containing d-peptides in adduct detection confer any add-on value to that obtained with GSH? All “risky” agents’ resulted in the formation of several GSH adducts in the incubation mixture and with at least one peptide adduct with both microsomal preparations. Amlodipine did not form any adducts with any of the trapping agents. No GSH and peptide 2 and 3 adducts were found with caffeine, but with peptide 1 one adduct with human liver microsomes was detected. Ibuprofen produced one Peptide 1-adduct with human and mouse liver microsomes but not with GSH. In conclusion, GSH still remains the gold trapping standard for reactive metabolites. However, targeted d-peptides could provide additional information about protein binding potential of electrophilic agents, but their clinical significance needs to be clarified using a wider spectrum of chemicals together with other safety estimates.

Detecting reactive drug metabolites for reducing the potential for drug toxicity

INTRODUCTION

A number of withdrawn drugs are known to undergo bioactivation by a range of drug metabolizing enzymes to chemically reactive metabolites that bind covalently to protein and DNA resulting in organ toxicity and carcinogenesis, respectively. An important goal in drug discovery is to identify structural sites of bioactivation within discovery molecules for providing strategic modifications that eliminate or minimize reactive metabolite formation, while maintaining target potency, selectivity and desired pharmacokinetic properties leading to the development of efficacious and nontoxic drugs.

AREAS COVERED

This review covers experimental techniques currently used to detect reactive drug metabolites and provides recent examples where information from mechanistic in vitro studies was successfully used to redesign candidate drugs leading to blocked or minimized bioactivation. Reviewed techniques include in vitro radiolabeled drug covalent binding to protein and reactive metabolite trapping with reagents such as glutathione, cyanide, semicarbazide and DNA bases. Case studies regarding reactive metabolite detection using a combination of varied techniques, including liquid chromatography-tandem mass spectrometry and NMR analyses and subsequent structural modification are discussed.

EXPERT OPINION

Information derived from state-of-art mechanistic drug metabolism studies can be used successfully to direct medicinal chemistry towards the synthesis of candidate drugs devoid of bioactivation liabilities, while maintaining desired pharmacology and pharmacokinetic properties.

Detection of reactive metabolites using isotope-labeled glutathione trapping and simultaneous neutral loss and precursor ion scanning with ultra-high-pressure liquid chromatography triple quadruple mass spectrometry

Metabolic activation of drugs to electrophilic species is responsible for over 60% of black box warnings and drug withdrawals from the market place in the United States. Reactive metabolite trapping using glutathione (GSH) and analysis using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) or HPLC with high resolution mass spectrometry (mass defect filtering) have enabled screening for metabolic activation to become routine during drug development. However, current MS-based approaches cannot detect all GSH conjugates present in complex mixtures, especially those present in extracts of botanical dietary supplements. To overcome these limitations, a fast triple quadrupole mass spectrometer-based approach was developed that can detect positively and negatively charged GSH conjugates in a single analysis without the need for advanced knowledge of the elemental compositions of potential conjugates and while avoiding false positives. This approach utilized UHPLC instead of HPLC to shorten separation time and enhance sensitivity, incorporated stable-isotope labeled GSH to avoid false positives, and used fast polarity switching electrospray MS/MS to detect GSH conjugates that form positive and/or negative ions. The general new method was then used to test the licorice dietary supplement Glycyrrhiza glabra, which was found to form multiple GSH conjugates upon metabolic activation. Among the GSH conjugates found in the licorice assay were conjugates with isoliquiritigenin and glabridin, which is an irreversible inhibitor of cytochrome P450 enzymes.

LTQ-Orbitrap-based strategy for traditional Chinese medicine targeted class discovery, identification and herbomics research: a case study on phenylethanoid glycosides in three different species of Herba Cistanches

An LTQ-Orbitrap-based strategy for traditional Chinese medicine targeted class discovery, identification and herbomics research was developed.

Post-acquisition analysis of untargeted accurate mass quadrupole time-of-flight MS(E) data for multiple collision-induced neutral losses and fragment ions of glutathione conjugates

RATIONALE

Analytical methods to assess glutathione (GSH) conjugate formation based on mass spectrometry usually take advantage of the specific fragmentation behavior of the glutathione moiety. However, most methods used for GSH adduct screening monitor only one specific neutral loss or one fragment ion, even though the peptide moiety of GSH adducts shows a number of other specific neutral fragments and fragment ions which can be used for identification.

METHODS

Nine reference drugs well known to form GSH adducts were incubated with human liver microsomes. Mass spectrometric analysis was performed with a quadrupole time-of-flight mass spectrometer in untargeted accurate mass MS(E) mode. The data analysis and evaluation was achieved in an automated approach with software to extract and identify GSH conjugates based on the presence of multiple collision-induced neutral losses and fragment ions specific for glutathione conjugates in the high-energy MS spectra.

RESULTS

In total 42 GSH adducts were identified. Eight (18%) adducts did not show the neutral loss of 129 but were identified based on the appearance of other GSH-specific neutral losses or fragment ions. In high-energy MS(E) spectra the GSH-specific fragment ions of m/z 308 and 179 as well as the neutral loss of 275 Da were complementary to the commonly used neutral loss of 129 Da. Further, one abundant (yet unpublished) GSH conjugate of troglitazone formed in human liver microsomes was found.

CONCLUSIONS

A software-aided approach was developed to reliably retrieve GSH adduct formation data out of untargeted complex full scan QTOFMS(E) data in a fast and efficient way. The present approach to detect and analyze multiple collision-induced neutral losses and fragment ions of glutathione conjugates in untargeted MS(E) data might be applicable to higher throughput to assess reactive metabolite formation in drug discovery.

Post-acquisition data processing for the screening of transformation products of different organic contaminants. Two-year monitoring of river water using LC-ESI-QTOF-MS and GCxGC-EI-TOF-MS

This study describes a comprehensive strategy for detecting and elucidating the chemical structures of expected and unexpected transformation products (TPs) from chemicals found in river water and effluent wastewater samples, using liquid chromatography coupled to electrospray ionization quadrupole-time-of-flight mass spectrometer (LC-ESI-QTOF-MS), with post-acquisition data processing and an automated search using an in-house database. The efficacy of the mass defect filtering (MDF) approach to screen metabolites from common biotransformation pathways was tested, and it was shown to be sufficiently sensitive and applicable for detecting metabolites in environmental samples. Four omeprazole metabolites and two venlafaxine metabolites were identified in river water samples. This paper reports the analytical results obtained during 2 years of monitoring, carried out at eight sampling points along the Henares River (Spain). Multiresidue monitoring, for targeted analysis, includes a group of 122 chemicals, amongst which are pharmaceuticals, personal care products, pesticides and PAHs. For this purpose, two analytical methods were used based on direct injection with a LC-ESI-QTOF-MS system and stir bar sorptive extraction (SBSE) with bi-dimensional gas chromatography coupled with a time-of-flight spectrometer (GCxGC-EI-TOF-MS).

Rapid identification of polymethoxylated flavonoids in traditional Chinese medicines with a practical strategy of stepwise mass defect filtering coupled to diagnostic product ions analysis based on a hybrid LTQ-Orbitrap mass spectrometer

INTRODUCTION

The methodology of stepwise mass defect filtering (MDF) approach coupled to diagnostic product ions (DPIs) analysis on a hybrid linear trap quadrupole (LTQ)/orbitrap mass spectrometer was the first to be established to screen and identify structural analogues from complex herbal extracts.

OBJECTIVE

To develop an analytical methodology that could be adopted to screen and identify structural analogues in traditional Chinese medicines (TCMs) rapidly and accurately.

METHODS

Taking polymethoxylated flavonoids (PMFs) in the leaves of Citrus reticulata Blanco as an example, high-resolution mass data were acquired by high-performance liquid chromatography (HPLC) coupled with a LTQ/orbitrap mass spectrometer. The stepwise MDF with multiple mass defect windows or mass windows enabled the original data to be analysed much faster and more accurately by reducing the potential interferences of matrix ions. Additionally, analysis of DPIs could provide a criterion to classify the target constituents detected into certain chemical families.

RESULTS

In total, 81 PMFs, including 50 polymethoxyflavones and 31 polymethoxyflavanones or polymethoxychalcones, were screened and identified from the original data and preliminarily identified.

CONCLUSION

The analytical methodology developed could be used as a rapid, effective technique to screen and identify compounds from TCM extracts and other organic matter mixtures with compounds that can also be classified into families based on the common carbon skeletons.

Screening and characterization of reactive compounds with in vitro peptide-trapping and liquid chromatography/high-resolution accurate mass spectrometry

The present study describes a novel methodology for the detection of reactive compounds using in vitro peptide-trapping and liquid chromatography-high-resolution accurate mass spectrometry (LC-HRMS). Compounds that contain electrophilic groups can covalently bind to nucleophilic moieties in proteins and form adducts. Such adducts are thought to be associated with drug-mediated toxicity and therefore represent potential liabilities in drug discovery programs. In addition, reactive compounds identified in biological screening can be associated with data that can be misinterpreted if the reactive nature of the compound is not appreciated. In this work, to facilitate the triage of hits from high-throughput screening (HTS), a novel assay was developed to monitor the formation of covalent peptide adducts by compounds suspected to be chemically reactive. The assay consists of in vitro incubations of test compounds (under conditions of physiological pH) with synthetically prepared peptides presenting a variety of nucleophilic moieties such as cysteine, lysine, histidine, arginine, serine, and tyrosine. Reaction mixtures were analyzed using full-scan LC-HRMS, the data were interrogated using postacquisition data mining, and modified amino acids were identified by subsequent LC-HRMS/mass spectrometry. The study demonstrated that in vitro nucleophilic peptide trapping followed by LC-HRMS analysis is a useful approach for screening of intrinsically reactive compounds identified from HTS exercises, which are then removed from follow-up processes, thus obviating the generation of data from biochemical activity assays.

Applications of high-resolution MS in bioanalysis

High-resolution MS (HRMS) in conjunction with LC (LC–HRMS) has become available to many laboratories in the pharmaceutical industry. Due to its enhanced, though sometime perceived, specificity using the high-resolution power and its capability of simultaneous quantitation and structural elucidation using the post-acquisition data mining feature, utilization of LC–HRMS for bioanalysis could lead to potential rapid and reliable method development as well as sample analysis, thus generating both cost and resource savings. Here, we would like to share our perspectives about several current and future applications of LC–HRMS in bioanalysis. We will also discuss the factors influencing the quality of method establishment and potential pitfalls that need to be considered for the utilization of LC–HRMS in the field of regulated bioanalysis. We believe when utilized appropriately, LC–HRMS will play a significant role in the future landscape of quantitative bioanalysis.

Metabolite structure analysis by high-resolution MS: supporting drug-development studies

Effective characterization of drug metabolites in complex biological matrices is facilitated by mass spectrometers with high resolving power, mass accuracy and sensitivity. This review begins with an overview of high-resolution MS terminology and the different types of instrumentation that are currently available. Metabolite structure analysis offers unique challenges and, therefore, the different types of approaches used to solve problems are highlighted through specific examples. Overall, this review describes the value that high-resolution MS brings to drug-metabolism studies.

A new strategy for the discovery of epimedium metabolites using high-performance liquid chromatography with high resolution mass spectrometry

In this paper, a new strategy of drug metabolite discovery and identification was established using high-performance liquid chromatography with high resolution mass spectrometry (HPLC-HRMS) and a mass spectral trees similarity filter (MTSF) technique. The MTSF technique was developed as a means to rapidly discover comprehensive metabolites from multiple active components in a complicated biological matrix. Using full-scan mass spectra as the stem and data-dependent subsequent stage mass spectra to form branches, the HRMS and multiple-stage mass spectrometric data from detected compounds were converted to mass spectral trees data. Potential metabolites were discovered based on the similarity between their mass spectral trees and that known compounds or metabolites in a mass spectra trees library. The threshold value for match similarity scores was set at above 200, allowing approximately 80% of interference to be filtered out. A total of 115 metabolites of five flavonoid monomers (epimedin A, epimedin B, epimedin C, icariin, and baohuoside I) and herbal extract of epimedium were discovered and identified in rats via this new strategy. As a result, a metabolic profile for epimedium was obtained and a metabolic pathway was proposed. In addition, comparing to the widely used neutral loss filter (NLF), product ion filter (PIF), and mass defect filter (MDF) techniques, the MTSF technique was shown superior efficiency and selectivity for discovering and identifying metabolites in traditional Chinese medicine (TCM).

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.

Recent advances in metabolite identification and quantitative bioanalysis by LC–Q-TOF MS

The need for rapid, sensitive and effective identification and quantitation of drugs and metabolites to accelerate drug discovery and development has given MS its central position in drug metabolism and pharmacokinetic research. This review attempts to orient the readers with respect to hybrid Q-TOF MS, which enables accurate mass measurement and generates information-rich datasets. The key properties of the Q-TOF MS system, including mass accuracy, resolution, scan speed and dynamic range, are herein discussed. Developments on tandem separation techniques (e.g., UHPLC® and ion mobility spectrometry), data acquisition and data-mining methods (e.g., mass defect, product/neutral loss, isotope pattern filters and background subtraction) that facilitate qualitative and quantitative analysis are then examined. The performance and versatility of LC–Q-TOF MS are thoroughly illustrated by its applications in metabolite identification and quantitative bioanalysis. Future perspectives are also discussed.

MS(M), an efficient workflow for metabolite identification using hybrid linear ion trap Orbitrap mass spectrometer

Identification of drug metabolites can often yield important information regarding clearance mechanism, pharmacologic activity, or toxicity for drug candidate molecules. Additionally, the identification of metabolites can provide beneficial structure-activity insight to help guide lead optimization efforts towards molecules with optimal metabolic profiles. There are challenges associated with detecting and identifying metabolites in the presence of complex biological matrices, and new LC-MS technologies have been developed to meet these challenges. In this report, we describe the development of an experimental approach that applies unique features of the hybrid linear ion trap Orbitrap mass spectrometer to streamline in vitro and in vivo metabolite identification experiments. The approach, referred to as MS(M), utilizes multiple collision cells, dissociation methods, mass analyzers, and detectors. With multiple scan types and different dissociation modes built into one experimental method, along with flexible post-acquisition analysis options, the MS(M) workflow offers an attractive option to fast and reliable identification of metabolites in different kinds of in vitro and in vivo samples. The MS(M) workflow was successfully applied to metabolite identification analysis of verapamil in both in vitro rat hepatocyte incubations and in vivo rat bile samples.