Rapid screening and characterization of drug metabolites using multiple ion monitoring dependent product ion scan and postacquisition data mining on a hybrid triple quadrupole-linear ion trap mass spectrometer

Uropathogenic Escherichia coli wield enterobactin-derived catabolites as siderophores

Uropathogenic Escherichia coli (UPEC) secrete multiple siderophore types to scavenge extracellular iron(III) ions during clinical urinary tract infections, despite the metabolic costs of biosynthesis. Here, we find the siderophore enterobactin (Ent) and its related products to be prominent components of the iron-responsive extracellular metabolome of a model UPEC strain. Using defined Ent biosynthesis and import mutants, we identify lower molecular weight dimeric exometabolites as products of incomplete siderophore catabolism, rather than prematurely released biosynthetic intermediates. In E. coli, iron acquisition from iron(III)-Ent complexes requires intracellular esterases that hydrolyze the siderophore. Although UPEC are equipped to consume the products of completely hydrolyzed Ent, we find that Ent and its derivatives may be incompletely hydrolyzed to yield products with retained siderophore activity. These results are consistent with catabolic inefficiency as means to obtain more than one iron ion per siderophore molecule. This is compatible with an evolved UPEC strategy to maximize the nutritional returns from metabolic investments in siderophore biosynthesis.

Uropathogenic Escherichia coli wield enterobactin-derived catabolites as siderophores

Uropathogenic E. coli (UPEC) secrete multiple siderophore types to scavenge extracellular iron(III) ions during clinical urinary tract infections, despite the metabolic costs of biosynthesis. Here we find the siderophore enterobactin and its related products to be prominent components of the iron-responsive extracellular metabolome of a model UPEC strain. Using defined enterobactin biosynthesis and import mutants, we identify lower molecular weight, dimeric exometabolites as products of incomplete siderophore catabolism, rather than prematurely released biosynthetic intermediates. In E. coli, iron acquisition from iron(III)-enterobactin complexes requires intracellular esterases that hydrolyze the siderophore. Although UPEC are equipped to consume the products of completely hydrolyzed enterobactin, we find that enterobactin and its derivatives may be incompletely hydrolyzed to yield products with retained siderophore activity. These results are consistent with catabolic inefficiency as means to obtain more than one iron ion per siderophore molecule. This is compatible with an evolved UPEC strategy to maximize the nutritional returns from metabolic investments in siderophore biosynthesis.

High-Throughput Metabolic Soft-Spot Identification in Liver Microsomes by LC/UV/MS: Application of a Single Variable Incubation Time Approach

CYP-mediated fast metabolism may lead to poor bioavailability, fast drug clearance and significant drug interaction. Thus, metabolic stability screening in human liver microsomes (HLM) followed by metabolic soft-spot identification (MSSID) is routinely conducted in drug discovery. Liver microsomal incubations of testing compounds with fixed single or multiple incubation time(s) and quantitative and qualitative analysis of metabolites using high-resolution mass spectrometry are routinely employed in MSSID assays. The major objective of this study was to develop and validate a simple, effective, and high-throughput assay for determining metabolic soft-spots of testing compounds in liver microsomes using a single variable incubation time and LC/UV/MS. Model compounds (verapamil, dextromethorphan, buspirone, mirtazapine, saquinavir, midazolam, amodiaquine) were incubated at 3 or 5 µM with HLM for a single variable incubation time between 1 and 60 min based on predetermined metabolic stability data. As a result, disappearances of the parents were around 20-40%, and only one or a few primary metabolites were generated as major metabolite(s) without notable formation of secondary metabolites. The unique metabolite profiles generated from the optimal incubation conditions enabled LC/UV to perform direct quantitative estimation for identifying major metabolites. Consequently, structural characterization by LC/MS focused on one or a few major primary metabolite(s) rather than many metabolites including secondary metabolites. Furthermore, generic data-dependent acquisition methods were utilized to enable Q-TOF and Qtrap to continuously record full MS and MS/MS spectral data of major metabolites for post-acquisition data-mining and interpretation. Results from analyzing metabolic soft-spots of the seven model compounds demonstrated that the novel MSSID assay can substantially simplify metabolic soft-spot identification and is well suited for high-throughput analysis in lead optimization.

Characterization of the metabolites of H3B-6545 in vitro and in vivo by using ultra-high performance liquid chromatography combined with electrospray ionization linear ion trap-orbitrap tandem mass spectrometry

H3B-6545 is a selective ERα covalent antagonist, which has been demonstrated to be effective in anti-tumor. To fully understand its mechanism of action, it is necessary to investigate the in vitro and in vivo metabolic profiles. For in vitro metabolism, H3B-6545 (50 μM) was incubated with the hepatocytes of rat and human for 2 h. For in vivo metabolism H3B-6545 was orally administered to rats at a single dose of 10 mg/kg, and plasma, urine and fecal samples were then collected. All samples were analyzed by using ultra-high performance liquid chromatography combined with linear ion trap-orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap-MS) operated in positive ion mode. The structures of the metabolites were elucidated by comparing their MS and MS² spectra with those of parent drug. A total of 11 metabolites, including a GSH adduct, were detected and structurally identified. M2, M7 and M8 were further unambiguously identified by using reference standards. Among these metabolites, M1, M5, M7 and M10 were newly found and reported for the first time. The metabolic pathways of H3B-6545 included deamination (M8 and M9), dealkylation (M2, M3 and M10), N-hydroxylation (M6), hydroxylation (M1 and M4), formation of amide derivatives (M5 and M7) and GSH conjugation (G1).

A targeted strategy to identify untargeted metabolites from in vitro to in vivo: Rapid and sensitive metabolites profiling of licorice in rats using ultra-high performance liquid chromatography coupled with triple quadrupole-linear ion trap mass spectrometry

It is challenging to conduct in vivo metabolic study for traditional Chinese medicines (TCMs) because of complex components, unpredictable metabolic pathways and low metabolite concentrations. Herein, we proposed a sensitive strategy to characterize TCM metabolites in vivo at an orally clinical dose using ultra-high performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS). Firstly, the metabolism of individual compounds in rat liver microsomes was studied to obtain the metabolic pathways and fragmentation patterns. The untargeted metabolites in vitro were detected by multiple ion monitoring-enhanced product ion (EPI) and neutral loss-EPI scans. Subsequently, a sensitive multiple reaction monitoring-EPI method was developed according to the in vitro results and predicted metabolites to profile the in vivo metabolites. Licorice as a model herb was used to evaluate and validate our strategy. A clinical dose of licorice water extract was orally administered to rats, then a total of 45 metabolites in urine, 21 metabolites in feces and 35 metabolites in plasma were detected. Among them, 18 minor metabolites have not been reported previously and 6 minor metabolites were first detected in vivo. Several isomeric metabolites were well separated and differentiated in our strategy. These results suggested that this new strategy could be widely used for the detection and characterization of in vivo metabolites of TCMs.

An Integrated Strategy for Global Qualitative and Quantitative Profiling of Traditional Chinese Medicine Formulas: Baoyuan Decoction as a Case

Clarification of the chemical composition of traditional Chinese medicine formulas (TCMFs) is a challenge due to the variety of structures and the complexity of plant matrices. Herein, an integrated strategy was developed by hyphenating ultra-performance liquid chromatography (UPLC), quadrupole time-of-flight (Q-TOF), hybrid triple quadrupole-linear ion trap mass spectrometry (Qtrap-MS), and the novel post-acquisition data processing software UNIFI to achieve automatic, rapid, accurate, and comprehensive qualitative and quantitative analysis of the chemical components in TCMFs. As a proof-of-concept, the chemical profiling of Baoyuan decoction (BYD), which is an ancient TCMF that is clinically used for the treatment of coronary heart disease that consists of Ginseng Radix et Rhizoma, Astragali Radix, Glycyrrhizae Radix et Rhizoma Praeparata Cum Melle, and Cinnamomi Cortex, was performed. As many as 236 compounds were plausibly or unambiguously identified, and 175 compounds were quantified or relatively quantified by the scheduled multiple reaction monitoring (sMRM) method. The findings demonstrate that the strategy integrating the rapidity of UNIFI software, the efficiency of UPLC, the accuracy of Q-TOF-MS, and the sensitivity and quantitation ability of Qtrap-MS provides a method for the efficient and comprehensive chemome characterization and quality control of complex TCMFs.

Metabolism and bioactivation of the tricyclic antidepressant amitriptyline in human liver microsomes and human urine

Aim: Amitriptyline is a widely used tricyclic antidepressant, but the metabolic studies were conducted almost 20 years ago using high-performance liquid chromatography coupled with ultraviolet detector or radiolabeled methods. Results: First, multiple ion monitoring (MIM)- enhanced product ion (EPI) scan was used to obtain the diagnostic ions or neutral losses in human liver microsome incubations with amitriptyline. Subsequently, predicted multiple reaction monitoring (MRM)-EPI scan was used to identify the metabolites in human urine with the diagnostic ions or neutral losses. Finally, product ion filtering and neutral loss filtering were used as the data mining tools to screen metabolites. Consequently, a total of 28 metabolites were identified in human urine after an oral administration using LC–MS/MS. Conclusion: An integrated workflow using LC–MS/MS was developed to comprehensively profile the metabolites of amitriptyline in human urine, in which five N-acetyl-l-cysteine conjugates were characterized as tentative biomarkers for idiosyncratic toxicity.

Identification of metabolites of the novel anti-tumor drug candidate MDH-7 in rat urine by liquid chromatography coupled with triple quadrupole linear ion trap mass spectrometry

RATIONALE

Our previous preliminary pharmacokinetic study demonstrated that the novel double pyrimidine tricyclic nucleoside MDH-7 in rats had a very short half-life (<30 min) after oral administration. As a result, the in vivo metabolic profile of MDH-7 should be investigated during early stages of drug development to better select drug candidates.

METHODS

In this study, a rapid method was developed to identify the metabolites of MDH-7 in rat urine by means of ultra-performance liquid chromatography (UPLC) coupled with electrospray ionization mass spectrometry (ESI-MS) using a triple quadrupole linear ion trap instrument. MDH-7 and its metabolites were detected and characterized by the combined use of the multiple reaction monitoring-information-dependent acquisition-enhanced product ion (MRM-IDA-EPI) mode and the precursor scan information-dependent acquisition-enhanced product ion (PREC-IDA-EPI) mode.

RESULTS

Ten novel metabolites of MDH-7 were identified and characterized in rat urine by LC/ESI-MS and collision-induced dissociation tandem mass spectrometry (CID-MS/MS) analyses. M1 was identified as 5-fluoro-N(4) -[(pentyloxy)carbonyl]cytosine; M2 and M3 were formed by hydroxylation products of M1. Metabolites M4-M10 were formed by a series of degradation reactions such as: deacetylation, hydroxylation, loss of the defluorocytosine base, oxidative-deamination, loss of the defluorouracil base, N-dealkylation and amide hydrolysis.

CONCLUSIONS

Based on the profiles of the metabolites, possible metabolic pathways of MDH-7 in rats were proposed for the first time. This study provides new and available information on the metabolism of MDH-7 which is very useful to further understand its in vivo metabolic fate. Copyright © 2016 John Wiley & Sons, Ltd.

Multiple stage MS in analysis of plasma, serum, urine and in vitro samples relevant to clinical and forensic toxicology

This paper reviews MS approaches applied to metabolism studies, structure elucidation and qualitative or quantitative screening of drugs (of abuse) and/or their metabolites. Applications in clinical and forensic toxicology were included using blood plasma or serum, urine, in vitro samples, liquids, solids or plant material. Techniques covered are liquid chromatography coupled to low-resolution and high-resolution multiple stage mass analyzers. Only PubMed listed studies published in English between January 2008 and January 2015 were considered. Approaches are discussed focusing on sample preparation and mass spectral settings. Comments on advantages and limitations of these techniques complete the review.

Analysis of trans-2,6-difluoro-4'-(N,N-dimethylamino)stilbene (DFS) in biological samples by liquid chromatography-tandem mass spectrometry: metabolite identification and pharmacokinetics

The metabolism of a promising antineoplastic agent, trans-2,6-difluoro-4'-(N,N-dimethylamino)stilbene (DFS), was studied in mouse, rat, and human liver microsomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with the multiple reaction monitoring-information-dependent acquisition-enhanced product ion scan (MRM-IDA-EPI) method. Ten putative metabolites were identified and the structures of four metabolites were confirmed using authentic standards. Since trans-2,6-difluoro-4'-(N-methylamino)stilbene (DMDFS, M1) was present in all species as metabolite and displayed in vitro growth inhibition superior to DFS, its pharmacokinetic profiles were examined in Sprague-Dawley rats using DFS as a comparator. A reliable LC-MS/MS multiple reaction monitoring (MRM) method was subsequently developed and validated for the simultaneous quantification of both DFS and DMDFS in rat plasma for this purpose. Upon intravenous administration (4 mg/kg), DFS had a moderate clearance (Cl = 62.7 ± 23.2 mL/min/kg), terminal elimination half-life (t 1/2 λZ  = 299 ± 73 min), and mean transit time (MTT = 123 ± 14 min) with demethylation metabolism accounting for about 10 % of its total clearance. DMDFS possessed an intravenous pharmacokinetic profile similar to DFS. During oral dosing (10 mg/kg) where both DFS and DMDFS were absorbed rapidly, the oral bioavailability of DFS was approximately 2-fold greater than that of DMDFS (DFS: F = 42.1 ± 12.8 %; DMDFS: F = 18.7 ± 3.9 %). Interestingly, the DMDFS exposure after oral dosing of DFS (10 mg/kg) was comparable to that after oral administration of DMDFS (10 mg/kg) alone. As DFS displayed potent anticancer activities and excellent pharmacokinetic profiles, it appears to be a favorable candidate for further pharmaceutical development.

Determination of species-difference in microsomal metabolism of amitriptyline using a predictive MRM-IDA-EPI method

We investigated to compare species differences in amitriptyline (AMI) metabolism among mouse, rat, dog, and human liver microsomes. We developed a method for simultaneous determination of metabolic stability and metabolite profiling using predictive multiple reaction monitoring information-dependent acquisition-enhanced product ion (MRM-IDA-EPI) scanning. In the cofactor-dependent microsomal metabolism study, AMI was metabolized more rapidly in rat and human liver microsomes incubated with NADPH than UDPGA. AMI incubated with NADPH+UDPGA in rat, dog, or mouse liver microsomes disappeared rapidly with a half-life of 3.5, 8.4, or 9.2 min, respectively, but slowly in human liver microsomes with a half-life of 96 min. In total, 9, 10, 11, and 6 putative metabolites of AMI were detected in mouse, rat, dog, and human liver microsomes, respectively, based on mass spectrometric analyses. Kinetic analysis of metabolites in liver microsomes from each species over 120 min showed common metabolic routes of AMI, such as N-demethylation, hydroxylation, and glucuronidation, and subtle interspecies differences in AMI metabolism. The main metabolic routes in mouse, rat, dog, and human liver microsomes were hydroxylation followed by glucuronide conjugation, methyl hydroxylation, and N-demethylation, respectively. The MRM-IDA-EPI method can provide quantitative and qualitative information about metabolic stability and metabolite profiling simultaneously. Moreover, time course analysis of metabolites can not only eliminate false identification of metabolites, but also provide a rationale for proposed metabolic pathways. The MRM-IDA-EPI method combined with time course analysis of metabolites is useful for investigating drug metabolism at the early drug discovery stage.

A generic multiple reaction monitoring based approach for plant flavonoids profiling using a triple quadrupole linear ion trap mass spectrometry

Flavonoids are one of the largest classes of plant secondary metabolites serving a variety of functions in plants and associating with a number of health benefits for humans. Typically, they are co-identified with many other secondary metabolites using untargeted metabolomics. The limited data quality of untargeted workflow calls for a shift from the breadth-first to the depth-first screening strategy when a specific biosynthetic pathway is focused on. Here we introduce a generic multiple reaction monitoring (MRM)-based approach for flavonoids profiling in plants using a hybrid triple quadrupole linear ion trap (QTrap) mass spectrometer. The approach includes four steps: (1) preliminary profiling of major aglycones by multiple ion monitoring triggered enhanced product ion scan (MIM-EPI); (2) glycones profiling by precursor ion triggered EPI scan (PI-EPI) of major aglycones; (3) comprehensive aglycones profiling by combining MIM-EPI and neutral loss triggered EPI scan (NL-EPI) of major glycone; (4) in-depth flavonoids profiling by MRM-EPI with elaborated MRM transitions. Particularly, incorporation of the NH3 loss and sugar elimination proved to be very informative and confirmative for flavonoids screening. This approach was applied for profiling flavonoids in Astragali radix (Huangqi), a famous herb widely used for medicinal and nutritional purposes in China. In total, 421 flavonoids were tentatively characterized, among which less than 40 have been previously reported in this medicinal plant. This MRM-based approach provides versatility and sensitivity that required for flavonoids profiling in plants and serves as a useful tool for plant metabolomics.

A comprehensive workflow of mass spectrometry-based untargeted metabolomics in cancer metabolic biomarker discovery using human plasma and urine

Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC-LC), reversed-phase liquid chromatography (RP-LC), and gas chromatography (GC). All three techniques are coupled to a mass spectrometer (MS) in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM) and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery

Background: The ability to supplement high-throughput metabolic clearance data with structural information defining the site of metabolism should allow design teams to streamline their synthetic decisions. However, broad application of metabolite identification in early drug discovery has been limited, largely due to the time required for data review and structural assignment. The advent of mass defect filtering and its application toward metabolite scouting paved the way for the development of software automation tools capable of rapidly identifying drug-related material in complex biological matrices. Two semi-automated commercial software applications, MetabolitePilot™ and Mass-MetaSite™, were evaluated to assess the relative speed and accuracy of structural assignments using data generated on a high-resolution MS platform. Results/Conclusion: Review of these applications has demonstrated their utility in providing accurate results in a time-efficient manner, leading to acceleration of metabolite identification initiatives while highlighting the continued need for biotransformation expertise in the interpretation of more complex metabolic reactions.

Metabolomics in chronic kidney disease

Chronic kidney disease (CKD) represents a major challenge to public healthcare. Traditional clinical biomarkers of renal function (blood urea nitrogen and serum creatinine) are not sensitive or specific enough and only increase significantly after the presence of substantial CKD. Therefore, more sensitive biomarkers of CKD are needed. CKD-specific biomarkers at an early disease stage and early diagnosis of specific renal diseases would enable improved therapeutic treatment and reduced the personal and financial burdens. The goal of metabolomics is to identify non-targeted, global small-molecule metabolite profiles of complex samples, such as biofluids and tissues. This method offers the potential for a holistic approach to clinical medicine, as well as improvements in disease diagnoses and the understanding of pathological mechanisms. This review article presents an overview of the recent developments in the field of metabolomics, followed by an in-depth discussion of its application to the study of CKD (primary, chronic glomerulonephritis such as IgA nephropathy; secondary, chronic renal injury such as diabetic nephropathy; chronic renal failure including end-stage kidney disease with and without undergoing replacement therapies, etc), including metabolomic analytical technologies, chemometrics, and metabolomics in experimental and clinical research. We describe the current status of the identification of metabolic biomarkers in CKD. Several markers have been confirmed across multiple studies to detect CKD earlier than traditional clinical chemical and histopathological methods. The application of metabolomics in CKD studies provides researchers the opportunity to gain new insights into metabolic profiling and pathophysiological mechanisms. Particular challenges in the field are presented and placed within the context of future applications of metabolomic approaches to the studies of CKD.

Strategic identification of in vitro metabolites of 13-desmethyl spirolide C using liquid chromatography/high-resolution mass spectrometry

A strategy to identify metabolites of a marine biotoxin, 13-desmethyl spirolide C, has been developed using liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS). Metabolites were generated in vitro through incubation with human liver microsomes. A list of metabolites was established by selecting precursor ions of a common fragment ion characteristic of the spirolide toxin which was known to contain a cyclic imine ring. Accurate mass measurements were subsequently used to confirm the molecular formula of each biotransformation product. Using this approach, a total of nine phase I metabolites was successfully identified with deviations of mass accuracy less than 2 ppm. The biotransformations observed included hydroxylation, dihydroxylation, oxidation of a quaternary methyl group to hydroxymethyl or carboxylic acid groups, dehydrogenation and hydroxylation, as well as demethylation and dihydroxylation reactions. In a second step, tandem mass spectrometry (MS/MS) was performed to elucidate structures of the metabolites. Using the unique fragment ions in the spectra, the structures of the three major metabolites, 13,19-didesmethyl-19-carboxy spirolide C, 13,19-didesmethyl-19-hydroxymethyl spirolide C and 13-desmethyl-17-hydroxy spirolide C, were assigned. Levels of 13-desmethyl spirolide C and its metabolites were monitored at selected time points over a 32-h incubation period with human liver microsomes. It was determined that 13,19-didesmethyl-19-carboxy spirolide C became the predominant metabolite after 2 h of incubation. The stability plot of 13-desmethyl spirolide C showed first-order kinetics for its metabolism and the intrinsic clearance was calculated to be 41 μL/min/mg, suggesting first-pass metabolism may contribute to limiting oral toxicity of 13-desmethyl spirolide C.

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.

Reversible time-dependent inhibition of cytochrome P450 enzymes by duloxetine and inertness of its thiophene ring towards bioactivation

Duloxetine is a selective serotonin-norepinephrine reuptake inhibitor (SNRI) approved to treat major depressive disorder and diabetic peripheral neuropathic pain. It is known to cause hepatotoxicity, in some cases leading to death. It has been reported that duloxetine causes time-dependent inhibition (TDI) of CYP1A2, CYP2B6, CYP2C19 and CYP3A4/5; but the nature of these TDI (whether reversible or irreversible) is not known. Irreversible TDI can cause clinically significant drug-drug interactions and also immune-mediated hepatotoxicity. Structurally, duloxetine possesses several toxicophores, i.e. the naphthyl and thiophene rings. It has been reported that the naphthyl ring undergoes epoxidation and was subsequently adducted to glutathione, but bioactivation related to the thiophene ring has not been completely elucidated. In this paper, the potential of duloxetine in causing irreversible TDI and generating reactive metabolites was investigated. Human liver microsomal assays demonstrated that duloxetine did not cause irreversible TDI of CYP1A2, CYP2B6, CYP2D6, CYP2C19 and CYP3A4/5. Subsequently, reactive metabolite trapping assays using soft nucleophiles (glutathione and glutathione ethyl ester) revealed a previously reported adduct at the naphthyl ring of duloxetine but not at the thiophene ring. Trapping assays utilizing a hard nucleophile (semicarbazide) did not demonstrate adducts with the thiophene ring, indicating an absence of thiophene ring opening. The hepatotoxicity of duloxetine is possibly not related to the irreversible TDI of CYP450 or the bioactivation of its thiophene moiety, but might be due to the epoxidation of its naphthyl ring.

Drug metabolite profiling and identification by high-resolution mass spectrometry

Mass spectrometry plays a key role in drug metabolite identification, an integral part of drug discovery and development. The development of high-resolution (HR) MS instrumentation with improved accuracy and stability, along with new data processing techniques, has improved the quality and productivity of metabolite identification processes. In this minireview, HR-MS-based targeted and non-targeted acquisition methods and data mining techniques (e.g. mass defect, product ion, and isotope pattern filters and background subtraction) that facilitate metabolite identification are examined. Methods are presented that enable multiple metabolite identification tasks with a single LC/HR-MS platform and/or analysis. Also, application of HR-MS-based strategies to key metabolite identification activities and future developments in the field are discussed.

Analysis of the volatile compounds in Senecio scandens Buch-Ham by gas chromatography-tandem mass spectrometry based on diversified scan technologies

Static headspace gas chromatography-tandem mass spectrometry was used to identify volatile compounds from Senecio scandens Buch-Ham. The elemental composition of compounds was confirmed by exploiting the tandem mass spectra of isotopic peaks from the precursor ion. Some isomers were well distinguished by the diversified scan technologies of tandem mass spectrometry (MS/MS). The MS/MS included a product ion scan, a precursor ion scan and a neutral loss scan. The results showed that 46 volatile compounds were completely identified, and the great of majority compounds were α-pinene (11.93%), n-caproaldehyde (9.02%) and dehydrosabinene (6.22%). This qualitative method is convenient and accurate and can be considered as a complementary identification method for the qualitative analysis of volatile compounds in complex samples.

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users.

Identification of chemicals and their metabolites from PHY906, a Chinese medicine formulation, in the plasma of a patient treated with irinotecan and PHY906 using liquid chromatography/tandem mass spectrometry (LC/MS/MS)

Traditional Chinese Medicine (TCM) is increasingly being used in combination with Western medicine. In general, TCM is comprised of multiple components in sharp contrast to Western medicine, where a single active chemical is used. Presently, there are no well-established standards for most of the chemical compounds of TCM and their respective metabolites. Moreover, there are no formal analytical methods for the identification of these chemicals, especially in trace amounts. The ability to measure the pharmacokinetic behaviors of chemicals and their metabolites from these herbal formulations are critical in understanding of the action of TCM. This paper describes the use of LC/MS/MS along with enzyme treatments and n-octanol/water partition coefficient, to investigate the chemical components of PHY906 and their metabolites in the plasma of a patient with metastatic colorectal cancer (mCRC) treated with irinotecan and PHY906. The chemicals from an aqueous extract of PHY906 and the plasma from a patient was prepared and separated on an Agilent ZORBAX-SB C(18) column, and eluted with acetonitrile/0.05% (v/v) formic acid. From the PHY906 aqueous extract, a total of 57 compounds and 27 metabolites were identified and tentatively assigned structures based on their identified mass spectrometry, enzyme digestion and n-octanol/water partition coefficient. In contrast, analysis of patient plasma identified only 33 chemicals and new metabolites. These findings demonstrated that LC/MS/MS was and effective and reliable method for studying the parent chemicals of the Chinese herbal medicine PHY906 and their metabolites in a patient with metastatic colorectal cancer.

Comparison of triple quadrupole, hybrid linear ion trap triple quadrupole, time-of-flight and LTQ-Orbitrap mass spectrometers in drug discovery phase metabolite screening and identification in vitro--amitriptyline and verapamil as model compounds

Liquid chromatography in combination with mass spectrometry (LC/MS) is a superior analytical technique for metabolite profiling and identification studies performed in drug discovery and development laboratories. In the early phase of drug discovery the analytical approach should be both time- and cost-effective, thus providing as much data as possible with only one visit to the laboratory, without the need for further experiments. Recent developments in mass spectrometers have created a situation where many different mass spectrometers are available for the task, each with their specific strengths and drawbacks. We compared the metabolite screening properties of four main types of mass spectrometers used in analytical laboratories, considering both the ability to detect the metabolites and provide structural information, as well as the issues related to time consumption in laboratory and thereafter in data processing. Human liver microsomal incubations with amitriptyline and verapamil were used as test samples, and early-phase 'one lab visit only' approaches were used with all instruments. In total, 28 amitriptyline and 69 verapamil metabolites were found and tentatively identified. Time-of-flight mass spectrometry (TOFMS) was the only approach detecting all of them, shown to be the most suitable instrument for elucidating as comprehensive metabolite profile as possible leading also to lowest overall time consumption together with the LTQ-Orbitrap approach. The latter however suffered from lower detection sensitivity and false negatives, and due to slow data acquisition rate required slower chromatography. Approaches with triple quadrupole mass spectrometry (QqQ) and hybrid linear ion trap triple quadrupole mass spectrometry (Q-Trap) provided the highest amount of fragment ion data for structural elucidation, but, in addition to being unable to produce very high-important accurate mass data, they suffered from many false negatives, and especially with the QqQ, from very high overall time consumption.

Mass defect filter technique and its applications to drug metabolite identification by high-resolution mass spectrometry

Identification of drug metabolites by liquid chromatography/mass spectrometry (LC/MS) involves metabolite detection in biological matrixes and structural characterization based on product ion spectra. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of metabolites using triple-quadrupole and ion trap mass spectrometers. Recently, a novel mass defect filter (MDF) technique has been developed, which enables high-resolution mass spectrometers to be utilized for detecting both predicted and unexpected drug metabolites based on narrow, well-defined mass defect ranges for these metabolites. This is a new approach that is completely different from, but complementary to, traditional molecular mass- or MS/MS fragmentation-based LC/MS approaches. This article reviews the mass defect patterns of various classes of drug metabolites and the basic principles of the MDF approach. Examples are given on the applications of the MDF technique to the detection of stable and chemically reactive metabolites in vitro and in vivo. Advantages, limitations, and future applications are also discussed on MDF and its combinations with other data mining techniques for the detection and identification of drug metabolites.