Identification and Biosynthesis of an N-Glucuronide Metabolite of Camonsertib.

Camonsertib is a novel ATR kinase inhibitor in clinical development for advanced cancers targeting sensitizing mutations. This article describes the identification and biosynthesis of an N-glucuronide metabolite of camonsertib. This metabolite was first observed in human hepatocyte incubations and was subsequently isolated to determine the structure, evaluate its stability as part of bioanalytical method development and for use as a standard for estimating its concentration in Phase I samples. The N-glucuronide was scaled-up using a purified bacterial culture preparation and was subsequently isolated using preparative chromatography. The bacterial culture generated sufficient material of the glucuronide to allow for one- and two-dimensional 1H and 13C NMR structural elucidation and further bioanalytical characterization. The NOE data combined with the gradient HMBC experiment and molecular modeling, strongly suggests that the point of attachment of the glucuronide results in the formation of (2S,3S,4S,5R,6R)-3,4,5-trihydroxy-6-(5-(4-((1R,3r,5S)-3-hydroxy-8-oxabicyclo[3.2.1]octan-3-yl)-6-((R)-3-methylmorpholino)-1H-pyrazolo[3,4-b]pyridin-1-yl)-1H-pyrazol-1-yl)tetrahydro-2H-pyran-2-carboxylic acid. Significance Statement This is the first report of a glucuronide metabolite of camonsertib formed by human hepatocyte incubations. This study reveals the structure of an N-glucuronide metabolite of camonsertib using detailed elucidation by one- and two-dimensional NMR after scale-up using a novel bacterial culture approach yielding significant quantities of a purified metabolite.

3-epi-18ß-glycyrrhetinic acid or its glucuronide, the metabolites of glycyrrhizinic acid with individual differences, correlated with diagnostic maker for licorice-induced pseudoaldosteronism in humans.

Licorice is a crude drug that is used in traditional Japanese Kampo medicine and is also used as a sweetener. Occasionally, it causes pseudoaldosteronism (PsA) as a side effect. The major symptoms include hypokalemia, hypertension, edema, and low plasma aldosterone levels. PsA might be caused by the metabolites of glycyrrhizinic acid (GL), a component of licorice. The development of PsA markedly varies among individuals; however, the factors that cause these individual differences remain unknown. In this study, 78 patients who consumed Kampo medicines containing licorice were enrolled, and their laboratory data, including serum potassium levels, plasma aldosterone concentrations (PAC), and the concentrations of GL metabolites in the residual blood and/or urine samples were evaluated. Of the 78 participants, 18ß-glycyrrhetinic acid (GA), 3-epi-GA, 3-oxo-GA, 18ß-glycyrrhetinyl-30-O-glucuronide (GA30G), and 3-epi-GA30G were detected in the serum samples of 65, 47, 63, 62, and 3 participants, respectively. Of the 29 urine samples collected, GA30G and 3-epi-GA30G were detected in 27 and 19 samples. 3-epi-GA30G is a newly found GL metabolite. Moreover, 3-epi-GA, 3-oxo-GA, and 3-epi-GA30G were identified in human samples for the first time. High individual differences were found in the appearances of 3-epi-GA in serum and 3-epi-GA30G in urine, and the concentrations of these metabolites were correlated with serum PsA markers. The inhibitory titers of 3-epi-GA, 3-oxo-GA, GA30G, and 3-epi-GA30G on human 11ß-hydroxysteroid dehydrogenase type 2 (11ß-HSD2) were almost similar. These findings suggest that 3-epi-GA and/or 3-epi-GA30G are associated with individual differences in the development of PsA. Significance Statement In this study, we detected 3-epi-GA in human serum for the first time. We also identified 3-epi-GA30G as a novel GL metabolite in human urine. These GL metabolite levels showed correlations with markers of PsA. Additionally, there are individual differences in whether or not they appear in the serum/urine. In conclusion, 3-epi-GA/3-epi-GA30G correlates with individual differences in the development of PsA.

Implementation of pure shift 1 H NMR in metabolic phenotyping for structural information recovery of biofluid metabolites with complex spin systems.

NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.

Navigating common pitfalls in metabolite identification and metabolomics bioinformatics.

BACKGROUND: Metabolomics, the systematic analysis of small molecules in a given biological system, emerged as a powerful tool for different research questions. Newer, better, and faster methods have increased the coverage of metabolites that can be detected and identified in a shorter amount of time, generating highly dense datasets. While technology for metabolomics is still advancing, another rapidly growing field is metabolomics data analysis including metabolite identification. Within the next years, there will be a high demand for bioinformaticians and data scientists capable of analyzing metabolomics data as well as chemists capable of using in-silico tools for metabolite identification. However, metabolomics is often not included in bioinformatics curricula, nor does analytical chemistry address the challenges associated with advanced in-silico tools. AIM OF REVIEW: In this educational review, we briefly summarize some key concepts and pitfalls we have encountered in a collaboration between a bioinformatician (originally not trained for metabolomics) and an analytical chemist. We identified that many misunderstandings arise from differences in knowledge about metabolite annotation and identification, and the proper use of bioinformatics approaches for these tasks. We hope that this article helps other bioinformaticians (as well as other scientists) entering the field of metabolomics bioinformatics, especially for metabolite identification, to quickly learn the necessary concepts for a successful collaboration with analytical chemists. KEY SCIENTIFIC CONCEPTS OF REVIEW: We summarize important concepts related to LC-MS/MS based non-targeted metabolomics and compare them with other data types bioinformaticians are potentially familiar with. Drawing these parallels will help foster the learning of key aspects of metabolomics.

Metabolomics 2023 workshop report: moving toward consensus on best QA/QC practices in LC-MS-based untargeted metabolomics.

INTRODUCTION: During the Metabolomics 2023 conference, the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) presented a QA/QC workshop for LC-MS-based untargeted metabolomics. OBJECTIVES: The Best Practices Working Group disseminated recent findings from community forums and discussed aspects to include in a living guidance document. METHODS: Presentations focused on reference materials, data quality review, metabolite identification/annotation and quality assurance. RESULTS: Live polling results and follow-up discussions offered a broad international perspective on QA/QC practices. CONCLUSIONS: Community input gathered from this workshop series is being used to shape the living guidance document, a continually evolving QA/QC best practices resource for metabolomics researchers.

Biotransformation of Organophosphate Diesters Characterized via In Vitro Metabolism and In Vivo Screening.

Organophosphate diesters (di-OPEs), as additives in industrial applications and/or transformation products of emerging environmental pollutants, such as organophosphate triesters (tri-OPEs), have been found in the environment and biological matrices. The metabolic fate of di-OPEs in biological media is of great significance for tracing the inherent and precursor toxicity variations. This is the first study to investigate the metabolism of a suite of di-OPEs by liver microsomes and to identify any metabolite of metabolizable di-OPEs in in vitro and in vivo samples. Of the 14 di-OPEs, 5 are significantly metabolizable, and their abundant metabolites with hydroxyl, carboxyl, dealkylated, carbonyl, and/or epoxide groups are tentatively identified. More than half of the di-OPEs are detectable in human serum and/or wild fish tissues, and dibenzyl phosphate (DBzP), bis(2,3-dibromopropyl) phosphate (BDBPP), and isopropyl diphenyl phosphate (ip-DPHP) are first reported at a detectable level in humans and wildlife. Using an in vitro assay and a known biotransformation rule-based integrated screening strategy, 2 and 10 suspected metabolite peaks of DEHP are found in human serum and wild fish samples, respectively, and are then identified as phase I and phase II metabolites of DEHP. This study provides a novel insight into fate and persistence of di-OPE and confirms the presence of di-OPE metabolites in humans and wildlife.

Characterizing the Metabolism of Tire Rubber-Derived p-Phenylenediamine Quinones to Identify Potential Exposure Biomarkers in Humans.

There is growing evidence of the frequent detection of tire rubber-derived contaminants p-phenylenediamine-derived quinones (PPD-Qs) (e.g., highly toxic N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q)) in the environment and biota and the adverse impact on organisms. Hence, a better understanding of their biotransformation/metabolism in humans is essential. However, relevant data are lacking owing to recent discoveries. Herein, the biotransformation patterns of 6PPD-Q and other five commonly detected PPD-Qs were characterized via combined in vitro assay and maternal cord blood screening monitoring. Rapid metabolism was found for each PPD-Q incubated with human liver S9 fraction and microsomes, resulting in the formation of abundant phase I and phase II metabolites. The subsequent screening for potential PPD-Q metabolites in blood samples showed the presence of suspect metabolites. Three detected metabolites were confirmed by matching the mass spectra and retention times of in vitro metabolites. N-Dealkylated, carboxy, carbonyl, and reductive metabolites and glucose, cysteine, and methionine conjugates were observed for the first time. The semiquantitative concentrations of metabolites were higher than those of the parent PPD-Qs, and several metabolites such as carboxy products were proposed as candidate biomarkers of PPD-Q exposure to humans. 6PPD-Q and N,N'-diphenyl-p-phenylenediamine quinone were detected in maternal and/or cord whole blood samples for the first time. This study holds great importance in elucidating the potential risks and health effects of PPD-Qs.

Pharmaceutical metabolite identification in lettuce (Lactuca sativa) and earthworms (Eisenia fetida) using liquid chromatography coupled to high-resolution mass spectrometry and in silico spectral library.

Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and an in silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

Metabolite characterisation of the peptide-drug conjugate LN005 in liver S9s by UHPLC-Orbitrap-HRMS.

LN005 is a peptide-drug conjugate (PDC) targeting glucose-regulated protein 78 (GRP78) to treat several types of cancer, such as breast, colon, and prostate cancer.As a new drug modality, understanding its metabolism and elimination pathways will help us to have a whole picture of it. Currently, there are no metabolic studies on LN005; therefore, this study aimed to investigate the metabolism of LN005, clarify its metabolic profile in the liver S9s of different species, and identify the major metabolic pathways and differences between species.The incubation samples were measured by ultra-high performance liquid chromatography combined with orbitrap tandem mass spectrometry (UHPLC-Orbitrap-HRMS).The results showed that LN005 was metabolised by liver S9s, and four metabolites were identified. The main metabolic pathway of LN005 in liver S9s was oxidative deamination to ketone or hydrolysis. Similar metabolic profiles were observed in mouse, rat, dog, monkey, and human liver S9s, indicating no differences between these four animal species and humans.This study provides information for the structural modification and optimisation of LN005 and affords a reference for subsequent animal experiments and human metabolism of other PDCs.

Improved preclinical drug metabolism and pharmacokinetics of pibothiadine (HEC121210), a novel hepatitis B virus capsid assembly modulator.

Pibothiadine (PBD; HEC121120) is a novel hepatitis B virus capsid assembly modulator based on GLS4 (morphothiadine) and has inhibitory activities against resistant strains.To assess the overall preclinical drug metabolism and pharmacokinetics (DMPK) properties of PBD, in vivo pharmacokinetics studies in rats and dogs have been performed along with a series of in vitro metabolism assays.The oral bioavailability of PBD in rats and dogs might be related to its medium permeability in Caco-2 cells and largely be impacted by the pH-dependent solubility. PBD was highly distributed to the liver where the local exposure was 16.4 fold of the system exposure. PBD showed relatively low metabolic rate in recombinant human cytochrome P450 enzymes, whereas low to moderate in vitro clearance in liver microsomes and low (dog) to moderate (rat) in vivo clearance. Furthermore, ß-oxidation and dehydrogenation were proposed as the primary metabolic pathways of PBD in rats.Compared to GLS4, the higher systemic exposure of PBD might be attributed to its improved oral absorption and metabolic stability. In addition, the enhanced liver/plasma exposure ratio could further increase the local exposure around the target. These improved DMPK properties might indicate better development of PBD in the clinical phase.

Pharmacokinetics, mass balance, tissue distribution, metabolism, and excretion of [14C]aficamten following single oral dose administration to rats.

The pharmacokinetics, metabolism, excretion, mass balance, and tissue distribution of [14C]aficamten were evaluated following oral administration of an 8 mg/kg dose in Sprague Dawley rats and in a quantitative whole-body autoradiography study in Long Evans rats.[14C]Aficamten accounted for ∼80% and a hydroxylated metabolite (M1) accounted for ∼12% of total radioactivity in plasma over 48-h (AUC0-48). Plasma tmax was 4-h and the t1/2 of total plasma radioactivity was 5.8-h.Tissues showing highest Cmax exposures were myocardium and semitendinosus muscle.Most [14C]aficamten-derived radioactivity was excreted within 48-h post-administration. Mean cumulative recovery in urine and faeces over 168-h was 8.3% and 90.7%, respectively.In urine and bile, unchanged aficamten was detected at <0.1 and <0.2% of dose, respectively; however, based on total radioactivity excreted in urine (8.0%) and bile (51.7%), approximately 60% of dose was absorbed.[14C]Aficamten was metabolised by hydroxylation with subsequent glucuronidation where the most abundant metabolite recovered in bile was M5 (35.2%), the oxygen-linked glucuronide of hydroxylated aficamten (M1a). The major metabolite detected in faeces was a 1,2,4-oxadiazole moiety ring-cleaved metabolite (M18, 35.3%), shown to be formed from the metabolism of M5 in incubations with rat intestinal contents solution.

In vitro and in vivo preclinical pharmacokinetic characterization of aficamten, a small molecule cardiac myosin inhibitor.

Aficamten, a small molecule selective inhibitor of cardiac myosin, was characterised in preclinical in vitro and in vivo studies.Protein binding in human plasma was 10.4% unbound and ranged from 1.6% to 24.9% unbound across species. Blood-to-plasma ratios ranged from 0.69 to 1.14 across species. Aficamten hepatic clearance in human was predicted to be low from observed high metabolic stability in vitro in human liver microsomes. Aficamten demonstrated high permeability in Caco-2 cell monolayers.Aficamten in vivo clearance was low across species at 8.8, 2.1, 3.3, and 11 mL/min/kg in mouse, rat, dog, and monkey, respectively. The volume of distribution was low-to-high ranging from 0.53 in rat to 11 L/kg in dog. Oral bioavailability ranged from 41% in monkey to 98% in mouse.Aficamten was metabolised in vitro to eight metabolites with hydroxylated metabolites M1a and M1b predominating. CYP phenotyping indicated multiple CYPs (2C8, 2C9, 2D6, and 3A4) contributing to the metabolism of aficamten.Human clearance (1.1 mL/min/kg) and volume of distribution (6.5 L/kg) were predicted using 4-species allometry employing 'rule-of-exponents'. A predicted 69 hour half-life is consistent with observed half-life in human Phase-1.No CYP-based drug-drug interaction liability as a precipitant was predicted for aficamten.

Metabolism, Disposition, Excretion, and Potential Transporter Inhibition of 7-16, an Improving 5-HT2A Receptor Antagonist and Inverse Agonist for Parkinson's Disease.

Compound 7-16 was designed and synthesized in our previous study and was identified as a more potential selective 5-HT2A receptor antagonist and inverse agonist for treating Parkinson's disease psychosis (PDP). Then, the metabolism, disposition, and excretion properties of 7-16 and its potential inhibition on transporters were investigated in this study to highlight advancements in the understanding of its therapeutic mechanisms. The results indicate that a total of 10 metabolites of 7-16/[14C]7-16 were identified and determined in five species of liver microsomes and in rats using UPLC-Q Exactive high-resolution mass spectrometry combined with radioanalysis. Metabolites formed in human liver microsomes could be covered by animal species. 7-16 is mainly metabolized through mono-oxidation (M470-2) and N-demethylation (M440), and the CYP3A4 isozyme was responsible for both metabolic reactions. Based on the excretion data in bile and urine, the absorption rate of 7-16 was at least 74.7%. 7-16 had weak inhibition on P-glycoprotein and no effect on the transport activity of OATP1B1, OATP1B3, OAT1, OAT3, and OCT2 transporters. The comprehensive pharmacokinetic properties indicate that 7-16 deserves further development as a new treatment drug for PDP.

Rat Pharmacokinetics and In Vitro Metabolite Identification of KM-819, a Parkinson's Disease Candidate, Using LC-MS/MS and LC-HRMS.

FAF1 (FAS-associated factor 1) is involved in the activation of Fas cell surface death receptors and plays a role in apoptosis and necrosis. In patients with Parkinson's disease, FAF1 is overexpressed in dopaminergic neurons in the substantia nigra. KM-819, an FAF1 inhibitor, has shown potential for preventing dopaminergic neuronal cell death, promoting the degradation of α-synuclein and preventing its accumulation. This study aimed to develop and validate a quantitative analytical method for determining KM-819 levels in rat plasma using liquid chromatography-tandem mass spectrometry. This method was then applied to pharmacokinetic (PK) studies in rats. The metabolic stability of KM-819 was assessed in rat, dog, and human hepatocytes. In vitro metabolite identification and metabolic pathways were investigated in rat, dog, and human hepatocytes. The structural analog of KM-819, namely N-[1-(4-bromobenzyl)-3,5-dimethyl-1H-pyrazol-4-yl]-2-(phenylsulfanyl) acetamide, served as the internal standard (IS). Proteins were precipitated from plasma samples using acetonitrile. Analysis was carried out using a reverse-phase C18 column with a mobile phase consisting of 0.1% formic acid in distilled water and 0.1% formic acid in acetonitrile. The analytical method developed for KM-819 exhibited linearity within the concentration range of 0.002-10 µg/mL in rat plasma. The precision and accuracy of the intra- and inter-day measurements were <15% for the lower limit of quantification (LLOQ) and all quality control samples. KM-819 demonstrated stability under various sample storage conditions (6 h at room temperature (25 °C), four weeks at -20 °C, three freeze-thaw cycles, and pretreated samples in the autosampler). The matrix effect and dilution integrity met the criteria set by the Food and Drug Administration and the European Medicines Agency. This sensitive, rapid, and reliable analytical method was successfully applied in pharmacokinetic studies in rats. Pharmacokinetic analysis revealed the dose-independent kinetics of KM-819 at 0.5-5 mg/kg, with a moderate oral bioavailability of ~20% in rats. The metabolic stability of KM-819 was also found to be moderate in rat, dog, and human hepatocytes. Metabolite identification in rat, dog, and human hepatocytes resulted in the discovery of six, six, and eight metabolites, respectively. Glucuronidation and mono-oxidation have been proposed as the major metabolic pathways. Overall, these findings contribute to a better understanding of the pharmacokinetic characteristics of KM-819, thereby aiding future clinical studies.

Pickaxe: a Python library for the prediction of novel metabolic reactions.

BACKGROUND: Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user's application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation. RESULTS: Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset. CONCLUSION: Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.

Absorption, metabolism and excretion of 14C-emvododstat following repeat daily oral dose administration in human volunteers using a combination of microtracer radioactivity and high radioactivity doses.

Emvododstat is a potent inhibitor of dihydroorotate dehydrogenase and is now in clinical development for the treatment of COVID-19 and acute myeloid leukemia. Since the metabolism and pharmacokinetics of emvododstat in humans is time­dependent, a repeat dose study design using a combination of microtracer radioactivity and high radioactivity doses was employed to evaluate the metabolism and excretion of emvododstat near steady state. Seven healthy male subjects each received 16 mg/0.3 µCi 14C-emvododstat daily oral doses for 6 days followed by a 16 mg/100 µCi high radioactivity oral dose on Day 7. Following the last 16 mg/0.3 µCi 14C­emvododstat dose on Day 6, total radioactivity in plasma peaked at 6 h post-dose. Following a high radioactivity oral dose (16 mg/100 µCi) of 14C-emvododstat on Day 7, both whole blood and plasma radioactivity peaked at 6 h, rapidly declined from 6 h to 36 h post-dose, and decreased slowly thereafter with measurable radioactivity at 240 h post-dose. The mean cumulative recovery of the administered dose was 6.0% in urine and 19.9% in feces by 240 h post-dose, and the mean extrapolated recovery to infinity was 37.3% in urine and 56.6% in feces. Similar metabolite profiles were observed after repeat daily microtracer radioactivity oral dosing on Day 6 and after a high radioactivity oral dose on Day 7. Emvododstat was the most abundant circulating component, M443 and O-desmethyl emvododstat glucuronide were the major circulating metabolites; M474 was the most abundant metabolite in urine, while O­desmethyl emvododstat was the most abundant metabolite in feces. Significance Statement This study provides a complete set of the absorption, metabolism and excretion data of emvododstat, a potent inhibitor of dihydroorotate dehydrogenase, at close to steady state in healthy human subjects. Resolution of challenges due to slow metabolism and elimination of a lipophilic compound highlighted in this study can be achieved by repeat daily microtracer radioactivity oral dosing followed by a high radioactivity oral dosing at therapeutically relevant doses.

Impact of in vitro phytohormone treatments on the metabolome of the leafy liverwort Radula complanata (L.) Dumort.

INTRODUCTION: Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown. OBJECTIVES: To investigate the metabolic stress-response of the leafy liverwort Radula complanata. METHODS: Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts. RESULTS: It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments. CONCLUSION: Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.

MetaPro: a web-based metabolomics application for LC-MS data batch inspection and library curation.

INTRODUCTION: Metabolomics analysis based on liquid chromatography-mass spectrometry (LC-MS) has been a prevalent method in the metabolic field. However, accurately quantifying all the metabolites in large metabolomics sample cohorts is challenging. The analysis efficiency is restricted by the abilities of software in many labs, and the lack of spectra for some metabolites also hinders metabolite identification. OBJECTIVES: Develop software that performs semi-targeted metabolomics analysis with an optimized workflow to improve quantification accuracy. The software also supports web-based technologies and increases laboratory analysis efficiency. A spectral curation function is provided to promote the prosperity of homemade MS/MS spectral libraries in the metabolomics community. METHODS: MetaPro is developed based on an industrial-grade web framework and a computation-oriented MS data format to improve analysis efficiency. Algorithms from mainstream metabolomics software are integrated and optimized for more accurate quantification results. A semi-targeted analysis workflow is designed based on the concept of combining artificial judgment and algorithm inference. RESULTS: MetaPro supports semi-targeted analysis workflow and functions for fast QC inspection and self-made spectral library curation with easy-to-use interfaces. With curated authentic or high-quality spectra, it can improve identification accuracy using different peak identification strategies. It demonstrates practical value in analyzing large amounts of metabolomics samples. CONCLUSION: We offer MetaPro as a web-based application characterized by fast batch QC inspection and credible spectral curation towards high-throughput metabolomics data. It aims to resolve the analysis difficulty in semi-targeted metabolomics.

Characterization of Divergent Metabolic Pathways in Elucidating an Unexpected, Slow-Forming, and Long Half-Life Major Metabolite of Iclepertin.

PURPOSE: After single oral dosing of the glycine reuptake transporter (GlyT1) inhibitor, iclepertin (BI 425809), a single major circulating metabolite, M530a, was identified. However, upon multiple dosing, a second major metabolite, M232, was observed with exposure levels ~ twofold higher than M530a. Studies were conducted to characterize the metabolic pathways and enzymes responsible for formation of both major human metabolites. METHODS: In vitro studies were conducted with human and recombinant enzyme sources and enzyme-selective inhibitors. The production of iclepertin metabolites was monitored by LC-MS/MS. RESULTS: Iclepertin undergoes rapid oxidation to a putative carbinolamide that spontaneously opens to an aldehyde, M528, which then undergoes reduction by carbonyl reductase to the primary alcohol, M530a. However, the carbinolamide can also undergo a much slower oxidation by CYP3A to form an unstable imide metabolite, M526, that is subsequently hydrolyzed by a plasma amidase to form M232. This difference in rate of metabolism of the carbinolamine explains why high levels of the M232 metabolite were not observed in vitro and in single dose studies in humans, but were observed in longer-term multiple dose studies. CONCLUSIONS: The long half-life iclepertin metabolite M232 is formed from a common carbinolamine intermediate, that is also a precursor of M530a. However, the formation of M232 occurs much more slowly, likely contributing to its extensive exposure in vivo. These results highlight the need to employ adequate clinical study sampling periods and rigorous characterization of unexpected metabolites, especially when such metabolites are categorized as major, thus requiring safety assessment.

Interspecies Differences in 6PPD-Quinone Toxicity Across Seven Fish Species: Metabolite Identification and Semiquantification.

N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q) is a recently identified contaminant that originates from the oxidation of the tire antidegradant 6PPD. 6PPD-Q is acutely toxic to select salmonids at environmentally relevant concentrations, while other fish species display tolerance to concentrations that surpass those measured in the environment. The reasons for these marked differences in sensitivity are presently unknown. The objective of this research was to explore potential toxicokinetic drivers of species sensitivity by characterizing biliary metabolites of 6PPD-Q in sensitive and tolerant fishes. For the first time, we identified an O-glucuronide metabolite of 6PPD-Q using high-resolution mass spectrometry. The semiquantified levels of this metabolite in tolerant species or life stages, including white sturgeon (Acipenser transmontanus), chinook salmon (Oncorhynchus tshawytscha), westslope cutthroat trout (Oncorhynchus clarkii lewisi), and nonfry life stages of Atlantic salmon (Salmo salar), were greater than those in sensitive species, including coho salmon (Oncorhynchus kisutch), brook trout (Salvelinus fontinalis), and rainbow trout (Oncorhynchus mykiss), suggesting that tolerant species might detoxify 6PPD-Q more effectively. Thus, we hypothesize that differences in species sensitivity are a result of differences in basal expression of biotransformation enzyme across various fish species. Moreover, the semiquantification of 6PPD-Q metabolites in bile extracted from wild-caught fish might be a useful biomarker of exposure to 6PPD-Q, thereby being valuable to environmental monitoring and risk assessment.