High-throughput, accurate mass liquid chromatography/tandem mass spectrometry on a quadrupole time-of-flight system as a 'first-line' approach for metabolite identification studies

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.

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.

Metabolomics in clinical and forensic toxicology, sports anti-doping and veterinary residues

Metabolomics is a multidisciplinary field providing workflows for complementary approaches to conventional analytical determinations. It allows for the study of metabolically related groups of compounds or even the study of novel pathways within the biological system. The procedural stages of metabolomics; experimental design, sample preparation, analytical determinations, data processing and statistical analysis, compound identification and validation strategies are explored in this review. The selected approach will depend on the type of study being conducted. Experimental design influences the whole metabolomics workflow and thus needs to be properly assessed to ensure sufficient sample size, minimal introduced and biological variation and appropriate statistical power. Sample preparation needs to be simple, yet potentially global in order to detect as many compounds as possible. Analytical determinations need to be optimised either for the list of targeted compounds or a universal approach. Data processing and statistical analysis approaches vary widely and need to be better harmonised for review and interpretation. This includes validation strategies that are currently deficient in many presented workflows. Common compound identification approaches have been explored in this review. Metabolomics applications are discussed for clinical and forensic toxicology, human and equine sports anti-doping and veterinary residues.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

An integrated analytical approach based on enhanced fragment ions interrogation and modified Kendrick mass defect filter data mining for in-depth chemical profiling of glucosinolates by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry

High resolution mass spectrometry (HRMS)-based analytical technique promotes the discovery and development of new bioactive molecules from natural sources. However, challenges for MS analysis of natural products include their structural diversity, numerous trace components, as well as the interference from complex matrices that limits the rapid detection and identification of all target analytes in the extracts. Herein, we presented an integrated analytical approach to obtain chemical profile of glucosinolates (GLSs) in Eutrema yunnanense, a perennial herb, which is used as a condiment (Wasabi), by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry (UHPLC-Orbitrap/HRMS). The intelligent AcquireX deep scan greatly improved the detection efficiency and coverage of data-dependent acquisition (DDA) mode, and enhanced structurally significant product ions interrogation by generating exhaustive MS/MS spectra with more informative fragmentation. Massive HRMS data mining for searching GLSs was then achieved by a modified Kendrick mass defect filter (MKMDF), which enabled the visualization of their homologous characteristics and reduced the complicacy of data post-processing. Ultimately, a total of 175 GLSs were tentatively identified or characterized based on the MS fragmentation patterns, including 52 potentially new compounds among which 37 malonylated GLSs were first discovered. These compounds were then applied to analyse the chemical differentiation between the rhizome and leaf of E. yunnanense. This study provides a feasible approach for screening and confident structure characterization of GLSs and has practical implications for profiling other natural bioactive homologous compounds.

Equine metabolism of the selective androgen receptor modulator AC-262536 in vitro and in urine, plasma and hair following oral administration

AC-262536 is one of a number of selective androgen receptor modulators that are being developed by the pharmaceutical industry for treatment of a range of clinical conditions including androgen replacement therapy. Though not available therapeutically, selective androgen receptor modulators are widely available to purchase online as (illegal) supplement products. The growth- and bone-promoting effects, along with fewer associated negative side effects compared with anabolic-androgenic steroids, make these compounds a significant threat with regard to doping control in sport. The aim of this study was to investigate the metabolism of AC-262536 in the horse following in vitro incubation and oral administration to two Thoroughbred horses, in order to identify the most appropriate analytical targets for doping control laboratories. Urine, plasma and hair samples were collected and analysed for parent drug and metabolites. Liquid chromatography-high-resolution mass spectrometry was used for in vitro metabolite identification and in urine and plasma samples. Nine phase I metabolites were identified in vitro; four of these were subsequently detected in urine and three in plasma, alongside the parent compound in both matrices. In both urine and plasma samples, the longest detection window was observed for an epimer of the parent compound, which is suggested as the best target for detection of AC-262536 administration. AC-262536 and metabolites were found to be primarily glucuronide conjugates in both urine and plasma. Liquid chromatography-tandem mass spectrometry analysis of post-administration hair samples indicated incorporation of parent AC-262536 into the hair following oral administration. No metabolites were detected in the hair.

Time of flight mass spectrometry based in vitro and in vivo metabolite profiling of ribociclib and their toxicity prediction

The metabolic investigation in the drug discovery process is an imperative aspect for selection of drug candidates with excellent therapeutic efficacy and safety profile. Ribociclib (RIBO), an orally active Cyclin dependent kinases inhibitor recently approved by USFDA for its clinical efficacy against human epithelial growth factor receptor negative and hormonal receptor positive advanced breast cancer. Although an in vitro metabolite identification study of RIBO is available in literature, no systematic metabolic investigation including detailed structural characterization and toxicity prediction of the metabolites generated in in vivo system is reported till date. Therefore, in this study, we focused on the characterization of its entire metabolites generated in in vitro as well as in vivo matrices. In vitro study includes incubation of RIBO in rat and human liver microsomes and human S9 fraction, while in vivo study was carried out using plasma, urine and faeces samples of male Sprague Dawley rats. A total of 22 metabolites were successfully separated on Agilent SB C18 (100 × 4.6 mm, 2.7µ) column using ammonium formate (pH 3.5) and acetonitrile as mobile phase. Metabolites were identified with the help of UHPLC-ESI-Q-TOF-MS/MS by accurate mass measurement. RIBO was found to be metabolised by N- dealkylation, sulphation, acetylation, oxidation, hydroxylation, carbonylation, dehydrogenation and by a combination of these reactions. The in silico toxicity profiling of all the metabolites was carried out with the help of ProTox-II software. Ten out of twenty two newly identified metabolites showed to have potential for possessing immunotoxicity. Novelty of this investigation can be justified by the unavailability of any previously published literature on complete in vitro and in vivo metabolite profiling of RIBO. Moreover, in silico toxicity of the metabolites were also not known till date.

An investigation on the metabolic pathways of synthetic isoflavones by gas chromatography coupled to high accuracy mass spectrometry

RATIONALE

Isoflavones are a group of flavonoids that may be of interest in sport doping because they can be used by athletes in the recovery periods after the administration of anabolic steroids, with the aim of increasing the natural production of luteinizing hormone (LH) and, consequently, the biosynthesis of endogenous androgens.

METHODS

The in vivo metabolism of methoxyisoflavone (5-methyl-7-methoxyisoflavone) and ipriflavone (7-isopropoxyisoflavone), respectively present in a dietary supplement and in a pharmaceutical preparation, was investigated. The study was carried out by the analysis of urinary samples collected from male Caucasian subjects before, during and after the oral administration of methoxyisoflavone or ipriflavone. After enzymatic hydrolysis and liquid-liquid extraction, all urinary samples were analyzed by gas chromatography/quadrupole time-of-flight (qTOF MS system/qTOF) electron ionization mass spectrometry (EI-MS).

RESULTS

Eight metabolites of methoxyisoflavone and six metabolites of ipriflavone were isolated. The corresponding accurate mass spectra are specific for isoflavone structures and revealed also a retro-Diels-Alder fragmentation.

CONCLUSIONS

When excreted in large amounts, the urinary metabolites of methoxyisoflavone and ipriflavone can be traced to potential confounding factors in doping analysis. As methoxyisoflavone and ipriflavone have been shown to inhibit the enzyme aromatase, thus interfering with the normal metabolic pathways of testosterone, the detection of their intake, by screening for the presence of their main metabolites in urine, might be helpful in routine doping control analysis.

SWATH Tandem Mass Spectrometry Workflow for Quantification of Mass Isotopologue Distribution of Intracellular Metabolites and Fragments Labeled with Isotopic 13C Carbon

Accurate quantification of mass isotopologue distribution (MID) of metabolites is a prerequisite for ¹³C-metabolic flux analysis. Currently used mass spectrometric (MS) techniques based on multiple reaction monitoring (MRM) place limitations on the number of MIDs that can be analyzed in a single run. Moreover, the deconvolution step results in amplification of error. Here, we demonstrate that SWATH MS/MS, a data independent acquisition (DIA) technique allows quantification of a large number of precursor and product MIDs in a single run. SWATH sequentially fragments all precursor ions in stacked mass isolation windows. Co-fragmentation of all precursor isotopologues in a single SWATH window yields higher sensitivity enabling quantification of MIDs of fragments with low abundance and lower systematic and random errors. We quantify the MIDs of 53 precursor and product ions corresponding to 19 intracellular metabolites from a dynamic ¹³C-labeling of a model cyanobacterium, Synechococcus sp. PCC 7002. The use of product MIDs resulted in an improved precision of many measured fluxes compared to when only precursor MIDs were used for flux analysis. The approach is truly untargeted and allows additional metabolites to be quantified from the same data.

Metabolism of novel opioid agonists U-47700 and U-49900 using human liver microsomes with confirmation in authentic urine specimens from drug users

Recently, the number of adverse events, including death, involving novel opioids has continued to increase, providing additional and sustained challenges for forensic and medical communities. Identification of emerging novel opioids can be challenging, compounded by detection windows and unknown metabolic profiles. In this study, human liver microsomes were used for the generation of in vitro metabolic profiles of U-47700 and U-49900. Generated metabolites were analyzed via a SCIEX TripleTOF® 5600+ quadrupole time-of-flight mass spectrometer and resulting data files were processing using MetabolitePilot™. Characterized metabolites were verified in vivo by analysis of authentic human urine specimens collected after analytically confirmed cases of overdose involving U-47700 or U-49900. In total, four metabolites were identified and present in urine specimens for U-47700, and five metabolites for U-49900. N-Desmethyl-U-47700 was determined to be the primary metabolite of U-47700. Parent U-47700 was identified in all urine specimens. N-Desmethyl-U-47700 and N,N-didesmethyl-U-47700 were structurally confirmed for the first time during this study following acquisition of standard reference material. N-Desethyl-U-49900 was determined to be the primary metabolite of U-49900 following microsomal incubations, while N,N-didesethyl-N-desmethyl-U-49900 was the most abundant in a urine specimen. Similarities in metabolic transformation were identified between U-47700 and U-49900, resulting in a common metabolite and isomeric species. These phenomena should be considered in cases involving U-47700 or U-49900. This study is the first to map the metabolic profiles of U-47700 and U-49900 using human liver microsomes, as well as the first to report any literature involving U-49900 and analysis of case specimens.

Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome

Global profiling of xenobiotics in human matrices in an untargeted mode is gaining attention for studying the environmental chemical space of the human exposome. Defined as the study of a comprehensive inclusion of environmental influences and associated biological responses, human exposome science is currently evolving out of the metabolomics science. In analogy to the latter, the development and applications of high resolution mass spectrometry (HRMS) has shown potential and promise to greatly expand our ability to capture the broad spectrum of environmental chemicals in exposome studies. HRMS can perform both untargeted and targeted analysis because of its capability of full- and/or tandem-mass spectrum acquisition at high mass accuracy with good sensitivity. The collected data from target, suspect and non-target screening can be used not only for the identification of environmental chemical contaminants in human matrices prospectively but also retrospectively. This review covers recent trends and advances in this field. We focus on advances and applications of HRMS in human biomonitoring studies, and data acquisition and mining. The acquired insights provide stepping stones to improve understanding of the human exposome by applying HRMS, and the challenges and prospects for future research.

Implementation of a novel ultra fast metabolic stability analysis method using exact mass TOF-MS

AIM

Increasing numbers of compounds requiring stability data means highly optimized methods capable of rapid turnaround are desirable during early discovery. Materials and methods/results: An advanced, generic analytical workflow for metabolic stability has been developed that utilizing ballistic gradient LC (sub 1 min run times), exact mass TOF-MS (Waters Xevo-G2-XS Q-TOF) and automated data processing (Waters UNIFI software) allowed for rapid integration and interpretation of all data produced, eliminating the need for method development and manual processing. We can analyze and process 96 compounds across two species in quadruplicate in a 24-h period with no method development.

CONCLUSION

An advanced bioanalytical workflow has increased our capacity threefold and reduced our instrument/processing needs threefold.

Discovery bioanalysis and in vivo pharmacology as an integrated process: a case study in oncology drug discovery

Background: A bioanalytical team dedicated to in vivo pharmacology was set up to accelerate the selection and characterization of compounds to be evaluated in animal models in oncology. Results: A DBS-based serial microsampling procedure was optimized from sample collection to extraction to obtain a generic procedure. UHPLC–high-resolution mass spectrometer configuration allowed for fast quantitative and qualitative analysis. Using an optimized lead compound, we show how bioanalysis supported in vivo pharmacology by generating blood and tumor exposure, drug monitoring and PK/PD data. Conclusion: This process provided unique opportunities for the characterization of drug properties, selection and assessment of compounds in animal models and to support and expedite proof-of-concept studies in oncology.

UPLC/ESI-MS/MS-based determination of metabolism of several new illicit drugs, ADB-FUBINACA, AB-FUBINACA, AB-PINACA, QUPIC, 5F-QUPIC and α-PVT, by human liver microsome

The metabolism by human liver microsomes of several new illicit drugs, that is, N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(4-fluorobenzyl)-1H-indazole-3- carboxamide (ADB-FUBINACA), N-(1-amino-3-methyl-1-oxobutan-2-yl)-1- (4-fluorobenzyl)-1H-indazole-3-carboxamide (AB-FUBINACA), N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-pentyl-1H-indazole-3-carboxamide (AB-PINACA), quinolin-8-yl 1-pentyl-(1H-indole)-3-carboxylate (QUPIC), quinolin-8-yl 1-(5-fluoropentyl)-(1H-indole)-3-carboxylate (5 F-QUPIC) and α-pyrrolidinovalerothiophenone (α-PVT), which have indole, indazole, quinolinol ester and thiophene structures, was investigated using reversed-phase chromatography and mass spectrometry. The present method is based upon the oxidation by cytochrome p450 superfamily enzymes in the microsomes. The oxidation of ADB-FUBINACA and AB-FUBINACA mainly occurred on the N-(1-amino-alkyl-1-oxobutan) moiety. However, the oxidation of AB-PINACA seemed to occur on the 1-pentyl moiety. On the other hand, QUPIC and 5 F-QUPIC, which have a quinolinol ester structure, predominantly underwent a cleavage reaction to produce indoleacetic acid type metabolites. In contrast, the metabolism reaction of α-PVT was different from that of the other tested drugs, and various oxidation products were observed on the chromatograms. The obtained metabolites are not in conflict with the results predicted by MetaboLynx software. However, the exact structures of the metabolites, except for 1-pentyl-1H-indole-3-carboxylic acid (QUPIC metabolite) and 1-(5-fluoropentyl)-1H-indole-3-carboxylic acid (5 F-QUPIC metabolite), are currently not proven, because we have no authentic compounds for comparison. The proposed approach using human liver microsome seems to provide a new technology for the prediction of possible metabolites occuring in humans.

Data acquisition and data mining techniques for metabolite identification using LC coupled to high-resolution MS

Metabolite identification plays a pivotal role through all stages of drug discovery and development. The task of detecting and characterizing drug metabolites in complex biological matrices is very challenging, due in part to the co-existence of drug-related material with a large excess of endogenous material. Deciphering information on drug metabolites in these complex biological systems requires not only sophisticated LC-MS systems, but also software that can help differentiate drug-related compounds from endogenous material in the MS data. Fortunately, there have been considerable advances in high-resolution MS technologies with improved mass accuracy. The high resolution and mass accuracy capabilities have necessitated and augmented the development of integrated data acquisition methods, which have significantly facilitated metabolite detection and identification. In this review, we discuss various data-dependent and -independent acquisition methods in combination with accurate mass-based data mining tools for metabolite identification in drug discovery and development.

Metabolite identification of a new tyrosine kinase inhibitor, HM781-36B, and a pharmacokinetic study by liquid chromatography/tandem mass spectrometry

RATIONALE

HM781-36B (1-[4-[4-(3,4-dichloro-2-fluorophenylamino)-7-methoxyquinazolin-6-yloxy]-piperidin-1-yl]prop-2-en-1-one hydrochloride) is a new anticancer drug to treat advanced solid tumors in clinical trial. In order to understand the behavior of HM781-36B in vitro and in vivo we validated an analytical method for HM781-36B and its major metabolites in plasma.

METHODS

In vivo and in vitro metabolism of HM781-36B was studied in dog plasma, urine and feces as well as using human and dog liver microsomes with extraction by ethyl acetate or methyl tert-butyl ether, respectively, and successfully separated by high-performance liquid chromatography diode-array detection mass spectrometry (HPLC-DAD/MS). Ten metabolites were identified by LC/ESI-ion trap mass spectrometry (MS, MS(2) , MS(3) and MRM) and LC/Q-TOF-MS/MS for exact mass measurement. For accurate characterization of the major metabolites, authentic standards (M1, M2, M4, and M10) were synthesized.

RESULTS

Ten metabolites of HM781-36B in an in vitro mixture were separated and identified by LC/ESI-MS(n) . The MS/MS spectral patterns of the parent drug and metabolites exhibited two characteristic ions (A- and B-type ions) attributed to the cleavage of the ether bond between the piperidine ring and the quinazoline ring, providing important information on the site of chemical conversion during the metabolism. Six hydroxylated derivatives including dehalogenation and demethylation, two N-oxide forms, a demethylated form and de-acryloylpiperideine metabolites were observed.

CONCLUSIONS

The LC/ESI-ion trap MS(n) technique was effective in obtaining structural information and yielded diagnostic ions for the identification of diverse metabolites. The multiple metabolic pathways of HM781-36B were suggested in in vitro and in vivo samples and the dihydroxylation (M1) and demethylation (M2) appeared to be the major metabolites.

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.

Exploring the utility of high-resolution MS with post-acquisition data mining for simultaneous exogenous and endogenous metabolite profiling

Background: The utility of high-resolution MS (HRMS) with post-acquisition data mining in DMPK goes much further than the now established approach to simultaneously acquire quantitative and qualitative information for lead compounds at the discovery stage. Indeed, HRMS has promise for addressing multiple complex drug-development applications in a single experiment. In the present study, one HRMS dataset acquired for in vitro incubations of the model compound dasatinib was mined post-acquisition to address four different issues: stability, metabolite profiling, glutathione conjugate analysis, and endogenous lipid profiling. Results & Conclusion: The derived results demonstrated that HRMS has potential for generating high information content datasets that can be stored and mined as needed to answer numerous complex development-stage questions without the need for additional sample generation or analysis.

Software aided approaches to structure-based metabolite identification in drug discovery and development

Technological advances in mass spectrometry (MS) such as accurate mass high resolution instrumentation have fundamentally changed the approach to systematic metabolite identification over the past decade. Despite technological break-through on the instrumental side, metabolite identification still requires tedious manual data inspection and interpretation of huge analytical datasets. The process of metabolite identification has become largely facilitated and partly automated by cheminformatics approaches such as knowledge base metabolite prediction using, for example, Meteor, MetaDrug, MetaSite and StarDrop that are typically applied pre-acquisition. Likewise, emerging new technologies in postacquisition data analysis like mass defect filtering (MDF) have moved the technology driven analytical methodology to metabolite identification toward generic, structure-based workflows. The biggest challenge for automation however remains the structural assignment of drug metabolites. Software-guided approaches for the unsupervised metabolite identification still cannot compete with expert user manual data interpretation yet. Recently MassMetaSite has been introduced for the automated ranked output of metabolite structures based on the combination of metabolite prediction and interrogation of analytical mass spectrometric data. This approach and others are promising milestones toward an unsupervised process to metabolite identification and structural characterization moving away from a sample focused per-compound approach to a structure-driven generic workflow.

Fixing clearance as early as lead optimization using high throughput in vitro incubations in combination with exact mass detection and automatic structure elucidation of metabolites

New enabling MS technologies have made it possible to elucidate metabolic pathways present in ex vivo (blood, bile and/or urine) or in vitro (liver microsomes, hepatocytes and/or S9) samples. When investigating samples from high throughput assays the challenge that the user is facing now is to extract the appropriate information and compile it so that it is understandable to all. Medicinal chemist may then design the next generation of (better) drug candidates combining the needs for potency and metabolic stability and their synthetic creativity. This review focuses on the comparison of these enabling MS technologies and the IT tools developed for their interpretation.

Use of time-of-flight mass spectrometry for large screening of organic pollutants in surface waters and soils from a rice production area in Colombia

The irrigate district of Usosaldaña, an important agricultural area in Colombia mainly devoted to rice crop production, is subjected to an intensive use of pesticides. Monitoring these compounds is necessary to know the impact of phytosanitary products in the different environmental compartments. In this work, surface water and soil samples from different sites of this area have been analyzed by applying an analytical methodology for large screening based on the use of time-of-flight mass spectrometry (TOF MS) hyphenated to liquid chromatography (LC) and gas chromatography (GC). Several pesticides were detected and unequivocally identified, such as the herbicides atrazine, diuron or clomazone. Some of their main metabolites and/or transformation products (TPs) like deethylatrazine (DEA), deisopropylatrazine (DIA) and 3,4-dichloroaniline were also identified in the samples. Among fungicides, carbendazim, azoxystrobin, propiconazole and epoxiconazole were the most frequently detected. Insecticides such as thiacloprid, or p,p'-DDT metabolites (p,p'-DDD and p,p'-DDE) were also found. Thanks to the accurate-mass full-spectrum acquisition in TOF MS it was feasible to widen the number of compounds to be investigated to other families of contaminants. This allowed the detection of emerging contaminants, such as the antioxidant 3,5-di-tertbutyl-4-hydroxy-toluene (BHT), its metabolite 3,5-di-tert-butyl-4-hydroxy-benzaldehyde (BHT-CHO), or the solar filter benzophenone, among others.

[An ultra performance liquid chromatography-time-of-flight-mass spectrometric method for fast analysis of ginsenosides in Panax ginseng root]

A method for fast analysis of ginsenosides in Panax ginseng roots was developed using ultra performance liquid chromatography-time-of-flight-mass spectrometry (UPLC-TOF-MS). The column used was HSS T3 (100 mm x 2.1 mm, 1.8 microm). The mobile phase consisted of 15 mmol/L ammonium formate and acetonitrile, eluted with the gradient program. The separations of 9 ginsenoside standards and ginseng root extracts were achieved. Based on the MS/ MS fragments and accurate masses of the target compounds and with combination of the MS/ MS fragments of the 9 ginsenoside standards, 27 ginsenosides were identified from the extracts of the ginseng roots. The validation of the analytical method was thoroughly investigated with 9 ginsenoside standards. It was found that 9 ginsenosides had a better linearity in 0.04 - 9.00 mg/L. The recoveries at the three spiked levels (low, medium and high) were 90% - 100%, 98% - 104% and 96% - 103%, respectively. The relative standard deviations (RSDs) of the peak area ratio of 9 ginsenoside standards to internal standard at the medium spiked level were not more than 11.3%, which were satisfactory for profiling analysis of herb extracts. This method is characterized by its high resolution, rapidness, simplicity and reliability, and has been successfully applied to the evaluation of the differentiation between 2- and 6-year-old ginseng roots. It can be expected that this method is also useful for the fast determination of the ginsenosides in other ginseng related samples.

High-resolution mass spectrometry elucidates metabonate (false metabolite) formation from alkylamine drugs during in vitro metabolite profiling

In vitro metabolite profiling and characterization experiments are widely employed in early drug development to support safety studies. Samples from incubations of investigational drugs with liver microsomes or hepatocytes are commonly analyzed by liquid chromatography/mass spectrometry for detection and structural elucidation of metabolites. Advanced mass spectrometers with accurate mass capabilities are becoming increasingly popular for characterization of drugs and metabolites, spurring changes in the routine workflows applied. In the present study, using a generic full-scan high-resolution data acquisition approach with a time-of-flight mass spectrometer combined with postacquisition data mining, we detected and characterized metabonates (false metabolites) in microsomal incubations of several alkylamine drugs. If a targeted approach to mass spectrometric detection (without full-scan acquisition and appropriate data mining) were employed, the metabonates may not have been detected, hence their formation underappreciated. In the absence of accurate mass data, the metabonate formation would have been incorrectly characterized because the detected metabonates manifested as direct cyanide-trapped conjugates or as cyanide-trapped metabolites formed from the parent drugs by the addition of 14 Da, the mass shift commonly associated with oxidation to yield a carbonyl. This study demonstrates that high-resolution mass spectrometry and the associated workflow is very useful for the detection and characterization of unpredicted sample components and that accurate mass data were critical to assignment of the correct metabonate structures. In addition, for drugs containing an alkylamine moiety, the results suggest that multiple negative controls and chemical trapping agents may be necessary to correctly interpret the results of in vitro experiments.

A unique automation platform for measuring low level radioactivity in metabolite identification studies

Generation and interpretation of biotransformation data on drugs, i.e. identification of physiologically relevant metabolites, defining metabolic pathways and elucidation of metabolite structures, have become increasingly important to the drug development process. Profiling using ¹⁴C or ³H radiolabel is defined as the chromatographic separation and quantification of drug-related material in a given biological sample derived from an in vitro, preclinical in vivo or clinical study. Metabolite profiling is a very time intensive activity, particularly for preclinical in vivo or clinical studies which have defined limitations on radiation burden and exposure levels. A clear gap exists for certain studies which do not require specialized high volume automation technologies, yet these studies would still clearly benefit from automation. Use of radiolabeled compounds in preclinical and clinical ADME studies, specifically for metabolite profiling and identification are a very good example. The current lack of automation for measuring low level radioactivity in metabolite profiling requires substantial capacity, personal attention and resources from laboratory scientists. To help address these challenges and improve efficiency, we have innovated, developed and implemented a novel and flexible automation platform that integrates a robotic plate handling platform, HPLC or UPLC system, mass spectrometer and an automated fraction collector.

Using high-resolution quadrupole TOF technology in DMPK analyses

Recent advances in quadrupole TOF (Q-TOF) MS have some bioanalytical scientists referring to a ‘paradigm shift’ in their field. They are speaking of a potential move away from workflows based upon triple-quadrupole MS. Gone would be the optimizing of numerous parameters in selected-reaction monitoring (SRM) experiments, replaced with more generic workflows provided by Q-TOF instruments with high data acquisition rates, excellent mass accuracy (≤5 ppm) and high resolving power (≥30,000). Such a move could pay real dividends for high-throughput workflows, especially in drug metabolism and pharmacokinetics analyses where quantitation and qualification studies could actually be merged. But, are modern Q-TOF-MS instruments, touted as high-resolution MS, ready for this? If not, how close is it? This article will examine these questions by reviewing recent advances in Q-TOF technology and some fascinating orthogonal technology (such as ion mobility) that modern Q-TOFs employ for even greater analytical power.

Integrated quantitative and qualitative workflow for in vivo bioanalytical support in drug discovery using hybrid Q-TOF-MS

Background: UHPLC coupled with orthogonal acceleration hybrid quadrupole-TOF (Q-TOF)-MS is an emerging technique offering new strategies for the efficient screening of new chemical entities and related molecules at the early discovery stage within the pharmaceutical industry. In the first part of this article, we examine the main instrumental parameters that are critical for the integration of UHPLC–Q-TOF technology to existing bioanalytical workflows, in order to provide simultaneous quantitative and qualitative bioanalysis of samples generated following in vivo studies. Material & Methods: Three modern Q-TOF mass spectrometers, including Bruker maXis™, Agilent 6540 and Sciex TripleTOF™ 5600, all interfaced with UHPLC systems, are evaluated in the second part of the article. The scope of this work is to demonstrate the potential of Q-TOF for the analysis of typical small molecules, therapeutic peptides (molecular weight <6000 Da), and enzymatically (i.e., trypsin, chymotrypsin and pepsin) cleaved peptides from larger proteins. Results & Discussion: This work focuses mainly on full-scan TOF data obtained under ESI conditions, the major mode of TOF operation in discovery bioanalytical research, where the compounds are selected based on their pharmacokinetic/pharmacodynamic behaviors using animal models prior to selecting a few desirable candidates for further development. Finally, important emerging TOF technologies that could potentially benefit bioanalytical research in the semi-quantification of metabolites without synthesized standards are discussed. Particularly, the utility of captive spray ionization coupled with TripleTOF 5600 was evaluated for improving sensitivity and providing normalized MS response for drugs and their metabolites. The workflow proposed compromises neither the efficiency, nor the quality of pharmacokinetic data in support of early drug discovery programs.

Use of relative 12C/14C isotope ratios to estimate metabolite concentrations in the absence of authentic standards

Background: There is considerable interest in the determination of relative abundances of human metabolites in plasma (and potentially excreta) with reasonable accuracy early on in the drug development process in order to make scientifically sound decisions with regard to the presence of potentially active or toxic disproportionate metabolites. At this point, authentic metabolite standards are generally not available. Results: A new methodology is proposed for the estimation of metabolite concentrations in the absence of authentic standards. A reference sample containing radiolabeled metabolites of interest is produced by incubating the 14C-labeled drug in vitro, and mixed with a sample to be quantitated containing the unlabeled metabolites. The 12C/14C isotope ratio is measured with high-resolution ESI–MS for each metabolite, and used as a basis for quantitation of the cold metabolite based on the concentration of radioactive metabolite, determined from independent analysis of the radioactive sample with LC-radiochemical detection. The 14C-labeled metabolite serves as an isotopically labeled internal standard, which corrects for any variations in injection volume, sample preparation, MS intensity drift, matrix effects and/or saturation of electrospray ionization. The approach was validated by the analysis of solutions containing variable amounts of the analyte with a fixed amount of radioactive standard on a QToF Synapt® G2 MS system. The same methodology was also successfully applied to first-in-human plasma samples analyzed on a LTQ-Orbitrap®. Conclusion: The metabolite abundances obtained by 12C/14C isotope ratio measurements showed suitable accuracy and precision and were very close to those obtained with matrix mixing. The parent drug concentrations also corresponded well with the bioanalytical results obtained with a validated LC–MS/MS method.

Driving efficiency in a high-throughput metabolic stability assay through a generic high-resolution accurate mass method and automated data mining

Improving analytical throughput is the focus of many quantitative workflows being developed for early drug discovery. For drug candidate screening, it is common practice to use ultra-high performance liquid chromatography (U-HPLC) coupled with triple quadrupole mass spectrometry. This approach certainly results in short analytical run time; however, in assessing the true throughput, all aspects of the workflow needs to be considered, including instrument optimization and the necessity to re-run samples when information is missed. Here we describe a high-throughput metabolic stability assay with a simplified instrument set-up which significantly improves the overall assay efficiency. In addition, as the data is acquired in a non-biased manner, high information content of both the parent compound and metabolites is gathered at the same time to facilitate the decision of which compounds to proceed through the drug discovery pipeline.

Fragmentation pathways of drugs of abuse and their metabolites based on QTOF MS/MS and MS(E) accurate-mass spectra

A study of the fragmentation pathways of several classes of drugs of abuse (cannabinoids, ketamine, amphetamine and amphetamine-type stimulants (ATS), cocaine and opiates) and their related substances has been made. The knowledge of the fragmentation is highly useful for specific fragment selection or for recognition of related compounds when developing MS-based analytical methods for the trace-level determination of these compounds in complex matrices. In this work, accurate-mass spectra of selected compounds were obtained using liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, performing both MS/MS and MS(E) experiments. As regards fragmentation behavior, the mass spectra of both approaches were quite similar and were useful to study the fragmentation of the drugs investigated. Accurate-mass spectra of 37 drugs of abuse and related compounds, including metabolites and deuterated analogues, were studied in this work, and structures of fragment ions were proposed. The accurate-mass data obtained allowed to confirm structures and fragmentation pathways previously proposed based on nominal mass measurements, although new insights and structure proposals were achieved in some particular cases, especially for amphetamine and ATS, 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THC-COOH) and opiates.

From known knowns to known unknowns: predicting in vivo drug metabolites

'It is better to be useful than perfect'. This review attempts to critically cover and assess the currently available approaches and tools to answer the crucial question: Is it possible (and if it is, to what extent is it possible) to predict in vivo metabolites and their abundances on the basis of in vitro and preclinical animal studies? In preclinical drug development, it is possible to produce metabolite patterns from a candidate drug by virtual means (i.e., in silico models), but these are not yet validated. However, they may be useful to cover the potential range of metabolites. In vitro metabolite patterns and apparent relative abundances are produced by various in vitro systems employing tissue preparations (mainly liver) and in most cases using liquid chromatography-mass spectrometry analytical techniques for tentative identification. The pattern of the metabolites produced depends on the enzyme source; the most comprehensive source of drug-metabolizing enzymes is cultured human hepatocytes, followed by liver homogenate fortified with appropriate cofactors. For specific purposes, such as the identification of metabolizing enzyme(s), recombinant enzymes can be used. Metabolite data from animal in vitro and in vivo experiments, despite known species differences, may help pinpoint metabolites that are not apparently produced in in vitro human systems, or suggest alternative experimental approaches. The range of metabolites detected provides clues regarding the enzymes attacking the molecule under study. We also discuss established approaches to identify the major enzymes. The last question, regarding reliability and robustness of metabolite extrapolations from in vitro to in vivo, both qualitatively and quantitatively, cannot be easily answered. There are a number of examples in the literature suggesting that extrapolations are generally useful, but there are only a few systematic and comprehensive studies to validate in vitro-in vivo extrapolations. In conclusion, extrapolation from preclinical metabolite data to the in vivo situation is certainly useful, but it is not known to what extent.

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.

Recent advances in computational analysis of mass spectrometry for proteomic profiling

The proteome, defined as an organism's proteins and their actions, is a highly complex end-effector of molecular and cellular events. Differing amounts of proteins in a sample can be indicators of an individual's health status; thus, it is valuable to identify key proteins that serve as 'biomarkers' for diseases. Since the proteome cannot be simply inferred from the genome due to pre- and posttranslational modifications, a direct approach toward mapping the proteome must be taken. The difficulty in evaluating a large number of individual proteins has been eased with the development of high-throughput methods based on mass spectrometry (MS) of peptide or protein mixtures, bypassing the time-consuming, laborious process of protein purification. However, proteomic profiling by MS requires extensive computational analysis. This article describes key issues and recent advances in computational analysis of mass spectra for biomarker identification.

Urinary metabonomic study of lung cancer by a fully automatic hyphenated hydrophilic interaction/RPLC-MS system

Lung cancer is one of the most common and lethal cancers in the world. In this study, a home-devised hydrophilic interaction chromatography/RPLC-MS (HILIC/RPLC-MS) system was developed to study the urinary metabonomics of lung cancer patients. This system combined the orthogonal selectivity of HILIC and RPLC and could chromatographically reveal more comprehensive information of the urinary metabolites. Within a total analysis time of 50 min, we detected 577 polar metabolite ions on the first HILIC column and 261 apolar ones on the second RPLC column. In addition, an orthogonal signal correction partial least-squares discriminant analysis model was constructed to characterize differences between health and lung cancer cases. Eleven potential biomarkers, ten from HILIC column and one from the second RP column, were identified and all of these biomarkers were found upregulated in lung cancer patients. Overall, the results indicated that the developed HILIC/RPLC-MS system is a promising tool for metabonomic studies in revealing more information of highly complex samples.