Accelerated throughput metabolic route screening in early drug discovery using high-resolution liquid chromatography/quadrupole time-of-flight mass spectrometry and automated data analysis

The photo- and microbial degradation kinetics and pathways of sulfadoxine in seawater elucidated by liquid chromatography coupled with time-of-flight mass spectrometry

Sulfadoxine (SDX) is a broad-spectrum veterinary antibiotic, which was used alone for the treatment of various infections in the past, and detected ubiquitously in the aqueous environment. However, understanding SDX's photo- and microbial degradation within the environment, especially in marine matrixes, remains limited. This research hones in on SDX's degradation dynamics in seawater. Photodegradation emerges as the dominant process, surpassing microbial degradation in speed and efficiency. Notably, 90% of SDX is photo-degraded within 12 h, while only 52% is removed via microbial degradation over two weeks. Time-of-flight mass spectrometry provides high-resolution molecular mass information on degradation products. The molecular structures of hydrolysis, photo-, and microbial degradation products are deduced from accurate precursor and fragment ion masses, alongside an integrated data processing workflow. Six hydrolysis products arise from the treatment, and photodegradation and microbial degradation yield nine and eighteen products, respectively. Molecular insights from these products inform plausible degradation pathways involving hydrolysis, photodegradation, and microbial degradation. Processes like bond cleavage, methylation, hydroxylation, oxidation, reduction, and methoxylation are identified and associated with degradation. This study presents a comprehensive workflow for acquiring and processing degradation product data linked to emerging organic pollutants. Moreover, it contributes to our comprehension of the environmental fate of veterinary drugs in marine ecosystems.

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.

A Discovery Biotransformation Strategy: Combining In Silico Tools with High-Resolution Mass Spectrometry and Software-Assisted Data Analysis for High-Throughput Metabolism

Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increasedconfidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC-MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined.Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust UHPLC separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent MS/MS targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used.Confidence in the globally-aligned workflow is demonstrated with sixteen marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design-make-test cycle; thus improving the translatability of early in vitro metabolism data.

A Practitioner's Dilemma Mass Spectrometry-Based Annotation and Identification of Human Plasma and Urinary Polyphenol Metabolites

The practitioner's dilemma in metabolite assignment can be described as follows: For compound and metabolite identification, should we follow strict guidelines using authentic standards only, or should we accept uncertainties in structure assignment of compounds with the certainty of consequential errors. These uncertainties arise due to limitation of software and databases in combination with the complexity of the human body fluid samples. This article is protected by copyright. All rights reserved.

Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals

The presence of pharmaceutical compounds in the aquatic environment is a significant environmental health concern, which is exacerbated by recent evidence of the contribution of drug metabolites to the overall pharmaceutical load. In light of a recent report of the occurrence of metabolites of antiretroviral drugs (ARVDs) in wastewater, we investigate in the present work the occurrence of further ARVD metabolites in samples obtained from a domestic wastewater treatment plant in the Western Cape, South Africa. Pharmacokinetic data indicate that ARVDs are biotransformed into several positional isomeric metabolites, only two of which have been reported wastewater samples. Given the challenges associated with the separation and identification of isomeric species in complex wastewater samples, a method based on liquid chromatography hyphenated to ion mobility spectrometry-high resolution mass spectrometry (LC-IMS-HR-MS) was implemented. Gradient LC separation was achieved on a sub-2 µm reversed phase column, while the quadrupole-time-of-flight MS was operated in data independent acquisition (DIA) mode to increase spectral coverage of detected features. A mass defect filter (MDF) template was implemented to detect ARVD metabolites with known phase I and phase II mass shifts and fractional mass differences and to filter out potential interferents. IMS proved particularly useful in filtering the MS data for co-eluting species according to arrival time to provide cleaner mass spectra. This approach allowed us to confirm the presence of two known hydroxylated efavirenz and nevirapine metabolites using authentic standards, and to tentatively identify a carboxylate metabolite of abacavir previously reported in literature. Furthermore, three hydroxylated-, two sulphated and one glucuronidated metabolite of efavirenz, two hydroxylated metabolites of nevirapine and one hydroxylated metabolite of ritonavir were tentatively or putatively identified in wastewater samples for the first time. Assignment of the metabolites is discussed in terms of high resolution fragmentation data, while collisional cross section (CCS) values measured for the detected analytes are reported to facilitate further work in this area.

Locating Functionalized Gold Nanoparticles Using Electrical Impedance Tomography

OBJECTIVE

An imaging device to locate functionalized nanoparticles, whereby therapeutic agents are transported from the site of administration specifically to diseased tissues, remains a challenge for pharmaceutical research. Here, we show a new method based on electrical impedance tomography (EIT) to provide images of the location of gold nanoparticles (GNPs) and the excitation of GNPs with radio frequencies (RF) to change impedance permitting an estimation of their location in cell models Methods: We have created an imaging system using quantum cluster GNPs as a contrast agent, activated with RF fields to heat the functionalized GNPs, which causes a change in impedance in the surrounding region. This change is then identified with EIT.

RESULTS

Images of impedance changes of around 804% are obtained for a sample of citrate stabilized GNPs in a solution of phosphate-buffered saline. A second quantification was carried out using colorectal cancer cells incubated with culture media, and the internalization of GNPs into the colorectal cancer cells was undertaken to compare them with the EIT images. When the cells were incubated with functionalized GNPs, the change was more apparent, approximately 402%. This change was reflected in the EIT image as the cell area was more clearly identifiable from the rest of the area.

SIGNIFICANCE

EIT can be used as a new method to locate functionalized GNPs in human cells and help in the development of GNP-based drugs in humans to improve their efficacy in the future.

LC-MS based metabolomic approach for the efficient identification and relative quantification of bioavailable cocoa phenolics in human urine

This study was designed to investigate the rate and extent of urinary excretion of cocoa phenolic metabolites after human intake using metabolomics approach. In this context, a feeding trial was conducted where urine samples were collected at different time points over 48-h period. Several biomarkers were highlighted in LC-MS based chemometrics using principal component (PCA) and partial least squares discriminant analysis (PLS-DA), which revealed the presence of both epicatechin and gut microbial phenyl-γ-valerolactones (PVLs) conjugated analogues. The presences of these metabolites segregated and grouped the samples based on cocoa and non-cocoa ingestion. Furthermore, semi quantification of major bioavailable metabolites was performed to determine the interindividual differences and assess the relative bioavailability of cocoa compounds in the human body. Our approach presented here is unique in displaying a combination of LC-MS based chemometrics visualization strategies, which revealed and identified significant biomarkers that could reduce the problems associated with data screening complexity.

Automatic Identification of Lansoprazole Degradants under Stress Conditions by LC-HRMS with MassChemSite and WebChembase

Stress testing is one of the most important parts of the drug development process, helping to foresee stability problems and to identify degradation products. One of the processes involving stress testing is represented by forced degradation studies, which can predict the impact of certain conditions of pH, moisture, heat, or other negative effects due to transportation or packaging issues on drug potency and purity, ensuring patient safety. Regulatory agencies have been working on a standardization of laboratory procedures since the past two decades. One of the results of those years of intensive research is the International Conference on Harmonization (ICH) guidelines, which clearly define which forced degradation studies should be performed on new drugs, which become a routine work in pharmaceutical laboratories. Since used techniques based on high-performance liquid chromatography coupled with high-resolution mass spectrometry have been developed years ago and are now mastered by pharmaceutical scientists, automation of data analysis, and thus data processing, is becoming a hot topic nowadays. In this work, we present MassChemSite and WebChembase as a tandem to automatize the routine analysis studies without missing information quality, using as a case study the degradation of lansoprazole under acidic, oxidative, basic, and neutral stress conditions.

Identification of the major metabolites of (R)-salbutamol in human urine, plasma and feces using ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

(R)-Salbutamol is a selective β2-adrenoreceptor agonist, which produces a short-acting bronchodilator effect and is widely used for the treatment of respiratory diseases in humans. Drug metabolism and identification of the metabolites play an essential role in the evaluation of the overall efficacy and safety of the drugs in clinical practices. There are few reports on the identification of major metabolites of (R)-salbutamol in humans, and the number of identified metabolites is very limited. In this research, a method of ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was developed for the discovery and identification of (R)-salbutamol and its major metabolites in human biological samples. Totally, twelve metabolites of (R)-salbutamol were found and identified and all the metabolites could be found in urine, one metabolite in plasma and two metabolites in feces. Among all the metabolites, eight metabolites have never been reported before. The results indicated that (R)-salbutamol was mainly metabolized through isomerization, oxidation, reduction, glucuronidation, and sulfation pathways in vivo. The possible metabolic pathways of (R)-salbutamol were subsequently presented in this study, which contribute to a better understanding of the metabolism of (R)-salbutamol in humans.

A tutorial in small molecule identification via electrospray ionization-mass spectrometry: The practical art of structural elucidation

The identification of unknown molecules has been one of the cornerstone applications of mass spectrometry for decades. This tutorial reviews the basics of the interpretation of electrospray ionization-based MS and MS/MS spectra in order to identify small-molecule analytes (typically below 2000 Da). Most of what is discussed in this tutorial also applies to other atmospheric pressure ionization methods like atmospheric pressure chemical/photoionization. We focus primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds, rather than describing strategies for large-scale identification in complex samples. We critically discuss topics like the detection of protonated and deprotonated ions ([M + H]+ and [M - H]- ) as well as other adduct ions, the determination of the molecular formula, and provide some basic rules on the interpretation of product ion spectra. Our tutorial focuses primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds (eg, contaminants in chemical production, pharmacological alteration of drugs), rather than describing strategies for large-scale identification in complex samples. This tutorial also discusses strategies to obtain useful orthogonal information (UV/Vis, H/D exchange, chemical derivatization, etc) and offers an overview of the different informatics tools and approaches that can be used for structural elucidation of small molecules. It is primarily intended for beginning mass spectrometrists and researchers from other mass spectrometry sub-disciplines that want to get acquainted with structural elucidation are interested in some practical tips and tricks.

Systematic study on metabolism and activity evaluation of Radix Scutellaria extract in rat plasma using UHPLC with quadrupole time-of-flight mass spectrometry and microdialysis intensity-fading mass spectrometry

Radix Scutellaria is a widely used traditional Chinese medicine in the treatment of various diseases. However, the activities of the absorbed components and metabolites of its main flavones in rat plasma need further investigation. In this study, a systematic method based on ultra-high performance liquid chromatography with quadruple time-of-flight mass spectrometry was developed to speculate the absorbed components and metabolites of the main flavonoids in Radix Scutellaria extract in rat plasma sample after oral administration of the extract. Twelve compounds, including four prototype components and eight metabolites, were confirmed in drug-containing plasma. In these metabolites, five were originally detected in rat plasma. The possible metabolic pathways of these polyhydroxy flavones in vivo were described and clarified. Microdialysis with intensity-fading mass spectrometry was originally employed to investigate the binding affinities of the absorbed components and metabolites with α-glucosidase. The order of their binding affinities was P4 > P3 > P2 > P1≥M5 > M3 > M1. The research result is helpful to deepen the understanding of the absorbed components and metabolic pathways of main flavones from Radix Scutellaria, and provide a new approach to screen potential inhibitors from in vivo components originated from Chinese herb.

Identification of rotundic acid metabolites after oral administration to rats and comparison with the biotransformation by Syncephalastrum racemosum AS 3.264

The objective of this study was to identify the metabolites of rotundic acid after oral administration to rats and compare the similarities with its biotransformation by Syncephalastrum racemosum AS 3.264 using ultra-high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry. A total of fourteen metabolites were determined based on the mass spectrometry and chromatographic behaviors, among which eleven (M1-M3, M7-M14) and six (M2, M4-M8) metabolites were identified in rats and S. racemosum, respectively. Three identical metabolites (M2, M7 and M8) were found in rats and S. racemosum, indicating that there were metabolic similarities. Moreover, to confirm the results of mass spectrometry, three (M2, M4 and M7) metabolites were obtained by the means of amplifying incubation and their structures were determined by various spectroscopic analyses, and M4 was proved to be a previously undescribed compound. This results showed that in vitro assisted preparation by microbial transformation is a feasible and effective method of obtaining metabolites which are in low amounts and difficult to be prepared in vivo.

In vivo drug metabolite identification in preclinical ADME studies by means of UPLC/TWIMS/high resolution-QTOF MS(E) and control comparison: cost and benefit of vehicle-dosed control samples

1. Liquid chromatography (LC)-high resolution mass spectrometry (HRMS) techniques proved to be well suited for the identification of predicted and unexpected drug metabolites in complex biological matrices. 2. To efficiently discriminate between drug-related and endogenous matrix compounds, however, sophisticated postacquisition data mining tools, such as control comparison techniques are needed. For preclinical absorption, distribution, metabolism and excretion (ADME) studies that usually lack a placebo-dosed control group, the question arises how high-quality control data can be yielded using only a minimum number of control animals. 3. In the present study, the combination of LC-traveling wave ion mobility separation (TWIMS)-HRMS(E) and multivariate data analysis was used to study the polymer patterns of the frequently used formulation constituents polyethylene glycol 400 and polysorbate 80 in rat plasma and urine after oral and intravenous administration, respectively. 4. Complex peak patterns of both constituents were identified underlining the general importance of a vehicle-dosed control group in ADME studies for control comparison. Furthermore, the detailed analysis of administration route, blood sampling time and gender influences on both vehicle peak pattern as well as endogenous matrix background revealed that high-quality control data is obtained when (i) control animals receive an intravenous dose of the vehicle, (ii) the blood sampling time point is the same for analyte and control sample and (iii) analyte and control samples of the same gender are compared.

UPLC/Q-TOF-MS analysis of iridoid glycosides and metabolites in rat plasma after oral administration of Paederia scandens extracts

A rapid and validated UPLC-MS method was developed for investigating the absorbed components of Paederia scandens (Lour.) Merrill (P. scandensy) in rat plasma. The bioactive constituents in plasma samples from rats administrated orally with P. scandens extract were analyzed by Ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Four prototype compounds were identified in rat serum as potential bioactive components of P. scandens by comparing their retention times and mass spectrometry data or by mass spectrometry analysis and retrieving the reference literatures. Glucuronidation after deglycosylation was the major metabolic pathway for the iridoid glycosides in P. scandens. These results showed that the methods had high sensitivity and resolution and were suitable for identifying the bioactive constituents in plasma after oral administration of P. scandens. providing helpful chemical information for further pharmacological and mechanistic researched on the P. scandens.

Enhanced Mass Defect Filtering To Simplify and Classify Complex Mixtures of Lignin Degradation Products

High resolution mass spectrometry was utilized to study the highly complex product mixtures resulting from electrochemical breakdown of lignin. As most of the chemical structures of the degradation products were unknown, enhanced mass defect filtering techniques were implemented to simplify the characterization of the mixtures. It was shown that the implemented ionization techniques had a major impact on the range of detectable breakdown products, with atmospheric pressure photoionization in negative ionization mode providing the widest coverage in our experiments. Different modified Kendrick mass plots were used as a basis for mass defect filtering, where Kendrick mass defect and the mass defect of the lignin-specific guaiacol (C7H7O2) monomeric unit were utilized, readily allowing class assignments independent of the oligomeric state of the product. The enhanced mass defect filtering strategy therefore provided rapid characterization of the sample composition. In addition, the structural similarities between the compounds within a degradation sequence were determined by comparison to a tentatively identified product of this compound series. In general, our analyses revealed that primarily breakdown products with low oxygen content were formed under electrochemical conditions using protic ionic liquids as solvent for lignin.

A Simple, Rapid and Reliable Method to Determine Imipramine and Desipramine in Mouse Serum Using Ultra-High-Performance Liquid Chromatography-Quadrupole-Time-of-Flight Mass Spectrometry

A rapid and sensitive ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometric (UHPLC-Q-TOF-MS) method was developed for quantification of imipramine, one of the most widely used tricyclic antidepressants, and desipramine, an active metabolite of imipramine, in mouse serum. The developed method included a simple protein precipitation with acetonitrile in 50 μL of serum and analyte separation on an Acquity UPLC BEH C18 column using a gradient elution of acetonitrile with 0.1% formic acid and 20 mM ammonium formate. As a result, the entire analysis time was <20 min including the sample preparation and the LC-MS analysis. The limit of quantification was 5.0 ng mL(-1) for both imipramine and desipramine, and calibration curves were linear over the concentration range of 5.0-1,000.0 and 5.0-250.0 ng mL(-1) for imipramine and desipramine, respectively. Intraday precisions at three levels were 2.2-3.6 and 1.7-4.2% for imipramine and desipramine, respectively, whereas interday precisions were 2.6-5.0 and 2.0-8.4% for imipramine and desipramine, respectively. Accuracy ranged between 93.6 and 106.6% for imipramine and 94.1 and 106.4% for desipramine. Absolute recovery was 96.0-97.6% for imipramine and 87.0-99.5% for desipramine. Finally, the described method was applied to mice administered with imipramine, demonstrating the suitability for quantification of imipramine and desipramine for therapeutic drug monitoring or bioequivalence studies.

UPLC-Q-TOF/MS-based screening and identification of the main flavonoids and their metabolites in rat bile, urine and feces after oral administration of Scutellaria baicalensis extract

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese Medicines (TCMs) are increasingly used in combination with Western medicine. Scutellaria baicalensis Georgi (Lamiaceae) is a widely used TCM in treating various diseases. However, the in vivo metabolism of its main bioactive flavonoids, baicalin, baicalein, wogonoside and wogonin, needs further study.

MATERIALS AND METHODS

A systematic method based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technique combined with Metabolynx(TM) software was developed to speculate the metabolites and excretion profiles of the main flavonoids in S. baicalensis extract in rats bile, urine and feces samples after oral administration of the extract.

RESULTS

Four parent components and a total of 15 metabolites were tentatively detected in vivo. All metabolites were detected including sulfate and glucuronide conjugates, hydroxylated, methylated, acetylated and deoxygenated products. Twelve metabolites were from the rat urine, five from the feces and two from the bile. Among them, several products were reported firstly.

CONCLUSION

The research provided useful information for further study of the pharmacology and mechanism of action of S. baicalensis extract in vivo and a proposed method which could develop an integrated template approach to analyze screening and identification of biological samples after oral administration of TCMs.

Integration of microfluidic LC with HRMS for the analysis of analytes in biofluids: past, present and future

Capillary LC (cLC) coupled to MS has the potential to improve detection limits, address limited sample volumes and allow multiple analyses from one sample. This is particularly attractive in areas where ultrahigh assay sensitivity, low limits of detection and small sample volumes are becoming commonplace. However, implementation of cLC–MS in the bioanalytical–drug metabolism area had been hampered by the lack of commercial instrumentation and the need for experts to operate the system. Recent advances in microfabricated devices such as chip-cube and ion-key technologies offer the potential for true implementation of cLC in the modern laboratory including the benefits of the combination of this type of separation with high-resolution MS.

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction

Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Identification of xenobiotic metabolites from biological fluids using flow injection analysis high-resolution mass spectrometry and post-acquisition data filtering

RATIONALE

Concern for public health entails the need to evaluate the degree of exposure of population to toxicants. To do this, robust high-throughput approaches are required to be able to perform a large number of analyses in cohort studies. In this study, a data-filtering procedure was applied to mass spectral data acquired by direct analysis of biological fluids leading to rapid detection of metabolites in a model xenobiotic system.

METHODS

Flow injection analysis (FIA) coupled to negative electrospray ionization (ESI)-LTQ Orbitrap Fourier transform mass spectrometry was used to directly analyze urine of rats treated with vinclozolin. Tandem mass spectrometry (MS/MS) experiments were subsequently performed for confirmation of a new metabolite structure. The isotope filtering based on the difference between accurate masses of (35)Cl and (37)Cl was applied to the raw data for the specific detection of ions containing at least one chlorine atom.

RESULTS

Seven metabolites of vinclozolin were manually identified thanks to the characteristic isotope pattern of dichlorinated compounds. A new metabolite of vinclozolin was detected for the first time and identified as a sulfate conjugate. The application of an isotope-filtering procedure allowed the selective extraction of pertinent signals from the data. The processed mass spectrum was greatly simplified, significantly facilitating the detection of the seven metabolites previously identified.

CONCLUSIONS

The use of FIA-HRMS in combination with dedicated bio-informatics data processing is shown to be an efficient approach for the rapid detection of metabolites in biological fluids. This is a very promising high-throughput approach for rapid characterization of the exposure status to xenobiotics.

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

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

Identification of metabolites of Radix Paeoniae Alba extract in rat bile, plasma and urine by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC–Q-TOF/MS) was developed to identify the absorbed parent components and metabolites in rat bile, plasma and urine after oral administration of Radix Paeoniae Alba extract (RPAE). A total of 65 compounds were detected in rat bile, plasma and urine samples, including 11 parent compounds and 54 metabolites. The results indicated that glucuronidation, hydroxylation and methylation were the major metabolic pathways of the components of RPAE. Furthermore, the results of this work demonstrated that UPLC–Q-TOF/MS combined with MetaboLynx^™ software and mass defect filtering (MDF) could provide unique high throughput capabilities for drug metabolism study, with excellent MS mass accuracy and enhanced MS^E data acquisition. With the MS^E technique, both precursor and fragment mass spectra can be simultaneously acquired by alternating between high and low collision energy during a single chromatographic run.

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.

LC-MS-based Metabolomics of Xenobiotic-induced Toxicities

Xenobiotic exposure, especially high-dose or repeated exposure of xenobiotics, can elicit detrimental effects on biological systems through diverse mechanisms. Changes in metabolic systems, including formation of reactive metabolites and disruption of endogenous metabolism, are not only the common consequences of toxic xenobiotic exposure, but in many cases are the major causes behind development of xenobiotic-induced toxicities (XIT). Therefore, examining the metabolic events associated with XIT generates mechanistic insights into the initiation and progression of XIT, and provides guidance for prevention and treatment. Traditional bioanalytical platforms that target only a few suspected metabolites are capable of validating the expected outcomes of xenobiotic exposure. However, these approaches lack the capacity to define global changes and to identify unexpected events in the metabolic system. Recent developments in high-throughput metabolomics have dramatically expanded the scope and potential of metabolite analysis. Among all analytical techniques adopted for metabolomics, liquid chromatography-mass spectrometry (LC-MS) has been most widely used for metabolomic investigations of XIT due to its versatility and sensitivity in metabolite analysis. In this review, technical platform of LC-MS-based metabolomics, including experimental model, sample preparation, instrumentation, and data analysis, are discussed. Applications of LC-MS-based metabolomics in exploratory and hypothesis-driven investigations of XIT are illustrated by case studies of xenobiotic metabolism and endogenous metabolism associated with xenobiotic exposure.

Profiling of hepatic clearance pathways of Pittsburgh compound B and human liver cytochrome p450 phenotyping

Background

¹¹C-PiB has been developed as a positron-emission tomography (PET) ligand for evaluating fibrillar β-amyloid (Aβ) in the human brain. The ligand is rapidly metabolized, with approximately 10% of intact tracer remaining 30 min after injection. When ¹¹C-PiB is used as a treatment endpoint in intervention studies for Alzheimer’s disease (AD), a concern is whether the clearance of the tracer changes from one scan to the next, increasing within subject variability in the PET signal. Subjects enrolled in AD trials may start or stop medications that inhibit or induce xenobiotic metabolizing enzymes such as the cytochrome P450 (CYP) isozymes.

Findings

We conducted CYP phenotyping in recombinantly expressed systems, and in human liver microsomes, to evaluate CYP isozyme contributions to the metabolism of PiB (carrier) and profiled microsomal and hepatocyte incubations for metabolites. The metabolism of PiB appears to be polyzymic, with direct conjugation via UDP-glucuronosyltransferases (UGTs) also occurring.

Conclusion

It is unlikely that CYP inhibition or induction will significantly influence the clearance of ¹¹C-PiB.

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.

Structures of the ozonolysis products and ozonolysis pathway of aflatoxin B1 in acetonitrile solution

The ozonolysis of aflatoxin B(1) (400 μg/mL) in acetonitrile solution was conducted with an ozone concentration of 6.28 mg/L at the flow rate of 60 mL/min for different times. The results showed that ozone was an effective detoxification agent because of its powerful oxidative role. Thin-layer chromatography and liquid chromatography-quadrupole time-of-flight mass spectra were applied to confirm and identify the ozonolysis products of aflatoxin B(1). A total of 13 products were identified, and 6 of them were main products. The structural identification of these products provided effective information for understanding the ozonolysis pathway of aflatoxin B(1). Two ozonolysis pathways were proposed on the basis of the accurate mass and molecular formulas of these product ions. Nine ozonolysis products came from the first oxidative pathway based on the Criegee mechanism, and the other four products were produced from the second pathway based on the oxidative and electrophilic reactions of ozone. According to the toxicity mechanism of aflatoxin B(1) to animals, the toxicity of aflatoxin B(1) was significantly reduced because of the disappearance of the double bond on the terminal furan ring or the lactone moiety on the benzene ring.

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

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

Is nontarget screening of emerging contaminants by LC-HRMS successful? A plea for compound libraries and computer tools

This review focuses on the possibilities and limits of nontarget screening of emerging contaminants, with emphasis on recent applications and developments in data evaluation and compound identification by liquid chromatography-high-resolution mass spectrometry (HRMS). The general workflow includes determination of the elemental composition from accurate mass, a further search for the molecular formula in compound libraries or general chemical databases, and a ranking of the proposed structures using further information, e.g., from mass spectrometry (MS) fragmentation and retention times. The success of nontarget screening is in some way limited to the preselection of relevant compounds from a large data set. Recently developed approaches show that statistical analysis in combination with suspect and nontarget screening are useful methods to preselect relevant compounds. Currently, the unequivocal identification of unknowns still requires information from an authentic standard which has to be measured or is already available in user-defined MS/MS reference databases or libraries containing HRMS spectral information and retention times. In this context, we discuss the advantages and future needs of publicly available MS and MS/MS reference databases and libraries which have mostly been created for the metabolomic field. A big step forward has been achieved with computer-based tools when no MS library or MS database entry is found for a compound. The numerous search results from a large chemical database can be condensed to only a few by in silico fragmentation. This has been demonstrated for selected compounds and metabolites in recent publications. Still, only very few compounds have been identified or tentatively identified in environmental samples by nontarget screening. The availability of comprehensive MS libraries with a focus on environmental contaminants would tremendously improve the situation.

Identifying metabolite ions of peptide drugs in the presence of an in vivo matrix background

Background: Peptides represent a growing class of potential drugs. Information on metabolic clearance can be valuable for peptide drug development but different challenges are encountered with the identification of peptide metabolites in comparison to the process used for small-molecule therapeutics. Results: Enfuvirtide was selected as a test compound and dosed intravenously at 2 mg/kg to rats. Plasma samples were collected and analyzed on two different quadrupole-TOF instruments in positive and negative ion modes. Different post-acquisition processing tools were evaluated to identify the metabolites of a peptide drug in the presence of an in vivo matrix. Charge state filtering and ion mobility extraction were applied to reduce the matrix background and combined with more comprehensive software tools generally used for large molecule analyses as well as tools designed for small-molecule metabolite identification work. Conclusion: Both ion mobility spectrometry and charge state filtration proved to be successful in extracting peptide ions and significantly reducing background signals. Both small- and large-molecule software tools contain specific capabilities that could be usefully combined in a single package for peptide metabolite identification.

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.

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.

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.

High-resolution chromatography/time-of-flight MSE with in silico data mining is an information-rich approach to reactive metabolite screening

Electrophilic reactive metabolite screening by liquid chromatography/mass spectrometry (LC/MS) is commonly performed during drug discovery and early-stage drug development. Accurate mass spectrometry has excellent utility in this application, but sophisticated data processing strategies are essential to extract useful information. Herein, a unified approach to glutathione (GSH) trapped reactive metabolite screening with high-resolution LC/TOF MS(E) analysis and drug-conjugate-specific in silico data processing was applied to rapid analysis of test compounds without the need for stable- or radio-isotope-labeled trapping agents. Accurate mass defect filtering (MDF) with a C-heteroatom dealkylation algorithm dynamic with mass range was compared to linear MDF and shown to minimize false positive results. MS(E) data-filtering, time-alignment and data mining post-acquisition enabled detection of 53 GSH conjugates overall formed from 5 drugs. Automated comparison of sample and control data in conjunction with the mass defect filter enabled detection of several conjugates that were not evident with mass defect filtering alone. High- and low-energy MS(E) data were time-aligned to generate in silico product ion spectra which were successfully applied to structural elucidation of detected GSH conjugates. Pseudo neutral loss and precursor ion chromatograms derived post-acquisition demonstrated 50.9% potential coverage, at best, of the detected conjugates by any individual precursor or neutral loss scan type. In contrast with commonly applied neutral loss and precursor-based techniques, the unified method has the advantage of applicability across different classes of GSH conjugates. The unified method was also successfully applied to cyanide trapping analysis and has potential for application to alternate trapping agents.

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.

Database searching for structural identification of metabolites in complex biofluids for mass spectrometry-based metabonomics

MS and HPLC are commonly used for compound characterization and obtaining structural information; in the field of metabonomics, these two analytical techniques are often combined to characterize unknown endogenous or exogenous metabolites present in complex biological samples. Since the structures of a majority of these metabolites are not actually identified, the result of most metabonomic studies is a list of m/z values and retention times. However, without knowing actual structures, the biological significance of these 'features' cannot be determined. The process of identifying the structures of unknown compounds can be time intensive, costly and frequently requires the use of multiple orthogonal analytical techniques - this laborious procedure seems insurmountable for the long lists of unknowns that must be identified for each study. In addition, the limited sample volume and the extremely low concentration of most endogenous analytes frequently make purification and identification by other instrumentation nearly impossible. This review is intended to explore the problems and progress with current tools that are available for MS-based structure identification for both endogenous and exogenous metabolites.

Peptide and protein drug analysis by MS: challenges and opportunities for the discovery environment

Straightforward assay development using MS has become commonplace in most modern pharmaceutical laboratories. In particular, MS is an invaluable tool in the discovery environment of this industry, making it possible to characterize the structures of target drugs and to screen large numbers of potential drug candidates in metabolism and pharmacokinetics studies, and much more. Furthermore, as drug portfolios expand to include biotherapeutic species, such as peptides and proteins, MS is there to meet any analytical challenges. In this article, general aspects of MS in the discovery environment are discussed, as well as what the future might hold.