Metabolite identification by mass spectrometry: forty years of evolution

Recent advances in identifying and utilizing metabolites of selected doping agents in human sports drug testing

Probing for evidence of the administration of prohibited therapeutics, drugs and/or drug candidates as well as the use of methods of doping in doping control samples is a central assignment of anti-doping laboratories. In order to accomplish the desired analytical sensitivity, retrospectivity, and comprehensiveness, a considerable portion of anti-doping research has been invested into studying metabolic biotransformation and elimination profiles of doping agents. As these doping agents include lower molecular mass drugs such as e.g. stimulants and anabolic androgenic steroids, some of which further necessitate the differentiation of their natural/endogenous or xenobiotic origin, but also higher molecular mass substances such as e.g. insulins, growth hormone, or siRNA/anti-sense oligonucleotides, a variety of different strategies towards the identification of employable and informative metabolites have been developed. In this review, approaches supporting the identification, characterization, and implementation of metabolites exemplified by means of selected doping agents into routine doping controls are presented, and challenges as well as solutions reported and published between 2010 and 2020 are discussed.

Case Study 4: Application of Basic Enzyme Kinetics to Metabolism Studies-Real-Life Examples

An appreciation of enzyme kinetic principles can be applied in a number of drug metabolism applications. The concept for this chapter arose from a simple discussion on selecting appropriate time points to most efficiently assess metabolite profiles in a human Phase 1a clinical study (Subheading 4). By considering enzyme kinetics, a logical approach to the issue was derived. The dialog was an important learning opportunity for the participants in the discussion, and we have endeavored to capture this experience with other questions related to determination of K_m and V_max parameters, a consideration of the value of hepatocytes vs. liver microsomes, and enzyme inhibition parameters.

Phenolic Compounds in Chilean Mistletoe (Quintral, Tristerix tetrandus) Analyzed by UHPLC-Q/Orbitrap/MS/MS and Its Antioxidant Properties

Mass spectrometry has become a method of choice to characterize bioactive compounds in biological samples because of its sensitivity and selectivity. Hybrid ultra-HPLC hyphenated with Orbitrap mass analyzer is an innovative state of the art technology that allows fast and accurate metabolomic analyses. In this work the metabolites of a Chilean mistletoe endemic to the VIII region of Chile were investigated for the first time using UHPLC mass analysis (UHPLC-PDA-HESI-Orbitrap MSⁿ). The anthocyanins, together with the non-pigmented phenolics were fingerprinted and correlated with the antioxidant capacities measured by the bleaching of the DPPH radical, the ferric reducing antioxidant power (FRAP), the superoxide anion scavenging activity assay (SA), and total content of phenolics, flavonoids and anthocyanins measured by spectroscopic methods. Six anthocyanins were identified, and among them, the 3-O-glycosides of delphinidin and cyanidin were the major ones. In addition, several phenolic acids (including feruloylquinic acid, feruloyl glucose, chlorogenic acid) and several flavonols (luteolin, quercetin, apigenin, isorhamnetin and glycoside derivatives) were also identified. The mistletoe leaves showed the highest antioxidant activity as measured by the DPPH radical bleaching, ferric reducing antioxidant power and superoxide anion scavenging activity tests (13.38 ± 0.47 µg/mL, 125.32 ± 5.96 µmolTE/g DW and 84.06 ± 4.59 at 100 µg/mL, respectively).

High-resolution twin-ion metabolite extraction (HiTIME) mass spectrometry: nontargeted detection of unknown drug metabolites by isotope labeling, liquid chromatography mass spectrometry, and automated high-performance computing

The metabolic fate of a compound can often determine the success of a new drug lead. Thus, significant effort is directed toward identifying the metabolites formed from a given molecule. Here, an automated and nontargeted procedure is introduced for detecting drug metabolites without authentic metabolite standards via the use of stable isotope labeling, liquid chromatography mass spectrometry (LC/MS), and high-performance computing. LC/MS of blood plasma extracts from rats that were administered a 1:1 mixture of acetaminophen (APAP) and (13)C6-APAP resulted in mass spectra that contained "twin" ions for drug metabolites that were not detected in control spectra (i.e., no APAP administered). Because of the development of a program (high-resolution twin-ion metabolite extraction; HiTIME) that can identify twin-ions in high-resolution mass spectra without centroiding (i.e., reduction of mass spectral peaks to single data points), 9 doublets corresponding to APAP metabolites were identified. This is nearly twice that obtained by use of existing programs that make use of centroiding to reduce computational cost under these conditions with a quadrupole time-of-flight mass spectrometer. By a manual search for all reported APAP metabolite ions, no additional twin-ion signals were assigned. These data indicate that all the major metabolites of APAP and multiple low-abundance metabolites (e.g., acetaminophen hydroxy- and methoxysulfate) that are rarely reported were detected. This methodology can be used to detect drug metabolites without prior knowledge of their identity. HiTIME is freely available from https://github.com/bjpop/HiTIME .

Phenolic profiling of the South American "Baylahuen" tea (Haplopappus spp., Asteraceae) by HPLC-DAD-ESI-MS

The aerial parts of several Haplopappus species (Asteraceae), known under the common name "baylahuen", are used as herbal teas in Chile and Argentina. In Chile, "baylahuen" comprises H. multifolius, H. taeda, H. baylahuen and H. rigidus. Little is known about the chemical identity of the infusion constituents in spite of widespread consumption. The aim of the present work was the characterization of phenolics occurring in the infusions and methanol extracts of "baylahuen" by HPLC-DAD-ESI-MS. A simple HPLC-DAD-ESI-MS method was developed for the fast identification and differentiation of Haplopappus spp. used as a tea source, based on the phenolics from the tea and methanol extracts. Some 27 phenolics were tentatively identified in the infusions and methanol extract, including 10 caffeoyl quinic and feruloyl quinic acid derivatives and 17 flavonoids. The HPLC patterns of the Haplopappus tea and methanol extract allow a clear differentiation at the species level. The occurrence of hydroxycinnamic acid derivatives and flavonoids can explain the reputed nutraceutical and health beneficial properties of this herbal tea.

Biotransformation in vitro: An essential consideration in the quantitative in vitro-to-in vivo extrapolation (QIVIVE) of toxicity data

Early consideration of the multiplicity of factors that govern the biological fate of foreign compounds in living systems is a necessary prerequisite for the quantitative in vitro-in vivo extrapolation (QIVIVE) of toxicity data. Substantial technological advances in in vitro methodologies have facilitated the study of in vitro metabolism and the further use of such data for in vivo prediction. However, extrapolation to in vivo with a comfortable degree of confidence, requires continuous progress in the field to address challenges such as e.g., in vitro evaluation of chemical-chemical interactions, accounting for individual variability but also analytical challenges for ensuring sensitive measurement technologies. This paper discusses the current status of in vitro metabolism studies for QIVIVE extrapolation, serving today's hazard and risk assessment needs. A short overview of the methodologies for in vitro metabolism studies is given. Furthermore, recommendations for priority research and other activities are provided to ensure further widespread uptake of in vitro metabolism methods in 21st century toxicology. The need for more streamlined and explicitly described integrated approaches to reflect the physiology and the related dynamic and kinetic processes of the human body is highlighted i.e., using in vitro data in combination with in silico approaches.

Case study 3. Application of basic enzyme kinetics to metabolism studies: real-life examples

An appreciation of the principles of enzyme kinetics can be applied in a number of drug metabolism applications. The concept for this chapter arose from a simple discussion on selecting appropriate time points to most efficiently assess metabolite profiles in a human Phase 1a clinical study (Subheading 4). By considering enzyme kinetics, a logical approach to the issue was derived. The dialog was an important learning opportunity for the participants in the discussion, and we have endeavored to capture this experience with other questions related to determination of K m and V max parameters, a consideration of the value of hepatocytes versus liver microsomes and enzyme inhibition parameters.

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

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

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.

Biotransformation and biocatalysis: roles and applications in the discovery of antimalarials

Several strategies to discover new antimalarials have been proposed to augment and complement the conventional drug-discovery paradigm. One approach, which has not yet been fully exploited, is the use of drug biotransformation to identify new active molecules. This concept rests on the use of the biotransformation of drugs to their pharmacologically active metabolites. This approach has been used successfully in human chemotherapy, with the discovery and development of several metabolite-based drugs. This review looks at the contribution that biotransformations can play in antimalarial drug discovery.

PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

Background

Gas chromatography–mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines.

Results

PyMS comprises a library of functions for processing of instrument GC-MS data developed in Python. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. A novel common ion single quantitation algorithm allows automated, accurate quantitation of GC-MS electron impact (EI) fragmentation spectra when a large number of experiments are being analyzed. PyMS implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments. A set of specifically designed experiments was performed in-house and used to comparatively evaluate the performance of PyMS and three widely used software packages for GC-MS data processing (AMDIS, AnalyzerPro, and XCMS).

Conclusions

PyMS is a novel software package for the processing of raw GC-MS data, particularly suitable for scripting of customized processing pipelines and for data processing in batch mode. PyMS provides limited graphical capabilities and can be used both for routine data processing and interactive/exploratory data analysis. In real-life GC-MS data processing scenarios PyMS performs as well or better than leading software packages. We demonstrate data processing scenarios simple to implement in PyMS, yet difficult to achieve with many conventional GC-MS data processing software. Automated sample processing and quantitation with PyMS can provide substantial time savings compared to more traditional interactive software systems that tightly integrate data processing with the graphical user interface.

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.