Comparison of LC-NMR and conventional NMR for structure elucidation in drug metabolism studies

A compound post-column re-focusing approach in supercritical fluid chromatography

Supercritical-fluid chromatography (SFC) is regaining popularity in various fields of analytical chemistry owning to significant advances in instrumentation made in the past decade. However, due to the CO₂ based mobile phase and the high flow rates often employed, detection of trace amounts of analytes and coupling with certain detectors or other chromatography techniques are still difficult under many circumstances. In this study we propose a post-column re-focusing approach for SFC analysis to achieve not only signal enhancement in UV-Vis detection, but also actual concentration enhancement of the analyte. By heart-cutting and transporting a selected fraction from the SFC flow into a trapping column with a flushing solvent, re-focusing of the collected analytes can be achieved by re-mobilization with another solvent once the depressurized CO₂ is eliminated. By carefully selecting the trapping stationary phase and the two solvents, signal-enhancement ratios between 2.2 and 6.4 were realized for four representative compounds eluting with very different percentages of SFC modifier (methanol). The actual concentration enhancement was lower (ratios between 1.7 to 2.9), because the UV response of the analytes was found to differ significantly under SFC and LC conditions.

Advance in Methodology and Strategies To Unveil Metabolic Mechanisms of Pesticide Residues in Food Crops

Pesticide residues are a food safety concern. A good detection method is critical for rapid and accurate determination of pesticide metabolites in crops and studying metabolism. The pretreatment methods have mainly been ultrasonic extraction-solid-phase extraction and QuEChERS, while detection methods have been radio-chromatography, nuclear magnetic resonance, and mass spectrometry. This perspective briefed the progress of analytical methods used for studying pesticide transformation in crops over the past decade. With the combination of the characteristics of the pesticide molecular structure and the transformation principles of pesticides in crops, we presented specific methods for elucidating new metabolites and the approaches to identify metabolites using multi-high-resolution mass spectrometry.

Fractionation platform for target identification using off-line directed two-dimensional chromatography, mass spectrometry and nuclear magnetic resonance

The unambiguous identification of unknown compounds is of utmost importance in the field of metabolomics. However, current identification workflows often suffer from error-sensitive methodologies, which may lead to incorrect structure annotations of small molecules. Therefore, we have developed a comprehensive identification workflow including two highly complementary techniques, i.e. liquid chromatography (LC) combined with mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), and used it to identify five taste-related retention time and m/z features in soy sauce. An off-line directed two-dimensional separation was performed in order to purify the features prior to the identification. Fractions collected during the first dimension separation (reversed phase low pH) were evaluated for the presence of remaining impurities next to the features of interest. Based on the separation between the feature and impurities, the most orthogonal second dimension chromatography (hydrophilic interaction chromatography or reversed phase high pH) was selected for further purification. Unknown compounds down to tens of micromolar concentrations were tentatively annotated by MS and structurally confirmed by MS and NMR. The mass (0.4-4.2 μg) and purity of the isolated compounds were sufficient for the acquisition of one and two-dimensional NMR spectra. The use of a directed two-dimensional chromatography allowed for a fractionation that was tailored to each feature and remaining impurities. This makes the fractionation more widely applicable to different sample matrices than one-dimensional or fixed two-dimensional chromatography. Five proline-based 2,5-diketopiperazines were successfully identified in soy sauce. These cyclic dipeptides might contribute to taste by giving a bitter flavour or indirectly enhancing umami flavour.

The utility of nuclear magnetic resonance spectroscopy in assisted reproduction

Infertility affects approximately 15-20% of individuals of reproductive age worldwide. Over the last 40 years, assisted reproductive technology (ART) has helped millions of childless couples. However, ART is limited by a low success rate and risk of multiple gestations. Devising methods for selecting the best gamete or embryo that increases the ART success rate and prevention of multiple gestation has become one of the key goals in ART today. Special emphasis has been placed on the development of non-invasive approaches, which do not require perturbing the embryonic cells, as the current morphology-based embryo selection approach has shortcomings in predicting the implantation potential of embryos. An observed association between embryo metabolism and viability has prompted researchers to develop metabolomics-based biomarkers. Nuclear magnetic resonance (NMR) spectroscopy provides a non-invasive approach for the metabolic profiling of tissues, gametes and embryos, with the key advantage of having a minimal sample preparation procedure. Using NMR spectroscopy, biologically important molecules can be identified and quantified in intact cells, extracts or secretomes. This, in turn, helps to map out the active metabolic pathways in a system. The present review covers the contribution of NMR spectroscopy in assisted reproduction at various stages of the process.

Asymmetric dimethylarginine (ADMA) is identified as a potential biomarker of insulin resistance in skeletal muscle

To unravel metabolic determinats of insulin resistance, we performed a targeted metabolomics analysis in Korean Children-Adolescent Cohort Study (KoCAS, n = 430). Sixty-seven metabolites were associated with insulin resistance in adolescents and the association also found in an adult population (KoGES, n = 2,485). Functional interactions of metabolites with gene/proteins using biological pathway with insulin resistance were not identified biological significance and regulatory effects of asymmetric dimethylarginine (ADMA). However, ADMA showed a higher association with adolescent obesity (P < 0.001) and adult diabetes (P = 0.007) and decreased after obesity intervention program. Functional studies in cellular and mouse models demonstrated that an accumulation of ADMA is associated with the regulation of obesity-induced insulin resistance in skeletal muscle. ADMA treatment inhibited dimethylarginine-dimethylaminohydrolase (DDAH) activity and mRNA expression in insulin resistance muscle cell. Moreover, the treatment led to decrease of phosphorylation of insulin receptor (IR), AKT, and GLUT4 but increase of protein-tyrosine phosphatase 1B (PTP1B). Accordingly, increased ADMA significantly inhibited glucose uptake in myotube cell. We suggest that accumulation of ADMA is associated with modulation of insulin signaling and insulin resistance. ADMA might expand the possibilities of new therapeutic target for functional and clinical implications in the control of energy and metabolic homeostasis in humans.

Combination of UHPLC/Q-TOF-MS, NMR spectroscopy, and ECD calculation for screening and identification of reactive metabolites of gentiopicroside in humans

The metabolic investigation of natural products is a great challenge because of unpredictable metabolic pathways, little knowledge on metabolic effects, and lack of recommended analytical methodology. Herein, a combined strategy based on ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC/Q-TOF-MS), nuclear magnetic resonance (NMR) spectroscopy, and electronic circular dichroism (ECD) calculation was developed and employed for the human metabolism study of gentiopicroside (GPS), a naturally hepato-protective iridoid glycoside. The whole metabolic study consisted of three major procedures. First, an improved UHPLC/Q-TOF-MS method was used to separate and detect a total of 15 GPS metabolites that were obtained from urine samples (0 to 72 h) of 12 healthy male participants after a single 50-mg oral dose of GPS. Second, a developed "MS-NMR-MS" method was applied to accurately identify molecular structures of the observed metabolites. Finally, given that the associated stereochemistry may be a crucial factor of the metabolic activation, the absolute configuration of the reactive metabolites was revealed through chemical calculations. Based on the combined use, a pair of diastereoisomers (G05 and G06) were experimentally addressed as the bioreactive metabolites of GPS, and the stereochemical determination was completed. Whereas several novel metabolic transformations, occurring via oxidation, N-heterocyclization and glucuronidation after deglycosylation, were also observed. The results indicated that GPS has to undergo in vivo metabolism-based activation to generate reactive molecules capable of processing its hepato-protective activity.

Identification of crotonyl glycine in urine of sheep after 48 h road transport

Thousands of metabolites are excreted in urine, and potentially can be detected in NMR spectra. Currently, NMR spectral information for about one thousand metabolites has been deposited in publicly available sources, limiting the identification of chemical compounds that are potential biomarkers for clinical and subclinical applications. This study reports the identification of crotonyl glycine, one of the key metabolites detected by ¹H NMR as excreted in the urine of sheep after 48 h road transport and during the subsequent 72 h recovery period. This metabolite was important in separating the metabolic responses as expressed in the urine from animals undergoing shorter road transport treatments. At the time of the metabonomic analysis, the NMR signals from this metabolite were designated as unassigned as no match was found in public databases or the literature. Selected sheep urine samples containing the metabolite were resolved by reversed phase HPLC reducing the sample complexity. Subsequent ¹H NMR spectra of the collected fractions revealed that the unknown metabolite was present in a single HPLC fraction. High-resolution 1D and 2D ¹H NMR spectra of this fraction followed by mass determination of the parent ion and its fragments by nanoESI-TOF-MS/MS revealed the identity of the compound as crotonyl glycine (N-but-(E)-2-enoyl glycine). The HPLC fraction was subsequently spiked with synthetic crotonyl glycine which confirmed identification.

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure–activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein–ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.

NMR spectroscopy as a tool to close the gap on metabolite characterization under MIST

Withdrawals from the market due to unforeseen adverse events have triggered changes in the way therapeutics are discovered and developed. This has resulted in an emphasis on truly understanding the efficacy and toxicity profile of new chemical entities (NCE) and the contributions of their metabolites to on-target pharmacology and off-target receptor-mediated toxicology. Members of the pharmaceutical industry, scientific community and regulatory agencies have held dialogues with respect to metabolites in safety testing (MIST); and both the US FDA and International Conference on Harmonisation have issued guidances with respect to when and how to characterize metabolites for human safety testing. This review provides a brief overview of NMR spectroscopy as applied to the structure elucidation and quantification of drug metabolites within the drug discovery and development process. It covers advances in this technique, including cryogenic cooling of detection circuitry for enhanced sensitivity, hyphenated LC-NMR techniques, improved dynamic range through new solvent-suppression pulse sequences and quantitation. These applications add to the already diverse NMR toolkit and further anchor NMR as a technique that is directly applicable to meeting the requirements of MIST guidelines.

Approaches for the rapid identification of drug metabolites in early clinical studies

Understanding the metabolism of a novel drug candidate in drug discovery and drug development is as important today as it was 30 years ago. What has changed in this period is the technology available for proficient metabolite characterization from complex biological sources. High-efficiency chromatography, sensitive MS and information-rich NMR spectroscopy are approaches that are now commonplace in the modern laboratory. These advancements in analytical technology have led to unequivocal metabolite identification often being performed at the earliest opportunity, following the first dose to man. For this reason an alternative approach is to shift from predicting and extrapolating possible human metabolism from in silico and nonclinical sources, to actual characterization at steady state within early clinical trials. This review provides an overview of modern approaches for characterizing drug metabolites in these early clinical studies. Since much of this progress has come from technology development over the years, the review is concluded with a forward-looking perspective on how this progression may continue into the next decade.

Looking back through the MIST: a perspective of evolving strategies and key focus areas for metabolite safety analysis

The publication of the US FDA MIST guidance document in 2008 reignited the debate around the most appropriate strategies to underwrite metabolite safety for novel compounds. Whilst some organizations have suggested that the guidelines necessitate a paradigm shift to more thorough metabolite analysis during early development, an evaluation of historical practices shows that the principles of the guidelines have always largely underpinned metabolism studies within the pharmaceutical industry. Therefore, it is argued that existing practices, when coupled to appropriate emerging analytical tools and a case-by-case consideration of the relevance of the generated metabolism data in terms of structure, physicochemisty, abundance and activity, represent a fit-for-purpose approach to metabolite-safety assessments.

Metabolite quantitation: detector technology and MIST implications

HPLC detector technology has advanced dramatically over the past 20 years, with a range of highly sensitive and specific detectors becoming available. What is still missing from the bioanalyst’s armoury, however, is a highly sensitive detector that gives an equimolar response independent of the compound. This would allow for quantification of compounds without the requirement for a synthetic standard or a radiolabeled analogue. In particular, such a detector applied to metabolism studies would establish the relative significance of the various metabolic routes. The recently issued US FDA guidelines on metabolites in safety testing (MIST) focus on the relative quantitation of human metabolites being obtained as soon as feasible in the drug-development process. In this article, current detector technology is reviewed with respect to its potential for quantitation without authentic standards or a radiolabel and put in the context of the MIST guidelines. The potential for future developments are explored.