Combination Of Nuclear Magnetic Resonance Spectroscopy Research Articles

Discriminating the origin of fish from closely related water bodies by combining NMR spectroscopy with statistical analysis and machine learning

Pikeperch, perch and bream are among the most traded and valued fish species in North-Eastern Europe. Therefore, it is necessary to be able to distinguish fish from different lakes and coastal sea regions to ensure a good traceability of products in the fish market and to protect both consumers and fish stocks. Untargeted metabolomics using nuclear magnetic resonance (NMR) spectroscopy is a suitable tool for this purpose. It is an established method for determining various properties of biological and living systems, such as health, origin, type, etc. Statistical methods including principal component analysis (PCA) and linear discriminant analysis (LDA) are typically applied to NMR data to correlate spectra with a particular research question.Herein we examine fish from three closely related water bodies and demonstrate that reliable determination of the water body that a particular fish originates from by traditional statistical analysis (PCA and LDA) of fish NMR spectra is not possible. In contrast, determining the fish species is possible. We proceed to show that machine learning methods perform better and that a combination of statistical analysis (LDA) and random forest (RF), a supervised machine learning technique, allows reliable determination of the originating water body, while being also tolerant to seasonal variations. This is an improvement over prior work, which has dealt with more clearly distinguished origins of fish. Exceptional accuracy was achieved in correctly assigning fish to their origin even in a scenario where two of the water bodies are connected by a river through which the fish are known to migrate. Since determining the origin of fish is important in environmental protection, we recommend following up this approach and using it as the basis of a robust tool for environmental protection and other monitoring purposes.

NMR Analysis Suggests Synergy between the RRM2 and the Carboxy-Terminal Segment of Human La Protein in the Recognition and Interaction with HCV IRES.

The La protein (lupus antigen) is a ubiquitous RNA-binding protein found in all human cells. It is mainly localized in the nucleus, associates with all RNA polymerase III (Pol III) transcripts, as the first factor they interact with, and modulates subsequent processing events. Export of La to the cytoplasm has been reported to stimulate the decoding of specific cellular and viral mRNAs through IRES-dependent (Internal ribosome entry site) binding and translation. Using NMR (Nuclear Magnetic Resonance) spectroscopy, we provide atomic-level-resolution structural insights on the dynamical properties of human La (hLa) protein in solution. Moreover, using a combination of NMR spectroscopy and isothermal titration calorimetry (ITC), we provide evidence about the role and ligand specificity of the C-terminal domain of the La protein (RRM2 and C-terminal region) that could mediate the recognition of HCV-IRES.

Abstract 2322: Multiplatform metabolomics studies of human cancers with NMR and mass spectrometry imaging

Abstract Unfortunately, at present, there is no single technique that possesses all the characteristics needed to be considered an ideal global metabolite profiling tool. Thus, the use of multiple analytical platforms, such as combining the strengths of Mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), for metabolic profiling can maximize coverage and generate more global metabolomic profiles. In this study, we demonstrate the utilities of the combined NMR and MSI multiplatform in our metabolomics results on human prostate and lung cancers. Statistical data on the natural history of prostate cancer (PCa) show that >70% of patients diagnosed by PSA screening will likely experience indolent disease with little impact on well-being. For about 17% of newly PSA-diagnosed patients, however, aggressive PCa proliferation ensues, truncating life expectancy. At present, no reliable clinical test can differentiate between these two groups. Using HRMAS 1HNMR followed by quantitative histology, we showed statistically significant correlations between concentrations of Spm and the amount of histologically-benign epithelial (Hb Epi) prostatic cells and glands in human cancerous prostates. However, as above discussed that using HRMAS NMR alone we cannot prove that Spm was indeed generated or resided in the Hb Epi cells. Nevertheless, using MALDI MSI, we were able to locate Spm (m/z: 203.223 ± 0.001Da) onto Hb Epi, where spermine on the PCa lesions appeared below detection limits. From these maps, for the first time, we could visualize and confirm the differential localizations of Spm in prostates. This proof of Sym relationship to prostate pathologies and its proposed PCa inhibitory effects may support further studies that are critical in differentiating aggressive from indolent PCa for disease evaluations and patient personalized treatment strategies. To search for such screening metabolomics biomarkers in lung cancer, we used HRMAS NMR to analyze 93 pairs of human LuCa tissue and serum samples, and 29 healthy human sera. A number of potential metabolite candidates capable to differentiate LuCa characteristics were identified, including glutamate, lipids, alanine, glycerylphosphorylcholine, glutamine, phosphorylcholine, etc. This list can be further expanded by analyzing metabolite composition in the serum of cancer patients and control healthy subjects using LC-MS, which offers a dramatic increase in sensitivity compared to HRMAS NMR and, therefore, is better suited for the biomarker discovery. In addition to acquiring high-resolution mass data, the high data acquisition rate allows the fragment ion mass spectra (MS/MS) to be generated for the most abundant ionic species in each chromatographic peak. This feature allows specific classes of tumor-attenuated metabolites to be identified based on the presence of unique structurally diagnostic fragment ions in MS/MS spectra. Citation Format: Leo L. Cheng, Anya B. Zhong, Isabella H. Muti, Stephen J. Eyles, Richard W. Vachet, Sylwia A. Stopka, Kristen N. Sikora, Cedric E. Bobst, Jeffrey N. Agar, Mari A. Mino-Kenudson, Chin-Lee Wu, David C. Christiani, Igor A. Kaltashov, Nathalie Y. Agar. Multiplatform metabolomics studies of human cancers with NMR and mass spectrometry imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2322.

Composition analysis of natural gas by combined benchtop NMR spectroscopy and mechanistical multivariate regression

Natural gas is an essential energy source for a large variety of applications in today’s society. Forecasts predict that it will also play a vital role in decarbonizing the energy sector. The price of natural gas is determined by its calorific value, which depends on its composition. Thus, the accurate composition quantification of natural gas is essential to both producers and consumers. In this context, proton Nuclear Magnetic Resonance (NMR) spectra of pure and mixed hydrocarbon gases have been studied with a desktop spectrometer in the range between 1 to 200 bar. Although spectral linewidth, chemical shift, and relaxation times depend on pressure and composition, the hydrocarbon concentrations of binary, ternary, and an eleven-component gas mixture could be quantified by spectral analysis using Spectral Hard Modeling, a mechanistical multivariate regression. Concentrations determined for the main components at 200 bar by NMR deviated by 0.1 to 0.18 mol% from Gas Chromatography values, leading to a difference in calorific values of only 0.15%. The presented results demonstrate that benchtop NMR combined with chemometrics can quantify complex hydrocarbon-gas mixtures reliably and quickly.

Halogenation at the Phenylalanine Residue of Monomethyl Auristatin F Leads to a Favorable cis/trans Equilibrium and Retained Cytotoxicity.

Halogenation can be utilized for the purposes of labeling and molecular imaging, providing a means to, e.g., follow drug distribution in an organism through positron emission tomography (PET) or study the molecular recognition events unfolding by nuclear magnetic resonance (NMR) spectroscopy. For cancer therapeutics, where often highly toxic substances are employed, it is of importance to be able to track the distribution of the drugs and their metabolites in order to ensure minimal side effects. Labeling should ideally have a negligible disruptive effect on the efficacy of a given drug. Using a combination of NMR spectroscopy and cytotoxicity assays, we identify a site susceptible to halogenation in monomethyl auristatin F (MMAF), a widely used cytotoxic agent in the antibody–drug conjugate (ADC) family of cancer drugs, and study the effects of fluorination and chlorination on the physiological solution structure of the auristatins and their cytotoxicity. We find that the cytotoxicity of the parent drug is retained, while the conformational equilibrium is shifted significantly toward the biologically active trans isomer, simultaneously decreasing the concentration of the inactive and potentially disruptive cis isomer by up to 50%. Our results may serve as a base for the future assembly of a multifunctional toolkit for the assessment of linker technologies and exploring bystander effects from the warhead perspective in auristatin-derived ADCs.

NMR spectroscopy in wine authentication: An official control perspective.

Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2 H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1 H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1 H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.

Chemometrics Analysis Combined with GC-MS and NMR Spectroscopy Analysis of Fatty Acids as a Means of Discriminating Butterfat Adulteration

The adulteration of butter has become a major problem in food industries. Butter has the similar characteristic to lard which makes lard a desirable adulterant in butter due to economic advantages. Therefore, the method of detection to analyse the adulteration practice must be developed. This study used NMR spectroscopy in combination with chemometrics for the authentication of butter from lard. The presence of lard as an adulterant in butter has been analysed using Gas Chromatography–Mass Spectrometry (GC-MS) and Nuclear Magnetic Resonance (NMR) spectroscopy with the aid of chemometric of Principal Component Analysis (PCA) and Discriminant Analysis (DA). PC1 described 82% of the variation while PC2 accounted for 15% of the variation resulted in a model that described 80% of the total variance in the data. With 82% of the peak variation along the first PC, it was clear that all seventeen samples of butter in the market and pure lard sample were formed according to their own group and showed two well-defined and well-separated group. DA model classified 100% of all samples accurately according to its group (butter and butter adulterated with animal fats), meaning that no samples were misclassified into the wrong group. Lard was successfully determined at 2.63 ppm. In this study, NMR and PCA analysis has successfully discriminated between the market sample and lard and the results established that there is no lard being adulterated in all commercial butter samples. This could be a potential identification approach to determine if the product has been deceived in market.

Understanding the Molecular Structure of the Sialic Acid-Phenylboronic Acid Complex by using a Combined NMR Spectroscopy and DFT Study: Toward Sialic Acid Detection at Cell Membranes.

The origin of the unusually high stability of the sialic acid (SA) and phenylboronic acid (PBA) complex was investigated by a combined nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) study. SA is a glycan‐terminating monosaccharide, and its importance as a clinical target has long been recognized. Inspired by the fact that the binding properties of SA–PBA complexation are anomalously high relative to those of typical monosaccharides, great effort has been made to build a clinical platform with the use of PBA as a SA‐selective receptor. Although a number of applications have been reported in recent years, the ability of PBA to recognize SA‐terminating surface glycans selectively is still unclear, because high‐affinity SA–PBA complexation might not occur in a physiological environment. In particular, different forms of SA (α‐ and β‐pyranose) were not considered in detail. To answer this question, the combined NMR spectroscopy/DFT study revealed that the advantageous binding properties of the SA–PBA complex arise from ester bonding involving the α‐carboxylate moieties (C1 and C2) of β‐SA but not α‐SA. Moreover, the facts that the C2 atom is blocked by a glycoside bond in a physiological environment and that α‐SA basically exists on membrane‐bound glycans in a physiological environment lead to the conclusion that PBA cannot selectively recognize the SA unit to discriminate specific types of cells. Our results have a significant impact on the field of SA‐based cell recognition.

A Combined NMR-Computational Study of the Interaction between Influenza Virus Hemagglutinin and Sialic Derivatives from Human and Avian Receptors on the Surface of Transfected Cells.

The development of small-molecule inhibitors of influenza virus Hemagglutinin could be relevant to the opposition of the diffusion of new pandemic viruses. In this work, we made use of Nuclear Magnetic Resonance (NMR) spectroscopy to study the interaction between two derivatives of sialic acid, Neu5Ac-α-(2,6)-Gal-β-(1–4)-GlcNAc and Neu5Ac-α-(2,3)-Gal-β-(1–4)-GlcNAc, and hemagglutinin directly expressed on the surface of recombinant human cells. We analyzed the interaction of these trisaccharides with 293T cells transfected with the H5 and H1 variants of hemagglutinin, which thus retain their native trimeric conformation in such a realistic environment. By exploiting the magnetization transfer between the protein and the ligand, we obtained evidence of the binding event, and identified the epitope. We analyzed the conformational features of the glycans with an approach combining NMR spectroscopy and data-driven molecular dynamics simulations, thus obtaining useful information for an efficient drug design.

1H NMR-based compositional identification of different powdered infant formulas.

Infant formulas (IFs), most of which are bovine milk-based, are important for normal growth and development. However, information regarding the ingredients in IFs is often limited in detail, and chemical changes during production and storage appear common. Therefore, it is important to understand in detail the composition of IFs. In this study, a wide range of low-molecular-weight organic components in commercial IFs were determined using the 1H nuclear magnetic resonance (NMR) technique. The components emerging after multivariate data analysis could be used to discriminate certain infant formulas from each other. Particular attention was given to the components with potentially beneficial bioactivities. Our study indicates that NMR spectroscopy in combination with multivariate data analysis constitutes an efficient tool for the comprehensive characterization of various IFs and the in-depth understanding of the nutritional value of IFs for infants.

Combined application of NMR- and GC-MS-based metabonomics yields a superior urinary biomarker panel for bipolar disorder.

Bipolar disorder (BD) is a debilitating mental disorder that cannot be diagnosed by objective laboratory-based modalities. Our previous studies have independently used nuclear magnetic resonance (NMR)-based and gas chromatography-mass spectrometry (GC-MS)-based metabonomic methods to characterize the urinary metabolic profiles of BD subjects and healthy controls (HC). However, the combined application of NMR spectroscopy and GC-MS may identify a more comprehensive metabolite panel than any single metabonomic platform alone. Therefore, here we applied a dual platform (NMR spectroscopy and GC-MS) that generated a panel of five metabolite biomarkers for BD-four GC-MS-derived metabolites and one NMR-derived metabolite. This composite biomarker panel could effectively discriminate BD subjects from HC, achieving an area under receiver operating characteristic curve (AUC) values of 0.974 in a training set and 0.964 in a test set. Moreover, the diagnostic performance of this panel was significantly superior to the previous single platform-derived metabolite panels. Thus, the urinary biomarker panel identified here shows promise as an effective diagnostic tool for BD. These findings also demonstrate the complementary nature of NMR spectroscopy and GC-MS for metabonomic analysis, suggesting that the combination of NMR spectroscopy and GC-MS can identify a more comprehensive metabolite panel than applying each platform in isolation.

The dynamic duo: Combining NMR and small angle scattering in structural biology

Structural biology provides essential information for elucidating molecular mechanisms that underlie biological function. Advances in hardware, sample preparation, experimental methods, and computational approaches now enable structural analysis of protein complexes with increasing complexity that more closely represent biologically entities in the cellular environment. Integrated multidisciplinary approaches are required to overcome limitations of individual methods and take advantage of complementary aspects provided by different structural biology techniques. Although X-ray crystallography remains the method of choice for structural analysis of large complexes, crystallization of flexible systems is often difficult and does typically not provide insights into conformational dynamics present in solution. Nuclear magnetic resonance spectroscopy (NMR) is well-suited to study dynamics at picosecond to second time scales, and to map binding interfaces even of large systems at residue resolution but suffers from poor sensitivity with increasing molecular weight. Small angle scattering (SAS) methods provide low resolution information in solution and can characterize dynamics and conformational equilibria complementary to crystallography and NMR. The combination of NMR, crystallography, and SAS is, thus, very useful for analysis of the structure and conformational dynamics of (large) protein complexes in solution. In high molecular weight systems, where NMR data are often sparse, SAS provides additional structural information and can differentiate between NMR-derived models. Scattering data can also validate the solution conformation of a crystal structure and indicate the presence of conformational equilibria. Here, we review current state-of-the-art approaches for combining NMR, crystallography, and SAS data to characterize protein complexes in solution.

Determination of rice type by 1H NMR spectroscopy in combination with different chemometric tools

A 400‐MHz 1H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis were used in the context of food surveillance to discriminate 46 authentic rice samples according to type. It was found that the optimal sample preparation consists of preparing aqueous rice extracts at pH 1.9. For the first time, the chemometric method independent component analysis (ICA) was applied to differentiate clusters of rice from the same type (Basmati, non‐Basmati long‐grain rice, and round‐grain rice) and, to a certain extent, their geographical origin. ICA was found to be superior to classical principal component analysis (PCA) regarding the verification of rice authenticity. The chemical shifts of the principal saccharides and acetic acid were found to be mostly responsible for the observed clustering. Among classification methods (linear discriminant analysis, factorial discriminant analysis, partial least squares discriminant analysis (PLS‐DA), soft independent modeling of class analogy, and ICA), PLS‐DA and ICA gave the best values of specificity (0.96 for both methods) and sensitivity (0.94 for PLS‐DA and 1.0 for ICA). Hence, NMR spectroscopy combined with chemometrics could be used as a screening method in the official control of rice samples. Copyright © 2013 John Wiley & Sons, Ltd.

Red wines attenuate TNFα production in human histiocytic lymphoma cell line: An NMR spectroscopy and chemometrics based study

Nuclear magnetic resonance (NMR) spectroscopy and multivariate data analyses methods are applied to the metabolic profiling of different red wines from Portugal. The water, methanol–water (1:1), and methanol fractions from solid phase extraction (SPE) with C18 resin were subjected to in vitro TNFα activity assay. Principal component analysis allowed the clear separation among the different SPE fractions according to the activity. Various supervised data reduction algorithms were tested and compared to highlight the TNFα inhibition by SPE fractions of wines. Partial least squares-discriminant analysis and orthogonal bidirectional PLS-DA were found most effective in discriminating the samples with different activities. By calculating variable importance in the projection, the active ingredients in the high activity samples have been identified as caftaric acid, quercetin, and catechin. Among the different vintages, samples from 2010 vintage were found with maximum anti-TNFα activity. The effectiveness of NMR spectroscopy in combination with chemometrics to identify the possible bioactivity in the several crude extracts is highlighted.

Discrimination of sugarcane according to cultivar by ¹H NMR and chemometric analyses

Several technologies for the development of new sugarcane cultivars have mainly focused on the increase in productivity and greater disease resistance. Sugarcane cultivars are usually identified by the organography of the leaves and stems, the analysis of peroxidase and esterase isoenzyme activities and the total soluble protein as well as soluble solid content. Nuclear magnetic resonance (NMR) associated with chemometric analysis has proven to be a valuable tool for cultivar assessment. Thus, this article describes the potential of chemometric analysis applied to ¹H high resolution magic angle spinning (HRMAS) and NMR in solution for the investigation of sugarcane cultivars. For this purpose, leaves from eight different cultivars of sugarcane were investigated by ¹H NMR spectroscopy in combination with chemometric analysis. The approach shows to be a useful tool for the distinction and classification of different sugarcane cultivars as well as to access the differences on its chemical composition.

NMR identifies atherogenic lipoprotein abnormalities in early diabetic nephropathy that are unrecognized by conventional analysis

Lipoprotein abnormalities are likely contributors to the high risk of cardiovascular disease in the chronic kidney disease (CKD) population, although information is limited. Specifically, little is known about lipoprotein abnormalities during the early stages of diabetic kidney disease. The aim of this study was to investigate the relationship between lipoproteins and early manifestations of CKD in the 517 Type 2 diabetes mellitus (T2DM) patients who participated in the Insulin Resistance Atherosclerosis Study (IRAS). Lipoprotein abnormalities were measured by conventional lipid analysis, nuclear magnetic resonance (NMR) spectroscopy, gel gradient electrophoresis (GE), immunoprecipitation (IP), and ELISA. We grouped the cases into albumin to creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) quartiles. In the conventional lipid analysis, triglycerides (TG) correlated directly with ACR and inversely with eGFR quartiles (p = 0.01), while LDL, HDL cholesterol did not correlate with change in ACR or eGFR. ACR was directly associated with apoB, total VLDL, medium VLDL, IDL and small LDL particle concentrations (p < or = 0.03), and inversely with large LDL particles (p = 0.01) and LDL size (p = 0.008). Estimated GFR quartiles were inversely associated with total VLDL, small VLDL, IDL, and medium HDL particles (p < or = 0.01). In subjects with T2DM, mild albuminuria and reduction in eGFR were associated with numerous atherogenic lipoprotein abnormalities that were detected by the combination of NMR spectroscopy, gel gradient electrophoresis, immunoprecipitation and ELISA but not by the standard clinical lipid analysis.

Comparison of metabolic profile of normal and keratoconus corneas using HR MAS 1HNMR spectroscopy and HPLC

Abstract Purpose The aim of this study is to examine possible differences in the metabolic profile between keratoconus and normal corneas. Methods Samples of corneas with keratoconus were obtained during the transplantation surgery from 3 patients (age: 22‐27 years). The control corneal tissues were excised during enucleating of eyes with malign melanoma in the retina from 4 patients (age: 65‐72 years). The samples were immediately frozen at ‐80 ºC. The metabolic profiles of the samples were investigated either with HR MAS (High Resolution Magic Angle Spinning) 1H NMR (Nuclear Magnetic Resonance) spectroscopy (14.1 T) operating at 600.132 MHz and HPLC (High Performance Liquid Chromatography). All data obtained with both methods were analysed using special software for: (i) analysis of complex mixtures, (ii) principal component analysis – PCA, (iii) detailed statistical analysis. Results In all samples, 9 amino acids were detected with HPLC, and 19 metabolites (including amino acids) with HR MAS 1H NMR spectroscopy, respectively. PCA analysis of NMR spectra showed no grouping pattern between the keratoconus and control samples. Detailed analysis of data obtained with NMR spectroscopy and with HPLC revealed no significant differences in amino acid profiles between keratoconus and control corneas. Conclusion The study presents metabolic profiles of human cornea examined with new approach combining NMR spectroscopy and HPLC. Significant differences in the metabolic profiles of corneas with keratoconus and healthy corneas examined with both methods were not revealed. Small number of samples analysed in this study represents a limitation of the results, and further investigation will be performed to focus on particular metabolites.

Structural Basis for a Munc13–1 Homodimer to Munc13–1/RIM Heterodimer Switch

C 2 domains are well characterized as Ca 2+/phospholipid-binding modules, but little is known about how they mediate protein–protein interactions. In neurons, a Munc13–1 C 2A-domain/RIM zinc-finger domain (ZF) heterodimer couples synaptic vesicle priming to presynaptic plasticity. We now show that the Munc13–1 C 2A domain homodimerizes, and that homodimerization competes with Munc13–1/RIM heterodimerization. X-ray diffraction studies guided by nuclear magnetic resonance (NMR) experiments reveal the crystal structures of the Munc13–1 C 2A-domain homodimer and the Munc13–1 C 2A-domain/RIM ZF heterodimer at 1.44 Å and 1.78 Å resolution, respectively. The C 2A domain adopts a β-sandwich structure with a four-stranded concave side that mediates homodimerization, leading to the formation of an eight-stranded β-barrel. In contrast, heterodimerization involves the bottom tip of the C 2A-domain β-sandwich and a C-terminal α-helical extension, which wrap around the RIM ZF domain. Our results describe the structural basis for a Munc13–1 homodimer–Munc13–1/RIM heterodimer switch that may be crucial for vesicle priming and presynaptic plasticity, uncovering at the same time an unexpected versatility of C 2 domains as protein–protein interaction modules, and illustrating the power of combining NMR spectroscopy and X-ray crystallography to study protein complexes.

A new method for classification of wines based on proton and carbon-13 NMR spectroscopy in combination with pattern recognition techniques

Proton and carbon-13 nuclear magnetic resonance (NMR) spectroscopic methods were applied in the differentiation of 53 German white wines from the regions Rheinhessen, Rheingau and Mosel—Saar—Ruwer. The robustness of these differentiations was tested by leaving out one sample at a time and replacing it into the set as a test sample. Small variations in the position of the lines in the spectra, which lowered the classification ability of the tested systems, were successfully eliminated using a novel data pre-processing algorithm called partial linear fit.

19F and 1H magnetic resonance strategies for metabolic studies on fluorinated xenobiotics: Application to flurbiprofen [2-(2-fluoro-4-biphenylyl)propionic acid

Strategies for the use of 1H and 19F nuclear magnetic resonance (NMR) spectroscopy as an aid to the study of the metabolic fate of fluorinated drugs are discussed with reference to the application of these methods to flurbiprofen metabolism in man. 1H and 19F NMR analysis of untreated urine enabled the detection of two major and eight minor metabolites of the drug. The two major metabolites were identified using a combination of NMR spectroscopy, solid-phase extraction chromatography with 19F and 1H NMR detection and chemical hydrolysis to a flurbiprofen glucuronide and the glucuronide of the 4-hydroxy metabolite. 1H-19F 2D shift correlated spectroscopy and spin-echo difference experiments are discussed in relation to their use in the structural identification of drug metabolites.