Matthias Niemitz

Essential Parameters for Structural Analysis and Dereplication by 1H NMR Spectroscopy

The present study demonstrates the importance of adequate precision when reporting the δ and J parameters of frequency domain 1H NMR (HNMR) data. Using a variety of structural classes (terpenoids, phenolics, alkaloids) from different taxa (plants, cyanobacteria), this study develops rationales that explain the importance of enhanced precision in NMR spectroscopic analysis and rationalizes the need for reporting Δδ and ΔJ values at the 0.1–1 ppb and 10 mHz level, respectively. Spectral simulations paired with iteration are shown to be essential tools for complete spectral interpretation, adequate precision, and unambiguous HNMR-driven dereplication and metabolomic analysis. The broader applicability of the recommendation relates to the physicochemical properties of hydrogen (1H) and its ubiquity in organic molecules, making HNMR spectra an integral component of structure elucidation and verification. Regardless of origin or molecular weight, the HNMR spectrum of a compound can be very complex and encode a wealth of structural information that is often obscured by limited spectral dispersion and the occurrence of higher order effects. This altogether limits spectral interpretation, confines decoding of the underlying spin parameters, and explains the major challenge associated with the translation of HNMR spectra into tabulated information. On the other hand, the reproducibility of the spectral data set of any (new) chemical entity is essential for its structure elucidation and subsequent dereplication. Handling and documenting HNMR data with adequate precision is critical for establishing unequivocal links between chemical structure, analytical data, metabolomes, and biological activity. Using the full potential of HNMR spectra will facilitate the general reproducibility for future studies of bioactive chemicals, especially of compounds obtained from the diversity of terrestrial and marine organisms.

Proton Fingerprints Portray Molecular Structures: Enhanced Description of the 1H NMR Spectra of Small Molecules

The characteristic signals observed in NMR spectra encode essential information on the structure of small molecules. However, extracting all of this information from complex signal patterns is not trivial. This report demonstrates how computer-aided spectral analysis enables the complete interpretation of 1D (1)H NMR data. The effectiveness of this approach is illustrated with a set of organic molecules, for which replicas of their (1)H NMR spectra were generated. The potential impact of this methodology on organic chemistry research is discussed.

Complete Spectral Analysis of the 1H NMR 16‐Spin System of β‐Pinene

The complete analysis of the 1H NMR spectrum of β‐pinene, (1S)‐(‐)‐6,6‐dimethyl‐2‐methylenebicyclo[3.1.1]heptane, which is of the ABCDEFGHIJX3Y3 type, is reported and earlier results are corrected. The vicinal coupling constants, 3J(H,H), are compared with the theoretical values calculated by using the Altona and co‐workers’ equations for the structure derived by molecular modelling. The results were applied to the conformational analysis of β‐pinene.

Toward Structural Correctness: Aquatolide and the Importance of 1D Proton NMR FID Archiving.

The revision of the structure of the sesquiterpene aquatolide from a bicyclo[2.2.0]hexane to a bicyclo[2.1.1]hexane structure using compelling NMR data, X-ray crystallography, and the recent confirmation via full synthesis exemplify that the achievement of “structural correctness” depends on the completeness of the experimental evidence. Archived FIDs and newly acquired aquatolide spectra demonstrate that archiving and rigorous interpretation of 1D 1H NMR data may enhance the reproducibility of (bio)chemical research and curb the growing trend of structural misassignments. Despite being the most accessible NMR experiment, 1D 1H spectra encode a wealth of information about bonds and molecular geometry that may be fully mined by 1H iterative full spin analysis (HiFSA). Fully characterized 1D 1H spectra are unideterminant for a given structure. The corresponding FIDs may be readily submitted with publications and collected in databases. Proton NMR spectra are indispensable for structural characterization even in conjunction with 2D data. Quantum interaction and linkage tables (QuILTs) are introduced for a more intuitive visualization of 1D J-coupling relationships, NOESY correlations, and heteronuclear experiments. Overall, this study represents a significant contribution to best practices in NMR-based structural analysis and dereplication.

Subtle Chemical Shifts Explain the NMR Fingerprints of Oligomeric Proanthocyanidins with High Dentin Biomodification Potency

The ability of certain oligomeric proanthocyanidins (OPACs) to enhance the biomechanical properties of dentin involves collagen cross-linking of the 1.3-4.5 nm wide space via protein-polyphenol interactions. A systematic interdisciplinary search for the bioactive principles of pine bark has yielded the trimeric PAC, ent-epicatechin-(4β→8)-epicatechin-(2β→O→7,4β→8)-catechin (3), representing the hitherto most potent single chemical entity capable of enhancing dentin stiffness. Building the case from two congeneric PAC dimers, a detailed structural analysis decoded the stereochemistry, spatial arrangement, and chemical properties of three dentin biomodifiers. Quantum-mechanics-driven (1)H iterative full spin analysis (QM-HiFSA) of NMR spectra distinguished previously unrecognized details such as higher order J coupling and provided valuable information about 3D structure. Detection and quantification of H/D-exchange effects by QM-HiFSA identified C-8 and C-6 as (re)active sites, explain preferences in biosynthetic linkage, and suggest their involvement in dentin cross-linking activity. Mapping of these molecular properties underscored the significance of high δ precision in both (1)H and (13)C NMR spectroscopy. Occurring at low- to subppb levels, these newly characterized chemical shift differences in ppb are small but diagnostic measures of dynamic processes inherent to the OPAC pharmacophores and can help augment our understanding of nanometer-scale intermolecular interactions in biomodified dentin macromolecules.

MetIDB: A Publicly Accessible Database of Predicted and Experimental 1H NMR Spectra of Flavonoids

Identification of natural compounds, especially secondary metabolites, has been hampered by the lack of easy to use and accessible reference databases. Nuclear magnetic resonance (NMR) spectroscopy is the most selective technique for identification of unknown metabolites. High quality (1)H NMR (proton nuclear magnetic resonance) spectra combined with elemental composition obtained from mass spectrometry (MS) are essential for the identification process. Here, we present MetIDB, a reference database of experimental and predicted (1)H NMR spectra of 6000 flavonoids. By incorporating the stereochemistry, intramolecular interactions, and solvent effects into the prediction model, chemical shifts and couplings were predicted with great accuracy. A user-friendly web-based interface for MetIDB has been established providing various interfaces to the data and data-mining possibilities. For each compound, additional information is available comprising compound annotation, a (1)H NMR spectrum, 2D and 3D structure with correct stereochemistry, and monoisotopic mass as well as links to other web resources. The combination of chemical formula and (1)H NMR chemical shifts proved to be very efficient in metabolite identification, especially for isobaric compounds. Using this database, the process of flavonoid identification can then be significantly shortened by avoiding repetitive elucidation of already described compounds.

Comprehensive strategy for proton chemical shift prediction: linear prediction with nonlinear corrections.

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the descriptors are computed from an ensemble of the conformers found by conformational search based on Metropolis Monte Carlo (MMC) simulation; in the 4D model the conformational space was further expanded to the fourth dimension (time) by adding molecular dynamics to the MC conformers. An illustrative case study about the application and interpretation of the 4D prediction for a conformationally flexible structure, scopolamine, is described in detail.

NUCLEAR MAGNETIC RESONANCE AND MOLECULAR ORBITAL STUDY OF SOME COCAINE ANALOGUES

IH NMR spectra of (-)-cocaine and some of its derivatives ((x-CPT, (3-CPT, nor-(~lT, cocaine- HCI and ecgonine-HCI) were analysed and the spectral parameters were used for conformational analysis of the compounds in conjunction with theoretical HF/6-31G*, MMP2, AMI and molecular dynamics calculations. Comparison of the experimental and theoretical data reveals that the compounds are predominantly in a rigid chair conformation, which is rather similar for all compounds. No large differences were found in the dynamical behaviour of the molecules. The performance of the Haasnoot and Altona equations is discussed.

Metabolism of the dimethyl ester of [2,3-(13)C]succinic acid in rat hepatocytes.

Hepatocytes prepared from overnight fasted rats were incubated for 120 min in the presence of the dimethyl ester of [2,3-13C]succinic acid (10 mM). The identification and quantification of 13C-enriched metabolites in the incubation medium were performed by a novel computational strategy for the deconvolution of NMR spectra with multiplet structures and constraints. The generation of 13C-labelled metabolites, including succinate, fumarate, malate, lactate, alanine, aspartate and glucose accounted for about half of the initial amount of the ester present in the incubation medium. A fair correlation was observed between the experimental abundance of each 13C-labelled glucose isotopomer and the corresponding values derived from a model for the metabolism of [2,3-13C]succinate. Newly formed glucose was more efficiently labelled in the carbon C5 than C2, as well as the carbon C6 than C1, supporting the concept that D-glyceraldehyde-3-phosphate may undergo enzyme-to-enzyme channelling between glyceraldehyde-3-phosphate dehydrogenase and phosphofructoaldolase.

Evolution of Quantitative Measures in NMR: Quantum Mechanical qHNMR Advances Chemical Standardization of a Red Clover (Trifolium pratense) Extract

Chemical standardization, along with morphological and DNA analysis ensures the authenticity and advances the integrity evaluation of botanical preparations. Achievement of a more comprehensive, metabolomic standardization requires simultaneous quantitation of multiple marker compounds. Employing quantitative 1H NMR (qHNMR), this study determined the total isoflavone content (TIfCo; 34.5–36.5% w/w) via multimarker standardization and assessed the stability of a 10-year-old isoflavone-enriched red clover extract (RCE). Eleven markers (nine isoflavones, two flavonols) were targeted simultaneously, and outcomes were compared with LC-based standardization. Two advanced quantitative measures in qHNMR were applied to derive quantities from complex and/or overlapping resonances: a quantum mechanical (QM) method (QM-qHNMR) that employs 1H iterative full spin analysis, and a non-QM method that uses linear peak fitting algorithms (PF-qHNMR). A 10 min UHPLC-UV method provided auxiliary orthogonal quantitation. This is the first systematic evaluation of QM and non-QM deconvolution as qHNMR quantitation measures. It demonstrates that QM-qHNMR can account successfully for the complexity of 1H NMR spectra of individual analytes and how QM-qHNMR can be built for mixtures such as botanical extracts. The contents of the main bioactive markers were in good agreement with earlier HPLC-UV results, demonstrating the chemical stability of the RCE. QM-qHNMR advances chemical standardization by its inherent QM accuracy and the use of universal calibrants, avoiding the impractical need for identical reference materials.