Quantum Mechanical Quantitative Nuclear Magnetic Resonance Enables Digital Reference Standards at All Magnetic Fields and Enhances qNMR Sustainability.

Quantum mechanics (QM)-driven 1H iterative functionalized spin analysis produces HifSA profiles, which encode the complete 1H spin parameters ("nuclear genotype") of analytes of interest. HifSA profiles enable the establishment of digital reference standards (dRS) that are portable, FAIR (findable - accessible - interoperable - reusable), and fit for the purpose of quantitative 1H NMR (qHNMR) analysis at any magnetic field. This approach enhances the sustainability of analytical standards. Moreover, the analyte-specific complete chemical shift and J-coupling information in HifSA-based dRS enable computational quantitation of substances in mixtures via QM-total-line-shape fitting (QM-qHNMR). We present the proof of concept for HifSA-based dRS by resolving the highly overlapping NMR resonances in the experimental spectra ("nuclear phenotypes") of the diastereomeric mixture of (2RS, 4RS)- and (2RS, 4SR)-difenoconazole (DFZ), a widely used antifouling food additive. The underlying 1H spin parameters are highly conserved in various solvents, are robust against variation in measurement temperature, and work across a wide range of magnetic fields. QM-qHNMR analysis of DFZ samples at 80, 400, 600, and 800 MHz showed high congruence with metrological reference values. Furthermore, this study introduces QM-qHNMR combined with chiral shift reagents for the analysis of all four DFZ stereoisomers: (2R, 4R)-, (2S, 4S)-, (2R, 4S)-, and (2S, 4R)-DFZ to perform chiral qHNMR measurements.

The qNMR Summit 5.0: Proceedings and Status of qNMR Technology.

The goal of the qNMR Summit is to take stock of the status quo and the recent developments in qNMR research and applications in a timely and accurate manner. It provides a platform for both advanced and novice qNMR practitioners to receive a well-rounded update and discuss potential qNMR-related applications and collaborations. For over a decade, scientists from academia, industry, nonprofit institutions, and governmental bodies have focused on the standardization of qNMR methodology, as well as its metrological and pharmacopeial utility. This paper reviews key content of qNMR Summits 1.0 to 4.0 and puts into perspective the outcomes and available transcripts of the October 2019 Summit 5.0, with attendees from the United States, Canada, Japan, Korea, and several European countries. Summit presentations focused on qNMR methodology in the pharmaceutical industry, advanced quantitation algorithms, and promising developments.

NMR-Based Quantum Mechanical Analysis Builds Trust and Orthogonality in Structural Analysis: The Case of a Bisdesmosidic Triglycoside as Withania somnifera Aerial Parts Marker.

The present study demonstrates the relationship between conventional and quantum mechanical (QM) NMR spectroscopic analyses, shown here to assist in building a convincingly orthogonal platform for the solution and documentation of demanding structures. Kaempferol-3-O-robinoside-7-O-glucoside, a bisdesmosidic flavonol triglycoside and botanical marker for the aerial parts of Withania somnifera, served as an exemplary case. As demonstrated, QM-based 1H iterative full spin analysis (HiFSA) advances the understanding of both individual nuclear resonance spin patterns and the entire 1H NMR spectrum of a molecule and establishes structurally determinant, numerical HiFSA profiles. The combination of HiFSA with regular 1D 1H NMR spectra allows for simplified yet specific identification tests via comparison of high-quality experimental with QM-calculated spectra. HiFSA accounts for all features encountered in 1H NMR spectra: nonlinear high-order effects, complex multiplets, and their usually overlapped signals. As HiFSA replicates spectrum patterns from field-independent parameters with high accuracy, this methodology can be ported to low-field NMR instruments (40-100 MHz). With its reliance on experimental NMR evidence, the QM approach builds up confidence in structural characterization and potentially reduces identity analyses to simple 1D 1H NMR experiments. This approach may lead to efficient implementation of conclusive identification tests in pharmacopeial and regulatory analyses: from simple organics to complex natural products.

Quantum Mechanics-Based Structure Analysis of Cyclic Monoterpene Glycosides from Rhodiola rosea.

NMR- and MS-guided metabolomic mining for new phytoconstituents from a widely used dietary supplement, Rhodiola rosea, yielded two new (+)-myrtenol glycosides, 1 and 2, and two new cuminol glycosides, 3 and 4, along with three known analogues, 5-7. The structures of the new compounds were determined by extensive spectroscopic data analysis. Quantum mechanics-driven 1H iterative full spin analysis (QM-HiFSA) decoded the spatial arrangement of the methyl groups in 1 and 2, as well as other features not recognizable by conventional methods, including higher order spin-coupling effects. Expanding applied HiFSA methodology to monoterpene glycosides advances the toolbox for stereochemical assignments, facilitates their structural dereplication, and provides a more definitive reference point for future phytochemical and biological studies of R. rosea as a resilience botanical. Application of a new NMR data analysis software package, CT, for QM-based iteration of NMR spectra is also discussed.

The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research.

Covering: up to 2018With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets. A comprehensive compilation of historic to present-day cases as well as contemporary and future applications show that addressing the urgent need for a repository of publicly accessible raw NMR data has the potential to transform natural products (NPs) and associated fields of chemical and biomedical research. The call for advancing open sharing mechanisms for raw data is intended to enhance the transparency of experimental protocols, augment the reproducibility of reported outcomes, including biological studies, become a regular component of responsible research, and thereby enrich the integrity of NP research and related fields.

Correction: The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research.

Correction for 'The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research' by James B. McAlpine et al., Nat. Prod. Rep., 2018, DOI: .

Quality Control of Therapeutic Peptides by 1H NMR HiFSA Sequencing.

Ensuring identity, purity, and reproducibility are equally essential during synthetic chemistry, drug discovery, and for pharmaceutical product safety. Many peptidic APIs are large molecules that require considerable effort for integrity assurance. This study builds on quantum mechanical 1H iterative Full Spin Analysis (HiFSA) to establish NMR peptide sequencing methodology that overcomes the intrinsic limitations of principal compendial methods in identifying small structural changes or minor impurities that affect effectiveness and safety. HiFSA sequencing yields definitive identity and purity information concurrently, allowing for API quality assurance and control (QA/QC). Achieving full peptide analysis via NMR building blocks, the process lends itself to both research and commercial applications as 1D 1H NMR (HNMR) is the most sensitive and basic NMR experiment. The generated HiFSA profiles are independent of instrument or software tools and work at any magnetic field strength. Pairing with absolute or 100% qHNMR enables quantification of mixtures and/or determination of peptide conformer populations. Demonstration of the methodology uses single amino acids (AAs) and peptides of increasing size, including the octapeptide, angiotensin II, and the nonapeptide, oxytocin. The feasibility of HiFSA coupled with automated NMR and qHNMR for use in QC/QA efforts is established through case-based examples and recommended procedures.

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.

Stereochemistry of a Second Riolozane and Other Diterpenoids from Jatropha dioica.

The dichloromethane extract of the roots of Jatropha dioica afforded riolozatrione (1) and a C-6 epimer of riolozatrione, 6-epi-riolozatrione (2), as a new structure and only the second reported riolozane diterpenoid. The two known diterpenoids jatrophatrione (3) and citlalitrione (4) were also isolated and characterized. Both epimers 1 and 2 are genuine plant constituents, with 2 likely being the biosynthesis precursor of 1 due to the tendency for the quantitative transformation of 2 into 1 under base catalysis. The structural characterization and distinction of the stereoisomers utilized 1H iterative full-spin analysis, yielding complete J-correlation maps that were represented as quantum interaction and linkage tables. The absolute configuration of compounds 1-4 was established by means of vibrational circular dichroism and via X-ray diffraction analysis for 1, 2, and 4. Additionally, the cytotoxic and antiherpetic in vitro activities of the isolates were evaluated.

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 (1)H 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 (1)H spectra encode a wealth of information about bonds and molecular geometry that may be fully mined by (1)H iterative full spin analysis (HiFSA). Fully characterized 1D (1)H 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-(4ß→8)-epicatechin-(2ß→O→7,4ß→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.

Universal J-coupling prediction.

A data driven approach for small molecule J-coupling prediction is presented. The method is targeted for use as part of an automatic spectrum analysis, therefore emphasizing prediction coverage, maintainability, and speed in the design. The database search involves encoding the coupling path atom types into hash codes, which are used to retrieve the matching coupling constant entries from the database. The fast hash dictionary search is followed by a k Nearest Neighbors regression to resolve the substituent and conformational dependencies, parametrized with atomic charges, torsion angles, and steric bulk.

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.

Essential parameters for structural analysis and dereplication by (1)H NMR spectroscopy.

The present study demonstrates the importance of adequate precision when reporting the δ and J parameters of frequency domain (1)H 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 ((1)H) 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.

Identification by HSQC and quantification by qHNMR innovate pharmaceutical amino acid analysis.

This study introduces a new NMR-based methodology for identification (ID) and quantification (purity, strength) assays of widely used amino acids. A detailed analysis of four amino acids and their available salts was performed with both a high-field (600 MHz) and a benchtop (60 MHz) NMR instrument. To assess sensitivity constraints, samples for 1H NMR analysis were initially prepared using only 10 mg of analyte and 1 mg of maleic acid (MA) as an internal calibrant (IC) and secondary chemical shift reference. The characteristic dispersion of the peak patterns indicating the presence or absence of a counterion (mostly chloride) was conserved at both high and low-field strength instruments, showing that the underlying NMR spectroscopic parameters, i.e., chemical shifts and coupling constants, are independent of the magnetic field strength. However, as the verbal descriptions of 1H NMR spectra are challenging in the context of reference materials and pharmaceutical monographs, an alternative method for the identification (ID) of amino acids is proposed that uses 13C NMR patterns from multiplicity-edited HSQC (ed-HSQC), which are both compound-specific and straightforward to document. For ed-HSQC measurements, the sample amount was increased to 30 mg of the analyte and several acquisition parameters were tested, including t1 increments used in the pulse program, number of scans, and repetition time. Excellent congruence with deviations <0.1 ppm was achieved for the 13C chemical shifts from 1D 13C NMR spectra (150 MHz) vs. those extracted from ed-HSQC (15 MHz traces). Finally, all samples of amino acid candidate reference materials were quantified by 1H qNMR (abs-qHNMR) at both 600 and 60 MHz. At high field, both IC and relative quantitations were performed, however, with the low-field instrument, only the IC method was used. The results showed that the analyzed reference material candidates were generally highly pure compounds. To achieve adequately low levels of uncertainty for such high-purity materials, the sample amounts were increased to 100 mg of analytes and 10 mg of the IC and replicates were analyzed for selected amino acids.

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.

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.

Pharmaceutical analysis by NMR can accommodate strict impurity thresholds: The case of choline.

The ICH guidelines recommend reporting thresholds for regular impurities in drug substances at the level of 0.05% or 0.03% (w/w) depending on the maximum daily intake. Therefore, any instrumental method of analysis applicable to the impurity analysis should be able to detect and quantify the analytes at those levels. This investigation was designed to verify the suitability of 1H NMR spectroscopy for the detection of impurities, as a first step in the process before attempting quantification. In order to minimize demand on equipment, this study employed a 400 MHz instrument for structural confirmation and signal assignments of choline (1) and O-(2-hydroxyethyl)choline (2), a known impurity. The limit of detection (LOD) of 2 in 10 mg of 1 was established as 0.01% on a 400 MHz instrument and 2% on a 60 MHz (benchtop) NMR spectrometer. Thus, impurities for which quantification is required are readily detected at 400 MHz or above. These results are in contrast to the widespread belief that 1H NMR sensitivity is insufficient for pharmaceutical impurity analysis. The choice of solvent was recognized as a critical parameter for 1H NMR LOD analysis. Furthermore, publicly available NMR raw data (HMDB) proved to be valuable for unveiling the otherwise cryptic information hidden in complex signal patterns via 1H NMR iterative Full Spin Analysis. Finally, the study uncovered the less noticed, yet characteristic, 14N-1H coupling in the -N+(CH3)3 groups, adding strong arguments for the Raw NMR Data Initiative. Collectively, the data prove that the analytical capabilities of high-field NMR easily fulfill the ICH requirements for detection of impurity in the presence of an actual substance of interest which makes it a step closer to achieving regulatory standards.

NMR-based metabolomics of mammalian cell and tissue cultures.

NMR spectroscopy was used to evaluate growth media and the cellular metabolome in two systems of interest to biomedical research. The first of these was a Chinese hamster ovary cell line engineered to express a recombinant protein. Here, NMR spectroscopy and a quantum mechanical total line shape analysis were utilized to quantify 30 metabolites such as amino acids, Krebs cycle intermediates, activated sugars, cofactors, and others in both media and cell extracts. The impact of bioreactor scale and addition of anti-apoptotic agents to the media on the extracellular and intracellular metabolome indicated changes in metabolic pathways of energy utilization. These results shed light into culture parameters that can be manipulated to optimize growth and protein production. Second, metabolomic analysis was performed on the superfusion media in a common model used for drug metabolism and toxicology studies, in vitro liver slices. In this study, it is demonstrated that two of the 48 standard media components, choline and histidine are depleted at a faster rate than many other nutrients. Augmenting the starting media with extra choline and histidine improves the long-term liver slice viability as measured by higher tissues levels of lactate dehydrogenase (LDH), glutathione and ATP, as well as lower LDH levels in the media at time points out to 94 h after initiation of incubation. In both models, media components and cellular metabolites are measured over time and correlated with currently accepted endpoint measures.

Quantum mechanical NMR full spin analysis in pharmaceutical identity testing and quality control.

Issues related to pharmaceutical quality are arising at an alarming rate. Pharmaceutical quality concerns both the Active Pharmaceutical Ingredients (APIs) and the Finished Drug Product/ Formulation. Recently, there has been a significant increase in the number of reports of harmful impurities in marketed drug formulations. Impurities range from solvents, reactants, adulterants, and catalysts to synthetic byproducts. Quality concerns in commercial preparations may also arise due to shelf life stability. Furthermore, a number of falsified and substandard drug cases have been reported. Most of the techniques which are currently in place can, at best, detect the impurities, but cannot identify them unless they are already known and can be compared to a standard. On the other hand, 1H NMR spectroscopy detects all the hydrogen containing species, typically provides information to elucidate structures partially or even completely, and through its absolute quantitative capabilities even can detect the presence hydrogen-free species indirectly. The structural properties that produce 1H NMR signals as characteristic representations of a given molecule are the chemical shifts (δ in ppm) and coupling constants (J in Hz). Along with the line widths (ω1/2 in Hz), these parameters are bound to both the molecule and the NMR experimental conditions by quantum mechanical (QM) principles. This means that the 1H NMR spectra of APIs can be precisely calculated and compared to the experimental data. This review explains how 1H NMR spectroscopy coupled with Full Spin Analysis can contribute towards the quality control of pharmaceuticals by improving structural dereplication and achieving simultaneous quantification of both APIs and their contaminants.