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Curcuma longa (turmeric) has an extensive history of ethnomedical use for common ailments, and “curcumin”-containing dietary supplements (CDS) are a highly visible portion of today’s self-medication market. Owing to raw material cost pressure, CDS products are affected by economically motivated, nefarious adulteration with synthetic curcumin (“syncumin”), possibly leading to unexpected toxicological issues due to “residual” impurities. Using a combination of targeted and untargeted (phyto)chemical analysis, this study investigated the botanical integrity of two commercial “turmeric” CDS with vitamin and other additives that were associated with reported clinical cases of hepatotoxicity. Analyzing multisolvent extracts of the CDS by 100% quantitative 1H NMR (qHNMR), alone and in combination with countercurrent separation (CCS), provided chemical fingerprints that allowed both the targeted identification and quantification of declared components and the untargeted recognition of adulteration. While confirming the presence of curcumin as a major constituent, the universal detection capability of NMR spectroscopy identification of significant residual impurities, including potentially toxic components. While the loss-free nature of CCS captured a wide polarity range of declared and unwanted chemical components, and also increased the dynamic range of the analysis, (q)HNMR determined their mass proportions and chemical constitutions. The results demonstrate that NMR spectroscopy can recognize undeclared constituents even if they represent only a fraction of the mass balance of a dietary supplement product. The chemical information associated with the missing 4.8% and 7.4% (m/m) in the two commercial samples, exhibiting an otherwise adequate curcumin content of 95.2% and 92.6%, respectively, pointed to a product integrity issue and adulteration with undeclared synthetic curcumin. Impurities from synthesis are most plausibly the cause of the observed adverse clinical effects. The study exemplifies how the simultaneously targeted and untargeted analytical principle of the 100% qHNMR method, performed with entry-level high-field instrumentation (400 MHz), can enhance the safety of dietary supplements by identifying adulterated, non-natural “natural” products.

Whereas generic, LC-based pharmaceutical control quality procedures depend largely on the detection mode and can be particularly ‘blind’ to certain impurities, NMR is a more versatile and, thus, often more judicious detector. While adulteration presents ever-evolving challenges for the analysis of active pharmaceutical ingredients (APIs) and finished products sold in the worldwide (online) marketplace, research chemicals are usually trusted rather than being considered flawed or even adulterated.

This report shows how NMR analysis uncovered the unanticipated presence of substantial amounts of mannitol (20 and 43% w/w) as undeclared constituent in two custom synthetic peptides, DR and DRVYI, that were sourced commercially. Quantitative 1H NMR (qHNMR) readily detected the contaminant, even on a 60 MHz benchtop instrument, and quantified the highly polar and UV-transparent adulterant. Quantum-mechanical 1H iterative Full Spin Analysis (HiFSA) not only achieved unambiguous identification of both the mannitol and the peptides, but also confirmed the quantitative results.

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.

With 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.

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.

The acquisition of 1D 1H NMR (HNMR) spectra is one of earliest steps in characterizing natural products and other organic molecules. For publication, HNMR information usually is “converted” into a table format, and sometimes spectral plots are provided. However, this transformation is lossy and frequently insufficient for unambiguous dereplication. This ambiguity can even lead to structural revision, such as in the recent case of aquatolide (1), a sesquiterpene lactone from Asteriscus aquaticus. Our study demonstrates that public dissemination of original (digital) HNMR data (FIDs) can be a powerful means of enhancing the reproducibility of structural assignments and, thus, any downstream biological studies. Using the archived 800 MHz HNMR spectrum, and employing a semi-automated quantum mechanics-driven spectral analysis (HiFSA), we were able to rule out the initial assignment (1a), confirm the revision (1b), and achieve the full interpretation of the HNMR fingerprints. Using additional examples of constitutional and diastereomeric isomers which exhibit complex and near-identical HNMR spectra, we show that the public sharing of original HNMR data (FIDs) is not only essential for robust structural assignments, but can enhance the reproducibility of research with bioactive natural products and other organic molecules simply and productively.

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.