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Chlorophylls are present in all extracts from the aerial parts of green plant materials. Chlorophylls may act as in vitro bioassay nuisance compounds, possibly preventing the reproducibility and accurate measurement of readouts due to their UV/vis absorbance, fluorescence properties, and tendency to precipitate in aqueous media. Despite the diversity of methods used traditionally to remove chlorophylls, details about their mode of operation, specificity, and reproducibility are scarce. Herein, we report a selective and efficient 45 min liquid–liquid/countercurrent chlorophyll cleanup method using Centrifugal Partition Chromatography (CPC) with a solvent system composed of hexanes–EtOAc–MeOH–water (5:5:5:5, v/v) in elution-extrusion mode. The broader utility of the method was assessed with four different extracts prepared from three well-characterized plant materials: Epimedium sagittatum (leaves), Senna alexandrina (leaves), and Trifolium pratense (aerial parts). The reproducibility of the method, the selectivity of the chlorophyll removal, as well as the preservation of the phytochemical integrity of the resulting chlorophyll-free (“degreened”) extracts were evaluated using HPTLC, UHPLC-UV, 1H NMR spectroscopy, and LC-MS as orthogonal phytochemical methods. The cleanup process adequately preserves the metabolomic diversity as well as the integrity of the original extracts. This method was found to be sufficiently rapid for the “degreening” of botanical extracts in higher-throughput sample preparation for further biological screening.

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.

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 notion of data transparency is gaining a strong awareness among the scientific community. The availability of raw data is actually regarded as a fundamental way to advance science by promoting both integrity and reproducibility of research outcomes. Particularly, in the field of natural product and chemical research, NMR spectroscopy is a fundamental tool for structural elucidation and quantification (qNMR). As such, the accessibility of original NMR data, i.e., Free Induction Decays (FIDs), fosters transparency in chemical research and optimizes both peer review and reproducibility of reports by offering the fundamental tools to perform efficient structural verification. Although original NMR data are known to contain a wealth of information, they are rarely accessible along with published data. This viewpoint discusses the relevance of the availability of original NMR data as part of good research practices not only to promote structural correctness, but also to enhance traceability and reproducibility of both chemical and biological results.