Combining PARAFAC Analysis of HPLC-PDA Profiles and Structural Characterization Using HPLC-PDA-SPE-NMR-MS Experiments: Commercial Preparations of St. John's Wort

Application of PLS-NN model based on mid-infrared spectroscopy in the origin identification of Cornus officinalis

Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of Cornus officinalis samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, F1-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of Cornus officinalis with an accuracy of 91.9%.

Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics

Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis.

Origin identification of Cornus officinalis based on PCA-SVM combined model

Infrared spectroscopy can quickly and non-destructively extract analytical information from samples. It can be applied to the authenticity identification of various Chinese herbal medicines, the prediction of the mixing amount of defective products, and the analysis of the origin. In this paper, the spectral information of Cornus officinalis from 11 origins was used as the research object, and the origin identification model of Cornus officinalis based on mid-infrared spectroscopy was established. First, principal component analysis was used to extract the absorbance data of Cornus officinalis in the wavenumber range of 551~3998 cm-1. The extracted principal components contain more than 99.8% of the information of the original data. Second, the extracted principal component information was used as input, and the origin category was used as output, and the origin identification model was trained with the help of support vector machine. In this paper, this combined model is called PCA-SVM combined model. Finally, the generalization ability of the PCA-SVM model is evaluated through an external test set. The three indicators of Accuracy, F1-Score, and Kappa coefficient are used to compare this model with other commonly used classification models such as naive Bayes model, decision trees, linear discriminant analysis, radial basis function neural network and partial least square discriminant analysis. The results show that PCA-SVM model is superior to other commonly used models in accuracy, F1 score and Kappa coefficient. In addition, compared with the SVM model with full spectrum data, the PCA-SVM model not only reduces the redundant variables in the model, but also has higher accuracy. Using this model to identify the origin of Cornus officinalis, the accuracy rate is 84.8%.

Open-Source Chromatographic Data Analysis for Reaction Optimization and Screening

Automation and digitalization solutions in the field of small molecule synthesis face new challenges for chemical reaction analysis, especially in the field of high-performance liquid chromatography (HPLC). Chromatographic data remains locked in vendors' hardware and software components, limiting their potential in automated workflows and data science applications. In this work, we present an open-source Python project called MOCCA for the analysis of HPLC-DAD (photodiode array detector) raw data. MOCCA provides a comprehensive set of data analysis features, including an automated peak deconvolution routine of known signals, even if overlapped with signals of unexpected impurities or side products. We highlight the broad applicability of MOCCA in four studies: (i) a simulation study to validate MOCCA's data analysis features; (ii) a reaction kinetics study on a Knoevenagel condensation reaction demonstrating MOCCA's peak deconvolution feature; (iii) a closed-loop optimization study for the alkylation of 2-pyridone without human control during data analysis; (iv) a well plate screening of categorical reaction parameters for a novel palladium-catalyzed cyanation of aryl halides employing O-protected cyanohydrins. By publishing MOCCA as a Python package with this work, we envision an open-source community project for chromatographic data analysis with the potential of further advancing its scope and capabilities.

Discovery of unreported ginkgolides of anti-PAF activity using characteristic ion and neutral loss recognition strategy in Ginkgo biloba L

Ginkgolides are the most important bioactive components of Ginkgo biloba L, of which ginkgolide B has been successfully developed and marketed as a drug. The reported ginkgolides are very rare and exhibit a complex matrix due to the chemodiversity of Ginkgo biloba L. Herein, the global profile of characteristic ion and neutral loss recognition strategy were used for to discover eight undescribed ginkgolides, very rare cyclohexane ginkgolides R-V, ginkgolides D-F, and eight known ginkgolides. These ginkgolides were target isolated and identified using high-resolution mass spectrometry, nuclear magnetic resonance spectroscopy, and X-ray crystallography. The undescribed and known ginkgolides exhibited antiplatelet aggregation activities. In particular, compounds U and D had IC₅₀ values of 2.20 ± 0.15 and 6.50 ± 0.87 μM, respectively. This study has enriched the known structural diversity of ginkgolides and extended the application of mass spectrometry to the global profiling of natural products present in Ginkgo biloba L. Moreover, it could help chemists rapidly discover unreported compounds from a complex matrix.

Quality evaluation of commercial herbal products using chemical methods

Herbal products comprise a wide spectrum of locally, nationally or internationally commercialized commodities. As these products have an increasingly important position in healthcare systems worldwide, a detailed product quality assessment is of crucial importance. For the quality evaluation of commercial herbal products, a wide range of methods were used, from simpler, quicker, and cost-effective HPTLC, to hyphenated methods with MS or NMR, where more precise quantification or specific structural information is required. Additionally, most of the methods have been coupled with chemometric tools, such as PCA, or PDA, for the multivariate analysis of the high amount of data generated by chromatograms, electropherograms or spectra. The chemical methods have revealed the widespread presence of low or variable quality herbal products in the marketplace. The majority of analytical investigations present major, qualitative and quantitative, inter-product variations of their chemical composition, ranging from missing ingredients, to strikingly and unnaturally high concentrations of some compounds. Moreover, the inter-batch quality variations were frequently reported, as well as the presence of some undesirable substances. The chemical analysis of herbal products is a vital component to raise the overall awareness of quality in the herbal market and generate a quality driven approach.

Multiway resolution of spectrochromatographic measurements for the quantification of echinuline in marine-derived fungi Aspergillus chevalieri using parallel factor analysis

A multiway resolution of incomplete chromatographic separation was presented for spectrochromatographic quantification of echinuline in marine-derived fungi Aspergillus chevalieri. Two-dimensional spectrochromatographic maps of calibration, validation and real samples were recorded as a function of time and wavelength using UPLC-PDA instrument under non-optimized chromatographic conditions, which gave rise to co-elution of echinuline and the constituents of sample matrix. A three-way array was obtained by concatenating the data matrices of the spectrochromatographic maps. Then, parallel factor analysis was applied to the multiway array to extract the individual contribution of echinuline in three modes (time, wavelength and sample). While time and wavelength profiles were used for the characterization of echinuline, the sample profile was used for its quantitative determination of the analyte in validation set and in real samples. Validity of the analytical method was evaluated by analyzing the validation set, which consist of test samples, standard addition samples, intra-day and inter-day samples. The proposed multiway analysis method was then applied to marine-derived fungi extracts and echinuline content was found to be 31.9 µg/g based on the average of ten assay results. The assay results provided by PARAFAC model were statistically compared with those obtained by a newly developed classical UPLC method, which ensured the complete separation of echinuline in a run time of nine minutes. The assay results were found to be comparable due to the fact that there was no significant difference between the analysis results (F = 1.63, Fcrit = 3.17; t = 0.69, tcrit = 2.11) at the significance level of 95%). Consequently, the PARAFAC method permitted the accurate determination of echinuline in fungal extracts despite the partial chromatographic separation with a run time of only three minutes.

Chemometrics and Related Fields in Python

The Python programing language is becoming a promising tool for data analysis in various fields. However, little attention has been paid to using Python in the field of analytical chemistry, though recent advances in instrumental analysis require robust and reliable data analysis. In order to overcome the difficulty in accurate analysis, multivariate analysis, or chemometrics, has been widely applied to various kinds of data obtained by instrumental analysis. In the present work, the potential usefulness of Python for chemometrics and related fields in chemistry is reviewed. Many practical tools for chemometrics, e.g., principal component analysis (PCA), partial least squares (PLS), support vector machine (SVM), etc., are included in the scikit-learn machine learning (ML) library for Python. Other useful libraries such as pyMCR for multivariate curve resolution (MCR), 2Dpy for two-dimensional correlation spectroscopy (2D-COS), etc. can be obtained from GitHub. For these reasons, a computational environment for chemometrics is easily constructed in Python.

Potential of Sorbus berry extracts for management of type 2 diabetes: Metabolomics investigation of 1H NMR spectra, α-amylase and α-glucosidase inhibitory activities, and in vivo anti-hyperglycaemic activity of S. norvegica

ETHNOPHARMACOLOGICAL RELEVANCE

Berries of Sorbus species have been used to treat type 2 diabetes in many regions in Europe.

AIMS OF THE STUDY

To investigate the inhibitory activity of berry extract of Sorbus on the digestive enzymes α-amylase and α-glucosidase, two important targets for management of blood glucose for type 2 diabetics. Furthermore, to test the anti-hyperglycaemic potential of S. norvegica berry extract in vivo.

MATERIALS AND METHODS

70% acetone berry extracts of 16 Sorbus species were tested in vitro for inhibition of α-amylase and α-glucosidase. Single berry extracts were analysed by ¹H-NMR spectroscopy and principal component analysis to evaluate the chemical profiles of the extracts. The anti-hyperglycaemic effect was evaluated in an oral starch tolerance test in STZ-treated C57BL/6 mice.

RESULTS

The lowest IC₅₀ values against α-amylase and α-glucosidase were obtained with the Sorbus species belonging to the subspecies Aria, which have simple leaves compared to pinnately compound leaves of the other Sorbus species. Species belonging to subspecies Aria grouped together and away from the other Sorbus species in the score plot, indicating a difference in chemistry. Both the carbohydrate- and polyphenol-fraction contributed to the enzyme inhibition. Extract of the most active species, S. norvegica, had anti-hyperglycaemic activity, at a level 36 times lower than clinically used acarbose, corresponding to a needed daily dose of 900 mg extract.

CONCLUSIONS

Sorbus species of subspecies Aria have the potential to be used for management of type 2 diabetes.

Inhibitory Effects of Bioassay-Guided Isolation of Anti-Glycation Components from Taraxacum coreanum and Simultaneous Quantification

Inhibition of the formation of advanced glycation end products (AGEs) is an attractive strategy in diabetes treatment. Taraxacum coreanum extracts were suggested to have antidiabetic effects. However, studies on the components of T. coreanum are lacking, and there is no report on the inhibitory effects of T. coreanum on the formation of AGEs. Therefore, T. coreanum extracts and fractions were tested for their inhibitory effects on α-glucosidase and AGEs formation in two systems (bovine serum albumin (BSA)⁻glucose and BSA⁻methylglyoxal (MGO)). Bioassay-guided isolation of compounds from T. coreanum led to six flavones (1⁻6) and four hydroxycinnamic acid derivatives (7⁻11). Compound 11 exhibited the highest inhibitory activity against α-glucosidase and AGEs formation and had the highest content in T. coreanum extract. All compounds except compound 9 showed a stronger inhibition than the positive control in the BSA-glucose and BSA-MGO system. In addition, T. coreanum showed a higher content of bioactive compounds and stronger inhibition of AGE formation and α-glucosidase activity than T. officinale. Our study demonstrated the preventive and therapeutic efficacy of T. coreanum and its potential use as a cost-effective phytopharmaceutical in complementary therapy against type-2 diabetes and its complications.

Optimized and Validated HPLC Analysis of St. John's Wort Extract and Final Products by Simultaneous Determination of Major Ingredients

Aim of this work was to develop a validated high performance liquid chromatography method for the analysis of extracts and final products of St. John's wort, according to international guidelines for bioanalytical method validation. Chromatographic separation was performed on a C18 column with a combination of gradient and isocratic steps; the mobile phase composed of ammonium acetate solution (pH 4.5; 10 mM), acetonitrile and methanol. Quantification and method validation was performed using extract spiked with external reference standards of chlorogenic acid, rutin, hyperoside, isoquercitrin, quercetin and hypericin. Validation study revealed that trans-chlorogenic acid is partially transformed into its cis-isomer during analysis. The method showed good linearity, precision and accuracy. Hyperforin was completely unstable. All other ingredients were stable at -18°C and after three freeze-thaw cycles, while stability of most ingredients was limited at room temperature and 4 - 8°C; quercetin was the most unstable one. The major ingredients of methanolic extracts, infusions and final products of Hypericum perforatum were completely resolved and quantified. Beyond its potential usefulness in the analysis of St. John's wort products, this study addresses the issue of validation from the perspective of the field of bioanalysis and reveals the wealth of critical information which can be derived.

Inhibition of human monoamine oxidase A and B by flavonoids isolated from two Algerian medicinal plants

BACKGROUND

Monoamine oxidases (MAOs) are outer mitochondrial membrane flavoenzymes. They catalyze the oxidative deamination of a variety of neurotransmitters. MAO-A and MAO-B may be considered as targets for inhibitors to treat neurodegenerative diseases and depression and for managing symptoms associated with Parkinson's and Alzheimer's diseases.

PURPOSE

The objective was to evaluate the inhibitory effect of Hypericum afrum and Cytisus villosus against MAO-A and B and to isolate the compounds responsible for the MAO-inhibitory activity.

METHODS

The inhibitory effect of extracts and purified constituents of H. afrum and C. villosus were investigated in vitro using recombinant human MAO-A and B, and through bioassay-guided fractionation of ethyl acetate fractions of areal parts of the two plants collected in northeastern Algeria. In addition, computational protein-ligand docking and molecular dynamics simulations were carried out to explain the MAO binding at the molecular level.

RESULTS

The ethyl acetate (EtOAc) fractions of H. afrum and C. villosus showed the highest MAO inhibition activity against MAO A and B with IC50 values of 3.37 µg/ml and 13.50 µg/ml as well as 5.62 and 1.87 µg/ml, respectively. Bioassay-guided fractionation of the EtOAc fractions resulted in the purification and identification of the known flavonoids quercetin, myricetin, genistein and chrysin as the principal MAO-inhibitory constituents. Their structures were established by extensive 1 and 2D NMR studies and mass spectrometry. Quercetin, myricetin and chrysin showed potent inhibitory activity towards MAO-A with IC50 values of 1.52, 9.93 and 0.25 µM, respectively, while genistein more efficiently inhibited MAO-B (IC50 value: 0.65 µM). The kinetics of the inhibition and the study of dialysis dissociation of the complex of quercetin and myricetin and the isoenzyme MAO-A showed competitive and mixed inhibition, respectively. Both compounds showed reversible binding. Molecular docking experiments and molecular dynamics simulations allowed to estimate the binding poses and to identify the most important residues involved in the selective recognition of molecules in the MAOs enzymatic clefts.

CONCLUSION

Quercetin and myricetin isolated from H. afrum together with genistein and chrysin isolated from C. villosus have been identified as potent MAO-A and -B inhibitors. H. afrum and C. villosus have properties indicative of potential neuroprotective ability and may be new candidates for selective MAO-A and B inhibitors.

The One-Sample PARAFAC Approach Reveals Molecular Size Distributions of Fluorescent Components in Dissolved Organic Matter

Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM) spectroscopy in full spectral (60 emission and 34 excitation wavelengths) and chromatographic resolution (<1 Hz), to enable the mathematical decomposition of fluorescence on an individual sample basis by parallel factor analysis (PARAFAC). The approach allowed cross-system comparisons of molecular size distributions for individual fluorescence components obtained from independent data sets. Spectra extracted from allochthonous DOM were highly similar. Allochthonous and autochthonous DOM shared some spectra, but included unique components. In agreement with the supramolecular assembly hypothesis, molecular size distributions of the fluorescence fractions were broad and chromatographically unresolved, possibly representing reoccurring fluorophores forming noncovalently bound assemblies of varying molecular size. Samples shared underlying fluorescence components that differed in their size distributions but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical opportunities for elucidating the origins and biogeochemical properties of FDOM.

Quality control of Hypericum perforatum L. analytical challenges and recent progress

Objectives

The most widely applied qualitative and quantitative analytical methods in the quality control of Hypericum perforatum extracts will be reviewed, including routine analytical tools and most modern approaches.

Key findings

Biologically active components of H. perforatum are chemically diverse; therefore, different chromatographic and detection methods are required for the comprehensive analysis of St. John's wort extracts. Naphthodianthrones, phloroglucinols and flavonoids are the most widely analysed metabolites of this plant. For routine quality control, detection of major compounds belonging to these groups seems to be sufficient; however, closer characterization requires the detection of minor compounds as well.

Conclusions

TLC and HPTLC are basic methods in the routine analysis, whereas HPLC-DAD is the most widely applied method for quantitative analysis due to its versatility. LC-MS is gaining importance in pharmacokinetic studies due to its sensitivity. Modern approaches, such as DNA barcoding, NIRS and NMR metabolomics, may offer new possibilities for the more detailed characterization of secondary metabolite profile of H. perforatum extracts.

Community analysis of pigment patterns from 37 microalgae strains reveals new carotenoids and porphyrins characteristic of distinct strains and taxonomic groups

Phytoplankton, with an estimated 30 000 to 1 000 000 species clustered in 12 phyla, presents a high taxonomic and ecophysiological diversity, reflected by the complex distribution of pigments among the different algal classes. High performance liquid chromatography is the gold standard method for qualitative and quantitative analysis of phytoplankton pigments in seawater and culture samples, but only a few pigments can be used as robust chemotaxonomic markers. A major challenge is thus to identify new ones, characteristic of a strain, species, class or taxon that cannot be currently identified on the basis of its pigment signature. Using an optimized extraction process coupled to a HPLC de-replication strategy, we examined the pigment composition of 37 microalgae strains, representative of the broad taxonomic diversity of marine and freshwater species (excluding cyanobacteria). For each species, the major pigments already described were unambiguously identified. We also observed the presence of several minor unidentified pigments in each chromatogram. The global analysis of pigment compositions revealed a total of 124 pigments, including 98 pigments or derivatives unidentified using the standards. Absorption spectra indicated that 35 corresponded to chlorophyll/porphyrin derivatives, 57 to carotenoids and six to derivatives having both spectral signatures. Sixty-one of these unidentified or new carotenoids and porphyrin derivatives were characteristic of particular strains or species, indicating their possible use as highly specific chemotaxonomic markers capable of identifying one strain out of the 37 selected. We developed a graphical analysis using Gephi software to give a clear representation of pigment communities among the various phytoplankton strains, and to reveal strain-characteristic and shared pigments. This made it possible to reconstruct the taxonomic evolution of microalgae classes, on the basis of the conservation, loss, and/or appearance of pigments.

Total synthesis of I3,II8-biapigenin and ridiculuflavone A

The first total synthesis of I3,II8-biapigenin and ridiculuflavone A was achieved via Sonogashira and rhodium-catalyzed oxidative coupling as the key steps.

Comparison of analytical techniques for the identification of bioactive compounds from natural products

Covering: 2000 to 2016Natural product extracts are a rich source of bioactive compounds. As a result, the screening of natural products for the identification of novel biologically active metabolites has been an essential part of several drug discovery programs. It is estimated that more than 70% of all drugs approved from 1981 and 2006, were either derived from or structurally similar to nature based compounds indicating the necessity for the development of a rapid method for the identification of novel compounds from plant extracts. The screening of biological matrices for the identification of novel modulators is nevertheless still challenging. In this review we discuss current techniques in phytochemical analysis and the identification of biologically active components.

High-resolution PTP1B inhibition profiling combined with high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction-nuclear magnetic resonance spectroscopy: Proof-of-concept and antidiabetic constituents in crude extract of Eremophila lucida

Type 2 diabetes (T2D) constituted 90% of the global 387 million diabetes cases in 2014. The enzyme protein-tyrosine phosphatase 1B (PTP1B) has been recognized as a therapeutic target for treatment of T2D and its adverse complications. With the aim of accelerating the investigation of complex natural sources, such as crude plant extracts, for potential PTP1B inhibitors, we have developed a bio-analytical platform combining high-resolution PTP1B inhibition profiling and high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction-nuclear magnetic resonance spectroscopy, i.e., HR-bioassay/HPLC-HRMS-SPE-NMR. Human recombinant PTP1B enzyme was used for the microplate-based PTP1B inhibition assay, which was optimized for pH and substrate concentration to be compatible with rate measurements within the 10 min incubation time. Subsequently, analytical-scale HPLC-based microfractionation followed by colorimetric microplate-based PTP1B bioassaying enabled construction of a high-resolution inhibition profile corresponding to the HPLC profile. The high-resolution PTP1B inhibition profiling was validated using an artificial mixture of known PTP1B inhibitors and non-inhibiting compounds as negative controls. Finally, a proof-of-concept study with a real sample was performed using crude ethyl acetate extract of the phytochemically hitherto unexplored plant Eremophila lucida. This led to the identification of the first viscidane type diterpene, i.e., 5-hydroxyviscida-3,14-dien-20-oic acid (9) as PTP1B inhibitor with an IC50 value of 42.0 ± 5.9 μM. In addition, a series of flavonoids, i.e., luteolin (1), dinatin (3a), tricin (3b), 3,6-dimethoxyapigenin (4), jaceidin (5), and cirsimaritin (6) as well as a cembrene diterpene, (3Z, 7E, 11Z)-15-hydroxycembra-3,7,11-trien-19-oic acid (8), were also identified for the first time from E. lucida.

Hyperforin production in Hypericum perforatum root cultures

Extracts of the medicinal plant Hypericum perforatum are used to treat depression and skin irritation. A major API is hyperforin, characterized by sensitivity to light, oxygen and temperature. Total synthesis of hyperforin is challenging and its content in field-grown plants is variable. We have established in vitro cultures of auxin-induced roots, which are capable of producing hyperforin, as indicated by HPLC-DAD and ESI-MS analyses. The extraction yield and the productivity upon use of petroleum ether after solvent screening were ∼5 mg/g DW and ∼50 mg/L culture after six weeks of cultivation. The root cultures also contained secohyperforin and lupulones, which were not yet detected in intact plants. In contrast, they lacked another class of typical H. perforatum constituents, hypericins, as indicated by the analysis of methanolic extracts. Hyperforins and lupulones were stabilized and enriched as dicyclohexylammonium salts. Upon up-scaling of biomass production and downstream processing, H. perforatum root cultures may provide an alternative platform for the preparation of medicinal extracts and the isolation of APIs.

Global Profiling and Novel Structure Discovery Using Multiple Neutral Loss/Precursor Ion Scanning Combined with Substructure Recognition and Statistical Analysis (MNPSS): Characterization of Terpene-Conjugated Curcuminoids in Curcuma longa as a Case Study

To fully understand the chemical diversity of an herbal medicine is challenging. In this work, we describe a new approach to globally profile and discover novel compounds from an herbal extract using multiple neutral loss/precursor ion scanning combined with substructure recognition and statistical analysis. Turmeric (the rhizomes of Curcuma longa L.) was used as an example. This approach consists of three steps: (i) multiple neutral loss/precursor ion scanning to obtain substructure information; (ii) targeted identification of new compounds by extracted ion current and substructure recognition; and (iii) untargeted identification using total ion current and multivariate statistical analysis to discover novel structures. Using this approach, 846 terpecurcumins (terpene-conjugated curcuminoids) were discovered from turmeric, including a number of potentially novel compounds. Furthermore, two unprecedented compounds (terpecurcumins X and Y) were purified, and their structures were identified by NMR spectroscopy. This study extended the application of mass spectrometry to global profiling of natural products in herbal medicines and could help chemists to rapidly discover novel compounds from a complex matrix.

Magnetic Ligand Fishing as a Targeting Tool for HPLC-HRMS-SPE-NMR: α-Glucosidase Inhibitory Ligands and Alkylresorcinol Glycosides from Eugenia catharinae

A bioanalytical platform combining magnetic ligand fishing for α-glucosidase inhibition profiling and HPLC-HRMS-SPE-NMR for structural identification of α-glucosidase inhibitory ligands, both directly from crude plant extracts, is presented. Magnetic beads with N-terminus-coupled α-glucosidase were synthesized and characterized for their inherent catalytic activity. Ligand fishing with the immobilized enzyme was optimized using an artificial test mixture consisting of caffeine, ferulic acid, and luteolin before proof-of-concept with the crude extract of Eugenia catharinae. The combination of ligand fishing and HPLC-HRMS-SPE-NMR identified myricetin 3-O-α-L-rhamnopyranoside, myricetin, quercetin, and kaempferol as α-glucosidase inhibitory ligands in E. catharinae. Furthermore, HPLC-HRMS-SPE-NMR analysis led to identification of six new alkylresorcinol glycosides, i.e., 5-(2-oxopentyl)resorcinol 4-O-β-D-glucopyranoside, 5-propylresorcinol 4-O-β-D-glucopyranoside, 5-pentylresorcinol 4-O-[α-D-apiofuranosyl-(1→6)]-β-D-glucopyranoside, 5-pentylresorcinol 4-O-β-D-glucopyranoside, 4-hydroxy-3-O-methyl-5-pentylresorcinol 1-O-β-D-glucopyranoside, and 3-O-methyl-5-pentylresorcinol 1-O-[β-D-glucopyranosyl-(1→6)]-β-D-glucopyranoside.

Fungal plasma membrane H⁺-ATPase inhibitory activity of o-hydroxybenzylated flavanones and chalcones from Uvaria chamae P. Beauv

In our ongoing efforts of finding natural fungicides to fight food and feed spoilage during production and storage, the antifungal potential of Ghanaian Uvaria chamae P. Beauv. was investigated, with emphasis on plant metabolites targeting the fungal plasma membrane (PM) H(+)-ATPase. Ethyl acetate extract of U. chamae was subjected to high-resolution fungal PM H(+)-ATPase inhibition screening followed by structural elucidation by high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction-nuclear magnetic resonance spectroscopy (HPLC-HRMS-SPE-NMR). This led to identification of a series of uncommon o-hydroxybenzylated flavanones and chalcones, i.e., chamanetin (8), isochamanetin (9), isouvaretin (10), uvaretin (11), dichamanetin (12), and diuvaretin (15). Preparative-scale isolation of the active metabolites allowed determination of IC50 values for inhibition of the PM H(+)-ATPase, and growth inhibition of Saccharomyces cerevisiae and Candida albicans. These revealed a strong correlation between o-hydroxybenzyl substituents and PM H(+)-ATPase activity, with dichamanetin being the most potent compound, but showing moderate activity in the fungal growth inhibition assays.

Structure Elucidation of the Metabolites of 2', 3', 5'-Tri-O-Acetyl-N6-(3-Hydroxyphenyl) Adenosine in Rat Urine by HPLC-DAD, ESI-MS and Off-Line Microprobe NMR

2', 3', 5'-Tri-O-acetyl-N6-(3-hydroxyphenyl) adenosine (also known as WS070117) is a new adenosine analog that displays anti-hyperlipidemic activity both in vitro and in vivo experiments as shown in many preliminary studies. Due to its new structure, little is known about the metabolism of WS070117. Hence, the in vivo metabolites of WS070117 in rat urine following oral administration were investigated. Identification of the metabolites was conducted using the combination of high-performance liquid chromatography (HPLC) coupled with diode array detector (DAD), ion trap electrospray ionization-mass spectrometry (ESI-MS), and off-line microprobe nuclear magnetic resonance (NMR) measurements. Seven metabolites were obtained as pure compounds at the sub-milligram to milligram levels. Results of structure elucidation unambiguously revealed that the phase I metabolite, N6-(3-hydroxyphenyl) adenosine (M8), was a hydrolysate of WS070117 by hydrolysis on the three ester groups. N6-(3-hydr-oxyphenyl) adenine (M7), also one of the phase I metabolites, was the derivative of M8 by the loss of ribofuranose. In addition to two phase I metabolites, there were five phase II metabolites of WS070117 found in rat urine. 8-hydroxy-N6-(3-hydroxy-phenyl) adenosine (M6) was the product of M7 by hydrolysis at position 8. The other four were elucidated to be N6-(3-O-β-D-glucuronyphenyl) adenine (M2), N8-hydroxy-N6-(3-O-sulfophenyl) adenine (M3), N6-(3-O-β-D-glucuronyphenyl) adenosine (M4), and N6-(3-O- sulfophenyl) adenosine (M5). Phase II metabolic pathways were proven to consist of hydroxylation, glucuronidation and sulfation. This study provides new and valuable information on the metabolism of WS070117, and also demonstrates the HPLC/MS/off-line microprobe NMR approach as a robust means for rapid identification of metabolites.

Combined use of high-resolution α-glucosidase inhibition profiling and high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction-nuclear magnetic resonance spectroscopy for investigation of antidiabetic principles in crude plant extracts

Type 2 diabetes is a metabolic disorder affecting millions of people worldwide, and new drug leads or functional foods containing selective α-glucosidase inhibitors are needed. Crude extract of 24 plants were assessed for α-glucosidase inhibitory activity. Methanol extracts of Cinnamomum zeylanicum bark, Rheum rhabarbarum peel, and Rheum palmatum root and ethyl acetate extracts of C. zeylanicum bark, Allium ascalonicum peel, and R. palmatum root showed IC50 values below 20 μg/mL. Subsequently, high-resolution α-glucosidase profiling was used in combination with high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction-nuclear magnetic resonance spectroscopy for identification of metabolites responsible for the α-glucosidase inhibitory activity. Quercetin (1) and its dimer (2), trimer (3), and tetramer (4) were identified as main α-glucosidase inhibitors in A. ascalonicum peel, whereas (E)-piceatannol 3'-O-β-D-glucopyranoside (5), (E)-rhapontigenin 3'-O-β-D-glucopyranoside (6), (E)-piceatannol (8), and emodin (12) were identified as main α-glucosidase inhibitors in R. palmatum root.

High-resolution screening combined with HPLC-HRMS-SPE-NMR for identification of potential health-promoting constituents in sea aster and searocket--new Nordic food ingredients

Sea aster (Aster tripolium L.) and searocket (Cakile maritima Scop.), potential ingredients in the New Nordic Diet, were analyzed by high-resolution radical scavenging and high-resolution α-glucosidase inhibition assays. Results from the two bioactivity profiles were used to guide subsequent structural analysis toward constituents with potential health-promoting effects. Structural analysis was performed by high-performance liquid chromatography-high-resolution mass spectrometry-solid-phase extraction and automated tube transfer nuclear magnetic resonance spectroscopy, that is, HPLC-HRMS-SPE-ttNMR. High-resolution mass spectrometry together with detailed analysis of one- and two-dimensional proton detected NMR experiments enabled unambiguous assignment of the targeted analytes. This revealed a series of caffeoyl esters (1, 2, 5), flavonoid glycosides (3, 4, 6, 11-15), flavonoids (7-9), sinapate esters (10, 16, 17), and sinapinic acid (18) associated with radical scavenging and/or α-glucosidase inhibition. In vitro assays implemented in this study showed that sea aster holds potential as a future functional food ingredient for lowering postprandial blood glucose level for diabetics, but further investigations are needed to prove the effect in vivo.

Biflavonoids, Main Constituents from Garcinia Bakeriana Leaves

The genus Garcinia is a source of a large variety of organic compounds including biflavonoids, acylphloroglucinols and xanthones mainly, but few data are available about the chemical composition of Cuban species. The aim of this investigation was to identify the main constituents of G. bakeriana Urb., a rare Cuban endemic plant. A new biflavonoid, 4″’- O-methyl-I3,II8-biapigenin (1), together with 9 known compounds, namely, the biflavonoids amentoflavone (2), 4″’- O-methylamentoflavone (3), 4′- O-methylcupressuflavone (4), GB-2a (5), volkensiflavone (6), 6″-(2-hydroxy-3-methyl-3-butenyl)-amentoflavone (7), I3,II8-biapigenin (8), and GB-1a (9), and the xanthone norathyriol (10), were isolated from the leaves of this species. All the structures were elucidated by spectroscopic methods including 1D and 2D NMR experiments, as well as ESIMS analysis. These results showed that the isolated biflavonoids possess a C-C interflavonoid linkage between the apigenin units or its derivatives.

HPLC-NMR revisited: using time-slice high-performance liquid chromatography-solid-phase extraction-nuclear magnetic resonance with database-assisted dereplication

Time-based trapping of chromatographically separated compounds onto solid-phase extraction (SPE) cartridges and subsequent elution to NMR tubes was done to emulate the function of HPLC-NMR for dereplication purposes. Sufficient mass sensitivity was obtained by use of a state-of-the-art HPLC-SPE-NMR system with a cryogenically cooled probe head, designed for 1.7 mm NMR tubes. The resulting (1)H NMR spectra (600 MHz) were evaluated against a database of previously acquired and prepared spectra. The in-house-developed matching algorithm, based on partitioning of the spectra and allowing for changes in the chemical shifts, is described. Two mixtures of natural products were used to test the approach: an extract of Carthamus oxyacantha (wild safflower), containing an array of spiro compounds, and an extract of the endophytic fungus Penicillum namyslowski, containing griseofulvin and analogues. The database matching of the resulting spectra positively identified expected compounds, while the number of false positives was few and easily recognized.

Application of parallel factor analysis to total synchronous fluorescence spectrum of dilute multifluorophoric solutions: addressing the issue of lack of trilinearity in total synchronous fluorescence data set

In recent years, total synchronous fluorescence (TSF) spectroscopy has become popular for the analysis of multifluorophoric systems. Application of PARAFAC, a popular deconvolution tool, requires trilinear structure in the three-way data array. The present work shows that TSF based three-way array data set of dimension sample × wavelength × Δλ does not have trilinear structure and hence it should not be subjected to PARAFAC analysis. This work also proposes that a TSF data set can be converted to an excitation-emission matrix fluorescence (EEMF) like data set which has trilinear structure, so that PARAFAC analysis can be performed on it. This also enables the retrieval of PARAFAC-separated component TSF spectra.

Isolation of mono-caffeoylquinic acids from tobacco waste using continuous resin-based pre-separation and preparative HPLC

Three isomers of mono-caffeoylquinic acid, specifically, 3-O-caffeoylquinic acid, 4-O-caffeoylquinic acid and 5-O-caffeoylquinic acid, were successfully isolated from a crude extract of tobacco (Nicotiana tobaccum L.) wastes using continuous resin-based pre-separation and preparative high-performance liquid chromatography (HPLC). The extract of tobacco wastes was continuously pre-separated by resin-based columns packed with D101 and XAD-4, yielding total mono-caffeoylquinic acids with a purity of 67.71% and a recovery rate of 90.06%. Variables affecting resolution and productivity of three mono-caffeoylquinic acid isomers in preparative HPLC (i.e. mobile-phase composition, pH, flow rate and loading amount) were studied. The optimum chromatographic conditions were determined to be a mobile phase consisting of 15% (v/v) methanol and aqueous acetic acid with a pH of 4.5, a flow rate of 4.0 mL/min, a loading amount of 4 mL and a detection wavelength of 360 nm. From 300 mg of loading sample, 56.3 mg of 3-O-caffeoylquinic acid, 92.8 mg of 5-O-caffeoylquinic acid and 73.1 mg of 4-O-caffeoylquinic acid were obtained in a single run, each with a purity of over 98% by HPLC. The structures of the isolated compounds were elucidated by ESI-MS, (1) H-NMR and (13) C-NMR spectral data.

Metabolic profiling based on two-dimensional J-resolved 1H NMR data and parallel factor analysis

Metabolic profiling of natural products is used to map correlated concentration variances of known and unknown secondary metabolites in extracts. NMR-spectroscopy is in this respect regarded as a convenient and reproducible technique with the ability to detect a wide range of small organic compounds. Two-dimensional J-resolved NMR-spectra are used in this context to resolve overlapping signals by separating the effect of J-coupling from the effect of chemical shifts. Often one-dimensional projections of these data are used as input for standard multivariate statistical methods, and only the intensity variances along the chemical shift axis are taken into account. Here, we describe the use of parallel factor analysis (PARAFAC) as a tool to preprocess a set of two-dimensional J-resolved spectra with the aim of keeping the J-coupling information intact. PARAFAC is a mathematical decomposition method that fits three-way experimental data to a model whose parameters in this case reflect concentrations and individual component spectra along the chemical shift axis and corresponding profiles along the J-coupling axis. A set of saffron samples, directly extracted with methanol-d(4), were used as a model system to evaluate the feasibility and merits of the method. To successfully use PARAFAC, the two-dimensional spectra (n = 96) had to be aligned and processed in narrow windows (0.04 ppm wide) along the chemical shift axis. Selection of windows and number of components for each PARAFAC-model was done automatically by evaluating amount of explained variance and core consistency values. Score plots showing the distribution of objects in relation to each other, and loading plots in the form of two-dimensional pseudospectra with the same appearance as the original J-resolved spectra but with positive and negative contributions are presented. Loadings are interpreted not only in terms of signals with different chemical shifts but also the associated J-coupling profiles.

Isolation and purification of series bioactive components from Hypericum perforatum L. by counter-current chromatography

Counter-current chromatography (CCC) combined with pre-separation by ultrasonic solvent extraction was successively used for the separation of series bioactive compounds from the crude extract of Hypericum perforatum L. The petroleum ether extract was separated by the solvent system of n-heptane-methanol-acetonitrile (1.5:0.5:0.5, v/v) and n-heptane-methanol (1.5:1, v/v) in gradient elution, yielding a phloroglucinol compound, hyperforin with HPLC purity over 98%. The ethyl acetate extract was separated by using the solvent system composed of hexane-ethyl acetate-methanol-water (1:1:1:1 and 1:3:1:3, v/v) in gradient through both reverse phase and normal phase elution mode, yielding a naphthodianthrone compound, hypericin with HPLC purity about 95%. The n-butanol extract was separated with the solvent system composed of n-butanol-ethyl acetate-water (1:4:5 and 1.5:3.5:5, v/v) in elution and back-extrusion mode, yielding two of flavones, rutin and hyperoside, with HPLC purity over 95%. HPLC-MS, reference sample and UV spectrum were selectively used in separation to search for target compounds from HPLC-DAD profiles of different sub-extracts. The structures of isolated compounds were further identified by ESI-MS, ¹HNMR and ¹³CNMR.

Highly variable contents of phenolics in St. John's Wort products affect their transport in the human intestinal Caco-2 cell model: pharmaceutical and biopharmaceutical rationale for product standardization

The purposes of this study were to determine content uniformity of phenolics in the St. John's wort (SJW) supplements and to demonstrate how variations in the product matrices affect their absorption and efflux. LC and LC-MS/MS methods were used to determine the phenolic contents of 12 different products purchased locally or from the Internet. Three representative extracts were further submitted to Caco-2 cell transport experiment, and transport of rutin, hyperoside, and isoquercitrin was evaluated. The results indicated that the 12 different products displayed 12 different HPLC fingerprints, but all products contained the following major compounds: rutin, hyperoside, isoquercitrin, quercitrin, quercetin, and amentoflavone. The content uniformity of these major compounds was poor across products, with the smallest difference in the amounts of amentoflavone (3.6-fold) and largest difference in that of isoquercitrin (28.8-fold). The Caco-2 experiments indicated transport of rutin in products was vectorial, with the permeabilities varied about 3.6-fold in both directions of transport. The vectorial permeabilities of hyperoside and isoquercitrin were similarly different. Use of efflux transporter inhibitor studies suggested that MRP2 was involved in isoquercitrin's efflux and the product matrix affected the extent of its efflux. In conclusion, different SJW supplements had highly variable contents of phenolics, and the variability in product matrix and phytochemical compositions affected the permeabilities of key phenolics across the Caco-2 monolayers, which may further affect their bioavailabilities. Therefore, standardization will be necessary to ensure safe and efficacious using of supplements such as SJW.

H NMR-based metabolomics combined with HPLC-PDA-MS-SPE-NMR for investigation of standardized Ginkgo biloba preparations

Commercial preparations of Ginkgo biloba are very complex mixtures prepared from raw leaf extracts by a series of extraction and prepurification steps. The pharmacological activity is attributed to a number of flavonoid glycosides and unique terpene trilactones (TTLs), with largely uncharacterized pharmacological profiles on targets involved in neurological disorders. It is therefore important to complement existing targeted analytical methods for analysis of Ginkgo biloba preparations with alternative technology platforms for their comprehensive and global characterization. In this work, (1)H NMR-based metabolomics and hyphenation of high-performance liquid chromatography, photo-diode array detection, mass spectrometry, solid-phase extraction, and nuclear magnetic resonance spectroscopy (HPLC-PDA-MS-SPE-NMR) were used for investigation of 16 commercially available preparations of Ginkgo biloba. The standardized extracts originated from Denmark, Italy, Sweden, and United Kingdom, and the results show that (1)H NMR spectra allow simultaneous assessment of the content as well as identity of flavonoid glycosides and TTLs based on a very simple sample-preparation procedure consisting of extraction, evaporation and reconstitution in acetone-d(6). Unexpected or unwanted extract constituents were also easily identified in the (1)H NMR spectra, which contrasts traditional methods that depend on UV absorption or MS ionizability and usually require availability of reference standards. Automated integration of (1)H NMR spectral segments (buckets or bins of 0.02 ppm width) provides relative distribution plots of TTLs based on their H-12 resonances. The present study shows that (1)H NMR-based metabolomics is an attractive method for non-selective and comprehensive analysis of Ginkgo extracts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-009-0195-x) contains supplementary material, which is available to authorized users.

Piperidine and tetrahydropyridine alkaloids from Lobelia siphilitica and Hippobroma longiflora

The hyphenated technique HPLC-PDA-MS-SPE-NMR was used to assist targeted preparative-scale isolation of constituents of Lobelia siphilitica and Hippobroma longiflora (both Campanulaceae). This resulted in the isolation of two new alkaloids, (S)-2-[(2S,6R)-1-methyl-6-(2-oxo-2-phenylethyl)piperidin-2-yl]-1-phenylethyl acetate (3) and 6-[(E)-2-(3-methoxyphenyl)ethenyl]-2,3,4,5-tetrahydropyridine (4), the latter possessing a skeleton hitherto unseen among alkaloids of Lobelia and related genera. Lobeline (1), (1S,1'S)-2,2'-[(2R,6S)-1-methylpiperidine-2,6-diyl]bis(1-phenylethanol) (2), and lobetyolin (5) were also isolated. The structures of 1-5 were established using spectroscopic methods including homo- and heteronuclear two-dimensional NMR experiments and optical rotation data.