The Potential of Cannabichromene (CBC) as a Therapeutic Agent.

There is a growing interest in the use of medicinal plants to treat a variety of diseases, and one of the most commonly used medicinal plants globally is Cannabis sativa The two most abundant cannabinoids (Δ9-tetrahydrocannabinol and cannabidiol) have been governmentally approved to treat selected medical conditions; however, the plant produces over 100 cannabinoids, including cannabichromene (CBC). While the cannabinoids share a common precursor molecule, cannabigerol, they are structurally and pharmacologically unique. These differences may engender differing therapeutic potentials. In this review, we will examine what is currently known about CBC with regards to pharmacodynamics, pharmacokinetics, and receptor profile. We will also discuss the therapeutic areas that have been examined for this cannabinoid, notably antinociceptive, antibacterial, and anti-seizure activities. Finally, we will discuss areas where new research is needed and potential novel medicinal applications for CBC. Significance Statement Cannabichromene (CBC) has been suggested to have disparate therapeutic benefits such as anti-inflammatory, anticonvulsant, antibacterial, and antinociceptive effects. Most of the focus on the medical benefits of cannabinoids has been focused on THC and CBD. The preliminary studies on CBC indicate that this phytocannabinoid may have unique therapeutic potential that warrants further investigation. Following easier access to hemp, CBC products are commercially available over-the-counter and are being widely utilized with little or no evidence of their safety or efficacy.

Interaction Metabolomics to Discover Synergists in Natural Product Mixtures.

Mass spectrometry metabolomics has become increasingly popular as an integral aspect of studies to identify active compounds from natural product mixtures. Classical metabolomics data analysis approaches do not consider the possibility that interactions (such as synergy) could occur between mixture components. With this study, we developed "interaction metabolomics" to overcome this limitation. The innovation of interaction metabolomics is the inclusion of compound interaction terms (CITs), which are calculated as the product of the intensities of each pair of features (detected ions) in the data matrix. Herein, we tested the utility of interaction metabolomics by spiking known concentrations of an antimicrobial compound (berberine) and a synergist (piperine) into a set of inactive matrices. We measured the antimicrobial activity for each of the resulting mixtures against Staphylococcus aureus and analyzed the mixtures with liquid chromatography coupled to high-resolution mass spectrometry. When the data set was processed without CITs (classical metabolomics), statistical analysis yielded a pattern of false positives. However, interaction metabolomics correctly identified berberine and piperine as the compounds responsible for the synergistic activity. To further validate the interaction metabolomics approach, we prepared mixtures from extracts of goldenseal (Hydrastis canadensis) and habañero pepper (Capsicum chinense) and correctly correlated synergistic activity of these mixtures to the combined action of berberine and several capsaicinoids. Our results demonstrate the utility of a conceptually new approach for identifying synergists in mixtures that may be useful for applications in natural products research and other research areas that require comprehensive mixture analysis.

A comparison of high- and low-resolution gas chromatography-mass spectrometry for herbal product classification: A case study with Ocimum essential oils.

INTRODUCTION: Selection of marker compounds for targeted chemical analysis is complicated when considering varying instrumentation and closely related plant species. High-resolution gas chromatography-mass spectrometry (GC-MS), via orbitrap detection, has yet to be evaluated for improved marker compound selection. OBJECTIVE: This study directly compares high- and low-resolution GC-MS for botanical maker compound selection using Ocimum tenuiflorum L. (OT) and Ocimum gratissimum L. (OG) for botanical ingredient authentication. METHODS: The essential oils of OT and OG were collected via hydrodistillation before untargeted chemical analysis with gas chromatography coupled to single-quadrupole (GC-SQ) and orbitrap (GC-Orbitrap) detectors. The Global Natural Products Social Molecular Networking (GNPS) software was used for compound annotation, and a manual search was used to find the 41 most common Ocimum essential oil metabolites. RESULTS: The GC-Orbitrap resulted in 1.7-fold more metabolite detection and increased dynamic range compared to the GC-SQ. Spectral matching and manual searching were improved with GC-Orbitrap data. Each instrument had differing known compound concentrations; however, there was an overlap of six compounds with higher abundance in OG than OT and three compounds with a higher abundance in OT than OG, suggesting consistent detection of the most variable compounds. An unsupervised principal component analysis (PCA) could not discern the two species with either dataset. CONCLUSION: GC-Orbitrap instrumentation improves compound detection, dynamic range, and feature annotation in essential oil analysis. However, considering both high- and low-resolution data may improve reliable marker compound selection, as GC-Orbitrap analysis alone did not improve unsupervised separation of two Ocimum species compared to GC-SQ data.

Interlaboratory Comparison of Untargeted Mass Spectrometry Data Uncovers Underlying Causes for Variability.

Despite the value of mass spectrometry in modern natural products discovery workflows, it remains very difficult to compare data sets between laboratories. In this study we compared mass spectrometry data for the same sample set from two different laboratories (quadrupole time-of-flight and quadrupole-Orbitrap) and evaluated the similarity between these two data sets in terms of both mass spectrometry features and their ability to describe the chemical composition of the sample set. Somewhat surprisingly, the two data sets, collected with appropriate controls and replication, had very low feature overlap (25.7% of Laboratory A features overlapping 21.8% of Laboratory B features). Our data clearly demonstrate that differences in fragmentation, charge state, and adduct formation in the ionization source are a major underlying cause for these differences. Consistent with other recent literature, these findings challenge the conventional wisdom that electrospray ionization mass spectrometry (ESI-MS) yields a simple one-to-one correspondence between analytes in solution and features in the data set. Importantly, despite low overlap in feature lists, principal component analysis (PCA) generated qualitatively similar PCA plots. Overall, our findings demonstrate that comparing untargeted metabolomics data between laboratories is challenging, but that data sets with low feature overlap can yield the same qualitative description of a sample set using PCA.

Identification of adulteration in botanical samples with untargeted metabolomics.

Adulteration remains an issue in the dietary supplement industry, including botanical supplements. While it is common to employ a targeted analysis to detect known adulterants, this is difficult when little is known about the sample set. With this study, untargeted metabolomics using liquid chromatography coupled to ultraviolet-visible spectroscopy (LC-UV) or high-resolution mass spectrometry (LC-MS) was employed to detect adulteration in botanical dietary supplements. A training set was prepared by combining Hydrastis canadensis L. with a known adulterant, Coptis chinensis Franch., in ratios ranging from 5 to 95% adulteration. The metabolomics datasets were analyzed using both unsupervised (principal component analysis and composite score) and supervised (SIMCA) techniques. Palmatine, a known H. canadensis metabolite, was quantified as a targeted analysis comparison. While the targeted analysis was the most sensitive method tested in detecting adulteration, statistical analyses of the untargeted metabolomics datasets detected adulteration of the goldenseal samples, with SIMCA providing the greatest discriminating potential. Graphical abstract.

The Chemistry of Kratom [Mitragyna speciosa]: Updated Characterization Data and Methods to Elucidate Indole and Oxindole Alkaloids.

Two separate commercial products of kratom [Mitragyna speciosa (Korth.) Havil. Rubiaceae] were used to generate reference standards of its indole and oxindole alkaloids. While kratom has been studied for over a century, the characterization data in the literature for many of the alkaloids are either incomplete or inconsistent with modern standards. As such, full 1H and 13C NMR spectra, along with HRESIMS and ECD data, are reported for alkaloids 1-19. Of these, four new alkaloids (7, 11, 17, and 18) were characterized using 2D NMR data, and the absolute configurations of 7, 17, and 18 were established by comparison of experimental and calculated ECD spectra. The absolute configuration for the N(4)-oxide (11) was established by comparison of NMR and ECD spectra of its reduced product with those for compound 7. In total, 19 alkaloids were characterized, including the indole alkaloid mitragynine (1) and its diastereoisomers speciociliatine (2), speciogynine (3), and mitraciliatine (4); the indole alkaloid paynantheine (5) and its diastereoisomers isopaynantheine (6) and epiallo-isopaynantheine (7); the N(4)-oxides mitragynine-N(4)-oxide (8), speciociliatine-N(4)-oxide (9), isopaynantheine-N(4)-oxide (10), and epiallo-isopaynantheine-N(4)-oxide (11); the 9-hydroxylated oxindole alkaloids speciofoline (12), isorotundifoleine (13), and isospeciofoleine (14); and the 9-unsubstituted oxindoles corynoxine A (15), corynoxine B (16), 3-epirhynchophylline (17), 3-epicorynoxine B (18), and corynoxeine (19). With the ability to analyze the spectroscopic data of all of these compounds concomitantly, a decision tree was developed to differentiate these kratom alkaloids based on a few key chemical shifts in the 1H and/or 13C NMR spectra.

Chemical Evaluation of the Effects of Storage Conditions on the Botanical Goldenseal using Marker-based and Metabolomics Approaches.

Hydrastis canadensis, commonly known as goldenseal, is a botanical native to the southeastern United States that has been used for the treatment of infection. The activity of goldenseal is often attributed to the presence of alkaloids (cyclic, nitrogen-containing compounds) present within its roots. Chemical components of botanical supplements like goldenseal may face degradation if not stored properly. The purpose of the research was to analyze the stability of known and unknown metabolites of H. canadensis during exposure to different storage conditions using mass spectrometry. Three abundant metabolites of H. canadensis, berberine, canadine, and hydrastine, were chosen for targeted analysis, and the stability of unknown metabolites was evaluated using untargeted metabolomics. The analysis and evaluation of H. canadensis samples were performed utilizing LC-MS and Principal Component Analysis (PCA). The research project focused on identifying the chemical changes in the metabolite content of H. canadensis under different temperature conditions (40°C ± 5°C, 20°C ± 5°C , and 4°C ± 5°C), different light:dark (hr:hr) cycles (16:8, 12:12, and 0:24), and different sample conditions (powdered roots versus whole roots) over a six month period. The results of this 6-month study revealed that the storage conditions evaluated had no significant effects on the chemical composition of H. canadensis roots. Hence, as long as H. canadensis roots are stored within the storage conditions tested in the study, no significant changes in chemical compositions of metabolites are expected.

Selection and characterization of botanical natural products for research studies: a NaPDI center recommended approach.

Covering: up to the end of 2018 Dietary supplements, which include botanical (plant-based) natural products, constitute a multi-billion-dollar industry in the US. Regulation and quality control for this industry is an ongoing challenge. While there is general agreement that rigorous scientific studies are needed to evaluate the safety and efficacy of botanical natural products used by consumers, researchers conducting such studies face a unique set of challenges. Botanical natural products are inherently complex mixtures, with composition that differs depending on myriad factors including variability in genetics, cultivation conditions, and processing methods. Unfortunately, many studies of botanical natural products are carried out with poorly characterized study material, such that the results are irreproducible and difficult to interpret. This review provides recommended approaches for addressing the critical questions that researchers must address prior to in vitro or in vivo (including clinical) evaluation of botanical natural products. We describe selection and authentication of botanical material and identification of key biologically active compounds, and compare state-of-the-art methodologies such as untargeted metabolomics with more traditional targeted methods of characterization. The topics are chosen to be of maximal relevance to researchers, and are reviewed critically with commentary as to which approaches are most practical and useful and what common pitfalls should be avoided.

Opportunities and Limitations for Untargeted Mass Spectrometry Metabolomics to Identify Biologically Active Constituents in Complex Natural Product Mixtures.

Compounds derived from natural sources represent the majority of small-molecule drugs utilized today. Plants, owing to their complex biosynthetic pathways, are poised to synthesize diverse secondary metabolites that selectively target biological macromolecules. Despite the vast chemical landscape of botanicals, drug discovery programs from these sources have diminished due to the costly and time-consuming nature of standard practices and high rates of compound rediscovery. Untargeted metabolomics approaches that integrate biological and chemical data sets potentially enable the prediction of active constituents early in the fractionation process. However, data acquisition and data processing parameters may have major impacts on the success of models produced. Using an inactive botanical mixture spiked with known antimicrobial compounds, untargeted mass spectrometry-based metabolomics data were combined with bioactivity data to produce selectivity ratio models subjected to a variety of data acquisition and data processing parameters. Selectivity ratio models were used to identify active constituents that were intentionally added to the mixture, along with an additional antimicrobial compound, randainal (5), which was masked by the presence of antagonists in the mixture. These studies found that data-processing approaches, particularly data transformation and model simplification tools using a variance cutoff, had significant impacts on the models produced, either masking or enhancing the ability to detect active constituents in samples. The current study highlights the importance of the data processing step for obtaining reliable information from metabolomics models and demonstrates the strengths and limitations of selectivity ratio analysis to comprehensively assess complex botanical mixtures.

Identification of Intestinal UDP-Glucuronosyltransferase Inhibitors in Green Tea (Camellia sinensis) Using a Biochemometric Approach: Application to Raloxifene as a Test Drug via In Vitro to In Vivo Extrapolation.

Green tea (Camellia sinensis) is a popular beverage worldwide, raising concern for adverse interactions when co-consumed with conventional drugs. Like many botanical natural products, green tea contains numerous polyphenolic constituents that undergo extensive glucuronidation. As such, the UDP-glucuronosyltransferases (UGTs), particularly intestinal UGTs, represent potential first-pass targets for green tea-drug interactions. Candidate intestinal UGT inhibitors were identified using a biochemometrics approach, which combines bioassay and chemometric data. Extracts and fractions prepared from four widely consumed teas were screened (20-180 µg/ml) as inhibitors of UGT activity (4-methylumbelliferone glucuronidation) in human intestinal microsomes; all demonstrated concentration-dependent inhibition. A biochemometrics-identified fraction rich in UGT inhibitors from a representative tea was purified further and subjected to second-stage biochemometric analysis. Five catechins were identified as major constituents in the bioactive subfractions and prioritized for further evaluation. Of these catechins, (-)-epicatechin gallate and (-)-epigallocatechin gallate showed concentration-dependent inhibition, with IC50 values (105 and 59 µM, respectively) near or below concentrations measured in a cup (240 ml) of tea (66 and 240 µM, respectively). Using the clinical intestinal UGT substrate raloxifene, the Ki values were ∼1.0 and 2.0 µM, respectively. Using estimated intestinal lumen and enterocyte inhibitor concentrations, a mechanistic static model predicted green tea to increase the raloxifene plasma area under the curve up to 6.1- and 1.3-fold, respectively. Application of this novel approach, which combines biochemometrics with in vitro-in vivo extrapolation, to other natural product-drug combinations will refine these procedures, informing the need for further evaluation via dynamic modeling and clinical testing.

Biochemometrics to Identify Synergists and Additives from Botanical Medicines: A Case Study with Hydrastis canadensis (Goldenseal).

A critical challenge in the study of botanical natural products is the difficulty of identifying multiple compounds that may contribute additively, synergistically, or antagonistically to biological activity. Herein, it is demonstrated how combining untargeted metabolomics with synergy-directed fractionation can be effective toward accomplishing this goal. To demonstrate this approach, an extract of the botanical goldenseal ( Hydrastis canadensis) was fractionated and tested for its ability to enhance the antimicrobial activity of the alkaloid berberine (4) against the pathogenic bacterium Staphylococcus aureus. Bioassay data were combined with untargeted mass spectrometry-based metabolomics data sets (biochemometrics) to produce selectivity ratio (SR) plots, which visually show which extract components are most strongly associated with the biological effect. Using this approach, the new flavonoid 3,3'-dihydroxy-5,7,4'-trimethoxy-6,8- C-dimethylflavone (29) was identified, as were several flavonoids known to be active. When tested in combination with 4, 29 lowered the IC50 of 4 from 132.2 ± 1.1 µM to 91.5 ± 1.1 µM. In isolation, 29 did not demonstrate antimicrobial activity. The current study highlights the importance of fractionation when utilizing metabolomics for identifying bioactive components from botanical extracts and demonstrates the power of SR plots to help merge and interpret complex biological and chemical data sets.

Integration of Biochemometrics and Molecular Networking to Identify Antimicrobials in Angelica keiskei.

Botanical medicines have been utilized for centuries, but it remains challenging to identify bioactive constituents from complex botanical extracts. Bioassay-guided fractionation is often biased toward abundant or easily isolatable compounds. To comprehensively evaluate active botanical mixtures, methods that allow for the prioritization of active compounds are needed. To this end, a method integrating bioassay-guided fractionation, biochemometric selectivity ratio analysis, and molecular networking was devised and applied to Angelica keiskei to comprehensively evaluate its antimicrobial activity against Staphylococcus aureus. This approach enabled the identification of putative active constituents early in the fractionation process and provided structural information for these compounds. A subset of chalcone analogs were prioritized for isolation, yielding 4-hydroxyderricin (1, minimal inhibitory concentration [MIC] ≤ 4.6 µM, IC50 = 2.0 µM), xanthoangelol (2, MIC ≤ 4.0 µM, IC50 = 2.3) and xanthoangelol K (4, IC50 = 168 µM). This approach allowed for the identification of a low-abundance compound (xanthoangelol K) that has not been previously reported to possess antimicrobial activity and facilitated a more comprehensive understanding of the compounds responsible for A. keiskei's antimicrobial activity.

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study.

A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods-untargeted ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1HNMR-were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products.

Biochemometrics for Natural Products Research: Comparison of Data Analysis Approaches and Application to Identification of Bioactive Compounds.

A central challenge of natural products research is assigning bioactive compounds from complex mixtures. The gold standard approach to address this challenge, bioassay-guided fractionation, is often biased toward abundant, rather than bioactive, mixture components. This study evaluated the combination of bioassay-guided fractionation with untargeted metabolite profiling to improve active component identification early in the fractionation process. Key to this methodology was statistical modeling of the integrated biological and chemical data sets (biochemometric analysis). Three data analysis approaches for biochemometric analysis were compared, namely, partial least-squares loading vectors, S-plots, and the selectivity ratio. Extracts from the endophytic fungi Alternaria sp. and Pyrenochaeta sp. with antimicrobial activity against Staphylococcus aureus served as test cases. Biochemometric analysis incorporating the selectivity ratio performed best in identifying bioactive ions from these extracts early in the fractionation process, yielding altersetin (3, MIC 0.23 µg/mL) and macrosphelide A (4, MIC 75 µg/mL) as antibacterial constituents from Alternaria sp. and Pyrenochaeta sp., respectively. This study demonstrates the potential of biochemometrics coupled with bioassay-guided fractionation to identify bioactive mixture components. A benefit of this approach is the ability to integrate multiple stages of fractionation and bioassay data into a single analysis.

An O-methylflavone from Artemisia afra kills non-replicating hypoxic Mycobacterium tuberculosis.

ETHNOPHARMACOLOGICAL RELEVANCE: African wormwood (Artemisia afra Jacq. ex Willd.) has been used traditionally in southern Africa to treat illnesses causing fever and was recently shown to possess anti-tuberculosis activity. As tuberculosis is an endemic cause of fever in southern Africa, this suggests that the anti-tubercular activity of A. afra may have contributed to its traditional medicinal use. AIM OF THE STUDY: Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a deadly and debilitating disease globally affecting millions annually. Emerging drug-resistant Mtb strains endanger the efficacy of the current therapies employed to treat tuberculosis; therefore, there is an urgent need to develop novel drugs to combat this disease. Given the reported activity of A. afra against Mtb, we sought to determine the mechanisms by which A. afra inhibits and kills this bacterium. MATERIALS AND METHODS: We used transcriptomics to investigate the impact of Artemisia spp. extracts on Mtb physiology. We then used chromatographic fractionation and biochemometric analyses to identify a bioactive fractions of A. afra extracts and identify an active compound. RESULTS: Transcriptomic analysis revealed that A. afra exerts different effects on Mtb compared to A. annua or artemisinin, suggesting that A. afra possesses other phytochemicals with unique modes of action. A biochemometric study of A. afra resulted in the isolation of an O-methylflavone (1), 5-hydroxy-7-methoxy-2-(4-methoxyphenyl)chromen-4-one, which displayed considerable activity against Mtb strain mc26230 in both log phase growth and metabolically downshifted hypoxic cultures. CONCLUSIONS: The present study demonstrated that an O-methylflavone constituent of Artemisia afra explains part of the activity of this plant against Mtb. This result contributes to a mechanistic understanding of the reported anti-tubercular activity of A. afra and highlights the need for further study of this traditional medicinal plant and its active compounds.

Molecular networking identifies an AHR-modulating benzothiazole from white button mushrooms (Agaricus bisporus).

Diet-derived aryl hydrocarbon receptor (AHR) ligands have potential to maintain gut health. However, among the myriad bioactive compounds from foods, identifying novel functional ligands which would significantly impact gastrointestinal health is a challenge. In this study, a novel AHR modulator is predicted, identified, and characterized in the white button mushroom (Agaricus bisporus). Using a molecular networking approach, a methylated analog to benzothiazole was indicated in white button mushrooms, which was subsequently isolated and identified as 2-amino-4-methyl-benzothiazole(2A4). Cell-based AHR transcriptional assays revealed that 2-amino-4-methyl-benzothiazole possesses agonistic activity and upregulated CYP1A1 expression. This contrasts with previous findings that whole white button mushroom extract has overall antagonistic activity in vivo, underscoring the importance of studying the roles each chemical component plays in a whole food. The findings suggest that 2-amino-4-methyl-benzothiazole is a previously unidentified AHR modulator from white button mushroom and demonstrate that molecular networking has potential to identify novel receptor modulators from natural products.

A methoxylated flavone from Artemisia afra kills Mycobacterium tuberculosis.

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a deadly and debilitating disease globally affecting millions annually. Emerging drug-resistant Mtb strains endanger the efficacy of the current combination therapies employed to treat tuberculosis; therefore, there is an urgent need to develop novel drugs to combat this disease. Artemisia afra is used traditionally in southern Africa to treat malaria and recently has shown anti tuberculosis activity. This genus synthesizes a prodigious number of phytochemicals, many of which have demonstrated human health effects. Transcriptomic analysis revealed that A. afra exerts different effects on Mtb compared to A. annua or the well-known antimalarial artemisinin, suggesting other phytochemicals present in A. afra with unique modes of action. A biochemometric study of A. afra resulted in the isolation of a methoxylated flavone (1), which displayed considerable activity against Mtb strain mc26230. Compound 1 had an MIC of 312.5 µg/mL and yielded no viable colonies after 6 days of treatment. In addition, 1 was effective in killing hypoxic Mtb cultures, with no viable cultures after 2 days of treatment. This suggested that A. afra is a source of potentially powerful anti-Mtb phytochemicals with novel mechanisms of action.

Secondary Terpenes in Cannabis sativa L.: Synthesis and Synergy.

Cannabis is a complex biosynthetic plant, with a long history of medicinal use. While cannabinoids have received the majority of the attention for their psychoactive and pharmacological activities, cannabis produces a diverse array of phytochemicals, such as terpenes. These compounds are known to play a role in the aroma and flavor of cannabis but are potent biologically active molecules that exert effects on infectious as well as chronic diseases. Furthermore, terpenes have the potential to play important roles, such as synergistic and/or entourage compounds that modulate the activity of the cannabinoids. This review highlights the diversity and bioactivities of terpenes in cannabis, especially minor or secondary terpenes that are less concentrated in cannabis on a by-mass basis. We also explore the question of the entourage effect in cannabis, which studies to date have supported or refuted the concept of synergy in cannabis, and where synergy experimentation is headed, to better understand the interplay between phytochemicals within Cannabis sativa L.

Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials.

Botanical supplements with broad traditional and medicinal uses represent an area of growing importance for American health management; 25% of U.S. adults use dietary supplements daily and collectively spent over $9. 5 billion in 2019 in herbal and botanical supplements alone. To understand how natural products benefit human health and determine potential safety concerns, careful in vitro, in vivo, and clinical studies are required. However, botanicals are innately complex systems, with complicated compositions that defy many standard analytical approaches and fluctuate based upon a plethora of factors, including genetics, growth conditions, and harvesting/processing procedures. Robust studies rely upon accurate identification of the plant material, and botanicals' increasing economic and health importance demand reproducible sourcing, as well as assessment of contamination or adulteration. These quality control needs for botanical products remain a significant problem plaguing researchers in academia as well as the supplement industry, thus posing a risk to consumers and possibly rendering clinical data irreproducible and/or irrelevant. Chemometric approaches that analyze the small molecule composition of materials provide a reliable and high-throughput avenue for botanical authentication. This review emphasizes the need for consistent material and provides insight into the roles of various modern chemometric analyses in evaluating and authenticating botanicals, focusing on advanced methodologies, including targeted and untargeted metabolite analysis, as well as the role of multivariate statistical modeling and machine learning in phytochemical characterization. Furthermore, we will discuss how chemometric approaches can be integrated with orthogonal techniques to provide a more robust approach to authentication, and provide directions for future research.

Assessing Transporter-Mediated Natural Product-Drug Interactions Via In vitro-In Vivo Extrapolation: Clinical Evaluation With a Probe Cocktail.

The botanical natural product goldenseal can precipitate clinical drug interactions by inhibiting cytochrome P450 (CYP) 3A and CYP2D6. Besides P-glycoprotein, effects of goldenseal on other clinically relevant transporters remain unknown. Established transporter-expressing cell systems were used to determine the inhibitory effects of a goldenseal extract, standardized to the major alkaloid berberine, on transporter activity. Using recommended basic models, the extract was predicted to inhibit the efflux transporter BCRP and uptake transporters OATP1B1/3. Using a cocktail approach, effects of the goldenseal product on BCRP, OATP1B1/3, OATs, OCTs, MATEs, and CYP3A were next evaluated in 16 healthy volunteers. As expected, goldenseal increased the area under the plasma concentration-time curve (AUC0-inf ) of midazolam (CYP3A; positive control), with a geometric mean ratio (GMR) (90% confidence interval (CI)) of 1.43 (1.35-1.53). However, goldenseal had no effects on the pharmacokinetics of rosuvastatin (BCRP and OATP1B1/3) and furosemide (OAT1/3); decreased metformin (OCT1/2, MATE1/2-K) AUC0-inf (GMR, 0.77 (0.71-0.83)); and had no effect on metformin half-life and renal clearance. Results indicated that goldenseal altered intestinal permeability, transport, and/or other processes involved in metformin absorption, which may have unfavorable effects on glucose control. Inconsistencies between model predictions and pharmacokinetic outcomes prompt further refinement of current basic models to include differential transporter expression in relevant organs and intestinal degradation/metabolism of the precipitant(s). Such refinement should improve in vitro-in vivo prediction accuracy, contributing to a standard approach for studying transporter-mediated natural product-drug interactions.