Systematic comparison of metabolic differences of Uncaria rhynchophylla in rat, mouse, dog, pig, monkey and human liver microsomes

Exploration of Q-Marker of Rhubarb Based on Intelligent Data Processing Techniques and the AUC Pooled Method

Rhubarb, as a traditional Chinese medicine, has several positive therapeutic effects, such as purging and attacking accumulation, clearing heat and purging fire, cooling blood, and detoxification. Recently, Rhubarb has been used in prescriptions for the prevention and treatment of COVID-19, with good efficacy. However, the exploration of effective quantitative approach to ensure the consistency of rhubarb’s therapeutic efficacy remains a challenge. In this case, this study aims to use non-targeted and targeted data mining technologies for its exploration and has comprehensively identified 72 rhubarb-related components in human plasma for the first time. In details, the area under the time-concentration curve (AUC)-pooled method was used to quickly screen the components with high exposure, and the main components were analyzed using Pearson correlation and other statistical analyses. Interestingly, the prototype component (rhein) with high exposure could be selected out as a Q-marker, which could also reflect the metabolic status changes of rhubarb anthraquinone in human. Furthermore, after comparing the metabolism of different species, mice were selected as model animals to verify the pharmacodynamics of rhein. The in vivo experimental results showed that rhein has a positive therapeutic effect on pneumonia, significantly reducing the concentration of pro-inflammatory factors [interleukin (IL)-6 and IL-1β] and improving lung disease. In short, based on the perspective of human exposure, this study comprehensively used intelligent data post-processing technologies and the AUC-pooled method to establish that rhein can be chosen as a Q-marker for rhubarb, whose content needs to be monitored individually.

An enhanced strategy integrating offline two-dimensional separation with data independent acquisition mode and deconvolution: Characterization of metabolites of Uncaria rhynchophylla in rat plasma as a case

The importance to clarify the drug metabolites is beyond doubt in view of their potential efficacy and safety. However, due to the complex matrix interference, relatively low content and the co-eluting effect, it is of a great challenge to comprehensively and systematically characterize the metabolites in vivo, especially for the traditional Chinese medicines (TCMs) due to the numerous types of components. In the present study, a comprehensive off-line two-dimensional separation system combining with data independent acquisition (DIA) mode and multi-dimensional data deconvolution method was established for chromatographic separation, data acquisition and data procession of indole alkaloids in rat plasma after intragastrically administrated with the extract of Uncaria rhynchophylla at the dose of 1 g/kg. The orthogonality of the off-line 2D separation system consisting of HILIC for first-dimensional separation and the PRLC for second-dimensional separation was valuated with the "asterisk" equations, and the results showed that off-line 2D separation system had passable orthogonality (A₀ = 53.3%). Furthermore, the DIA mode was applied to capture MS/MS spectra in view of its advantage in acquiring MS data, and an effective multi-dimensional deconvolution method integrating the calculation of chemical formula, the extraction of diagnostic ion, the filter of ring double bond (RDB) and the judgement of neutral loss was established to parse the spectra for the complicated DIA data for comprehensive analysis of metabolites in rat plasma. Ultimately, a total of 127 indole alkaloids were tentatively characterized, and the main metabolic pathways were inferred as demethylation, dehydrogenation, hydroxylation and deglycosylation. The off-line two-dimensional separation system was applied for the comprehensive characterization of metabolites in vivo for the first time. This study suggested a new approach to enable the enrichment, separation and analysis of the low content components in vivo.

The inhibitory effect of 225 frequently-used traditional Chinese medicines for CYP3A4 metabolic enzyme by isoform-specific probe

Traditional Chinese medicines (TCMs), have been widely used for the prevention, treatment, and cure of various diseases for thousands of years in China and Asian countries. It is usually applied either alone or in combination with synthetic drugs or other herbs to be more effective. However, the evaluation of TCMs against the main phase I metabolic enzyme CYP3A4 in vitro was limited. In the present study, a high throughput method based on an isoform-specific probe was applied to evaluate the inhibitory effect of 225 frequently-used TCMs on CYP3A4 activity. The results showed that 25 TCM herbs possessed inhibition effect with residual activity below 50%, and four TCMs (Curcumae Rhizoma, Piperis Longi Fructus, Dalbergiae Odoriferae Lignum, Arisaematis Rhizoma Preparatum) had fairly strong inhibition effect with residual activity below 20%. In an attempt to validate the results obtained from isoform-specific probe, the Curcumae Rhizoma with lowest residual activity was further tested to screen main bioactive constituents which possessed significant inhibitive effect. The crude extract of Curcumae Rhizoma was fractionated to investigate the inhibition effect of each fraction, the results showed that fractions 9-13 exhibited obvious inhibitory effect, and the main constituent (curdione) was identified with standard reference. The molecular docking results verified that the inhibiting effect of curdione could be explained that curdione was interacted with 7 amino acid residues to generate the hydrophobic interaction, and also interacted with imidazole to form hydrogen bond. It is anticipated that the results could be used as reference data to avoid drug-drug interaction and guide the clinical application of TCM or prescriptions.

A systematic strategy integrating solid-phase extraction, full scan range splitting, mass defect filter and precursor ion list for comprehensive metabolite profiling of Danqi Tongmai tablet in rats

In vivo metabolite profiling of herbal medicines remains a challenge due to the complex chemical composition and drastic interference from biological matrix. In this study, a systematic strategy was established for comprehensive metabolite profiling of Danqi Tongmai (DQTM) tablet, a combination of salvianolic acids and notoginsenosides, in rats after oral administration. This strategy was composed of six steps. Firstly, the rat plasma and tissue samples were collected at multiple time points to increase the representativeness of samples. Secondly, different sample preparation methods were systematically investigated including protein precipitation, liquid-liquid extraction and solid-phase extraction to obtain superior extraction efficiency for both salvianolic acids and notoginsenosides. Thirdly, the MS acquisition method was optimized by splitting the full scan range into two separate segments to improve the detection capability for minor components. Fourthly, an extended polygonal mass defect filter (EP-MDF) model was constructed to filter potential metabolites of salvianolic acids and notoginsenosides, and remove large amounts of interference ions. Fifthly, ion intensity-based time point-staggered precursor ion list (IITPS-PIL) was generated to trigger more targeted MS/MS acquisition for potential metabolites at the highest concentration. Finally, the absorbed prototypes and metabolites were comprehensively characterized by reference standards and MS/MS fragmentation. The proposed strategy significantly improved the detection ability for trace prototypes and metabolites in vivo. A total of 370 components, including 94 prototypes (38 confirmed with reference standards) and 276 metabolites, were tentatively characterized in rat plasma and tissue samples after oral administration of DQTM. Collectively, this paper provided an applicable reference for comprehensive metabolite profiling of herbal medicines in complex biological samples.