An Integrated Approach for Studying Exposure, Metabolism, and Disposition of Multiple Component Herbal Medicines Using High-Resolution Mass Spectrometry and Multiple Data Processing Tools

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

Pharmacokinetics and tissue distribution of four major bioactive components of Cynanchum auriculatum extract: a UPLC-MS/MS study in normal and functional dyspepsia rats

Introduction: Cynanchum auriculatum (CA) is usually used to treat digestive disorders, such as anorexia, enteritis, dysentery, and indigestion. Functional dyspepsia (FD) is characterized by a group of symptoms associated with the gastroduodenal region. Recent pharmacological studies have demonstrated the efficacy of CA for treating FD. However, the pharmacokinetics (PK) and tissue distribution of CA in physiological and FD states is still unclear. The present study aimed to clarify the differences in PK parameters and tissue distribution of the four major active components of CA (baishouwu benzophenone, deacylmet-aplexigenin, qingyangshengenin, and syringic acid) under both physiological and FD states. Methods: For this, normal and FD rats were orally administered 10 mg/kg CA extract. Then, plasma and tissue (heart, liver, spleen, lung, kidney, brain, stomach, and small intestine) samples were obtained. The four active components of CA in rat plasma and tissues were quantified by developing and validating a fast and reliable ultra-high-performance liquid chromatography-mass spectrometry method. Results: The area under the plasma concentration-time curve from time zero to time t (AUC0-t) of baishouwu benzophenone was significantly lower in the FD group than in the normal group (p < 0.01). The FD group had significantly lower (p < 0.001) apparent volume of distribution and plasma clearance of qing-yangshengenin and significantly higher (p < 0.05) AUC0-t of deacylmetaplexigenin and qingyangshengenin. The four active components were rapidly distributed into various tissues, and the main target organs of CA activity were the stomach and small intestine. In addition, baishouwu benzophenone, deacylmetaplexigenin, and qingyangshengenin could cross the blood-brain barrier, indicating that the brain may be another target organ in the treatment of FD. Discussion: These results indicate that the pathological state of FD alters the PK behavior and tissue distribution characteristics of baishouwu benzophenone, deacylmetaplexigenin, qingyangshengenin, and syringic acid in the CA extract, providing an experimental basis for the role of CA in FD treatment.

Identification of potential anti-pneumonia pharmacological components of Glycyrrhizae Radix et Rhizoma after the treatment with Gan An He Ji oral liquid

Glycyrrhizae Radix et Rhizoma, a traditional Chinese medicine also known as Gan Cao (GC), is frequently included in clinical prescriptions for the treatment of pneumonia. However, the pharmacological components of GC for pneumonia treatment are rarely explored. Gan An He Ji oral liquid (GAHJ) has a simple composition and contains GC liquid extracts and paregoric, and has been used clinically for many years. Therefore, GAHJ was selected as a compound preparation for the study of GC in the treatment of pneumonia. We conducted an in vivo study of patients with pneumonia undergoing GAHJ treatments for three days. Using the intelligent mass spectrometry data-processing technologies to analyze the metabolism of GC in vivo, we obtained 168 related components of GC in humans, consisting of 24 prototype components and 144 metabolites, with 135 compounds screened in plasma and 82 in urine. After analysis of the metabolic transformation relationship and relative exposure, six components (liquiritin, liquiritigenin, glycyrrhizin, glycyrrhetinic acid, daidzin, and formononetin) were selected as potential effective components. The experimental results based on two animal pneumonia models and the inflammatory cell model showed that the mixture of these six components was effective in the treatment of pneumonia and lung injury and could effectively downregulate the level of inducible nitric oxide synthase (iNOS). Interestingly, glycyrrhetinic acid exhibited the strongest inhibition on iNOS and the highest exposure in vivo. The following molecular dynamic simulations indicated a strong bond between glycyrrhetinic acid and iNOS. Thus, the current study provides a pharmaceutical basis for GC and reveals the possible corresponding mechanisms in pneumonia treatment.

Identification of Protosappanoside D from Caesalpinia decapetala and Evaluation of Its Pharmacokinetic, Metabolism and Pharmacological Activity

Protosappanoside D (PTD) is a new component isolated from the extract of Caesalpinia decapetala for the first time. Its structure was identified as protosappanin B-3-O-β-D-glucoside by ¹H-NMR, ¹³C-NMR, 2D-NMR and MS techniques. To date, the pharmacological activities, metabolism or pharmacokinetics of PTD has not been reported. Therefore, this research to study the anti-inflammatory activity of PTD was investigated via the LPS-induced RAW264.7 cells model. At the same time, we also used the UHPLC/Q Exactive Plus MS and UPLC-MS/MS methods to study the metabolites and pharmacokinetics of PTD, to calculate its bioavailability for the first time. The results showed that PTD could downregulate secretion of the pro-inflammatory cytokines. In the metabolic study, four metabolites were identified, and the primary degradative pathways in vivo involved the desaturation, oxidation, methylation, alkylation, dehydration, degradation and desugarization. In the pharmacokinetic study, PTD and its main metabolite protosappanin B (PTB) were measured after oral and intravenous administration. After oral administration of PTD, its T_max was 0.49 h, t_1/2z and MRT_(0–t) were 3.47 ± 0.78 h and 3.06 ± 0.63 h, respectively. It shows that PTD was quickly absorbed into plasma and it may be eliminated quickly in the body, and its bioavailability is about 0.65%.

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.

HRPIF data mining based on data-dependent/independent acquisition for Rhei Radix et Rhizoma metabolite screening in rats

In traditional Chinese medicine (TCM), components with identical nuclei often share structural similarity, indicating the possibility of similar second-level mass spectrometry (MS/MS) fragments. High-resolution product-ion filter (HRPIF) technique can be utilized to identify metabolites, with similar fragments, in vivo. In principle, this technique applies to TCM; however, its application has been restricted due to the limitations of traditional MS/MS data acquisition. Therefore, a novel analysis strategy, based on data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets, has been developed for the determination of template product ions and efficient non-targeted identification of TCM-related components in vivo by HRPIF and background subtraction (BS). This DDA-DIA combination strategy, taking Rhei Radix et Rhizoma as a test case, identified 71 anthraquinone prototype components in vitro (36 of which were discovered for the first time), and 45 related components in vivo, confirming glucuronidation and sulfation as the main reactions. The developed strategy could rapidly identify TCM-related components in vivo with high sensitivity, indicating the immense importance of this novel HRPIF data mining technology in TCM analysis.

Suspect screening and untargeted analysis of veterinary drugs in food by LC-HRMS: Application of background exclusion-dependent acquisition for retrospective analysis of unknown xenobiotics

The presence of veterinary drug and pesticide residues in food products pose considerable threats to human health. Monitoring of these residues in food is mainly carried out using targeted analysis by triple quadrupole mass spectrometry. However, these methods are not suitable for suspect screening and untargeted analysis of unknowns. The main objectives of this study were to develop a new high-resolution mass spectrometry (HRMS)-based analytical strategy for retrospective analysis of suspect and unknown xenobiotics and to evaluate its performance in the tentative identification of 48 veterinary drugs as "unknowns" spiked in a pork sample. In the analysis, a newly developed background exclusion data-dependent acquisition (BE-DDA) technique was employed to trigger the product ion (MS/MS) spectral acquisition of the "unknowns", and an in-house precise-and-thorough background-subtraction (PATBS) technique was applied to detect these "unknowns". Results showed that untargeted data mining of the acquired LC-MS dataset by PATBS was able to find all the 48 veterinary drugs and 46 of them were triggered by BE-DDA to generate accurate MS/MS spectra. The dataset of recorded accurate full-scan mass and MS/MS spectra of all the xenobiotics of the test pork sample is defined as the xenobiotics profile. Searching the xenobiotic profile of the test pork sample using mass spectral data of selected veterinary drugs (as suspects) from the mzCloud spectral library led to the correct hits. Searching against the mzCloud spectral library using the mass spectral data of selected individual veterinary drugs (as unknowns) from the xenobiotics profile tentatively confirmed their identities. In contrast, analysis of the same sample using ion intensity-data dependent acquisition only recorded the MS/MS spectra for 34 veterinary drugs. In addition, a data independent acquisition method enabled the acquisition of the fragment spectra for 44 veterinary drugs, but their spectral data displayed only one or a few true product ions of individual analytes of interest along with many fragments from coeluted biological components and background noises. This study demonstrates that this analytical strategy has a potential to become a practical tool for the retrospective suspect screening and untargeted analysis of unknown xenobiotics in a biological sample such as veterinary drugs and pesticides in food products.

Xiaoxuming Decoction: A Traditional Herbal Recipe for Stroke With Emerging Therapeutic Mechanisms

Xiaoxuming decoction (XXMD) has been traditionally used to manage stroke though debates on its clinical efficacy were present in the history. Till nowadays, it is still one of the most commonly used herbal recipes for stroke. One of the reasons is that a decent proportion of ischemic stroke patients still have residue symptoms even after thrombolysis with rt-PA or endovascular thrombectomy. Numerous clinical studies have shown that XXMD is an effective alternative therapy not only at the acute stage, but also at the chronic sequelae stage of ischemic stroke. Modern techniques have isolated groups of compounds from XXMD which have shown therapeutic effects, such as dilating blood vessels, inhibiting thrombosis, suppressing oxidative stress, attenuating nitric oxide induced damage, protecting the blood brain barrier and the neurovascular unit. However, which of the active compounds is responsible for its therapeutic effects is still unknown. Emerging studies have screened and tested these active compounds aiming to find individual compounds that can be used as drugs to treat stroke. The present study summarized both clinical evidence of XXMD in managing stroke and experimental evidence on its molecular mechanisms that have been reported recently using advanced techniques. A new perspective has also been discussed with an aim to provide new targets that can be used for screening active compounds from XXMD.

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.

Identifying potential anti-COVID-19 pharmacological components of traditional Chinese medicine Lianhuaqingwen capsule based on human exposure and ACE2 biochromatography screening

Lianhuaqingwen (LHQW) capsule, a herb medicine product, has been clinically proved to be effective in coronavirus disease 2019 (COVID-19) pneumonia treatment. However, human exposure to LHQW components and their pharmacological effects remain largely unknown. Hence, this study aimed to determine human exposure to LHQW components and their anti-COVID-19 pharmacological activities. Analysis of LHQW component profiles in human plasma and urine after repeated therapeutic dosing was conducted using a combination of HRMS and an untargeted data-mining approach, leading to detection of 132 LHQW prototype and metabolite components, which were absorbed via the gastrointestinal tract and formed via biotransformation in human, respectively. Together with data from screening by comprehensive 2D angiotensin-converting enzyme 2 (ACE2) biochromatography, 8 components in LHQW that were exposed to human and had potential ACE2 targeting ability were identified for further pharmacodynamic evaluation. Results show that rhein, forsythoside A, forsythoside I, neochlorogenic acid and its isomers exhibited high inhibitory effect on ACE2. For the first time, this study provides chemical and biochemical evidence for exploring molecular mechanisms of therapeutic effects of LHQW capsule for the treatment of COVID-19 patients based on the components exposed to human. It also demonstrates the utility of the human exposure-based approach to identify pharmaceutically active components in Chinese herb medicines.

The profiling of the metabolites of hirsutine in rat by ultra-high performance liquid chromatography coupled with linear ion trap Orbitrap mass spectrometry: An improved strategy for the systematic screening and identification of metabolites in multi-samples in vivo

Drug metabolites identification and construction of metabolic profile are meaningful work for the drug discovery and development. The great challenge during this process is the work of the structural clarification of possible metabolites in the complicated biological matrix, which often resulting in a huge amount data sets, especially in multi-samples in vivo. Analyzing these complex data manually is time-consuming and laborious. The object of this study was to develop a practical strategy for screening and identifying of metabolites from multiple biological samples efficiently. Using hirsutine (HTI), an active components of Uncaria rhynchophylla (Gouteng in Chinese) as a model and its plasma, urine, bile, feces and various tissues were analyzed with data processing software (Metwork), data mining tool (Progenesis QI), and HR-MSⁿ data by ultra-high performance liquid chromatography/linear ion trap-Orbitrap mass spectrometry (U-HPLC/LTQ-Orbitrap-MS). A total of 67 metabolites of HTI in rat biological samples were tentatively identified with established library, and to our knowledge most of which were reported for the first time. The possible metabolic pathways were subsequently proposed, hydroxylation, dehydrogenation, oxidation, N-oxidation, hydrolysis, reduction and glucuronide conjugation were mainly involved according to metabolic profile. The result proved application of this improved strategy was efficient, rapid, and reliable for metabolic profiling of components in multiple biological samples and could significantly expand our understanding of metabolic situation of TCM in vivo.