Metabolite identification of AZD8055 in Sprague-Dawley rats after a single oral administration using ultra-performance liquid chromatography and mass spectrometry

Characterization of the Components and Metabolites of Achyranthes Bidentata in the Plasma and Brain Tissue of Rats Based on Ultrahigh Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UHPLC-HR-MS)

BACKGROUND

Achyranthes bidentata (AR) is a traditional Chinese herb used for the treatment of hypertension and cerebral ischemia, but its pharmacological effects are not known.

AIM OF STUDY

We aimed to detect and accurately identify the components and metabolites of AR in the plasma and brain tissue of Sprague Dawley rats.

METHODS

We employed ultrahigh performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HR-MS) to detect AR components in the plasma and brain tissue of rats. The absorption and metabolites in the plasma and brain tissue of normal control rats and rats that underwent middle cerebral artery occlusion (MCAO) were characterized and compared.

RESULTS

A total of 281 compounds, including alkaloids, flavonoids, terpenoids, phenylpropanes, sugars and glycosides, steroids, triterpenes, amino acids, and peptides, was identified in samples of Achyranthes bidentata (TCM-AR). Four types of absorbable prototype components and 48 kinds of metabolites were identified in rats in the normal control plasma group which were given AR (AR plasma group), and five kinds of metabolites were identified in rats of the normal control brain tissue group which were given AR (AR brain group). Three absorbed prototype components and 13 metabolites were identified in the plasma of rats which underwent MCAO and were given AR (MCAO + AR plasma group). Six absorbed prototype components and two metabolites were identified in the brain tissue of rats who underwent MCAO and were administered AR (MCAO + AR brain group). These results showed that, after the oral administration of AR, the number of identified components in plasma was more than that in brain tissue. The number of prototype components in the AR plasma group was higher than that in the MCAO + AR plasma group, which may indicate that metabolite absorption in rats undergoing MCAO was worse. The number of prototype components in the MCAO + AR brain group was higher than that in the AR brain group, indicating that the blood-brain barrier was destroyed after MCAO, resulting in more compounds entering brain tissue.

CONCLUSIONS

UHPLC-HR-MS was used to rapidly analyze the components and metabolites of AR in the blood and brain of rats under normal and pathologic conditions, and to comprehensively characterize the components of TCM-AR. We also analyzed and compared the absorbable components and metabolites of normal rats under cerebral ischemia-reperfusion injury to explore the potential mechanism of action. This method could be applied to various Chinese herbs and disease models, which could promote TCM modernization.

Metabolites Identification and Mechanism Prediction of Neobavaisoflavone In Vitro and In Vivo of Rats through UHPLC-Q-Exactive Plus Orbitrap MS Integrated Network Pharmacology

Neobavaisoflavone is an important isoflavone component isolated from Psoraleae Fructus. It is used extensively worldwide because of its antibacterial, antioxidant, anti-inflammatory, anticancer, and anti-osteoporotic activities. However, there is no systematic and comprehensive research on the metabolism of neobavaisoflavone in vivo and in vitro. The study aimed to analyze the metabolic characteristics and mechanism of neobavaisoflavone for the first time. Firstly, biological samples were pretreated by the solid-phase extraction (SPE) method, methanol precipitation, and acetonitrile precipitation. Secondly, the samples were analyzed on UHPLC-Q-Exactive Plus Orbitrap MS. Thirdly, metabolites were tentatively identified based on retention time, parallel reaction monitoring strategy, diagnostic product ions, and neutral loss fragments. A total of 72 metabolites of neobavaisoflavone were tentatively identified, including 28 in plasma, 43 in urine, 18 in feces, six in the liver, and four in the liver microsome. The results suggested that neobavaisoflavone mainly underwent glucuronidation, sulfation, hydroxylation, methylation, cyclization, hydration, and their composite reactions in vivo and in vitro. In addition, nine active components with high bioavailability and 191 corresponding targets were predicted by the Swiss Drug Design database. The 1806 items of GO and 183 KEGG signaling pathways were enriched. These results showed that metabolites expanded the potential effects of neobavaisoflavone. The present study would provide the scientific basis for the further exploitation and application of neobavaisoflavone.

Comparative metabolomics and lipidomics study to evaluate the metabolic differences between first- and second-generation mammalian or mechanistic target of rapamycin inhibitors

Mammalian or mechanistic target of rapamycin (mTOR) drives its fundamental cellular functions through two distinct catalytic subunits, mTORC1 and mTORC2, and is frequently dysregulated in most cancers. To treat cancers, developed mTOR inhibitors have been classified into first and second generations based on their ability to inhibit single (first-generation) and dual (second-generation) mTOR subunits. However, the underlying metabolic differences due to the effects of first- and second-generation mTOR inhibitors have not been clearly evaluated. In this study, rapamycin (sirolimus) and AZD8055 and PP242 were selected as first- and second-generation mTOR inhibitors, respectively, to evaluate the metabolic differences due to these two generations of mTOR inhibitors after a single oral dose using untargeted metabolomics and lipidomics approaches. The metabolic differences at each time point were compared using multivariate analysis. The multivariate and data analyses showed that metabolic disparity was more prominent within 8 h after drug administration and a broad class of metabolites were affected by the administration of both generations of mTOR inhibitors. Among the metabolite classes, changes in the pattern of fatty acids and glycerophospholipids were opposite, specifically at 4 and 8 h between the two generations of mTOR inhibitors. We speculate that the inhibition of the mTORC2 subunit by the second-generation mTOR inhibitor may have resulted in a distinct metabolic pattern between the first- and second-generation inhibitors. Finally, the findings of this study could assist in a more detailed understanding of the key metabolic differences caused by first- and second-generation mTOR inhibitors.

An integrated strategy for comprehensive characterization of metabolites and metabolic profiles of bufadienolides from Venenum Bufonis in rats

Comprehensive characterization of metabolites and metabolic profiles in plasma has considerable significance in determining the efficacy and safety of traditional Chinese medicine (TCM) in vivo. However, this process is usually hindered by the insufficient characteristic fragments of metabolites, ubiquitous matrix interference, and complicated screening and identification procedures for metabolites. In this study, an effective strategy was established to systematically characterize the metabolites, deduce the metabolic pathways, and describe the metabolic profiles of bufadienolides isolated from Venenum Bufonis in vivo. The strategy was divided into five steps. First, the blank and test plasma samples were injected into an ultra-high performance liquid chromatography/linear trap quadrupole-orbitrap-mass spectrometry (MS) system in the full scan mode continuously five times to screen for valid matrix compounds and metabolites. Second, an extension-mass defect filter model was established to obtain the targeted precursor ions of the list of bufadienolide metabolites, which reduced approximately 39% of the interfering ions. Third, an acquisition model was developed and used to trigger more tandem MS (MS/MS) fragments of precursor ions based on the targeted ion list. The acquisition mode enhanced the acquisition capability by approximately four times than that of the regular data-dependent acquisition mode. Fourth, the acquired data were imported into Compound Discoverer software for identification of metabolites with metabolic network prediction. The main in vivo metabolic pathways of bufadienolides were elucidated. A total of 147 metabolites were characterized, and the main biotransformation reactions of bufadienolides were hydroxylation, dihydroxylation, and isomerization. Finally, the main prototype bufadienolides in plasma at different time points were determined using LC-MS/MS, and the metabolic profiles were clearly identified. This strategy could be widely used to elucidate the metabolic profiles of TCM preparations or Chinese patent medicines in vivo and provide critical data for rational drug use.

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Extension-mass defect filter model could reduce about 39% interfering ions.

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The optimized acquisition mode enhanced about 4 times acquisition capability than regular DDA mode.

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147 metabolites were characterized with metabolic network prediction, and the metabolic pathways were deduced in plasmas.

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The quantitative method of 14 prototypes was established by LC-MS/MS for metabolic profiles study.

Metabolite Profiling in Anticancer Drug Development: A Systematic Review

Drug metabolism is one of the most important pharmacokinetic processes and plays an important role during the stage of drug development. The metabolite profile investigation is important as the metabolites generated could be beneficial for therapy or leading to serious toxicity. This systematic review aims to summarize the research articles relating to the metabolite profile investigation of conventional drugs and herb-derived compounds for cancer chemotherapy, to examine factors influencing metabolite profiling of these drugs/compounds, and to determine the relationship between therapeutic efficacy and toxicity of their metabolites. The literature search was performed through PubMed and ScienceDirect databases up to January 2019. Out of 830 published articles, 78 articles were included in the analysis based on pre-defined inclusion and exclusion criteria. Both phase I and II enzymes metabolize the anticancer agents/herb-derived compounds . The major phase I reactions include oxidation/hydroxylation and hydrolysis, while the major phase II reactions are glucuronidation, methylation, and sulfation. Four main factors were found to influence metabolite formation, including species, gender, and route and dose of drug administration. Some metabolites were identified as active or toxic metabolites. This information is critical for cancer chemotherapy and anticancer drug development.