Background and Objective: A large number of people are facing the danger of fatigue due to the fast-paced lifestyle. Fatigue is common in some diseases, such as cancer. The mechanism of fatigue is not definite. Traditional Chinese medicine is often used for fatigue, but the potential mechanism of Polygonati Rhizoma (PR) is still not clear. This study attempts to explore the potential anti-fatigue mechanism of Polygonati Rhizoma through virtual screening based on network pharmacology. Methods: The candidate compounds of PR and the known targets of fatigue are obtained from multiple professional databases. PharmMapper Server is designed to identify potential targets for the candidate compounds. We developed a Herbal medicine-Compound-Disease-Target network and analyzed the interactions. Protein-protein interaction network is developed through the Cytoscape software and analyzed by topological methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment are carried out by DAVID Database. Finally, we develop Compound-Target-Pathway network to illustrate the anti-fatigue mechanism of PR. Results: This approach identified 12 active compounds and 156 candidate targets of PR. The top 10 annotation terms for GO and KEGG were obtained by enrichment analysis with 35 key targets. The interaction between E2F1 and PI3K-AKT plays a vital role in the anti-fatigue effect of PR due to this study. Conclusions: This study demonstrates that PR has multi-component, multi-target and multipathway effects.
Background and Objective: Mycoplasmal pneumonia (MP) can lead to inflammation, multiple system immune damage, and mixed infection in children. The pathogenesis is still unclear. Shuang-Huang-Lian (SHL) oral liquid can treat acute upper respiratory tract infection, acute bronchitis and light pneumonia. However, our current understanding of the molecular mechanisms supporting its clinical application still lags behind due to the lack of researches. It is difficult to understand the overall sensitization mechanism of SHL oral liquid. The purpose is to explain the mechanism of action of drugs in this study, which is useful to ensure the safety of medication for children. Methods: The therapeutic mechanism of SHL oral liquid was investigated by a systems pharmacology approach integrating drug-likeness evaluation, oral bioavailability prediction, ADMET, protein-protein interaction worknet, Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes database pathway performance, C-T-P network construction and molecular docking. Results: A total of 18 active ingredients contained in SHL oral liquid and 53 major proteins were screened out as effective players in the treatment of M. pneumoniae disease through some related pathways and molecular docking. The majority of targets, hubs and pathways were highly related with anti-mycoplasma therapy, immunity and inflammation process. Conclusions: This study shows that the anti-bacteria effect of SHL oral liquid has multi-component, multi-target and multi- pathway. The proposed approach may provide a feasible tool to clarify the mechanism of traditional Chinese medicines and further develop their therapeutic potentials.
Background: Diabetes mellitus is one of the most common endocrine metabolic disorder diseases. The application of herbal medicine to control glucose levels and improve insulin action might be a useful approach in the treatment of diabetes. Mulberry leaves (ML) has been reported to exert important activities of anti-diabetic. Objective: In this work, we aimed to explore the multi-targets and multi-pathways regulatory molecular mechanism of Mulberry leaves (ML, Morus alba Linne) acting on diabetes. Methods: Identification of active compounds of Mulberry leaves using Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Bioactive components were screened by FAF-Drugs4 website (Free ADME-Tox Filtering Tool). The targets of bioactive components were predicted from SwissTargetPrediction website, and the diabetes related targets were screened from GeneCards database. The common targets of ML and diabetes are used for Gene Ontology (GO) and pathway enrichment analysis. The visualization networks were constructed by Cytoscape 3.7.1 software. The construction of biological networks were performed to analyze the mechanisms as follows: (1) Compound-Target network; (2) Common target-Compound network; (3) Common targets protein interaction network; (4) Compound-Diabetes protein-protein interactions (PPI) network; (5) Target-Pathway network; (6) Compound-Target-Pathway network. At last, the prediction results of network pharmacology were verified by molecular docking method. Results: 17 active components were obtained by TCMSP database and FAF-Drugs4 website. 51 potential targets (11 common targets and 40 associated indirect targets) were obtained and used to build the PPI network by String database. Furthermore, the potential targets were used to GO and pathway enrichment analysis. 8 key active compounds (quercetin, Iristectorigenin A, 4-Prenylresveratrol, Moracin H, Moracin C, Isoramanone, Moracin E and Moracin D) and 8 key targets (AKT1, IGF1R, EIF2AK3, PPARG, AGTR1, PPARA, PTPN1 and PIK3R1) were obtained to play major roles in Mulberry leaf acting on diabetes. And the signal pathways involved in the mechanisms mainly include AMPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, insulin signaling pathway and insulin resistance. The molecular docking results show that the 8 key active compounds have good affinity with the key target of AKT1, and the 5 key targets (IGF1R, EIF2AK3, PPARG, PPARA and PTPN1) have better affinity than AKT1 with the key compound of quercetin. Conclusion: Based on network pharmacology and molecular docking of this work provided an important systematic and visualized basis for further understanding the synergy mechanism of ML acting on diabetes.
Triptolide (TP) is the major pharmacologically active ingredient and toxic component of Tripterygium wilfordii Hook. f. However, its clinical potential is limited by a narrow therapeutic window and multiple organ toxicity, especially hepatotoxicity. Furthermore, TP-induced hepatotoxicity shows significant inter-individual variability. Over the past few decades, research has been devoted to the study of TP-induced hepatotoxicity and its mechanism. In this review, we summarized the mechanism of TP-induced hepatotoxicity. Studies have demonstrated that TP-induced hepatotoxicity is associated with CYP450s, P-glycoprotein (P-gp), oxidative stress, excessive autophagy, apoptosis, metabolic disorders, immunity, and the gut microbiota. These new findings provide a comprehensive understanding of TP-induced hepatotoxicity and detoxification.
Moscatilin, a bioactive ingredient isolated from Dendrobium moscatum, has been demonstrated to have excellent anti‐cancer activity. The goals of the present study were to investigate the metabolic profiles of moscatilin and to identify and characterize its metabolites. In vitro studies were performed by incubating moscatilin (10 μM) with rat, dog, monkey, and human liver microsomes (0.5 mg protein/ml) to generate the metabolites. An analytical method of liquid chromatography combined with hybrid quadrupole orbitrap high‐resolution mass spectrometry in full mass/data‐dependent tandem mass spectrometry scan was utilized to separate and identify the metabolites in accordance with their accurate masses, formulas, and tandem mass spectrometry fragment ions determination. A total of six phase I metabolites were detected and structurally characterized. The phase I metabolic pathways of moscatilin were hydroxylation, demethylation, and dehydrogenation. In glutathione‐supplemented liver microsomes, nine glutathione conjugates were detected and identified. Our results demonstrated that moscatilin was susceptible to bioactivation with the result of ortho quinone and quinone‐methide intermediates. The present study provided an overview of the in vitro metabolic profiles of moscatilin, which will aid in the understanding of the efficacy and safety of this active compound.
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