Therapeutic effects of Siegesbeckia orientalis L. and its active compound luteolin in rheumatoid arthritis: network pharmacology, molecular docking and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Rheumatoid arthritis (RA) is a common difficult disease with a high disability rate. Siegesbeckia orientalis L. (SO), a Chinese medicinal herb that is commonly used for treating RA in clinical practice. While, the anti-RA effect and the mechanisms of action of SO, as well as its active compound(s) have not been elucidated clearly. AIM OF THE STUDY: We aim to explore the molecular mechanism of SO against RA by using network pharmacology analysis, as well as the in vitro and in vivo experimental validations, and to explore the potential bioactive compound(s) in SO. METHODS: Network pharmacology is an advanced technology that provides us an efficient way to study the therapeutic actions of herbs with the underlying mechanisms of action delineated. Here, we used this approach to explore the anti-RA effects of SO, and then the molecular biological approaches were used to verify the prediction. We first established a drug-ingredient-target-disease network and a protein-protein interaction (PPI) network of SO-related RA targets, followed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Further, we used lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages and vascular endothelial growth factor-A (VEGFA)-induced human umbilical vein endothelial cell (HUVEC) models, as well as adjuvant-induced arthritis (AIA) rat model to validate the anti-RA effects of SO. The chemical profile of SO was also determined by using the UHPLC-TOF-MS/MS analysis. RESULTS: Network pharmacology analysis highlighted inflammatory- and angiogenesis-related signaling pathways as promising pathways that mediate the anti-RA effects of SO. Further, in both in vivo and in vitro models, we found that the anti-RA effect of SO is at least partially due to the inhibition of toll like receptor 4 (TLR4) signaling. Molecular docking analysis revealed that luteolin, an active compound in SO, shows the highest degree of connections in compound-target network; moreover, it has a direct binding to the TLR4/MD-2 complex, which is confirmed in cell models. Besides, more than forty compounds including luteolin, darutoside and kaempferol corresponding to their individual peaks were identified tentatively via matching with the empirical molecular formulae and their mass fragments. CONCLUSION: We found that SO and its active compound luteolin exhibit anti-RA activities and potently inhibit TLR4 signaling both in vitro and in vivo. These findings not only indicate the advantage of network pharmacology in the discovery of herb-based therapeutics for treating diseases, but also suggest that SO and its active compound(s) could be developed as potential anti-RA therapeutic drugs.

[Research progress on chemical constituents and pharmacological effects of Ajania plants].

Ajania belonging to the subtribe Artemisiinae of Anthemideae(Asteraceae) is a genus of semi-shrubs closely related to Chrysanthemum. There are 24 species of Ajania in northwestern China, most of which are folk herbal medicines with strong stress tolerance. Modern medical studies have demonstrated that the chemical constituents of Ajania mainly include terpenoids, flavonoids, phenylpropanoids, alkynes, and essential oils. These compounds endow the plants with antimicrobial, anti-inflammatory, antitumor, antimalarial, antioxidant, and insecticide effects. In this study, we reviewed the research progress in the chemical constituents and pharmacological activities of Ajania, aiming to provide reference for the further research and development of Ajania.

Comprehensive profiling of chemical composition of Gleditsiae spina using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry.

RATIONALE: Gleditsiae spina (GS) is an important herb used in traditional and folk medicinal systems of East Asian countries for its various medicinal properties. In China, it has been traditionally used through the centuries for its anticancer, detoxication, detumescence, apocenosis, and antiparasitic effects. Although some of its ingredients have been isolated and identified, most active constituents remain unknown. Past research mostly exploited nuclear magnetic resonance for the identification of compounds, which is suitable for monomers only. Moreover, the extraction and isolation procedures for obtaining purified molecules are time consuming. Therefore, establishing an efficient approach will assist in rapid discovery of the potential active ingredients of GS. The present study aimed to identify the chemical constituents in GS by a data analysis strategy using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight tandem mass spectrometry. METHODS: First, the theoretical formula of the candidate compound was calculated using the accurate mass of the precursor/adduct ions. Second, the compounds were classified by the diagnostic ions from the MS/MS data. Third, characteristic ion filtering was used to identify the structures. Finally, the diverse skeletons and substitutions were further identified through the neutral loss in the GS. RESULTS: A total of 277 compounds were identified in GS, comprising 169 flavonoids, 70 lignans, and 38 other compounds. At least 43 potential new compounds were represented. CONCLUSIONS: This experiment devised an efficient and systematic method for detecting complex compounds and provided a foundation for future research into bioactive ingredients and quality control of GS.

The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation.

Objective: This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods: The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results: A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion: Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

Exploring the protective effect of Gynura procumbens against type 2 diabetes mellitus by network pharmacology and validation in C57BL/KsJ db/db mice.

Gynura procumbens (Lour.) (GP), which is an edible herb, has been shown to have prominent anti-hyperglycemic activity. Nevertheless, the complex chemical composition of GP has impeded clarification of the molecular mechanisms of its effects on type 2 diabetes mellitus (T2DM). In this study, we adopted a network pharmacology approach for the exploration of the potential mechanisms of GP on T2DM. The results suggested that the PI3K/Akt signaling pathway plays a momentous role in the effects of GP. Therefore, we further investigated the effects of GP on T2DM and the mechanism of action based on the PI3K/Akt signaling pathway. In vitro experiments showed that GP ameliorated insulin resistance (IR) and glucose metabolism, thus indicating marked hypoglycemic activity. In vivo experiments showed that blood glucose, liver damage, and insulin sensitivity were ameliorated by GP intervention. Furthermore, the results of RT-PCR and western blot analyses revealed that GP regulated IR and glucose metabolism via the PI3K/Akt signaling pathway. In summary, these results indicate that GP intervention ameliorates T2DM by activating the PI3K/Akt signaling pathway.

A four-step filtering strategy based on ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry for comprehensive profiling the major chemical constituents of Akebiae Fructus.

RATIONALE: Akebiae Fructus (AF) is a traditional Chinese medicine (TCM) with antiphlogistic, analgesic, antineoplastic, diuretic, antirheumatic, antidepressant and antiobesity activities. Identification of chemical constituents from AF is helpful to discover the potential active ingredients and to control its quality. METHODS: The four-step filtering strategy was as follows: (1) To extract the accurate mass by the different adduct ions. (2) To screen different types of the compounds using diagnostic ions. (3) By characteristic ion filtering, to confirm the substituted position and the sugar chain numbers. (4) Based on the neutral loss (NL), to identify the type of monosaccharide and the compositions of sugar chains of triterpenoid saponins and the structure of CGAs. RESULTS: A total of 94 compounds (85 triterpenoid saponins, 9 chlorogenic acids) were unambiguously or reasonably identified. Fifty constituents were discovered for the first time from AF. Nine types of triterpenoid saponins, including akebonoic acid (type I), norhederagenin (type II), oleanolic acid (type III), 2α,3ß-dihydroxy-23-oxo-30-norolean-12,20(21)-dien-28-oic acid (type IV), gypsogenin (type V), norarjunolic acid (type VI), hederagenin (type VII), 2α,3ß-dihydroxy-23-oxo-olean-12-en-28-oic acid (type VIII), arjunolic acid (type IX), and two types of chlorogenic acid (mono-CQA and di-CQA), were identified in AF. CONCLUSIONS: An ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry with MSE (UPLC-QTOF-MSE ) analysis with four-step filtering strategy was established and successfully applied to identify the chemical constituents of AF which can provide chemical support for further research and play an important role in the quality control of AF.

Network Pharmacology-Based Strategy to Investigate the Pharmacologic Mechanisms of Atractylodes macrocephala Koidz. for the Treatment of Chronic Gastritis.

Chronic gastritis (CG) is an inflammatory disease. Atractylodes macrocephala Koidz (AMK) is employed in traditional Chinese medicine (TCM) to treat various disorders. AMK can be efficacious against CG, but the active ingredients, drug targets, and its exact molecular mechanism are not known. We employed network pharmacology to analyze the active ingredients, drug targets, and key pathways of AMK in CG treatment. Seventy-seven AMK candidate ingredients were selected from four databases, and 27 active ingredients were selected for CG treatment. Twenty-five overlapping gene symbols related to CG and drugs were obtained from GeneCards and OMIM databases. A protein-protein interaction (PPI) network and TCM comprehensive network (Drug-Ingredients-Gene symbols-Disease network) were constructed, and 528 Gene Ontology (GO) terms and 26 pathways were obtained by analyses of enrichment of GO pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We suggest that the interleukin-17 signaling pathway, C-type lectin receptor signaling pathway, tumor necrosis factor signaling pathway, and AGE-RAGE signaling pathway in diabetic complications might serve as the key points and principal pathways for CG treatment. We also evaluated the reliability of some important active ingredients and targets by in vitro experiments. We showed that AMK probably influences the inflammatory response, amino acid synthesis, and energy metabolism when treating CG. This study provides novel insights for researchers to explore the mechanism of action of TCM systematically.