Humans ; Dementia, Vascular ; Proteomics ; Network Pharmacology ; Drugs, Chinese Herbal/pharmacology* ; Cognition

Two terpenes, 3-keto-tirucalla-8,24-dien-21-oic acid(KTDA) and 2-methoxy-5-acetoxy-furanogermacr-1(10)-en-6-one(FSA), are isolated from Olibanum and Myrrha respectively, which are characterized by high yield and easy crystallization during the preparation. The present study explored the regulatory targets and anti-inflammatory mechanism of KTDA and FSA based on network pharmacology and cell viability assay. First, the drug-likeness of KTDA and FSA was predicted by Swiss ADME. The target prediction of active components was carried out by Swiss Target Prediction and Pharmmapper. TTD, Drug Bank, and Gene Cards were searched for inflammation-related target genes of KTDA and FSA. Protein-protein interaction(PPI) analysis was performed on the inflammatory targets of KTDA and FSA by STRING, and Cytoscape was used to conduct topological analysis of the interaction results and construct the PPI network. GO function and KEGG pathway enrichment analyses of inflammatory targets of KTDA and FSA were carried out by DAVID, and a " component-target-pathway" network was constructed. Finally, lipopolysaccharide(LPS)-induced RAW264. 7 cells were treated with KTDA and FSA at different concentrations, and nitric oxide(NO) concentration and protein and m RNA expression levels were detected. The results showed that both KTDA and FSA showed good drug-likeness. A total of 157 and 142 inflammation-related targets of KTDA and FSA were screened out. PPI network analysis showed that MAPK1, AKT1, MAPK8, PIK3 CA,PIK3 R1, EGFR, etc. might be the key proteins for the anti-inflammatory effect. PI3 K/AKT and MAPK signaling pathways were obtained by KEGG and GO-BP enrichment. Cell experiment results showed that KTDA and FSA could exert anti-inflammatory effects by inhibiting NO production, reducing the phosphorylation levels of JNK, p38, and AKT proteins, and down-regulating the m RNA expression of interleukin(IL)-1β and IL-6. Meanwhile, FSA could also inhibit ERK phosphorylation. The results indicated that KTDA and FSA had significant anti-inflammatory activity, which provided a scientific basis and important support for the further research,development, and utilization of Olibanum and Myrrha.
Animals ; Ants ; Drugs, Chinese Herbal/pharmacology* ; Frankincense ; Lipopolysaccharides ; Molecular Docking Simulation ; Network Pharmacology

As a classic prescription for promoting blood circulation to remove blood stasis, Xuefu Zhuyu Decoction(XFZYD) is widely used in clinical practice and has notable curative effect. Based on the key targets of activating blood circulation, this study identified the active components of XFZYD to reveal the material basis. The components of XFZYD were collected from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The molecular docking models were built for the blood-activating targets obtained from the previous study with the components of XFZYD. The top five active components with measurability for each target were selected as the potential blood-activating components in the prescription. The efficacy of the prescription can embody key pharmacological and high-content components. In this study, anti-platelet aggregation activity was used to characterize the effect of activating blood, and the in vivo experiments were conducted to verify the accuracy of the active components. A total of 210 chemical components of XFZYD were screened out from TCMSP and docked with the key targets with the function of activating blood. Ligustrazine, acteoside, naringin, etc. were selected as the potential active components for activating blood in XFZYD. The anti-platelet aggregation activity of the combination of Chuanxiong Rhizoma, Rehmanniae Radix, Aurantii Fructus, Glycyrrhizae Radix et Rhizoma, and Carthami Flos was 9.82%±5.11%. Compared with that in the control group, the platelet aggregation induced by adenosine diphosphate(ADP) was significantly inhibited in the test group(P<0.01), which verified the accuracy of the active components. This study can guide the research on the material basis of XFZYD and provide insights into the development and utilization of the classical prescription.
Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Molecular Docking Simulation ; Network Pharmacology ; Rhizome

In this study, ultra-high performance liquid chromatography-linear ion trap/electrostatic field orbit trap combined-type mass spectrometry(UPLC-LTQ-Orbitrap-MS) was used to analyze the main active components of Huangqi Guizhi Wuwu Decoction(HQGZ). A total of 50 active components were identified from HQGZ and 108 potential targets of the components related to the treatment of rheumatoid arthritis were retrieved based on network pharmacology, including 87 key targets, followed by Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment of the targets. The result indicated that HQGZ may exert therapeutic effects mainly through the sphingolipid signaling pathway, tumor necrosis factor(TNF) signaling pathway, as well as the positive regulation of ribonucleic acid(RNA) polymerase Ⅱ promoter transcription, inflammatory response and other biological processes. At the same time, cell experiment was performed to verify the key proteins in the TNF signaling pathway. The results demonstrated that HQGZ significantly reduced the expression of caspase-3(CASP3), TNF, relaxed(RELA) protein, and IkappaB kinase beta(IKBKB) in fibroblast-like synoviocytes induced by TNF-α. The results of UPLC-LTQ-Orbitrap-MS, network pharmacology and cell experiment showed that the active components in HQGZ may inhibit inflammatory response and regulate immune function and cell apoptosis by modulating key proteins in TNF signaling pathway to treat rheumatoid arthritis.
Arthritis, Rheumatoid/genetics* ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Network Pharmacology ; Synoviocytes

Traditional Chinese medicine(TCM) has unique advantages in the prevention and treatment of diseases owing to its holistic view and more than 2 000 years of experience in the clinical use of natural medicine. The "holistic" characteristic of TCM gives birth to a new generation of research paradigm featuring "network" and "system", which has been developing rapidly in the era of biomedical big data and artificial intelligence. Network pharmacology, a representative research field, provides new ideas and methods for the research of the interdiscipline of artificial intelligence and medicine, the analysis of massive biomedical data, and the transformation from data to knowledge. TCM plays an important role in proposing the core theory of "network target" and promoting the establishment and development of network pharmacology, and has taken the lead in formulating the first international standard of network pharmacology--Network Pharmacology Evaluation Method Guidance. In terms of theory, network target can systematically link drugs and diseases and quantitatively interpret the overall regulatory mechanism of drugs. In the aspect of method, network pharmacology is developing towards a research model that combines computational, experimental, and clinical approaches. This review introduces the resent important progress of TCM network pharmacology in predicting drug targets, understanding the biological basis of drugs and diseases, and searching for disease and syndrome biomarkers. Under the guidance of Network Pharmacology Evaluation Method Guidance, the development of network pharmacology is expected to become more and more standardized and healthy. Network target will help produce more high-quality research outcomes in TCM and effectively boost the modernization and internationalization of TCM.
Artificial Intelligence ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Network Pharmacology ; Research Design

The present study explored the underlying mechanism of Astragali Radix-Curcumae Rhizoma-Paridis Rhizoma(AR-CR-PR) in the treatment of colorectal cancer(CRC) by network pharmacology and molecular docking and animal tests and verified the core targets based on the orthotopic transplantation model in nude mice. The active components of AR-CR-PR were retrieved from databases such as TCMSP. The targets of drugs and the disease were obtained from PubChem, SwissTargetPrediction, TTD, and DrugBank, and the intersection targets were imported into STRING for the analysis of the protein-protein interaction(PPI). Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses were performed through DAVID. AutoDock Vina was used to perform molecular docking and binding ability prediction between the active components and the core targets. The effects of AR-CR-PR on tumor growth, metastasis, and phosphorylation of core target proteins in tumor tissues based on the orthotopic transplantation model in nude mice. As revealed by network pharmacology, AR-CR-PR contained nine core components, such as quercetin, curcumin, and β-ecdysone, and the key targets included protein kinase B(AKT1), mitogen-activated protein kinase 3(MAPK3), MAPK1, and epithelial growth factor receptor(EGFR), which was indicated that the anti-CRC effect of AR-CR-PR was presumedly achieved by regulating tumor cell proliferation, apoptosis, migration, and angiogenesis through PI3 K-AKT, MAPK and other signaling pathways. The results of molecular docking showed that the nine core components had strong binding abilities to AKT1 and MAPK3. The results in vivo showed that AR-CR-PR could reduce the volume of the orthotopic tumor, inhibit liver metastasis, and decrease the phosphorylation of AKT1 and MAPK3 in the CRC model. The mechanism of AR-CR-PR in the intervention of CRC may be related to the activation of PI3 K-AKT and MAPK signaling pathway. This study provides a scientific basis for the clinical application of AR-CR-PR in the treatment of CRC and ideas for modern research on AR-CR-PR.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Mice, Nude ; Molecular Docking Simulation ; Neoplasms ; Network Pharmacology ; Rhizome

This study analyzed the molecular mechanism of Huangjing Qianshi Decoction(HQD) in the treatment of prediabetes based on network pharmacology and molecular docking. The active components of HQD were identified and screened based on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP, http://Lsp.nwu.edu.cn/tcmsp.php) and then the targets of the components and the genes related to prediabetes were retrieved, followed by identifying the common targets of the decoction and the disease. The medicinal component-target network was constructed by Cytoscape to screen key components. The protein-protein interaction(PPI) network was established by STRING and hub genes were identified by Cytoscape-CytoNCA, followed by Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) of the hub genes with R-clusterProfi-ler. Thereby, the possible signaling pathways were predicted and the molecular mechanism was deduced. A total of 79 active components of HQD and 785 diabetes-related targets of the components were screened out. The hub genes mainly involved the GO terms of tricarboxylic acid cycle, peptide binding, amide binding, hydrolase activity, and kinase activity regulation, and the KEGG pathways of AGE-RAGE signaling pathway, TNF signaling pathway, AMPK signaling pathway, IL-17 signaling pathway, and insulin signaling pathway. Western blot result showed that HQD-containing serum significantly reduced the expression of AKT1, AGE, and RAGE proteins in insulin resistance model cells. HQD's treatment of prediabetes is characterized by multiple pathways, multiple targets, and multiple levels. The main mechanism is that the components zhonghualiaoine, baicalein, kaempferol, and luteolin act on AKT1 and inhibit the AGE-RAGE axis.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Medicine, Chinese Traditional ; Molecular Docking Simulation ; Network Pharmacology ; Prediabetic State/genetics*

This study aimed to explore the anti-depressant components of Rehmanniae Radix and its action mechanism based on network pharmacology combined with molecular docking. The main components of Rehmanniae Radix were identified by ultra-high performance liquid chromatography-quadrupole/Orbitrap high resolution mass spectrometry(UPLC-Q-Orbitrap HRMS), and the related targets were predicted using SwissTargetPrediction. Following the collection of depression-related targets from GeneCards, OMIM and TTD, a protein-protein interaction(PPI) network was constructed using STRING. GO and KEGG pathway enrichment analysis was performed by Metascape. Cytoscape 3.7.2 was used to construct the networks of "components-targets-disease" and "components-targets-pathways", based on which the key targets and their corresponding components were obtained and then preliminarily verified by molecular docking. Rehmanniae Radix contained 85 components including iridoids, ionones, and phenylethanoid glycosides. The results of network analysis showed that the main anti-depressant components of Rehmanniae Radix were catalpol, melittoside, genameside C, gardoside, 6-O-p-coumaroyl ajugol, genipin-1-gentiobioside, jiocarotenoside A1, neo-rehmannioside, rehmannioside C, jionoside C, jionoside D, verbascoside, rehmannioside, cistanoside F, and leucosceptoside A, corresponding to the following 16 core anti-depression targets: AKT1, ALB, IL6, APP, MAPK1, CXCL8, VEGFA, TNF, HSP90 AA1, SIRT1, CNR1, CTNNB1, OPRM1, DRD2, ESR1, and SLC6 A4. As revealed by molecular docking, hydrogen bonding and hydrophobicity might be the main action forms. The key anti-depression targets of Rehmanniae Radix were concentrated in 24 signaling pathways, including neuroactive ligand-receptor interaction, neurodegenerative disease-multiple diseases pathway, phosphatidylinositol 3-kinase/protein kinase B pathway, serotonergic synapse, and Alzheimer's disease.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Molecular Docking Simulation ; Network Pharmacology ; Neurodegenerative Diseases ; Plant Extracts ; Rehmannia

This study aims to establish a method for analyzing the chemical constituents in Cistanches Herba by high performance liquid chromatography(HPLC) and quadrupole-time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS), and to reveal the pharmacological mechanism based on network pharmacology for mining the quality markers(Q-markers) of Cistanches Herba. The chemical constituents of Cistanche deserticola and C. tubulosa were analyzed via HPLC-Q-TOF-MS/MS. The potential targets and pathways of Cistanches Herba were predicted via SwissTargetPrediction and DAVID. The compound-target-pathway-pharmacological action-efficacy network was constructed via Cytoscape. A total of 47 chemical constituents were identified, involving 95 targets and 56 signaling pathways. We preliminarily elucidated the pharmacological mechanisms of echinacoside, acteoside, isoacteoside, cistanoside F, 2'-acetylacteoside, cistanoside A, campneoside Ⅱ, salidroside, tubuloside B, 6-deoxycatalpol, 8-epi-loganic acid, ajugol, bartsioside, geniposidic acid, and pinoresinol 4-O-β-D-glucopyranoside, and predicted them to be the Q-markers of Cistanches Herba. This study identified the chemical constituents of Cistanches Herba, explained the pharmacological mechanism of the traditional efficacy of Cistanches Herba based on network pharmacology, and introduced the core concept of Q-markers to improve the quality evaluation of Cistanches Herba.
Chromatography, High Pressure Liquid/methods* ; Cistanche ; Drugs, Chinese Herbal/pharmacology* ; Network Pharmacology ; Tandem Mass Spectrometry/methods*

To explore the mechanism of ovarian toxicity of Hook. F. (TwHF) by network pharmacology and molecular docking. The candidate toxic compounds and targets of TwHF were collected by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Comparative Toxicogenomics Database (CTD). Then, the potential ovarian toxic targets were obtained from CTD, and the target genes of ovarian toxicity of TwHF were analyzed using the STRING database. The protein-protein interaction (PPI) network was established by Cytoscape and analyzed by the cytoHubba plug-in to identify hub genes. Additionally, the target genes of ovarian toxicity of TwHF were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses by using the R software. Finally, Discovery Studio software was used for molecular docking verification of the core toxic compounds and the hub genes. Nine candidate toxic compounds of TwHF and 56 potential ovarian toxic targets were identified in this study. Further network analysis showed that the core ovarian toxic compounds of TwHF were triptolide, kaempferol and tripterine, and the hub ovarian toxic genes included , , , , , , , , and . Besides, the GO and KEGG analysis indicated that TwHF caused ovarian toxicity through oxidative stress, reproductive system development and function, regulation of cell cycle, response to endogenous hormones and exogenous stimuli, apoptosis regulation and aging. The docking studies suggested that 3 core ovarian toxic compounds of TwHF were able to fit in the binding pocket of the 10 hub genes. TwHF may cause ovarian toxicity by acting on 10 hub genes and 140 signaling pathways.
Drugs, Chinese Herbal/toxicity* ; Medicine, Chinese Traditional ; Molecular Docking Simulation ; Network Pharmacology ; Protein Interaction Maps