scholarly journals Reveals of New Candidate Active Components in Hemerocallis Radix and Its Anti-Depression Action of Mechanism Based on Network Pharmacology Approach

2020 ◽  
Vol 21 (5) ◽  
pp. 1868 ◽  
Author(s):  
Hsin-Yi Lin ◽  
Jen-Chieh Tsai ◽  
Lung-Yuan Wu ◽  
Wen-Huang Peng
Keyword(s):  
Network Pharmacology ◽  
Antidepressant Effect ◽  
Depression Symptoms ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Go Enrichment ◽  
Therapeutic Mechanism ◽  
And Cluster Analysis ◽  
Depression Disorder

The global depression population is showing a significant increase. Hemerocallis fulva L. is a common Traditional Chinese Medicine (TCM). Its flower buds are known to have ability to clear away heat and dampness, detoxify, and relieve depression. Ancient TCM literature shows that its roots have a beneficial effect in calming the spirit and even the temper in order to reduce the feeling of melancholy. Therefore, it is inferred that the root of Hemerocallis fulva L. can be used as a therapeutic medicine for depression. This study aims to uncover the pharmacological mechanism of the antidepressant effect of Hemerocallis Radix (HR) through network pharmacology method. During the analysis, 11 active components were obtained and screened using ADME—absorption, distribution, metabolism, and excretion— method. Furthermore, 267 HR targets and 740 depressive disorder (DD) targets were gathered from various databases. Then protein–protein interaction (PPI) network of HR and DD targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, gene ontology (GO) enrichment and pathway analysis was applied to further verify that the biological process related to the target protein is associated with the occurrence of depression disorder. In conclusion, the most important bioactive components—anthraquinone, kaempferol, and vanillic acid—can alleviate depression symptoms by regulating MAOA, MAOB, and ESR1. The proposed network pharmacology strategy provides an integrating method to explore the therapeutic mechanism of multi-component drugs on a systematic level.

scholarly journals Network Pharmacology-Based Identification of the Mechanisms of Shen-Qi Compound Formula in Treating Diabetes Mellitus

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Zhipeng Hu ◽  
Maoyi Yang ◽  
Liangjun Yang ◽  
Chunguang Xie ◽  
Hong Gao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
System Pharmacology ◽  
Target Network ◽  
Integrated Pathway ◽  
Go Enrichment Analysis

Aim. The purpose of this research is to identify the mechanisms of Shen-Qi compound formula (SQC), a traditional Chinese medicine (TCM), for treating diabetes mellitus (DM) using system pharmacology. Methods. The active components and therapeutic targets were identified, and these targets were analyzed using gene ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) analysis. Finally, an integrated pathway was constructed to show the mechanisms of SQC. Results. A total of 282 active components and 195 targets were identified through a database search. The component-target network was constructed, and the key components were screened out according to their degree. Through the GO, PPI, and KEGG analyses, the mechanism network of SQC treating DM was constructed. Conclusions. This study shows that the mechanisms of SQC treating DM are related to various pathways and targets. This study provides a good foundation and basis for further in-depth verification and clinical application.

scholarly journals Network Pharmacology and Experimental Assessment to Explore the Pharmacological Mechanism of Qimai Feiluoping Decoction Against Pulmonary Fibrosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Yingying Yang ◽  
Lu Ding ◽  
Tingting Bao ◽  
Yaxin Li ◽  
Jing Ma ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Epithelial Mesenchymal Transition ◽  
Clinical Symptoms ◽  
A549 Cells ◽  
Network Pharmacology ◽  
Active Components ◽  
Mesenchymal Transition ◽  
Pharmacological Mechanism ◽  
Ecm Degradation ◽  
Tgf Β1

Pulmonary fibrosis (PF) is one of the pathologic changes in COVID-19 patients in convalescence, and it is also a potential long-term sequela in severe COVID-19 patients. Qimai Feiluoping decoction (QM) is a traditional Chinese medicine formula recommended in the Chinese national medical program for COVID-19 convalescent patients, and PF is one of its indications. Through clinical observation, QM was found to improve the clinical symptoms and pulmonary function and reduce the degree of PF of COVID-19 convalescent patients. To further explore the pharmacological mechanisms and possible active components of QM in anti-PF effect, UHPLC/Q-TOF-MS was used to analyze the composition of the QM extract and the active components that can be absorbed into the blood, leading to the identification of 56 chemical compounds and 10 active components. Then, network pharmacology was used to predict the potential mechanisms and targets of QM; it predicted that QM exerts its anti-PF effects via the regulation of the epithelial–mesenchymal transition (EMT), extracellular matrix (ECM) degradation, and TGF-β signaling pathway. Finally, TGF-β1–induced A549 cells were used to verify and explore the pharmacological effects of QM and found that QM could inhibit the proliferation of TGF-β1–induced A549 cells, attenuate EMT, and promote ECM degradation by inhibiting the TGF-β/Smad3 pathway.

scholarly journals An Investigation of the Mechanism of Rapid Relief of Ulcerative Colitis Induced by Five-flavor Sophora Flavescens Enteric-coated Capsules Based on Network Pharmacology

2020 ◽  
Vol 23 (3) ◽  
pp. 239-252 ◽  
Author(s):  
Sizhen Gu ◽  
Yan Xue ◽  
Yuli Zhang ◽  
Kanjun Chen ◽  
Shigui Xue ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Immune Recognition ◽  
Sophora Flavescens ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
The Core ◽  
Correlation Parameters ◽  
Enteric Coated

Aim and Objective: Five-Flavor Sophora flavescens Enteric-Coated Capsules (FSEC) are the only proprietary Chinese medicine approved for the treatment of ulcerative colitis (UC) in China. Phase II and III clinical trials have shown that the curative effect of FSEC in relieving UC was not inferior to that of mesalazine granules and enteric-coated tablets, but its pharmacological mechanism is unclear. Therefore, the network pharmacology is used to reveal the more comprehensive effective components and targets of FSEC in the treatment of UC. Methods: We screened the components of FSEC based on the TCMSP database, determined the action targets of these compounds through target fishing, and integrated the UC disease targets of several disease gene databases. The FSEC-UC composite targets were obtained by matching the two results, and then a PPI network was constructed to analyze the relationship between these targets, and the core targets were selected by topological correlation parameters. Finally, GO-BP and KEGG enrichment analyses were carried out using the clusterProfiler software package. Results: One hundred and sixty active components of FSEC were identified and 77 targets were obtained. Of these, 30 core targets were the main targets of FESC in the treatment of UC. And quercetin, kaempferol, luteolin and mangiferin were regarded as the core active components of FSEC. The results screened by GO and KEGG enrichment analysis showed that FSEC played a comprehensive therapeutic role in immune recognition, anti-inflammation and antioxidation mainly through IL-17, TNF, Toll-like receptor, NF-kappa B, and Th17 cell differentiation. Conclusion: The molecular mechanism of UC remission induced by FSEC was predicted by network pharmacology. These findings provide an important theoretical basis for further study of the effective substances and mechanism of FSEC in the treatment of UC.

scholarly journals A Network Pharmacology Approach to Explore the Pharmacological Mechanism of Xiaoyao Powder on Anovulatory Infertility

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Huiping Liu ◽  
Liuting Zeng ◽  
Kailin Yang ◽  
Guomin Zhang
Keyword(s):  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Compounds ◽  
Pharmacological Mechanism ◽  
Go Enrichment ◽  
Human Proteins ◽  
Network Pictures ◽  
Go Enrichment Analysis ◽  
Anovulatory Infertility

Aim.To explore the pharmacological mechanism of Xiaoyao powder (XYP) on anovulatory infertility by a network pharmacology approach.Method.Collect XYP’s active compounds by traditional Chinese medicine (TCM) databases, and input them into PharmMapper to get their targets. Then note these targets by Kyoto Encyclopedia of Genes and Genomes (KEGG) and filter out targets that can be noted by human signal pathway. Get the information of modern pharmacology of active compounds and recipe’s traditional effects through databases. Acquire infertility targets by Therapeutic Target Database (TTD). Collect the interactions of all the targets and other human proteins via String and INACT. Put all the targets into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to do GO enrichment analysis. Finally, draw the network by Cytoscape by the information above.Result.Six network pictures and two GO enrichment analysis pictures are visualized.Conclusion.According to this network pharmacology approach some signal pathways of XYP acting on infertility are found for the first time. Some biological processes can also be identified as XYP’s effects on anovulatory infertility. We believe that evaluating the efficacy of TCM recipes and uncovering the pharmacological mechanism on a systematic level will be a significant method for future studies.

scholarly journals Network Pharmacology Study on the Pharmacological Mechanism of Cinobufotalin Injection against Lung Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yun Mao ◽  
Xi Peng ◽  
Peng Xue ◽  
Dianrong Lu ◽  
Linlu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Therapeutic Targets ◽  
Target Prediction ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Chinese Giant Salamander ◽  
Receptor Signaling Pathway

Cinobufotalin injection, extracted from the skin of Chinese giant salamander or black sable, has good clinical effect against lung cancer. However, owing to its complex composition, the pharmacological mechanism of cinobufotalin injection has not been fully clarified. This study aimed to explore the mechanism of action of cinobufotalin injection against lung cancer using network pharmacology and bioinformatics. Compounds of cinobufotalin injection were determined by literature retrieval, and potential therapeutic targets of cinobufotalin injection were screened from Swiss Target Prediction and STITCH databases. Lung-cancer-related genes were summarized from GeneCards, OMIM, and DrugBank databases. The pharmacological mechanism of cinobufotalin injection against lung cancer was determined by enrichment analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction network was constructed. We identified 23 compounds and 506 potential therapeutic targets of cinobufotalin injection, as well as 70 genes as potential therapeutic targets of cinobufotalin injection in lung cancer by molecular docking. The antilung cancer effect of cinobufotalin injection was shown to involve cell cycle, cell proliferation, antiangiogenesis effect, and immune inflammation pathways, such as PI3K-Akt, VEGF, and the Toll-like receptor signaling pathway. In network analysis, the hub targets of cinobufotalin injection against lung cancer were identified as VEGFA, EGFR, CCND1, CASP3, and AKT1. A network diagram of “drug-compounds-target-pathway” was constructed through network pharmacology to elucidate the pharmacological mechanism of the antilung cancer effect of cinobufotalin injection, which is conducive to guiding clinical medication.

Pharmacological mechanism of Xiaoyao San in the treatment of polycystic ovary syndrome based on network pharmacology

2020 ◽  
Author(s):  
Chunyu Zhu ◽  
Yajun Hu ◽  
Wangdong Zheng ◽  
Yanyan Zhang ◽  
Yiting Li ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Drug Targets ◽  
Polycystic Ovary ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Ovary Syndrome ◽  
Pharmacological Mechanism ◽  
R Project

Abstract Background : Xiaoyao San(XYS) has been widely used in the treatment of polycystic ovary syndrome(PCOS), but its mechanism is not clear. The purpose of this study is to elucidate the mechanism of XYS in the treatment of PCOS from the aspects of active components, targets and pathways. The purpose of the study is to explore the molecular mechanism of XYS in the treatment of PCOS. Methods : TCMSP database, UniProt and Perl were used to screen and collect the active components and targets of XYS. The genes related to PCOS were searched in GeneCards database. Collect the related targets of PCOS and XYS, use STRING database and Cytoscape software to process the data visually and analyze topology, and screen the key components and targets in the network. The key targets were enriched by R Project to predict the mechanism of XYS in the treatment of PCOS. Results : 68 active components and 96 drug targets in XYS were screened out. 3648 PCOS related disease targets were collected. 66 targets of XYS for PCOS treatment were obtained after analysis. 21 key targets of NCOA2, PGR, PTGS1, PPARG and AR were constructed after topology analysis. 63 biological functions and 111 biological pathways were obtained after gene ontology(GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) Pathway enrichment analysis. Conclusions : XYS has the characteristics of multi-component, multi-target and multi-path. This study discussed the active components, targets and potential mechanism of XYS in the treatment of PCOS, which provided a new direction for further study of the mechanism of XYS in the treatment of PCOS, and provides more ideas for clinical treatment of PCOS.

scholarly journals Predicting the Molecular Mechanism of “Angong Niuhuang Pills” in the Treatment of COVID-19 Based on Network Pharmacology

2021 ◽  
Vol 16 (6) ◽  
pp. 1934578X2110240
Author(s):  
Peng-yu Chen ◽  
Chen Wang ◽  
Ying Zhang ◽  
Chong Yuan ◽  
Bing Yu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Treatment Plan ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Pathway Annotation ◽  
Chinese Patent ◽  
8Th Edition

Introduction Angong Niuhuang Pills (AGNH), a Chinese patent medicine recommended in the “Diagnosis and Treatment Plan for COVID-19 (8th Edition),” may be clinically effective in treating COVID-19. The active components and signal pathways of AGNH through network pharmacology have been examined, and its potential mechanisms determined. Methods We screened the components in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) via Drug-like properties (DL) and Oral bioavailability (OB); PharmMapper and GeneCards databases were used to collect components and COVID-19 related targets; KEGG pathway annotation and GO bioinformatics analysis were based on KOBAS3.0 database; “herb-components-targets-pathways” (H-C-T-P) network and protein-protein interaction network (PPI) were constructed by Cytoscape 3.6.1 software and STRING 10.5 database; we utilized virtual molecular docking to predict the binding ability of the active components and key proteins. Results A total of 87 components and 40 targets were screened in AGNH. The molecular docking results showed that the docking scores of the top 3 active components and the targets were all greater than 90. Conclusion Through network pharmacology research, we found that moslosooflavone, oroxylin A, and salvigenin in AGNH can combine with ACE2 and 3CL, and then are involved in the MAPK and JAK-STAT signaling pathways. Finally, it is suggested that AGNH may have a role in the treatment of COVID-19.

scholarly journals Pharmacological Mechanisms Underlying the Anti-asthmatic Effects of Modified Guomin Decoction Determined by Network Pharmacology and Molecular Docking

2021 ◽  
Vol 8 ◽  
Author(s):  
Guishu Wang ◽  
Bo Zhou ◽  
Zheyi Wang ◽  
Yufeng Meng ◽  
Yaqian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanism ◽  
Airway Remodeling ◽  
Enrichment Analysis ◽  
Chronic Inflammatory Disease ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds ◽  
Protein Protein Interaction ◽  
Pathway Annotation

BackgroundAsthma is a chronic inflammatory disease characterized by Th2-predominant inflammation and airway remodeling. Modified Guo Min decoction (MGMD) has been an extensive practical strategy for allergic disorders in China. Although its potential anti-asthmatic activity has been reported, the exact mechanism of action of MGMD in asthma remains unexplored.MethodsNetwork pharmacology approach was employed to predict the active components, potential targets, and molecular mechanism of MGMD for asthma treatment, including drug-likeness evaluation, oral bioavailability prediction, protein–protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Reactome pathway annotation. Molecular docking was carried out to investigate interactions between active compounds and potential targets.ResultsA total of 92 active compounds and 72 anti-asthma targets of MGMD were selected for analysis. The GO enrichment analysis results indicated that the anti-asthmatic targets of MGMD mainly participate in inflammatory and in airway remolding processes. The Reactome pathway analysis showed that MGMD prevents asthma mainly through regulation of the IL-4 and IL-13 signaling and the specialized pro-resolving mediators (SPMs) biosynthesis. Molecular docking results suggest that each bioactive compounds (quercetin, wogonin, luteolin, naringenin, and kaempferol) is capable to bind with STAT3, PTGS2, JUN, VEGFA, EGFR, and ALOX5.ConclusionThis study revealed the active ingredients and potential molecular mechanism by which MGMD treatment is effective against airway inflammation and remodeling in asthma through regulating IL-4 and IL-13 signaling and SPMs biosynthesis.

scholarly journals Analysis of the Active Components and Mechanism of Three Prescriptions in the Treatment of COVID-19 Via Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110477
Author(s):  
Fei Wang ◽  
Jia-Hui Chen ◽  
Bo Liu ◽  
Ting Zhang
Keyword(s):  
Molecular Docking ◽  
Binding Energies ◽  
Network Pharmacology ◽  
Active Components ◽  
Chinese Medicines ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Ppi Networks ◽  
Infection And Inflammation ◽  
Analysis Platform

Purpose: Prescriptions of Han-Shi-Yu-Fei (HSYF), Han-Shi-Zu-Fei (HSZF), and Yi-Du-Bi-Fei (YDBF) were effective in treating COVID-19. Based on network pharmacology and molecular docking, overlapping Traditional Chinese medicines (TCMs), their active components, and core targets were explored in this study. Methods: First, the overlapping TCMs and their active components were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) by evaluating Oral Bioactivity (OB) and Drug Likeness (DL). The overlapping targets of potential components and COVID-19 were collected by SwissTargetPrediction, Gene Cards, and Venn 2.1.0 databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed via DAVID6.8.1 database. Through comprehensive analysis of the “prescriptions-TCMs-components” (P-T-C), “components-targets-pathways” (C-T-P) and “protein–protein interaction” (PPI) networks constructed by Cytoscape 3.7.1 software, the active components and core targets were obtained. Finally, the binding energies of these components with ACE2 and SARS-CoV-2 3CL were analyzed by AutDockTools-1.5.6 and PyMOL software. Results: In all, five overlapping TCMs, 40 potential active components, and 47 candidate targets were obtained and analyzed in these prescriptions. There were 288 GO entries ( P < 0.05), including 211 biological process (BP), 40 cell composition (CC), and 37 molecular function (MF) entries. Most of the 105 KEGG pathways ( P < 0.05) were involved with viral infection and inflammation. Through “PPI” and “C-T-P” networks, the core targets (EGFR, PTGS2, CDK2, GSK3B, PIK3R1, and MAPK3) and active components (Q27134551, acanthoside B, neohesperidin, and irisolidone) with high degrees were obtained. Molecular docking results showed that the above-mentioned four components could inhibit the binding of ACE2 and SARS-COV-2 3CL to protect against COVID-19. Conclusion: In this study, the active components and core targets of three prescriptions in the treatment of COVID-19 were elaborated by network pharmacology and molecular docking, providing a reference for their applications.

scholarly journals Uncovering the mechanism of Ge-Gen-Qin-Lian decoction for treating ulcerative colitis based on network pharmacology and molecular docking verification

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Lin Xu ◽  
Jiaqi Zhang ◽  
Yifan Wang ◽  
Zedan Zhang ◽  
Fengyun Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Potential Candidate ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Th17 Cell Differentiation ◽  
The Relationship

Abstract Background: Ge-Gen-Qin-Lian Decoction (GGQLD), a traditional Chinese medicine (TCM) formula, has been widely used for ulcerative colitis (UC) in China, but the pharmacological mechanisms remain unclear. This research was designed to clarify the underlying pharmacological mechanism of GGQLD against UC. Method: In this research, a GGQLD-compound-target-UC network was constructed based on public databases to clarify the relationship between active compounds in GGQLD and potential targets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed to investigate biological functions associated with potential targets. A protein–protein interaction network was constructed to screen and evaluate hub genes and key active ingredients. Molecular docking was used to verify the activities of binding between hub targets and ingredients. Results: Finally, 83 potential therapeutic targets and 118 corresponding active ingredients were obtained by network pharmacology. Quercetin, kaempferol, wogonin, baicalein, and naringenin were identified as potential candidate ingredients. GO and KEGG enrichment analyses revealed that GGQLD had anti-inflammatory, antioxidative, and immunomodulatory effects. The effect of GGQLD on UC might be achieved by regulating the balance of cytokines (e.g., IL-6, TNF, IL-1β, CXCL8, CCL2) in the immune system and inflammation-related pathways, such as the IL-17 pathway and the Th17 cell differentiation pathway. In addition, molecular docking results demonstrated that the main active ingredient, quercetin, exhibited good affinity to hub targets. Conclusion: This research fully reflects the multicomponent and multitarget characteristics of GGQLD in the treatment of UC. Furthermore, the present study provided new insight into the mechanisms of GGQLD against UC.

Sign in / Sign up

Export Citation Format

Share Document