scholarly journals Use of Network Pharmacology to Investigate the Mechanism of the Compound Xuanju Capsule in the Treatment of Rheumatoid Arthritis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wenyang Wei ◽  
Wanpeng Lu ◽  
Xiaolong Chen ◽  
Yunfeng Yang ◽  
Mengkai Zheng
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Active Ingredient ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Related Disease ◽  
Ppi Networks ◽  
Target Network ◽  
The Common

Objective. To clarify the therapeutic mechanisms of compound Xuanju capsule-treated rheumatoid arthritis (RA) based on network pharmacology tactics. Method. The TCMSP, TCMID and STITCH databases were used to screen the active ingredients and targets in the compound Xuanju capsule; the OMIM, TTD, PharmGKB and GeneCards databases were applied to screen the RA-related disease targets. Then, the obtained targets were imported into Cytoscape 3.7.1 software to construct the active ingredient-target network and the RA-related disease-target network. The active ingredient-target PPI network, the RA-related disease-target PPI network and the common target PPI network were built by using the STRING platform and Cytoscape 3.7.1 software. The GO and KEGG analyses of the common targets were analyzed by using the Metascape and Bioinformatics online tools. Results. A total of 51 active ingredients and 513 corresponding ingredient targets were harvested from the compound Xuanju capsule; 641 RA-related disease targets were obtained. After two PPI networks were constructed and merged, 116 RA-related targets of compound Xuanju capsules were identified and analyzed. 116 RA-related targets of compound Xuanju capsules are mainly involved in the biological processes and molecular functions, such as the cytokine-mediated signaling pathways, the response to lipopolysaccharide and the blood vascular development, the cytokine activity, the cytokine receptor binding and the receptor regulator activity. Furthermore, 116 RA-related targets of compound Xuanju capsules are concentrated in signaling pathways such as the IL-17, TNF, Th17 cell differentiation, Toll receptor and RA signaling pathway. Conclusion. The compound Xuanju capsule had the action characteristics of multiple components, multiple targets, and multiple pathways in the treatment of RA, which might primarily reduce the release of proinflammatory factors (such as IL-6 and TNF-α) and increase the production of anti-inflammatory factors (such as IL-10) by regulating inflammation-related signaling pathways (such as IL-17), thereby alleviating the inflammatory damage and improving the bone tissue repair.

scholarly journals Deciphering the Active Ingredients and Molecular Mechanisms of Tripterygium hypoglaucum (Levl.) Hutch against Rheumatoid Arthritis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Yunbin Jiang ◽  
Mei Zhong ◽  
Fei Long ◽  
Rongping Yang
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Molecular Mechanisms ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Clinical Effects ◽  
Overlapping Genes ◽  
Active Ingredients ◽  
Tripterygium Hypoglaucum

Tripterygium hypoglaucum (Levl.) Hutch (THH) shows well clinical effect on rheumatoid arthritis (RA), but the active ingredients and molecular mechanisms remain unclear. This work was designed to explore these issues by network pharmacology. Compounds from THH were gathered by retrieving literatures. Compound-related and RA-related genes were identified using databases, and the overlapping genes were identified by Venn diagram. The active ingredients and genes of THH against RA were confirmed by dissecting interactions between overlapping genes and compounds using Cytoscape. SystemsDock website was used to further verify the combining degree of key genes with active ingredients. Pathway enrichment analysis was performed to decipher the mechanisms of THH against RA by Database for Annotation, Visualization and Integrated Discovery. A total of 123 compounds were collected, and 110 compounds-related and 1871 RA-related genes were identified, including 64 overlapping genes. The target genes and active ingredients of THH against RA comprised 64 genes and 17 compounds, the focus of which was PTGS2, triptolide, and celastrol. SystemsDock website indicated that the combing degree of PTGS2 with triptolide or celastrol was very good. The mechanisms of THH against RA were linked to 31 signaling pathways, and the key mechanism was related to inhibition of inflammation response through inactivating TNF and NF-kappa B signaling pathways. This work firstly explored the active ingredients and mechanisms of THH against RA by network pharmacology and provided evidence to support clinical effects of THH on RA.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Mingjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology.Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

scholarly journals Network Pharmacology-Based Investigation of the Mechanism of Action of Plantaginis Herba in Hyperuricemia Treatment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Rong Tang ◽  
Xiaoqing Peng ◽  
Yan Wang ◽  
Xiaohong Zhou ◽  
Hong Liu
Keyword(s):  
Signaling Pathways ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Bioinformatics Analyses ◽  
Network Construction ◽  
Kegg Analysis ◽  
Underlying Mechanisms

This study used a network pharmacology approach to investigate the potential active ingredients of Plantaginis Herba and its underlying mechanisms in hyperuricemia treatment. The potential active ingredients of Plantaginis Herba were obtained from TCMSP and ETCM databases, and the potential targets of the active ingredients were predicted using the Swiss TargetPrediction database. The potential therapeutic targets of hyperuricemia were retrieved from the GeneCards, DisGeNET, and Online Mendelian Inheritance in Man (OMIM) databases. Then, the integrative bioinformatics analyses of candidates were performed by GO analysis, KEGG analysis, and PPI network construction. There were 15 predicted active ingredients in Plantaginis Herba and 41 common targets that may be involved in the treatment of hyperuricemia. A total of 61 GO annotations and 35 signaling pathways were identified by enrichment analysis ( P < 0.01 ). The underlying mechanisms of Plantaginis Herba may be related to insulin resistance, PI3K/AKT, TNF, VEGF, AMPK, and glucagon signaling pathways. Thus, the present study provided potential and promising strategies of Plantaginis Herba for hyperuricemia treatment.

Network Pharmacology and Molecular Docking Study of Jinwei Decoction for Enhancement of Glucocorticoid Anti-Inflammatory Effect in COPD through miR-21

2021 ◽  
Author(s):  
jianjun wu ◽  
Ping-an Zhang ◽  
Ming-zhe Chen ◽  
Yi-xuan Li ◽  
Ying-xue Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Ppi Networks ◽  
Core Proteins ◽  
Anti Inflammatory ◽  
Inflammatory Effect

Abstract PurposeJinwei decoction can enhance the anti-inflammatory effect of glucocorticoid (GC) on chronic obstructive pulmonary disease (COPD) by restoring the activity of HDAC2. But the upstream mechanism of Jinwei decoction on HDAC2 expression is not clear. ObjectiveTo explore whether Jinwei decoction can enhance the anti-inflammatory effect of GC on COPD through microRNA21 (miR-21) by network pharmacology. MethodsThe TCMSP database was used to screen active ingredients and target genes of Jinwei decoction, and miRWalk2.0 was used to predict downstream target genes of miR-21. COPD-related genes were identified by searching GeneCards and OMIM databases; Venny 2.1 was used to screen intersection genes; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of intersection genes were analyzed by R software. Protein-protein interactions (PPIs) were analyzed by Cytoscape 3.7.2 software to identify core genes. Finally, interactions between main compounds and potential targets were verified by molecular docking. ResultsTwo hundred ninety-two active ingredients, 316 Jinwei drug targets, 10170 miR-21 target genes, 6617 COPD target genes, and 184 intersection gene were identified. Eleven core proteins of PPI networks may be involved. GO enrichment analysis showed that oxidative stress, regulation of inflammatory response, hormone transport, and histone modification were involved; KEGG pathway enrichment analysis concentrated in the PI3K-Akt, mitogen-activated protein kinase (MAPK), HIF-1, neutrophil extracellular bactericidal network, and other signaling pathways. ConclusionJinwei decoction can regulate histone deacetylase-2 activity and enhance the anti-inflammatory effect of GC on COPD by modulating miR-21. Its mechanism of action may be related to its effect on the PI3K Akt, MAPK, and TNF signaling pathways and neutrophil extracellular trap formation through miR-21.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Minjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology. Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

scholarly journals A Network Pharmacology Approach to Explore Mechanism of Action of Longzuan Tongbi Formula on Rheumatoid Arthritis

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
An Huang ◽  
Gang Fang ◽  
Yuzhou Pang ◽  
Zongran Pang
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathway ◽  
Active Rheumatoid Arthritis ◽  
Trp Channels ◽  
Network Pharmacology ◽  
Mtor Signaling Pathway ◽  
Active Ingredients ◽  
Major Pathway ◽  
Pharmacological Mechanism ◽  
Ppar Signaling

Longzuan Tongbi Formula (LZTB) is an effective proved prescription in Zhuang medicine for treating active rheumatoid arthritis (RA). However, its active ingredients, underlying targets, and pharmacological mechanism are still not clear in treating RA. We have applied network pharmacology to study LZTB and found that 8 herbs in LZTB and 67 compounds in the 8 herbs are involved in the regulation of RA-related genes; we have conducted pathway analysis of overlapping genes and found that 7 herbs participate in the regulations of 24 pathways associated with RA and that 5 herbs in the 7 herbs and 25 compounds in the 5 herbs participate in the regulation of hsa05323 (rheumatoid arthritis). The results indicated that all herbs in LZTB and some compounds in those herbs participate in the treatment of RA; 25 compounds are main active ingredients and hsa05323 (rheumatoid arthritis) is the major pathway in the treatment of RA. We have also found that three pathways (inflammatory mediator regulation of TRP channels, PPAR signaling pathway, and mTOR signaling pathway) might have some effect on the treatment of RA.

scholarly journals Mechanism of Action of Bu-Fei-Yi-Shen Formula in Treating Chronic Obstructive Pulmonary Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Longchuan Wu ◽  
Yu Chen ◽  
Jiao Yi ◽  
Yi Zhuang ◽  
Lei Cui ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Chronic Obstructive ◽  
Biological Functions ◽  
Active Ingredients ◽  
Obstructive Pulmonary Disease ◽  
The Core ◽  
Target Network

Objective. To explore the mechanism of action of Bu-Fei-Yi-Shen formula (BFYSF) in treating chronic obstructive pulmonary disease (COPD) based on network pharmacology analysis and molecular docking validation. Methods. First of all, the pharmacologically active ingredients and corresponding targets in BFYSF were mined by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the analysis platform, and literature review. Subsequently, the COPD-related targets (including the pathogenic targets and known therapeutic targets) were identified through the TTD, CTD, DisGeNet, and GeneCards databases. Thereafter, Cytoscape was employed to construct the candidate component-target network of BFYSF in the treatment of COPD. Moreover, the cytoHubba plug-in was utilized to calculate the topological parameters of nodes in the network; then, the core components and core targets of BFYSF in the treatment of COPD were extracted according to the degree value (greater than or equal to the median degree values for all nodes in the network) to construct the core network. Further, the Autodock vina software was adopted for molecular docking study on the core active ingredients and core targets, so as to verify the above-mentioned network pharmacology analysis results. Finally, the Omicshare database was applied in enrichment analysis of the biological functions of core targets and the involved signaling pathways. Results. In the core component-target network of BFYSF in treating COPD, there were 30 active ingredients and 37 core targets. Enrichment analysis suggested that these 37 core targets were mainly involved in the regulation of biological functions, such as response to biological and chemical stimuli, multiple cellular life processes, immunity, and metabolism. Besides, multiple pathways, including IL-17, Toll-like receptor (TLR), TNF, and HIF-1, played certain roles in the effect of BFYSF on treating COPD. Conclusion. BFYSF can treat COPD through the multicomponent, multitarget, and multipathway synergistic network, which provides basic data for intensively exploring the mechanism of action of BFYSF in treating COPD.

scholarly journals Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ping Yang ◽  
Haifeng He ◽  
Shangfu Xu ◽  
Ping Liu ◽  
Xinyu Bai
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Target Prediction ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Xie ◽  
Jun Wu ◽  
Sihui Yang ◽  
Huaijun Zhou
Keyword(s):  
Molecular Docking ◽  
Drug Targets ◽  
Aloe Vera ◽  
Beta Carotene ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Molecule Docking

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.

scholarly journals Myrtenal and β-caryophyllene oxide screened from Liquidambaris Fructus suppress NLRP3 inflammasome components in rheumatoid arthritis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wen-xuan Li ◽  
Ping Qian ◽  
Yi-tong Guo ◽  
Li Gu ◽  
Jessore Jurat ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Nlrp3 Inflammasome ◽  
Network Pharmacology ◽  
Caryophyllene Oxide ◽  
Active Ingredients ◽  
Caspase 1 ◽  
Tnf Α ◽  
Cartilage Erosion ◽  
And Cartilage

Abstract Background Liquidambaris Fructus (LF) is the infructescence of Liquidambar formosana. In Traditional Chinese Medicine, LF has been used to treat joint pain, a common symptom of arthritis and rheumatism; however, a lack of pharmacological evidence has limited its applications in modern clinics. Therefore, this study aims to explore the protective effect of LF on rheumatoid arthritis (RA) and to identify its active ingredients. Methods Rats with adjuvant-induced arthritis (AIA) were divided into 4 groups and administered petroleum ether extract of LF (PEL), ethyl acetate extract of LF (EEL), water extract of LF (WEL), or piroxicam (PIR) respectively for 3 weeks. Two additional groups were used as normal control (NC) and model control (MC) and administered distilled water as a placebo. The clinical scores for arthritis, bone surface, synovial inflammation and cartilage erosion were used to evaluate the therapeutic efficacy of each treatment. The serum IL-1β and TNF-α level and the expression of NLRP3, IL-1β and caspase-1 p20 in the synovial tissue of AIA rats were evaluated by ELISA and Western blot. The active ingredients of LF were investigated using network pharmacology and molecular docking methods, and their inhibition of NLRP3 inflammasome activation was verified in the human rheumatoid arthritis fibroblast-like synovial cells (RA-FLS) model. Results PEL could alleviate paw swelling, bone and joint destruction, synovial inflammation and cartilage erosion in the AIA rats, with significantly superior efficacy to that of EEL and WEL. PEL reduced IL-1β and TNF-α serum levels, and attenuated the upregulation of NLRP3, IL-1β and caspase-1 p20 expression in the synovial tissue of AIA rats. Network pharmacology and molecular docking results indicated that myrtenal and β-caryophyllene oxide were the main two active ingredients of PEL, and these two compounds showed significant inhibition on TNF-α, NLRP3, IL-1β and caspase-1 p20 expression in RA-FLS. Conclusions Myrtenal and β-caryophyllene oxide screened from PEL could suppress the activation of NLRP3 inflammasome, thereby alleviating RA symptoms.

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