scholarly journals Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by Geo Gene Chip Combined With Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
tan xin ◽  
Wei Xian ◽  
Xiaorong Li ◽  
Yongfeng Chen ◽  
Jiayi Geng ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Chemical Structures ◽  
Drug Mechanism

Abstract PurposeAtrial fibrillation (AF) is a common atrial arrhythmia. Quercetin (Que) has some advantages in the treatment of cardiovascular disease arrhythmias, but its specific drug mechanism of action needs further investigation. To explore the mechanism of action of Que in AF, core target speculation and analysis were performed using network pharmacology and molecular docking methods.MethodsQue chemical structures were obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank , STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF from normal tissues by GEO database differentially expressed genes. Then, the intersecting genes were obtained by online Wayne mapping tool. The intersection genes were introduced into the top five targets selected for molecular docking via protein-protein interaction (PPI) network to verify the binding activity between Que and the target proteins. GO and KEGG enrichment analysis of the intersected genes using program R was performed to further screen for key genes and key pathways.ResultsThere were 65 effective targets for Que and AF. Through further screening, the top 5 targets were IL6, VEGFA, JUN, MMP9 and EGFR. Que treatment of AF may involve signaling pathways such as lipid and atherosclerosis pathway, AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. Molecular docking suggests that Que has strong binding to key targets.ConclusionThis study systematically elucidates the key targets of Que treatment for AF and the specific mechanisms through network pharmacology as well as molecular docking, providing a new direction for further basic experimental exploration and clinical treatment.

scholarly journals Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Mengshi Tang ◽  
Xi Xie ◽  
Pengji Yi ◽  
Jin Kang ◽  
Jiafen Liao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
New Combination ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

scholarly journals Study on the Mechanism of Acori Graminei Rhizoma in the Treatment of Alzheimer’s Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Kuan Du ◽  
Yue Xiao ◽  
Shao Min Zhong ◽  
Yi Xing Huang ◽  
Qian Wen Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Active Components

Alzheimer’s disease is a common neurodegenerative disease in the elderly. This study explored the curative effect and possible mechanism of Acori graminei rhizoma on Alzheimer’s disease. In this paper, 8 active components of Acori graminei rhizoma were collected by consulting literature and using the TCMSP database, and 272 targets were screened using the PubChem and Swiss Target Prediction databases. Introduce it into the software of Cytoscape 3.7.2 and establish the graph of “drug-active ingredient-ingredient target.” A total of 276 AD targets were obtained from OMIM, Gene Cards, and DisGeNET databases. Import the intersection targets of drugs and diseases into STRING database for enrichment analysis, and build PPI network in the Cytoscape 3.7.2 software, whose core targets involve APP, AMPK, NOS3, etc. GO analysis and KEGG analysis showed that there were 195 GO items and 30 AD-related pathways, including Alzheimer’s disease pathway, serotonin synapse, estrogen signaling pathway, dopaminergic synapse, and PI3K-Akt signaling pathway. Finally, molecular docking was carried out to verify the binding ability between Acori graminei rhizoma and core genes. Our results predict that Acori graminei rhizoma can treat AD mainly by mediating Alzheimer’s signal pathway, thus reducing the production of Aβ, inhibiting the hyperphosphorylation of tau protein, regulating neurotrophic factors, and regulating the activity of kinase to change the function of the receptor.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

scholarly journals Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by GEO Gene Chip Combined with Network Pharmacology and Molecular Docking

2022 ◽  
Author(s):  
Xin Tan ◽  
Wei Xian ◽  
Xiaorong Li ◽  
Yongfeng Chen ◽  
Jiayi Geng ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Prediction ◽  
Mapk Signaling ◽  
Differentially Expressed ◽  
Network Pharmacology ◽  
Therapeutic Drug ◽  
Geo Database

Abstract Atrial fibrillation (AF) is a common atrial arrhythmia for which there is no specific therapeutic drug. Quercetin (Que) has been used to treat cardiovascular diseases such as arrhythmias. In this study, we explored the mechanism of action of Que in AF using network pharmacology and molecular docking. The chemical structure of Que was obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank, STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF and normal tissue by GEO database differentially expressed genes by GEO database. The top targets were IL6, VEGFA, JUN, MMP9 and EGFR, and Que for AF treatment might involve the lipid and atherosclerosis pathway, the role of AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. In addition, molecular docking showed that Que binds strongly to key targets and is differentially expressed in AF. This study systematically elucidated the key targets of Que treatment for AF and the specific mechanisms, providing a new direction for further basic experimental exploration and clinical treatment.

A Network Pharmacology Approach to Explore the Underlying Mechanism of Tufuling Qiwei Tangsan in Treating Psoriasis

2021 ◽  
Vol 16 ◽  
Author(s):  
Xiaolei Ma ◽  
Yinan Lu ◽  
Yang Lu ◽  
Zhili Pei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds

Background: Tufuling Qiwei Tangsan (TQTS) is a commonly used Mongolian medicine preparation against psoriasis in China. However, its mechanism of action and molecular targets for the treatment of psoriasis is still unclear. Network pharmacology can reveal the synergistic mechanism of drugs at the molecular, target and pathway levels, and is suitable for the complex study of traditional Chinese medicine formulations. However, it is rarely involved in the application of Mongolian medicine with the same holistic concept of traditional Chinese medicine. Method: In this paper, the active compounds of TQTS were collected and their targets were identified. Psoriasis-related targets were obtained by analyzing the differential expressed genes between psoriasis patients and healthy individuals. Then, the network concerning the interactions of potential targets of TQTS with well-known psoriasis-related targets was built. The core targets were selected according to topological parameters. And the enrichment analysis was carried out to explore the mechanism of action of TQTS. Moreover, molecular docking was performed to study the interaction between the selected ligands and receptors related to psoriasis. Result and Conclusion: Eighty-five active compounds of TQTS were screened, with corresponding 270 targets, and 313 differentially expressed genes were identified. Additionally, enrichment analysis showed that the targets of TQTS for treating psoriasis were mainly concentrated in multiple biological processes, including apoptosis, growth factor response,etc., and related pathways including PI3K-Akt and MAPK signaling pathway, and so on. Genes such as NFKB1, TP53 and MAPK1 are the key genes in the gene pathway network of TQTS against psoriasis. The 4 main active components of TQTS have certain binding activity with 13 potential targets, and the stability of interaction with AKT1 is the best, which indicate the potential mechanism of TQTS on psoriasis.

scholarly journals To explore the material basis and mechanism of Lianhua Qingwen Prescription against COVID-19 based on network pharmacology

2020 ◽  
Vol 1 ◽  
pp. 3
Author(s):  
Wenpan Peng ◽  
Di Han ◽  
Yong Xu ◽  
Fanchao Feng ◽  
Zhichao Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
T Cell Activation ◽  
Mechanism Of Action ◽  
Cell Activation ◽  
Chemical Constituents ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Network Pharmacology ◽  
Material Basis

Objective: In the treatment of COVID-19, the application of Lianhua Qingwen Prescription has become growingly widespread, however, the mechanism of action is still unclear. To explore the material basis and mechanism of Lianhua Qingwen Prescription against SARS-CoV-2, to provide a reference for the treatment of COVID-19. Methods: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), SwissTargetPrediction, and Similarity Ensemble Approach (SEA) database were used to search the chemical constituents and targets of Lianhua Qingwen Prescription. The targets of COVID-19 were screened by GeneCards, Therapeutic Target Database (TTD), and Comparative Toxicogenomics Database (CTD). Cytoscape software was used to construct a “drug-component-target” network diagram and the mechanism of action was predicted by enrichment analysis. Results: Two hundred and twenty four active components, 246 drug therapeutic targets, and 16,611 potential targets of Lianhua Qingwen Prescription were mined out. Moreover, 163 common targets were obtained, including PTGS2, IL6, CASP3, mapk1, EGFR, ACE2, etc. Thirty seven items were obtained by Gene Ontology (GO) enrichment analysis, mainly involving T-cell activation, virus receptor, and inflammatory reaction, etc. One hundred and forty items were obtained by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched analysis, including TNF signaling pathway, MAPK signaling pathway, and IL-17 signaling pathway. Conclusion: Compounds such as quercetin and kaempferol play an important role in anti-COVID-19 through the TNF signaling pathway and MAPK signaling pathway.

scholarly journals Systematic Elucidation of the Mechanism of Action of Curcumin Against Colorectal Cancer via Network Pharmacology Approach

2021 ◽  
Author(s):  
Xinyue Han ◽  
Yimin Xu ◽  
Xiaoqiang Liu ◽  
Yuan Li ◽  
Cui Guo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Experimental Verification ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
In Vitro Experiments

Abstract Background: Curcumin is a potential drug for the treatment of colorectal cancer (CRC). Its mechanism of action has not been elucidated.Aim: To investigate the mechanism of action of curcumin in the treatment of CRC via network pharmacology, molecular docking and experimental verification.Methods: The targets of curcumin and CRC were obtained from the public databases. The component-targets network of curcumin in the treatment of CRC was constructed by Cytoscape v3.7.2. Through protein-protein interaction (PPI), the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), important targets and signaling pathways related to CRC treatment were identified. Finally, the results were verified by molecular docking and in vitro experiments.Results: A total of 30 potential targets of curcumin for CRC treatment were collectedThe core targets included AKT1, EGFR and STAT3 were identified. GO function enrichment analysis showed 140 items, and KEGG pathway enrichment analysis showed 61 signaling pathways, that were related to the regulation of protein kinase activity, negative regulation of apoptosis process, cancer signaling pathway and PI3K-Akt signali-ng pathway. In vitro experimental verification showed that curcumin could promote the apoptosis of CRC cells, and the key proteins of these signaling pathways were differentially expressed.Conclusion: This study explored the targets and pathways of curcumin in the treatment of colorectal cancer. In vitro experiments showed that curcumin has a therapeutic effect against CRC by inhibiting PI3K-Akt signaling pathway. Our results will lay a foundation for subsequent clinical research and drug development.

scholarly journals Based on Network Pharmacology to Explore the Molecular Targets and Mechanisms of Gegen Qinlian Decoction for the Treatment of Ulcerative Colitis

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Meiqi Wei ◽  
He Li ◽  
Qifang Li ◽  
Yi Qiao ◽  
Qun Ma ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Topological Analysis ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Ingredients

Background. Gegen Qinlian (GGQL) decoction is a common Chinese herbal compound for the treatment of ulcerative colitis (UC). In this study, we aimed to identify its molecular target and the mechanism involved in UC treatment by network pharmacology and molecular docking. Material and Methods. The active ingredients of Puerariae, Scutellariae, Coptis, and Glycyrrhiza were screened using the TCMSP platform with drug ‐ like   properties   DL ≥ 0.18 and oral   availability   OB ≥ 30 % . To find the intersection genes and construct the TCM compound-disease regulatory network, the molecular targets were determined in the UniProt database and then compared with the UC disease differential genes with P value < 0.005 and ∣ log 2   fold   change ∣ > 1 obtained in the GEO database. The intersection genes were subjected to protein-protein interaction (PPI) construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. After screening the key active ingredients and target genes, the AutoDock software was used for molecular docking, and the best binding target was selected for molecular docking to verify the binding activity. Results. A total of 146 active compounds were screened, and quercetin, kaempferol, wogonin, and stigmasterol were identified as the active ingredients with the highest associated targets, and NOS2, PPARG, and MMP1 were the targets associated with the maximum number of active ingredients. Through topological analysis, 32 strongly associated proteins were found, of which EGFR, PPARG, ESR1, HSP90AA1, MYC, HSPA5, AR, AKT1, and RELA were predicted targets of the traditional Chinese medicine, and PPARG was also an intersection gene. It was speculated that these targets were the key to the use of GGQL in UC treatment. GO enrichment results showed significant enrichment of biological processes, such as oxygen levels, leukocyte migration, collagen metabolic processes, and nutritional coping. KEGG enrichment showed that genes were particularly enriched in the IL-17 signaling pathway, AGE-RAGE signaling pathway, toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, transcriptional deregulation in cancer, and other pathways. Molecular docking results showed that key components in GGQL had good potential to bind to the target genes MMP3, IL1B, NOS2, HMOX1, PPARG, and PLAU. Conclusion. GGQL may play a role in the treatment of ulcerative colitis by anti-inflammation, antioxidation, and inhibition of cancer gene transcription.

scholarly journals An Investigation Into the Mechanism of Li Chong Pill for Treating Endometriosis Based on Network Pharmacology and Molecular Docking Verification

2021 ◽  
Author(s):  
Shao-Xuan Liu ◽  
Feng-Juan Han ◽  
Chun-Lan Zhang ◽  
Ying Shen ◽  
Jia Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Hormone Secretion ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Binding Property ◽  
Core Network

Abstract Background and objective: Li Chong Wan (Li Chong pill, LCP) origin from Yi Xue Zhong Zhong Can Xi Lu, (Records of Chinese Medicine with Reference to Western Medicine), widely used in the treatment of endometriosis (EM) in China. The purpose of this study is to investigate the intrinsic mechanisms of LCP against EM and to provide new evidence for its clinical application.Methods: Chemical compounds of LCP were screened and evaluated via retrieving public databases and literature. We also acquired their putative targets and obtained EM-related targets. The above-mentioned data were visualized as a component-target network. In addition, we use Cytoscape3.8.0 to build a protein-protein interaction network and identified hub genes and key active ingredients. Furthermore, through GO and KEGG pathway analyses, which were actualized by R3.6.1 (based on clusterProfiler, org.Hs.eg.Db, and pathview package), we obtained effective signaling pathways and biological functions. Molecular docking was used to verify binding activity between compounds and the key targets at last.Results: Finally, a total of 122 possible active targets and 47 components were screened. Identify the core network and screen out 10 main targets; GO and KEGG enrichment analysis revealed that LCP may have functions of anti-inflammatory, anti-angiogenesis, inhibition of cell proliferation, regulation of hormone secretion, etc. The effect of LCP on EM might be achieved by PI3K/Akt signaling pathway, HIF-1 signaling pathway, estrogen signaling pathway, and VEGF signaling pathway, etc. Finally, molecular docking results demonstrated that 14 components were exhibited good binding property to the key targets of EM.Conclusion: This research ocularly demonstrated the multi-component, multi-target, and multi-channel pharmacological effects for LCP in the treatments of EM and provides evidence for further clinical research and verification of the mechanism.

scholarly journals Network Pharmacology-Based Strategy to Investigate Pharmacological Mechanisms of the Drug Pair Astragalus-Angelica for Treatment of Male Infertility

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Feng Zhao ◽  
Yingjun Deng ◽  
Guanchao Du ◽  
Shengjing Liu ◽  
Jun Guo ◽  
...  
Keyword(s):  
Male Infertility ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Protein Protein Interactions ◽  
Drug Pair ◽  
Effective Components ◽  
New Ideas

Background. The traditional Chinese medicines Astragalus and Angelica are often combined to treat male infertility, but the specific therapeutic mechanism is not clear. Therefore, this study applies a network pharmacology approach to investigate the possible mechanism of action of the drug pair Astragalus-Angelica (PAA) in the treatment of male infertility. Methods. Relevant targets for PAA treatment of male infertility are obtained through databases. Protein-protein interactions (PPIs) are constructed through STRING database and screen core targets, and an enrichment analysis is conducted through the Metascape platform. Finally, molecular docking experiments were carried out to evaluate the affinity between the target protein and the ligand of PAA. Results. The active ingredients of 112 PAA, 980 corresponding targets, and 374 effective targets of PAA for the treatment of male infertility were obtained, which are related to PI3K-Akt signaling pathway, HIF-1 signaling pathway, AGE-RAGE signaling pathway, IL-17 signaling pathway, and thyroid hormone signaling pathway. Conclusion. In this study, using a network pharmacology method, we preliminarily analyzed the effective components and action targets of the PAA. We also explored the possible mechanism of action of PAA in treating male infertility. They also lay a foundation for expanding the clinical application of PAA and provide new ideas and directions for further research on the mechanisms of action of the PAA and its components for male infertility treatment.

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