scholarly journals Mechanism Underlying the Anxiolytic Effect of Cinnamomum Camphora Chvar. Borneol Essential Oil Revealed by Network Pharmacology

2021 ◽  
Author(s):  
Shanshan Xiao ◽  
Hang Yu ◽  
Yunfei Xie ◽  
Yahui Guo ◽  
Jiajia Fan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Anxiety Disorder ◽  
Central Area ◽  
Anxiolytic Effect ◽  
Network Pharmacology ◽  
Dependent Manner ◽  
Ppi Network ◽  
Active Components ◽  
Network Analyses ◽  
Dose Dependent

Abstract Background: Anxiety disorder, the most common mental health issue, can cause palpitations, fear, and compulsive behavior, and can severely endanger human health. Most drugs to treat anxiety disorder can cause a variety of side effects, therefore, it is important to seek natural and safe complementary and alternative therapies.Methods: The open field (OF), elevated plus maze (EPM), and light-dark box (LDB) tests were used to confirm the anxiolytic effect of BEO in mice. Further, we constructed a component-target-signaling pathway network and a protein-protein interaction (PPI) network for the regulation of anxiety by BEO through pharmacological network analyses, and performed Gene Ontology (GO) enrichment analyses of BEO targets, and analyzed the active components and targets of BEO through molecular docking.Results: In the OF test, BEO significantly prolonged the time spent by the mice in the central area (p < 0.05), in a dose dependent manner (r = 0.9992), and also significantly increased the number of central area entries (p < 0.01). In the EPM test, BEO significantly increased the time spent in the open arms (p < 0.01) and the number of entries into the open arms (p < 0.01) in a dose-dependent manner (r = 0.9733, r = 0.9669). In the LDB tests, BEO significantly increased the light area duration (p < 0.05) and the transition number (p < 0.01) in a dose-dependent manner (r = 0.9166, r = 0.9572), thus confirming its anxiolytic effect. Network pharmacology results showed that 33 active components in BEO acted on 54 targets, mainly through modulation of neuroactive ligand-receptor interactions, G-protein coupled receptor signaling pathways, and RNA polymerase II transcription factor activity. PPI network analysis identified 48 key proteins, including estrogen receptor 1 (ESR1), androgen receptor (AR), and mitogen-activated protein kinase 8 (MAPK8). Molecular docking results showed that the main active components of BEO are borneol, β-caryophyllene, α-cadinol, limonene, and α- selinene, which act on the key targets CNR2, ADRA2B, and ADORA2A.Conclusion: Our results indicated that BEO has multi-component, multi-target, and multi-pathway characteristics, thus providing a theoretical basis for further research on the mechanism of action of BEO as a potential anxiolytic agent.

Molecular Mechanism of The Effect of Huanglian Jiedu Decoction On Ulcerative Colitis Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Jing Yang ◽  
Chao-Tao Tang ◽  
Ruiri Jin ◽  
Bixia Liu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Signal Pathway ◽  
Intestinal Barrier Function ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Ppi Network ◽  
Active Components

Abstract Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC by means of network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are considered to be very important to PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had good affinity with Hub gene. This study systematically elucidates the "multi-component, multi-target, multi-pathway" mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

scholarly journals Investigation of Active Ingredients and Mechanism of Sanao Decoction in the Treatment of Chronic Cough by Network Pharmacology

2020 ◽  
Author(s):  
Mengke Sheng ◽  
Xing Liu ◽  
Qingsong Qu ◽  
Xiaowen Wu ◽  
Yuyao Liao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Chronic Cough ◽  
Fluid Shear Stress ◽  
Oxidant Stress ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Abstract Background: Chronic cough significantly affects human health and quality of life. Studies have shown that Sanao Decoction（SAD）can clinically treat chronic cough. To investigate its mechanisms, we used the method of network pharmacology to conduct research at the molecular level.Methods: The active ingredients and their targets were screened by pharmacokinetics parameters from the traditional Chinese medicine system pharmacology analysis platform (TCMSP). The relevant targets of chronic cough were obtained from two databases: GeneCards and DrugBank. Take the intersection to get potential targets of SAD to treat chronic cough and establish the component-target regulatory network by CytoScape3.7.2 and protein-protein interaction (PPI) network by STRING 1.0. The function of the target gene and related pathways were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The significant pathways and their relevant targets were obtained and the target-pathway network was established by CytoScape3.7.2. Finally, molecular docking of the core active components and relevant targets was performed.Results: A total of 98 active components, 113 targets were identified. The component-target and target-pathway network of SAD and PPI network were established. Enrichment analysis of DAVID indicated that 2062 terms were in biological processes, 77 in cellular components, 142 in molecular functions and 20 significant pathways. In addition, the molecular docking showed that quercetin and luteolin had a good combination with the corresponding targets.Conclusions: It indicates that the active compounds of SAD, such as quercetin, luteolin, may act on AKT1, MAPK1, RELA, EGFR, BCL2 and regulate PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic complications and Fluid shear stress and atherosclerosis pathway to exert the effects of anti-inflammatory, anti-airway remodeling, anti-oxidant stress and repair airway damage to treat chronic cough.

scholarly journals Integrative Analysis to Uncover the Molecular Mechanisms of Caesalpinia sappan L. for Anti-Cancer Activity

2021 ◽  
Vol 16 (11) ◽  
pp. 1934578X2110399
Author(s):  
Bing Liu ◽  
Hao Lian
Keyword(s):  
Molecular Docking ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
The Cancer Genome Atlas ◽  
Network Pharmacology ◽  
Dependent Manner ◽  
Genomic Databases ◽  
Caesalpinia Sappan ◽  
Dose Dependent

Objectives: Caesalpinia Sappan L. is a traditional Chinese medicine with a long history. Recent studies have confirmed that Sappan has an antitumor effect, but its specific mechanism is still unclear. Methods: In this study, we used network pharmacology to predict the target and signal pathway of Sappan. In addition, the Cancer Genome Atlas and cancer cell lines encyclopedia large-scale genomic databases were used to analyze the relationship between different subtypes of Akt. Based on molecular docking technology, the interaction mode between small molecule compounds and protein targets was explored. Finally, we studied the effect of Sappan on Akt protein expression by Western blot in vitro. Results: AKT1 and AKT2 were significantly expressed in breast cancer cells, but they were significantly different from AKT3. Finally, molecular docking analysis showed that (3R,5R)-1,3,4,5-tetrakis(((E)-3-(3,4-dihydroxyphenyl)acryloyl)oxy)cyclohexane-1-carboxylic acid had a very ideal binding mode with Akt. Subsequent experiments showed that Sappan extract could induce apoptosis of HepG2 cells in a dose-dependent manner, and down regulate the phosphorylation level of Akt protein thr308 in a dose-dependent manner. Conclusions: This study provides new ideas for Sappan's anticancer research through the strategy of system pharmacology.

scholarly journals Network Pharmacology and Molecular Docking Combined to Analyze the Molecular and Pharmacological Mechanism of Pinellia ternata in the Treatment of Hypertension

2021 ◽  
Vol 43 (1) ◽  
pp. 65-78
Author(s):  
Zhaowei Zhai ◽  
Xinru Tao ◽  
Mohammad Murtaza Alami ◽  
Shaohua Shu ◽  
Xuekui Wang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Western Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
Effective Components ◽  
Treatment Of Hypertension

Hypertension is a cardiovascular disease that causes great harm to health and life, affecting the function of important organs and accompanied by a variety of secondary diseases, which need to be treated with drugs for a long time. P. ternata alone or combination with western medicine has played an important role in traditional Chinese medicine. Although P. ternata is used clinically to treat hypertension, its functional molecular mechanism and pharmacological mechanism have not been elucidated. Therefore, in this study, the potentially effective components, and targets of P. ternata in the treatment of hypertension were screened by the method of network pharmacology, and the mechanism of P. ternata in the treatment of hypertension was analyzed by constructing a component-target relationship network, PPI interaction network, targets’ function analysis, and molecular docking. In the study, 12 potentially effective components and 88 targets were screened, and 3 potential protein modules were found and analyzed after constructing a PPI network using targets. In addition, 10 targets were selected as core targets of the PPI network. After that, the targets were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the molecular docking method is used to study the interaction between the targets and the active components. The above evidence shows that the mechanism of P. ternata in the treatment of hypertension is complicated, as it acts in many ways, mainly by affecting nerve signal transmission, cell proliferation, and apoptosis, calcium channels, and so on. The binding between targets and active components mainly depends on Pi bonds and hydrogen bonds. Using the method of network pharmacology and molecular docking to analyze the mechanism of P. ternata in the treatment of hypertension will help to provide a better scientific basis for the combined use of traditional Chinese medicine and western medicine, and will better help to improve the quality of P. ternata and point out its direction.

scholarly journals Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Buyang Huanwu Decoction in the Treatment of Ischemic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Qiang Gao ◽  
Danfeng Tian ◽  
Zhenyun Han ◽  
Jingfeng Lin ◽  
Ze Chang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Molecular Docking ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Nf Kappa B ◽  
Buyang Huanwu Decoction ◽  
Pathway Network ◽  
Target Network

Background and Objective. With the exact clinical efficacy, Buyang Huanwu decoction (BHD) is a classical prescription for the treatment of ischemic stroke (IS). Here, we aimed to investigate the pharmacological mechanisms of BHD in treating IS using systems biology approaches. Methods. The bioactive components and potential targets of BHD were screened by TCMSP, BATMAN-TCM, ETCM, and SymMap databases. Besides, compounds that failed to find the targets from the above databases were predicted through STITCH, SwissTargetPrediction, and SEA. Moreover, six databases were searched to mine targets of IS. The intersection targets were obtained and analyzed by GO and KEGG enrichment. Furthermore, BHD-IS PPI network, compound-target network, and herb-target-pathway network were constructed by Cytoscape 3.6.0. Finally, AutoDock was used for molecular docking verification. Results. A total of 235 putative targets were obtained from 59 active compounds in BHD. Among them, 62 targets were related to IS. PPI network showed that the top ten key targets were IL6, TNF, VEGFA, AKT1, etc. The enrichment analysis demonstrated candidate BHD targets were more frequently involved in TNF, PI3K-Akt, and NF-kappa B signaling pathway. Network topology analysis showed that Radix Astragali was the main herb in BHD, and the key components were quercetin, beta-sitosterol, kaempferol, stigmasterol, etc. The results of molecular docking showed the active components in BHD had a good binding ability with the key targets. Conclusions. Our study demonstrated that BHD exerted the effect of treating IS by regulating multitargets and multichannels with multicomponents through the method of network pharmacology and molecular docking.

scholarly journals Based on network pharmacology and molecular docking to explore the Traditional Chinese Medicine anti-influenza mechanisms:Chinese protocol for diagnosis and treatment of influenza.

2020 ◽  
Author(s):  
yifei Chen
Keyword(s):  
Molecular Docking ◽  
Influenza A ◽  
Influenza Infection ◽  
Diagnosis And Treatment ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
Severe Influenza ◽  
Target Network

Background Explore the possible mechanism of anti-influenza virus, based on the study of the active components-drug-target network, Protein-Protein Interaction (PPI) network and molecular docking verification, we explored the potential action mechanism of TCM in Chinese protocol for diagnosis and treatment of influenza 2019. Methods Screening the active components and potential targets of 12 drugs in the scheme by using TCMSP database, and Obtaining the target of influenza by GeneCard, Durgbank, OMIM, TTD and PharmGkb databases. Then, constructed the “component-durg-target” network and PPI network were by Cytoscape3.8.0 software. Morethan, analyzed and the biological function and pathway, verified the molecular docking by AutoDock Vina software. Results The 12 drugs in the recommended scheme (XBCQ) for severe influenza contain 192 active components and involve 31 key antiviral targets, which may play an antiviral role through biological processes such as lipopolysaccharide, pathogen molecular reaction and regulate signaling pathway via the IL-17, influenza A, TNF, Toll-like receptors. Conclusion TCM play critical therapeutic roles through “multi-components, multi-targets and multi-pathways” mechanisms in influenza infection. The antiviral pharmacological mechanism of Xuanbai Chengqi decoction, which was analyzed by network pharmacology and molecular docking, provide a new idea for further exploring the diagnosis and treatment of severe influenza.

scholarly journals Exploration of the Molecular Mechanism of Polygonati Rhizoma in the Treatment of Osteoporosis Based on Network Pharmacology and Molecular Docking

2022 ◽  
Vol 12 ◽  
Author(s):  
Jinlong Zhao ◽  
Fangzheng Lin ◽  
Guihong Liang ◽  
Yanhong Han ◽  
Nanjun Xu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Akt Signaling ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Akt Signaling Pathway ◽  
Ppi Network ◽  
Active Components ◽  
Treatment Of Osteoporosis ◽  
Effective Components

ObjectiveTo explore the effective components and mechanism of Polygonati Rhizoma (PR) in the treatment of osteoporosis (OP) based on network pharmacology and molecular docking methods.MethodsThe effective components and predicted targets of PR were obtained through the Traditional Chinese Medicine Systems Pharmacology and Analysis Platform (TCMSP) database. The disease database was used to screen the disease targets of OP. The obtained key targets were uploaded to the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database for protein-protein interaction (PPI) network analysis. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets. Analysis and docking verification of chemical effective drug components and key targets were performed with IGEMDOCK software.ResultsA total of 12 chemically active components, 84 drug target proteins and 84 common targets related to drugs and OP were obtained. Key targets such as JUN, TP53, AKT1, ESR1, MAPK14, AR and CASP3 were identified through PPI network analysis. The results of enrichment analysis showed that the potential core drug components regulate the HIF-1 signaling pathway, PI3K-Akt signaling pathway, estrogen signaling pathway and other pathways by intervening in biological processes such as cell proliferation and apoptosis and estrogen response regulation, with an anti-OP pharmacological role. The results of molecular docking showed that the key targets in the regulatory network have high binding activity to related active components.ConclusionsPR may regulate OP by regulating core target genes, such as JUN, TP53, AKT1, ESR1, AR and CASP3, and acting on multiple key pathways, such as the HIF-1 signaling pathway, PI3K-Akt signaling pathway, and estrogen signaling pathway.

scholarly journals Exploring the Potential Mechanism of Shennao Fuyuan Tang for Ischemic Stroke Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jia Min Li ◽  
Zhen Ni Mu ◽  
Tian Tian Zhang ◽  
Xin Li ◽  
Yan Shang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Molecular Docking ◽  
Signal Pathway ◽  
Biologically Active ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
The Core ◽  
Target Network ◽  
Core Components

Background and Objective. Shennao Fuyuan Tang (SNFYT) is an effective herbal formula for ischemic stroke (IS). It has been in China for more than 20 years, but its effective biologically active components and underlying mechanisms remain to be elucidated. This study aimed to investigate the mechanism of action of SNFYT for the treatment of IS from both network pharmacology and molecular docking aspects. Methods. Screen the biologically active components and potential targets of SNFYT through Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and related literature. In addition, DrugBank, OMIM, DisGeNET, and the Therapeutic Target Database were searched to explore the therapeutic targets of IS. The cross-targets of SNFYT potential targets and IS treatment targets were taken as candidate gene targets, and GO and KEGG enrichment analyses were performed on the candidate targets. On this basis, the SNFYT-component-target network and protein-protein interaction (PPI) network were constructed using Cytoscape 3.7.2. Finally, AutoDock was used to verify the molecular docking of core components and core targets. Results. We screened out 95 potentially active components and 143 candidate targets. SNFYT-component-target network, PPI network, and Cytoscape analysis identified four core active ingredients and 14 core targets. GO enrichment analyzed 2333 biological processes, 79 cell components, and 149 molecular functions. There are 170 KEGG-related signal pathways P < 0.05 , including the IL-17 signal pathway, TNF signal pathway, and HIF-1 signal pathway. The molecular docking results of the core components and the core targets showed good binding power. Conclusions. SNFYT may achieve the effect of treating ischemic stroke through its anti-inflammatory effect through a signal pathway with core targets as the core.

scholarly journals Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dan He ◽  
Qiang Li ◽  
Guangli Du ◽  
Jijia Sun ◽  
Guofeng Meng ◽  
...  
Keyword(s):  
Nephrotic Syndrome ◽  
Molecular Docking ◽  
Active Component ◽  
Network Pharmacology ◽  
Protective Mechanism ◽  
Ppi Network ◽  
Active Components ◽  
Active Compounds ◽  
The Core ◽  
Target Network

Objective. Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. Methods. The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. Results. According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. Conclusions. In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

scholarly journals Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Buyang Huanwu Decoction in the treatment of Ischemic Stroke

2020 ◽  
Author(s):  
Qiang Gao ◽  
Danfeng Tian ◽  
Zhenyun Han ◽  
Jingfeng Lin ◽  
Ze Chang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Molecular Docking ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Buyang Huanwu Decoction ◽  
Pathway Network ◽  
Drug Compound ◽  
Compound Target

Abstract Background and objective: With the exact clinical efficacy, Buyang Huanwu decoction (BHD) is a classical prescription for the treatment of ischemic stroke (IS). Here, we aimed to investigate the pharmacological mechanisms of BHD in treating IS using systems biology approaches.Methods: The bioactive components and potential targets of BHD were screened by TCMSP, BATMAN-TCM, ETCM, and SymMap databases. Besides, compounds that failed to find the targets from the above databases were predicted through STITCH, SWISS, and SEA. Moreover, six databases were searched to mine targets of IS. The intersection targets were obtained, and analyzed by GO and KEGG enrichment. Furthermore, BHD-IS PPI network, compound-compound target-IS network and pathway of drug-compound target-IS network were constructed by Cytoscape 3.6.0. Finally, AutoDock was used for molecular docking verification.Results：A total of 253 putative targets were obtained from 60 active compounds in BHD. Among them, 62 targets were related to IS. PPI network showed that the top ten key targets were IL6, TNF, VEGFA, and AKT1, etc. The enrichment analysis demonstrated candidate BHD targets were more frequently involved TNF, PI3K-Akt, and NF-kappa B signaling pathway. Network topology analysis showed that Radix Astragali was the main herb in BHD, and the key components were quercetin, beta-Sitosterol, kaempferol, and stigmasterol, etc. The results of molecular docking showed the active components in BHD had a good binding ability with the key targets.Conclusions: This study firstly adopted the methods of network pharmacology and molecular docking to reveal the relationships among herbs in BHD, the putative targets and IS-related pathways.

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