Acupoint Application Therapeutic Mechanism for Novel Coronavirus Pneumonia: A Network Pharmacology Analysis

2020 ◽  
Author(s):  
Shan Liu ◽  
Chi Zhang ◽  
Zexin Zhang ◽  
Wei Guo ◽  
Jiangnan Xia ◽  
...  
Keyword(s):  
Immune System ◽  
Chinese Medicine ◽  
Protein Binding ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Treatment Method ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Cytokine Signaling ◽  
Active Components

Abstract Background: Acupoint application (AA) therapy, a traditional Chinese medicine external treatment method, is recommended as a complementary Chinese medicine therapy for treating new coronavirus pneumonia (COVID-19), and can help improve curative effects, promote patient recovery, and improve immunity to prevent disease, but the mechanism is not clear. We sought to explore the key targets and mechanisms of Ephedra and Asarum, the main components used in AA, in the treatment of COVID-19 in this study.Methods: The active compounds and related targets of Ephedra and Asarum used in AA were screened by searching four databases. COVID-19-related target genes were identified from three disease databases, and the key targets of treating COVID-19 were obtained by Venn diagram using Cytoscape 3.2.1 software, gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to explore possible mechanisms and pathways. The verification of the binding force between the compounds and target genes was completed by performing molecular docking with Autodock and pymol software.Results: Twenty-four active components of AA corresponded to 252 targets, with 713 target genes related to COVID-19, and 56 key genes were selected. GO analysis results showed that biological processes mainly included the inflammatory and immune responses, and cell components were mainly the plasma membrane and nucleus, with molecular functions including protein binding and identical protein binding. The top pathways included Immune System, Cytokine Signaling in Immune System, Adaptive Immune System, Signaling by Interleukins, Innate Immune System, and Signaling by GPCR.Conclusion: The results of this study preliminarily verified that Ephedra and Asarum used in AA therapy could treat COVID-19 via multiple compounds and multi-pathways, which provided a basis for clinical application and further research.

scholarly journals Acupoint Application Therapeutic Mechanism for Novel Coronavirus Pneumonia: A Network Pharmacology Analysis

2020 ◽  
Author(s):  
Shan Liu ◽  
chi zhang ◽  
Zexin Zhang ◽  
Wei Guo ◽  
Jiangnan Xia ◽  
...  
Keyword(s):  
Immune System ◽  
Chinese Medicine ◽  
Protein Binding ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Treatment Method ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Cytokine Signaling ◽  
Active Components

Abstract Background and objective: Acupoint application (AA) therapy, a traditional Chinese medicine external treatment method, is recommended as a complementary Chinese medicine therapy for treating new coronavirus pneumonia (COVID-19), and can help improve curative effects, promote patient recovery, and improve immunity to prevent disease, but the mechanism is not clear. We sought to explore the key targets and mechanisms of Ephedra and Asarum, the main components used in AA, in the treatment of COVID-19 in this study. Methods: The active compounds and related targets of Ephedra and Asarum used in AA were screened by searching four databases. COVID-19-related target genes were identified from three disease databases, and the key targets of treating COVID-19 were obtained by Venn diagram using Cytoscape 3.2.1 software, gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to explore possible mechanisms and pathways. The verification of the binding force between the compounds and target genes was completed by performing molecular docking with Autodock and pymol software.Results: Twenty-four active components of AA corresponded to 252 targets, with 713 target genes related to COVID-19, and 56 key genes were selected. GO analysis results showed that biological processes mainly included the inflammatory and immune responses, and cell components were mainly the plasma membrane and nucleus, with molecular functions including protein binding and identical protein binding. The top pathways included Immune System, Cytokine Signaling in Immune System, Adaptive Immune System, Signaling by Interleukins, Innate Immune System, and Signaling by GPCR.Conclusion: The results of this study preliminarily verified that Ephedra and Asarum used in AA therapy could treat COVID-19 via multiple compounds and multi-pathways, which provided a basis for clinical application and further research.

scholarly journals Identification on the potential mechanism of Radix pueraria on colon cancer based on network pharmacology

2021 ◽  
Author(s):  
Yi Li ◽  
Chunli Zhang ◽  
Xiaohan Ma ◽  
Liuqing Yang ◽  
Huijun Ren
Keyword(s):  
Colon Cancer ◽  
Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
In Vivo Studies ◽  
Network Pharmacology ◽  
Biological Mechanism ◽  
Active Components

Abstract Radix Puerariae (RP), a dry root of the Pueraria lobata (Willd.) Ohwi, is used to treat a variety of diseases, including cancer. Several in vitro and in vivo studies have demonstrated the efficacy of RP in the treatment of colon cancer (CC). However, the biological mechanism of RP in the treatment of colon cancer remains unclear. In this study, the active component of RP and its potential molecular mechanism against CC were studied by network pharmacology and enrichment analysis. The methods adopted included screening of active ingredients of Chinese medicine, prediction of target genes of Chinese medicine and disease, construction of protein interaction network, and GO and KEGG Enrichment Analysis. Finally, the results of network pharmacology were further validated by molecular docking experiments and cell experiments. 8 active constituents and 14 potential protein targets were screened from RP, including EGFR, JAK2 and SRC. The biological mechanism of RP against CC was analyzed by studying the relationship between active components, targets, and enrichment pathway. This provides a basis for understanding the clinical application of RP in CC.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 and SARS Mechanism of Fufang Banlangen Keli

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098842
Author(s):  
Li Cheng ◽  
Fei Wang ◽  
Shun Bo Zhang ◽  
Qiu Yun You
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Docking Studies ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Components

Purpose Fufang Banlangen Keli (FBK) has been recommended for its clinical treatment of Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS), but the mechanism of action is unclear. So, using network pharmacology and molecular docking, we studied the active components and mechanism of FBK in the treatment of COVID-19 and SARS. Methods The Encyclopedia of Traditional Chinese Medicine and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform were used to screen the active components by oral bioactivity and drug likeness. Then, PharmMapper and SwissTargetPrediction databases were used to screen potential target genes of active components; the related target genes of COVID-19 and SARS were obtained from the GeneCards database. The intersection of the active components and disease-related targets was performed by the Venny2.1.0 database. The DAVID6.8 database and KOBAS3.0 database were used to get gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation of gene targets. The “components-targets-pathways (C-T-P)” network of FBK was conducted by Cytoscape3.6.1 software. The top active components, angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 3 Cl, were imported into AutoDock and PyMOL for molecular docking. Results From the FBK, a total of 28 active components and 73 gene targets were screened through network pharmacology. Twenty pathways were analyzed, including pathways in cancer, nod-like receptor signaling pathway, and pancreatic cancer, etc. ( P < 0.05). A total of 337 items were obtained by GO functional enrichment analysis ( P < 0.05), including 257 items for biological process, 38 items for cell composition, and 42 items for molecular function. Furthermore, molecular docking studies were performed to study potential binding between the key gene targets and selected active components. Conclusion Based on network pharmacology and molecular docking technology, qingdainone, (2Z)-2-(2-oxoindolin-3-ylidene) indolin-3-one, sinensetin, and acacetin in FBK were verified to bind to ACE2 and SARS-COV-2 3 Cl, so as to treat COVID-19 and SARS.

scholarly journals The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xi Cen ◽  
Yan Wang ◽  
LeiLei Zhang ◽  
XiaoXiao Xue ◽  
Yan Wang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Potential Mechanism ◽  
Active Components ◽  
The Core ◽  
Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

scholarly journals A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Chunli Piao ◽  
Qi Zhang ◽  
De Jin ◽  
Li Wang ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

scholarly journals Evidence-Based Complementary and Alternative Medicine Exploring Active Components and Mechanism of Jinhua Qinggan Granules in Treatment of COVID-19 Based on Virus-Host Interaction

2020 ◽  
Vol 15 (9) ◽  
pp. 1934578X2094721
Author(s):  
Yan Ren ◽  
Zheng-hao Yin ◽  
Jian-xing Dai ◽  
Zhuo Yang ◽  
Bin-bin Ye ◽  
...  
Keyword(s):  
Chemical Constituents ◽  
Enrichment Analysis ◽  
Holistic Approach ◽  
Network Pharmacology ◽  
Cytokine Signaling ◽  
Active Components ◽  
Protein Targets ◽  
S Protein ◽  
Host Interaction ◽  
Analysis Platform

This study aimed at exploring the active components and mechanisms of Jinhua Qinggan granules (JQG) in the prevention and treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking technology. These efforts were accomplished by employing the holistic approach of traditional Chinese medicine (TCM) and considering the virus-host interaction consisting of viral characteristics, the entry pathway into the host, and the resulting immune response. The chemical constituents and molecular targets of the 12 herbs from JQG were obtained using the TCM Systems Pharmacology database and analysis platform. UniProt was used to search for genes corresponding to JQG protein targets and Cytoscape 3.7.2 to construct the component-target (gene) network. Database for Annotation, Visualization and Integrated Discovery was used to perform enrichment analysis of gene ontology functions and the Kyoto Encyclopedia of Genes and Genomes pathways to predict the mechanism of action. The components ranked high in the network, and the major active components of the principal medicines, based on published literature, were docked with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL hydrolase, SARS-CoV-2 spike glycoprotein (S protein), angiotensin conversion enzyme II (ACE2), and suppressor of cytokine signaling 1 (SOCS1). Visualization analysis demonstrated that the core active components of JQG had a strong affinity for SARS-CoV-2 3CL hydrolase, SARS-CoV-2 S protein, ACE2, and SOCS1. These data imply that the potential active components of JQG may act on multiple signaling pathways by binding to targets such as SARS-CoV-2 3CL hydrolase, S protein, ACE2, and SOCS1, thereby inhibiting virus replication and targeting cell binding, reducing host inflammation, and activating antiviral immunity to a certain extent.

scholarly journals Network Pharmacology Analysis to Identify Phytochemicals in Traditional Chinese Medicines That May Regulate ACE2 for the Treatment of COVID-19

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Wenhao Niu ◽  
Feng Wu ◽  
Haiming Cui ◽  
Wenyue Cao ◽  
YuChieh Chao ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Gallic Acid ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Peroxisome Proliferator ◽  
Active Components ◽  
Peroxisome Proliferator Activated Receptor ◽  
Effective Components

“Three formulas and three medicines,” which include Jinhua Qinggan granule, Lianhua Qingwen capsule/granule, Xuebijing injection, Qingfei Paidu decoction, HuaShiBaiDu formula, and XuanFeiBaiDu granule, have been proven to be effective in curbing coronavirus disease 2019 (COVID-19), according to the State Administration of Traditional Chinese Medicine. The aims of this study were to identify the active components of “Three formulas and three medicines” that can be used to treat COVID-19, determine their mechanism of action via angiotensin-converting enzyme 2 (ACE2) by integrating network pharmacological approaches, and confirm the most effective components for COVID-19 treatment or prevention. We investigated all the compounds present in the aforementioned herbal ingredients. Compounds that could downregulate the transcription factors (TFs) of ACE2 and upregulate miRNAs of ACE2 were screened via a network pharmacology approach. Hepatocyte nuclear factor 4 alpha (HNF4A), peroxisome proliferator-activated receptor gamma (PPARG), hsa-miR-2113, and hsa-miR-421 were found to regulate ACE2. Several compounds, such as quercetin, decreased ACE2 expression by regulating the aforementioned TFs or miRNAs. After comparison with the compounds present in Glycyrrhiza Radix et Rhizoma, quercetin, glabridin, and gallic acid present in the herbal formulas and medicines were found to alter ACE2 expression. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to search for possible molecular mechanisms of these compounds. In conclusion, traditional Chinese medicine (TCM) plays a pivotal role in the prevention and treatment of COVID-19. Quercetin, glabridin, and gallic acid, the active components of recommended TCM formulas and medicines, can inhibit COVID-19 by downregulating ACE2.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Scutellariae Radix for Hepatocellular Carcinoma Treatment

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qian Wang ◽  
Yan Liang ◽  
Can Peng ◽  
Peng Jiang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Mechanistic Study ◽  
Network Pharmacology ◽  
Therapeutic Drug ◽  
Active Components ◽  
Scutellariae Radix

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.

scholarly journals Network Pharmacology Analysis of the active components and anticancer targets of Rhubarb

2021 ◽  
Author(s):  
Hu Junrui ◽  
Duan Yongqiang ◽  
Cui Gongning ◽  
Luo Qiang ◽  
Xi Shanshan ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Drug Targets ◽  
Target Genes ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds ◽  
Cellular Targets ◽  
Kegg Pathway Analysis

AbstractTo investigate the mechanisms and active components governing the anticancer activity of rhubarb.The TCMSP database was screened to identify the active components of rhubarb and Swiss target predictions were generated to predict their cellular targets. TTD and OMIM databases were used to predict tumor-related target genes. "Cytoscape" was used to construct drug targets. PPI network analysis, GO enrichment analysis and KEGG pathway analysis of the key targets were investigated using String and David databases. A total of 33 components and 116 corresponding targets were screened. Amongst them, the key active compounds in rhubarb included emodin, aloe emodin, β-sitosterol, emodin methyl ether and rhein, which were predicted to target TP53, AKT1, STAT3, PIK3CA, HRAS, and VEGFA. GO analysis revealed that the cellular targets clustered into 159 biological processes, including those involved in cellular composition (n=24) and molecular functions (n=42, P<0.01). KEGG pathway analysis revealed 85 (P < 0.01) pathways related to cancer. The active compounds in rhubarb target TP53, AKT1 and PIK3CA. Rhubarb therefore regulates cancer development through an array of biological pathways.

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