A Network Pharmacology and Molecular Docking Approach to Investigate the Anticoronavirus-Induced Diseases Effect of Yinqiao Powder Combined With Modified Sangju Decoction

Severe acute respiratory syndrome (SARS) once caused great harm in China, but now it is the coronavirus disease 2019 (COVID-19) pandemic that has become a huge threat to global health, which raises urgent demand for developing effective treatment strategies to avoid the recurrence of tragedies. Yinqiao powder, combined with modified Sangju decoction (YPCMSD), has been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanism of YPCMSD in the treatment of SARS and COVID-19 through network pharmacology and molecular docking and further explore the potential application value of YPCMSD in the treatment of coronavirus infections. Firstly, the active components were collected from the literature and Traditional Chinese Medicine Systems Pharmacology database platform. The COVID-19 and SARS associated targets of the active components were forecasted by the SwissTargetPrediction database and GeneCards. A protein–protein-interaction network was drawn and the core targets were obtained by selecting the targets larger than the average degree. By importing the core targets into database for annotation, visualization, and integrated discovery, enrichment analysis of gene ontology, and construction of a Kyoto Encyclopedia of genes and genomes pathway was conducted. Cytoscape 3.6.1 software was used to construct a “components–targets–pathways” network. Active components were selected to dock with acute respiratory syndrome coronavirus type 2 (SARS-COV-2) 3CL and angiotensin-converting enzyme 2 (ACE2) through Discovery Studio 2016 software. A network of “components–targets–pathways” was successfully constructed, with key targets involving mitogen-activated protein kinase 1, caspase-3 (CASP3), tumor necrosis factor (TNF), and interleukin 6. Major metabolic pathways affected were those in cancer, the hypoxia-inducible factor 1 signaling pathway, the TNF signaling pathway, the Toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway. The core components, such as arctiin, scopolin, linarin, and isovitexin, showed a strong binding ability with SARS-COV-2 3CL and ACE2. We predicted that the mechanism of action of this prescription in the treatment of COVID-19 and SARS might be associated with multicomponents that bind to SARS-COV-2 3CL and ACE2, thereby regulating targets that coexpressed with them and pathways related to inflammation and the immune system.

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Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

Natural Product Communications ◽

10.1177/1934578x211016727 ◽

2021 ◽

Vol 16 (5) ◽

pp. 1934578X2110167

Author(s):

Xing-Pan Wu ◽

Tian-Shun Wang ◽

Zi-Xin Yuan ◽

Yan-Fang Yang ◽

He-Zhen Wu

Keyword(s):

Molecular Docking ◽

Target Prediction ◽

Interaction Network ◽

Scientific Basis ◽

Network Pharmacology ◽

Chemical Components ◽

Active Components ◽

Discovery Studio ◽

The Core ◽

Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

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Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Yinma Jiedu Granules

Natural Product Communications ◽

10.1177/1934578x21991714 ◽

2021 ◽

Vol 16 (2) ◽

pp. 1934578X2199171

Author(s):

ZiXin Yuan ◽

Can Zeng ◽

Bing Yu ◽

Ying Zhang ◽

TianShun Wang ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Hypoxia Inducible Factor ◽

Growth Factor Receptor ◽

Interaction Network ◽

Mitogen Activated Protein Kinase ◽

Network Pharmacology ◽

Chemical Components ◽

Active Components ◽

Discovery Studio

To investigate the mechanism of action of components of Yinma Jiedu granules in the treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking. The main chemical components of Yinma Jiedu granules were collected in the literature and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Using the SwissTargetPrediction database, the targets of the active component were identified and further correlated to the targets of COVID-19 through the GeneCards database. The overlapping targets of Yinma Jiedu granules components and COVID-19 were identified as the research target. Using the Database for Annotation, Visualization and Integrated Discovery database to carry out the target gene function Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation and Cytoscape 3.6.1 software was used to construct a “component-target-pathway” network. The protein-protein interaction network was built using Search Tool for the Retrieval of Interacting Genes/Proteins database. Using Discovery Studio 2016 Client software to study the virtual docking of key protein and active components. One hundred active components were screened from the Yinma Jiedu Granules that involved 67 targets, including mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor, tumor necrosis factor, tumor protein 53, and MAPK1. These targets affected 109 signaling pathways including hypoxia-inducible factor-1, apoptosis, and Toll-like receptor signaling pathways. Molecular docking results showed that the screened active components have a strong binding ability to the key targets. In this study, through network pharmacology and molecular docking, we justified the multicomponent, multitarget, and multipathways of Yinma Jiedu Granules in the treatment of COVID-19.

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Network Pharmacology Approach to Uncover the Mechanism Governing the Effect of Simiao Powder on Knee Osteoarthritis

BioMed Research International ◽

10.1155/2020/6971503 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Zhengquan Huang ◽

Xiaoqing Shi ◽

Xiaochen Li ◽

Li Zhang ◽

Peng Wu ◽

...

Keyword(s):

Molecular Docking ◽

Knee Osteoarthritis ◽

Signaling Pathway ◽

Protein Interaction ◽

Cell Metabolism ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Active Components ◽

Discovery Studio

Objective. To explore the molecular mechanism of Simiao powder in the treatment of knee osteoarthritis. Methods. Based on oral bioavailability and drug-likeness, the main active components of Simiao powder were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). GeneCard, OMIM, DisGeNET, DrugBank, PharmGkb, and the Therapeutic Target Database were used to establish target databases for knee osteoarthritis. Cytoscape software was used to construct a visual interactive network diagram of “active ingredient - action target – disease.” The STRING database was used to construct a protein interaction network and analyze related protein interaction relationships. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis were performed on the core targets. Additionally, Discovery Studio software was used for molecular docking verification of active pharmaceutical ingredients and disease targets. Results. Thirty-seven active components of Simiao powder were screened, including 106 common targets. The results of network analysis showed that the targets were mainly involved in regulating biological processes such as cell metabolism and apoptosis. Simiao powder components were predicted to exert their therapeutic effect on the AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and HIF-1 signaling pathway. The molecular docking results showed that the active components of Simiao powder had a good match with the targets of IL1B, MMP9, CXCL8, MAPK8, JUN, IL6, MAPK1, EGF, VEGFA, AKT1, and PTGS2. Conclusion. Simiao powder has multisystem, multicomponent, and multitarget characteristics in treating knee osteoarthritis. Its possible mechanism of action includes inhibiting the inflammatory response, regulating immune function, and resisting oxidative stress to control the occurrence and development of the disease. Quercetin, wogonin, kaempferol, beta-sitosterol, and other active ingredients may be the material basis for the treatment of knee osteoarthritis.

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Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Xingnaojing Injection

Natural Product Communications ◽

10.1177/1934578x20978025 ◽

2020 ◽

Vol 15 (12) ◽

pp. 1934578X2097802

Author(s):

Bing Yu ◽

Xin-Ge Ke ◽

Chong Yuan ◽

Peng-Yu Chen ◽

Ying Zhang ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Growth Factor Receptor ◽

Docking Studies ◽

Mitogen Activated Protein Kinase ◽

Network Pharmacology ◽

Active Components ◽

Molecular Docking Studies ◽

Discovery Studio ◽

Xingnaojing Injection

In the process of fighting against COVID-19 in China, Xingnaojing injection has been recommended for its clinical treatment, but the information about its active components and mechanism is still lacking. Therefore, in this work, using network pharmacology and molecular docking, we studied the active components of Xingnaojing injection having anti-COVID-19 properties. Using the DL parameter, TCMSP and CNKI databases were used to screen the active components of the Xingnaojing injection. Then, the SwissTargetPrediction webserver was used to collect the corresponding gene targets, and the gene targets related to COVID-19 were searched in the Genecards database. The DAVID database was used to enrich the function of gene targets, and the KOBAS3.0 database for the annotation of related KEGG pathways. The “components–targets–pathways” network of Xingnaojing injection was constructed with Cytoscape 3.6.1 software. The protein–protein interaction networks were analyzed using the String database. Specific proteins, SARS-COV-2 3 Cl, ACE2, and the active components were imported into Discovery Studio 2016 Client for molecular docking studies. From the Xingnaojing injection, a total of 58 active components, including Divanillalaceton and Q27139023, were screened. These were linked to 53 gene targets including mitogen-activated protein kinase 1 (MAPK1), tumor necrosis factorTNF, epidermal growth factor receptor, MAPK3, and 196 signaling pathways related to COVID-19, such as apoptosis, C-type lectin receptor signaling pathway, and hypoxia-inducible factor 1 signaling pathway. Furthermore, molecular docking studies were performed to study potential binding between the key targets and selected active components. Xingnaojing injection exhibits anti-COVID-19 effects via multiple components, multiple targets, and multiple pathways. These results set a scientific basis for further elucidation of the anti-COVID-19 mechanism of Xingnaojing injection.

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Network Pharmacology Integrated Molecular Docking Analysis of Potential Common Mechanisms of Shu-Feng-Jie-Du Capsule in the Treatment of SARS, MERS, and COVID-19

Natural Product Communications ◽

10.1177/1934578x20972914 ◽

2020 ◽

Vol 15 (11) ◽

pp. 1934578X2097291

Author(s):

Ying Zhang ◽

Yi Xie ◽

Bing Yu ◽

Chong Yuan ◽

Zixin Yuan ◽

...

Keyword(s):

Molecular Docking ◽

Protein Kinase ◽

Signaling Pathways ◽

Interaction Network ◽

Mitogen Activated Protein Kinase ◽

Network Pharmacology ◽

Active Components ◽

Discovery Studio ◽

Mitogen Activated Protein ◽

Coronavirus Infection

Shu-Feng-Jie-Du Capsules (SFJDCs) have been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanisms of SFJDC in the treatment of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. We further explored the potential application value of SFJDC in the treatment of coronavirus infection. All components of SFJDC were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The viral associated targets of the active components were forecast using the Pharmmapper database and GeneCards. The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system were used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of SFJDC’s core targets. Further, the protein–protein interaction network was built using STRING database. The herb–component network and component–target–pathway network were constructed using Cytoscape 3.7.2. The core active components of SFJDC were docked with core targets and COVID-19 coronavirus 3 Cl hydrolase and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. A total of 110 active components were filtered from SFJDC, with 47 core targets, including epidermal growth factor receptor, mitogen-activated protein kinase 1, mitogen-activated protein kinase 3, and interleukin 6. There were 416 GO items in the GO enrichment analysis ( P < .05) and 57 signaling pathways ( P < .05) in KEGG, mainly including pathways in cancer, pancreatic cancer, colorectal cancer, apoptosis, and neurotrophin signaling pathway, among others. The results of molecular docking showed that luteolin and rhein had a higher docking score with 3 Cl, ACE2, and core targets of SFJDC for antiviral effect. SFJDC is characterized by multicomponent, multitarget, and multisignaling pathways for the treatment of coronavirus infection. The mechanism of action of SFJDC in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes coexpressed with ACE2 and immune- related signaling pathways.

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The Mechanism of Compound Danshen Dripping Pills in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-490037/v1 ◽

2021 ◽

Author(s):

Xuedong An ◽

LiYun Duan ◽

YueHong Zhang ◽

De Jin ◽

Shenghui Zhao ◽

...

Keyword(s):

Cluster Analysis ◽

Cell Proliferation ◽

Diabetic Retinopathy ◽

Molecular Docking ◽

Signaling Pathway ◽

Active Ingredient ◽

Network Pharmacology ◽

Asiatic Acid ◽

Active Components ◽

The Core

Abstract BackgroundOur previous randomized, double-blind, placebo-controlled, multi-center clinical study showed that Compound Danshen Dripping Pills (CDDP) had a significant and safe effect in the treatment of diabetic retinopathy (DR), but its mechanism is still unclear, which we would explain based on network pharmacology and molecular docking.MethodThe active ingredients of CDDP (composed of Panax notoginseng, Salvia miltiorrhiza Bge., and Borneol) were searched in the TCMSP database. The validated target and Smiles number of the active ingredient are queried through the PubChem database, and the predicted target of the active ingredient is obtained through the Swisstarget Prediction database. The Drugbank, TTD, and DisGeNET databases were retrieved to obtain the related targets of DR. The core targets were obtained by the cluster analysis function of Cytoscape, and then the Protein-Protein Interaction was performed. The GO and KEGG signal pathways were enriched and clustered in David database. The potential active components and targets were docking with Autodock Vina, and the results were visualized by PyMOL.Result51 active components and 922 validation and prediction targets of CDDP, 715 targets of DR and 154 co-targets were obtained. Cluster analysis showed that there were two clusters, a total of 64 targets. Go and KEGG signal pathway enrichment analysis showed that the top 20 mainly included TNF and HIF-1 signaling pathway. In GO analysis, BP mainly includes positive regulation of smooth muscle cell proliferation and response to hypoxia, CC mainly includes extracellular space and extracellular domain, MF mainly includes protein binding and protein binding recognition. In KEGG database, the key genes in the TNF signaling pathway were TNF, NFkB and VEGF, in HIF-1 signaling pathway were the IL-6, STAT3, HIF1A and VEGF. Molecular docking results showed that all components of CDDP had a certain docking ability with TNF, NFkB, VEGF, IL-6, STAT3 and HIF1A, which of Asiatic acid and Salvianolic acid j was the strongest.Conclusion Based on the network pharmacology and molecular docking, the core active components of CDDP, mainly including Asiatic acid and Salvianolic acid j, which may play a role in regulating cell proliferation and response to inflammation and hypoxia by regulating the binding and recognition of intracellular and extracellular proteins, that is, mainly through TNF signaling pathway and HIF-1 signaling pathway.

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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

10.21203/rs.3.rs-699020/v1 ◽

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.

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

10.21203/rs.3.rs-531851/v1 ◽

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.

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

BioMed Research International ◽

10.1155/2021/5418142 ◽

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.

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

10.21203/rs.3.rs-127466/v1 ◽

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.

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