scholarly journals Exploring the Mechanisms of Lian Hua Qing Wen Capsule against COVID-19 by Network Pharmacology and Molecular Docking Approach

2020 ◽  
Author(s):  
Li Chen ◽  
Hua Qu ◽  
Yu Tan ◽  
Tao Han Wu ◽  
Zhuo Da Shi
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Active Compounds ◽  
Related Target ◽  
Docking Approach ◽  
Omim Database

Abstract Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) disease has led to a wide-spread global pandemic. There is no specific antiviral drug proven effective for the treatment of patients with COVID-19 at present. Combination of western and traditional Chinese medicine (TCM) is recommended, and Lian Hua Qing Wen (LHQW) capsule is a basic prescription and widely used to treat COVID-19 in China. However, the mechanisms of LHQW capsule treating COVID-19 are not clear. The aim of the study is to explore the mechanisms of LHQW capsule treating COVID-19 based on network pharmacy and molecular docking approach. Methods The active compounds and targets of LHQW capsule were obtained from traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). COVID-19 related target genes were obtained from GeneCards database and OMIM database. Protein–protein interaction (PPI) networks of LHQW capsule targets and COVID-19-related genes were visualized and merged to identify the candidate targets for LHQW capsule treating COVID-19. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. The hub genes involved in the gene-related pathways were screened and their corresponding compounds were used for in vitro validation of molecular docking predictions.Results A total of 185 active compounds of LHQW capsule were screened out, and 263 targets were predicted. Third hundred and fifty-two COVID-19 related target genes were obtained from GeneCards database and OMIM database. GO functional enrichment analysis showed that the biological processes of LHQW capsule treating COVID-19 were closely linked with the regulation of inflammation, immunity, cytokines production, vascular permeability, oxidative stress and apoptosis. KEGG enrichment analysis revealed that the pathways of LHQW capsule treating COVID-19 were significantly enriched in AGE−RAGE signaling pathway in diabetic complications, Kaposi sarcoma−associated herpesvirus infection, TNF, IL−17, and Toll−like receptor (TLR) signaling pathway. The hub targets genes in the gene-related pathways analysis of LHQW capsule treating COVID-19 included MAPK1, MAPK3, RELA, IL-6 and CASP8, which closely associated with inflammation, cytokines storm and apoptosis. Finally, molecular docking showed that top 5 compounds of LHQW capsule also had good binding activities to the important targets in COVID-19.Conclusions The mechanisms of LHQW capsule treating COVID-19 may involve in inhibiting inflammatory response, cytokine storm and virus infection, and regulating immune reactions, apoptosis and endothelial barrier.

scholarly journals Network Pharmacology Reveals the Molecular Mechanism of Cuyuxunxi Prescription in Promoting Wound Healing in Patients with Anal Fistula

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Yin Qu ◽  
Zhijun Zhang ◽  
Yafeng Lu ◽  
De Zheng ◽  
Yang Wei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Herbal Medicines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Surgical Wound ◽  
Active Compounds

Background. The healing process of the surgical wound of anal fistulotomy is much slower because of the presence of stool within the wound. Cuyuxunxi (CYXX) prescription is a Chinese herbal fumigant that is being used to wash surgical wound after anal fistulotomy. This study aimed at investigating the molecular mechanism of CYXX prescription using a network pharmacology-based strategy. Materials and Methods. The active compounds in each herbal medicine were retrieved from the traditional Chinese medicine systems pharmacology (TCMSP) database and in Traditional Chinese Medicine Integrated Database (TCMID) analysis platform based on the criteria of oral bioavailability ≥40% and drug-likeness ≥0.2. The disease-related target genes were extracted from the Comparative Toxicogenomics Database. Protein-protein interaction network was built for the overlapped genes as well as functional enrichment analysis. Finally, an ingredient-target genes-pathway network was built by integrating all information. Results. A total of 375 chemical ingredients of the 5 main herbal medicines in CYXX prescription were retrieved from TCMSP database and TCMID. Among the 375 chemical ingredients, 59 were active compounds. Besides, 325 target genes for 16 active compounds in 3 herbal medicines were obtained. Functional enrichment analysis revealed that these overlapped genes were significantly related with immune response, biosynthesis of antibiotics, and complement and coagulation cascades. A comprehensive network which contains 133 nodes (8 disease nodes, 3 drug nodes, 8 ingredients, 103 target gene nodes, 7 GO nodes, and 4 pathway nodes) was built. Conclusion. The network built in this study might aid in understanding the action mechanism of CYXX prescription at molecular level to pathway level.

scholarly journals Research on Active Compounds of Huanglian Jiedu Decoction for the Treatment of Corona Virus Disease 2019 Based on Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Leping Liu ◽  
Xinyi Xu ◽  
Xueshuai Cao ◽  
Xi Long ◽  
Yanwei Luo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Virus Disease ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Compounds ◽  
Corona Virus

Abstract Background Huanglian Jiedu Decoction (HLJDD) is a traditional Chinese prescription for the treatment of influenza, inflammation and other ailments related to heat-syndrome, a typical pathological symptom in Traditional Chinese Medicine. It was recommended as one of the basic prescriptions among the Proposed Diagnoses and Treatment issued by China’s National Health Commission. In this work we investigated the molecular mechanism of action of Huanglian Jiedu Decoction in the treatment of Corona Virus Disease 2019 (COVID-19) through network pharmacology and molecular docking approaches. Methods The chemical constituents and action targets of Coptis chinensis, Scutellaria baicalensis, Phellodendron amurense, Gardenia jasminoides in HLJDD were retrieved on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The database of UniProt and GeneCards were used to query the target genes that corresponding to the active compounds, and then a compound-target network was constructed using Cytoscape 3.7.2. GO database was used to annotate GO functions. Reactome was used to analyze KEGG enrichment pathway, predicting the possible mechanisms of active compounds. DAVID database was used to analysis the tissue enrichment. The main active ingredient is molecularly docked with the SARS-CoV-2, ACE2 and TMPRSS2. Results We screened 84 compounds and obtained 341 corresponding target genes in the network. Gene annotation showed that the targets were involved mainly in 457 biological functions. 306 signaling pathways was enriched, involving chemokine and cytokine signaling pathways that mediate inflammation, interferon-γ signaling pathway, p53 pathway. And the targets mainly distributed in the lung liver and placenta, involving a variety of immune cells, such as T cells, B cells. The molecular docking results showed that core compounds such as beta-sitosterol, stigmasterol and quercetin had high affinity with SARS-CoV-2, ACE2 and TMPRSS2, which was comparable with drugs like abidol used to COVID-19 treatment by. Conclusions The active compounds in HLJDD may have a therapeutic effect on COVID-19 through regulating multiple signal pathways by targeting genes such as VEGF, NOS2, IL6, MMP9, IL10, and TGFB1.

scholarly journals Study on the Potential Mechanism of Fructus Tribuli in the Treatment of Hypertensive Vascular Remodeling Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shuyue Wang ◽  
Fei Guo ◽  
Xiaochen Sun ◽  
Xiao Song ◽  
Yaohui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Vascular Remodeling ◽  
Network Pharmacology ◽  
Research Approach ◽  
Active Components ◽  
Active Compounds ◽  
Ppi Networks

Background. Hypertensive vascular remodeling (HVR) is the pathophysiological basis of hypertension, which is also an important cause of vascular disease and target organ damage. Treatment with Fructus Tribuli (FT), a traditional Chinese medicine, has a positive effect on HVR. However, the pharmacological mechanisms of FT are still unclear. Therefore, this study aimed to reveal the potential mechanisms involved in the effects of FT on HVR based on network pharmacology and molecular docking. Materials and Methods. We selected the active compounds and targets of FT according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Swiss Target Prediction database, and the targets of HVR were collected from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases. The protein-protein interaction network (PPI) was established using the STRING database. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and network analysis were performed to further explore the potential mechanisms. Finally, molecular docking methods were used to evaluate the affinity between the active compounds and the main target. Results. Seventeen active compounds of FT  and 164 potential targets for the treatment of HVR were identified. Component-target and PPI networks were constructed, and 12 main active components and 33 main targets were identified by analyzing the topological parameters. Additionally, GO analysis indicated that the potential targets were enriched in 483 biological processes, 52 cellular components, and 110 molecular functions. KEGG analysis revealed that the potential targets were correlated with 122 pathways, such as the HIF-1 signaling pathway, ErbB signaling pathway, and VEGF signaling pathway. Finally, molecular docking showed that the 12 main active components had a good affinity for the top five main targets. Conclusion. This study demonstrated the multiple compounds, targets, and pathway characteristics of FT in the treatment of HVR. The network pharmacology method provided a novel research approach to analyze potential mechanisms.

scholarly journals Exploring the mechanism of aidi injection for lung cancer by network pharmacology approach and molecular docking validation

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Zhenjie Zhuang ◽  
Tong Lin ◽  
Lixia Luo ◽  
Weixin Zhou ◽  
Junmao Wen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Target Genes ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Hub Genes ◽  
Aidi Injection

Abstract Background. Aidi injection (ADI) is an effective Traditional Chinese medicine preparation widely used for lung cancer. However, the pharmacological mechanisms of ADI on lung cancer remain to be elucidated. Methods. A network pharmacology (NP)-based approach and the molecular docking validation were conducted to explore underlying mechanisms of ADI on lung cancer. The compounds and target genes were screened by Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (Batman-TCM) database. The STRING database was utilized for protein interaction network construction. The R package clusterProfiler was used for bioinformatics annotation of hub target genes. The gene expression analysis and survival analysis were performed based on The Cancer Genome Atlas (TCGA) database. The Autodock Vina was used for molecular docking validation. Results. A total of five key compounds with 324 putative target genes were screened out, and 14 hub target genes were identified for treating lung cancer. Six hub genes could influence the survival of non-small cell lung cancer (NSCLC) patients. Of these hub genes, the expression pattern of EGFR, MYC, PIK3CA, and SMAD3 were significantly higher in the LUSC, while PIK3CA and RELA expressed lower in the LUAD group and LUSC group, respectively. These six hub genes had good docking affinity with the key compounds of ADI. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that ADI may exert therapeutic effects on lung cancer by regulating critical pathways including the thyroid hormone signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. Conclusions. The present study explored the potential pharmacological mechanisms of ADI on lung cancer, promoting the clinical application of ADI in treating lung cancer, and providing references for advanced researches.

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.

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 A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Guimin Liu ◽  
Dan Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Oxidant Stress ◽  
Estrogen Signaling ◽  
Network Pharmacology

Abstract Background: Male infertility (MI) affects almost 5% adult men worldwide, and 75% of these cases are unexplained idiopathic. There are limitations in the current treatment due to the unclear mechanism of MI, which highlight the urgent need for a more effective strategy or drug. Traditional Chinese Medicine (TCM) prescriptions have been used to treat MI for thousands of years, but their molecular mechanism is not well defined. Methods: Aiming at revealing the molecular mechanism of TCM prescriptions on MI, a comprehensive strategy integrating data mining, network pharmacology, and molecular docking verification was performed. Firstly, we collected 289 TCM prescriptions for treating MI from National Institute of TCM Constitution and Preventive Medicine for 6 years. Then, Core Chinese Materia Medica (CCMM), the crucial combination of TCM prescriptions, was obtained by the TCM Inheritance Support System from China Academy of Chinese Medical Sciences. Next, the components and targets of CCMM in TCM prescriptions and MI-related targets were collected and analyzed through network pharmacology approach.Results: The results showed that the molecular mechanism of TCM prescriptions for treating MI are regulating hormone, inhibiting apoptosis, oxidant stress and inflammatory. Estrogen signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, and TNF signaling pathway are the most important signaling pathways. Molecular docking experiments were used to further validate network pharmacology results. Conclusions: This study not only discovers CCMM and the molecular mechanism of TCM prescriptions for treating MI, but may be helpful for the popularization and application of TCM treatment.

scholarly journals Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

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