scholarly journals Virtual Screening Technique Used to Estimate the Mechanism of Adhatoda vasica Nees for the Treatment of Rheumatoid Arthritis Based on Network Pharmacology and Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Wenxiang Wang ◽  
Yunsen Zhang ◽  
Jie Luo ◽  
Rushan Wang ◽  
Ce Tang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Experimental Studies ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Adhatoda Vasica

Adhatoda vasica Nees (AVN) is commonly used to treat joint diseases such as rheumatoid arthritis (RA) in ethnic minority areas of China, especially in Tibetan and Dai areas, and its molecular mechanisms on RA still remain unclear. Network pharmacology, a novel strategy, utilizes bioinformatics to predict and evaluate drug targets and interactions in disease. Here, network pharmacology was used to investigate the mechanism by which AVN acts in RA. The chemical compositions and functional targets of AVN were retrieved using the systematic pharmacological analysis platform PharmMapper. The targets of RA were queried through the DrugBank database. The protein-protein interaction network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets were constructed in the STRING database, and the network visualization analysis was performed in Cytoscape. Maestro 11.1, a type of professional software, was used for verifying prediction and analysis based on network pharmacology. By comparing the predicted target information with the targets of RA-related drugs, 25 potential targets may be related to the treatment of RA, among which MAPK1, TNF, DHODH, IL2, PTGS2, and JAK2 may be the main potential targets for the treatment of RA. Finally, the chemical components and potential target proteins were scored by molecular docking, and compared with the ligands of the protein, the prediction results of network pharmacology were preliminarily verified. The active ingredients and mechanism of AVN against RA were firstly investigated using network pharmacology. Additionally, this research provided a solid foundation for further experimental studies.

scholarly journals Study on the Multitarget Mechanism and Key Active Ingredients of Herba Siegesbeckiae and Volatile Oil against Rheumatoid Arthritis Based on Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Yang ◽  
Yahui Li ◽  
Runlin Lv ◽  
Haibing Qian ◽  
Xiangyun Chen ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Essential Oil ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
Experimental Studies ◽  
Volatile Oil ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Ingredients

Background. Herba Siegesbeckiae (HS, Xixiancao in Chinese) is widely used to treat inflammatory joint diseases such as rheumatoid arthritis (RA) and arthritis, and its molecular mechanisms and active ingredients have not been completely elucidated. Methods. In this study, the small molecule ligand library of HS was built based on Traditional Chinese Medicine Systems Pharmacology (TCMSP). The essential oil from HS was extracted through hydrodistillation and analyzed by Gas Chromatography-Mass Spectrometer (GC-MS). The target of RA was screened based on Comparative Toxicogenomics Database (CTD). The key genes were output by the four algorithms’ maximum neighborhood component (MNC), degree, maximal clique centrality (MCC), and stress in cytoHubba in Cytoscape, while biological functions and pathways were also analyzed. The key active ingredients and mechanism of HS and essential oil against RA were verified by molecular docking technology (Sybyl 2.1.1) in treating RA. The interaction between 6 active ingredients (degree ≥ 5) and CSF2, IL1β, TNF, and IL6 was researched based on the software Ligplot. Results. There were 31 small molecule constituents of HS and 16 main chemical components of essential oil (relative content >1%) of HS. There were 47 chemical components in HS. Networks showed that 9 core targets (TNF, IL1β, CSF2, IFNG, CTLA4, IL18, CD26, CXCL8, and IL6) of RA were based on Venn diagrams. In addition, molecular docking simulation indicated that CSF2, IL1β, TNF, and IL6 had good binding activity with the corresponding compounds (degree > 10).The 6 compounds (degree ≥ 5) of HS and essential oil had good interaction with 5 or more targets. Conclusion. This study validated and predicted the mechanism and key active ingredients of HS and volatile oil in treating RA. Additionally, this study provided a good foundation for further experimental studies.

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

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.

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

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.

Revealing the Synergistic Mechanism of Multiple Components in Compound Fengshiding Capsule for Rheumatoid Arthritis Therapeutics by Network Pharmacology

2019 ◽  
Vol 19 (4) ◽  
pp. 303-314 ◽  
Author(s):  
Hong Duan ◽  
Ke-feng Zhai ◽  
Ghulam J. Khan ◽  
Jie Zhou ◽  
Ting-yan Cao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Drug Targets ◽  
The Body ◽  
In Vivo Studies ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Pubmed Database ◽  
Synergistic Mechanism

Background:Compound Fengshiding capsule (CFC), is a Chinese formulation from herbal origin including Alangium platanifolium, Angelicae dahurica, Cynanchum paniculatum and Glycyrrhiza uralensis. CFC is widely used as clinical therapy against rheumatoid arthritis. However, its exact mechanism of action has not been explored yet.Methods:In order to explore the synergistic mechanism of CFC, we designed a study adopting network pharmacology scheme to screen the action targets in relation to the CFC components. The study analyses target facts of salicin, paeonol, liquiritin and imperatorin from PubMed database, and explores the potential pharmacological targets of rheumatoid arthritis, cervical neuralgia and sciatica related diseases for their interaction.Results:The results of boosted metabolic pathway showed that the chemical components of CFC interrupted many immune-related pathways, thus participating in immunity regulation of the body and playing a role in the treatment of rheumatism. Collectively, CFC has apoptotic, oxidative stress modulatory and anti-inflammatory effects that accumulatively serve for its clinical application against rheumatoid arthritis.Conclusion:Conclusively, our findings from present study reconnoiters and compacts systematic theoretical approach by utilizing the network pharmacology mechanism of four effective components for the treatment of rheumatism indicating sufficient potential drug targets associated with CFC against rheumatism. These interesting findings entreaties for further in vitro and in vivo studies on the mechanism of compound active ingredient against rheumatism.

scholarly journals Decoding the Mechanism of Huanglian Jiedu Decoction in Treating Pneumonia Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 9 ◽  
Author(s):  
Xianhai Li ◽  
Hua Tang ◽  
Qiang Tang ◽  
Wei Chen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Clinical Symptoms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Interleukin 17 ◽  
Active Ingredients ◽  
Hub Genes

Huang-Lian-Jie-Du decoction (HLJDD) has been used to treat pneumonia for thousands of years in China. However, our understanding of its mechanisms on treating pneumonia is still unclear. In the present work, network pharmacology was used to analyze the potential active ingredients and molecular mechanisms of HLJDD on treating pneumonia. A total of 102 active ingredients were identified from HLJDD, among which 54 were hit by the 69 targets associated with pneumonia. By performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we obtained the main pathways associated with pneumonia and those associated with the mechanism of HLJDD in the treatment of pneumonia. By constructing the protein–protein interaction network of common targets, 10 hub genes were identified, which were mainly involved in the tumor necrosis factor (TNF) signaling pathway, interleukin 17 (IL-17) signaling pathway, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway. Moreover, the results of molecular docking showed that the active ingredients of HLJDD had a good affinity with the hub genes. The final results indicate that HLJDD has a greater effect on bacterial pneumonia than on viral pneumonia. The therapeutic effect is mainly achieved by regulating the host immune inflammatory response and oxidative stress reaction, antibacterial microorganisms, alleviating the clinical symptoms of pneumonia, repairing damaged cells, and inhibiting cell migration.

scholarly journals Identification of the active compounds and pharmacological mechanisms of Xiaoqinglong decoction for asthma based on network pharmacology and molecular docking technology

2020 ◽  
Author(s):  
Haili Li ◽  
Jianpeng Zhou ◽  
Zuyou Wei ◽  
Feng Chen ◽  
Jingmin Deng
Keyword(s):  
Molecular Docking ◽  
Biological Networks ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Chronic Respiratory Disease ◽  
Network Pharmacology ◽  
Potential Drug ◽  
Active Compounds ◽  
Pharmacological Mechanism ◽  
Potential Drug Targets

Abstract Background and purposeAsthma has become the most common chronic respiratory disease in the world. Xiaoqinglong decoction (XQLD) is described as a commonly used drug for treatment and prevention of asthma for thousands of years, however, its underlying molecular mechanisms have not been clarified completely. Therefore, a network pharmacology and molecular docking technology were used to uncover the active compounds and pharmacological mechanism of XQLD on asthma.MethodsBioactive ingredients and targets of XQLD, asthma-related targets were obtained from public databases. Cytoscape software was used to construct biological networks. DAVID database was used to perform Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking was performed to further verify the internal relationship between the active ingredients and key targets.ResultsA total of 169 bioactive ingredients and 127 gene targets of XQLD were identified. The network analysis indicated that quercetin, kaempferol, stigmasterol, β-sitosterol, and luteolin may be candidate agents. The IL6, VEGFA, NFKBIA, ICAM1, VCAM1, PPARG, IRF1, CYP3A4, CYP1B1 and CYP1A1 could become potential drug targets. The KEGG suggested that PI3K-AKT, Estrogen, FoxO, MAPK, HIF-1 signaling pathway may play a significant role in treating asthma. Molecular docking showed that quercetin, kaempferol, stigmasterol, β-sitosterol, and luteolin combined well with IL6, VEGFA, PPARG, CYP3A4.ConclusionThis study predicted the main ingredients, potential drug targets and pharmacological mechanism of XQLD on asthma from a new sight, as well as provided a promising approach for the research of chemical basis and pharmacology in Traditional Chinese medicine (TCM).

scholarly journals Exploring the Biological Mechanism of Huang Yam in Treating Tumors and Preventing Antitumor Drug-Induced Cardiotoxicity Using Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hui Zhang ◽  
Wenchao Dan ◽  
Qingyong He ◽  
Jianbo Guo ◽  
Shuang Dai ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Antitumor Drugs ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Ingredients ◽  
Drug Induced ◽  
Anticancer Properties ◽  
The Core

Drugs for the treatment of tumors could result in cardiotoxicity and cardiovascular diseases. We aimed to explore the anticancer properties of Huang yam as well as its cardioprotective properties using network pharmacology and molecular docking technology. The cardiovascular targets of the major chemical components of Huang yam were obtained from the following databases: TCMSP, ETCM, and BATMAN-TCM. The active ingredients of Huang yam were obtained from SwissADME. The cardiovascular targets of antitumor drugs were obtained using GeneCards, OMIM, DrugBank, DisGeNET, and SwissTargetPrediction databases. The drug-disease intersection genes were used to construct a drug-compound-target network using Cytoscape 3.7.1. A protein-protein interaction network was constructed using Cytoscape’s BisoGenet, and the core targets of Huang yam were screened to determine their antitumor properties and identify the cardiovascular targets based on topological parameters. Potential targets were imported into the Metascape platform for GO and KEGG analysis. The results were saved and visualized using R software. The components with higher median values in the network were molecularly docked with the core targets. The network contained 10 compounds, including daucosterol, delusive, dioxin, panthogenin-B, and 124 targets, such as TP53, RPS27A, and UBC. The GO function enrichment analysis showed that there were 478 items in total. KEGG enrichment analysis showed a total of 140 main pathways associated with abnormal transcription of cancer, PI3K-Akt signaling pathway, cell cycle, cancer pathway, ubiquitination-mediated proteolysis, and other pathways. Molecular docking results showed that daucosterol, delusive, dioxin, and panthogenin-B had the highest affinity for TP53, RPS27A, and UBC. The treatment of diseases using traditional Chinese medicine encompasses multiple active ingredients, targets, and pathways. Huang yam has the potential to treat cardiotoxicity caused by antitumor drugs.

Discussion on the Mechanism of Lithospermum erythrorhizon in the Treatment of Cervical Cancer Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 7 (5) ◽  
pp. 3927-3933
Author(s):  
Qiong Yan ◽  
Fangwu Ye
Keyword(s):  
Cervical Cancer ◽  
Molecular Docking ◽  
Drug Targets ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Drug Candidate ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Stable Conformation

Objective To explore the “multi-component, multi-target, multi-pathway” mechanism of Lithospermum erythrorhizonagairtst cervical cancer. Methods The active ingredients and corresponding targets were screened through TCMSP, PubChem and SwissTargetPrediction databases. The GeneCarts platform was used to collect cervical cancer-related genes, and the intersection of drug targets and cervical cancer targets was analyzed. Use STRING to analyze protein interaction network, use Cytoscape software to construct component-target and core target interaction network, perform KEGG pathway enrichment analysis on core target genes, and conduct molecular docking verification.Results After screening, 12 main active ingredients of comfrey (including Shikonin A, 1-methoxyacetylshikonin, Shikonin B, etc.) and 35 key targets related to comfrey and cervical cancer were obtained (including ESR1, SRC, MMP9, PTGS2, etc.). And these genes were mainly enriched in 39 signaling pathways such as PI3K-Akt and estrogen. Molecular docking reminder that Lithospermum A has a higher affinity with ESR1, and Lithospermum B can form a stable conformation with SRC, MMP9, and PTGS2. Conclusion Lithospermum erythrorhizon is a potential drug candidate for the treatment of cervical cancer. It can treat cervical cancer through multi-component, multi-target, and multi-channel action.

scholarly journals New perspective: the multi-targets mechanism of hydroxychloroquine in the treatment of rheumatoid arthritis based on network pharmacology

2020 ◽  
Author(s):  
Bo Xie ◽  
Haojie Lu ◽  
Jinhui Xu ◽  
Yebei Hu ◽  
Haixin Luo ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Drug Targets ◽  
Cell Activation ◽  
Acid Amide ◽  
Network Pharmacology ◽  
Protein Targets ◽  
Protein Protein Interaction ◽  
Amide Hydrolase ◽  
New Perspective

Abstract Background Network pharmacology is a new method of bioinformatics in exploring drug targets in recent 3 years. Hydroxychloroquine (HCQ) is a multi-targets drug that are clinically effective in rheumatoid arthritis (RA) but whose mechanism is not well understood. Methods The predicted targets of HCQ and the proteins related to RA were returned from databases. Followed by protein-protein interaction (PPI) network, the intersection of the two group of proteins was conducted. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was used to analyse these proteins in a macro perspective. Finally, the candidate targets were verified by molecular docking. Results The results suggest that the efficacy of HCQ against RA is mainly associated with 4 targets of smoothened homolog (SMO), sphingosine kinase (SPHK) 1, SPHK2 and gatty-acid amide hydrolase (FAAH), with their related 3316 proteins’ network which regulate ErbB, HIF-1, NF-κB, FoxO, Chemokine, MAPK, PI3K/Akt pathways and so forth. Biological process are mainly concentrated in the regulation of cell activation, myeloid leukocyte activation, regulated exocytosis and so forth. Molecular docking analysis shows that hydrogen bonding and π-π stacking are the main forms of chemical force. Conclusions Our research provides protein targets affected by HCQ in the treatment of RA. SMO, SPHK1, SPHK2 and FAAH involving 3316 proteins become the multi-targets mechanism of HCQ in the treatment of RA. As well, the research also provides a new idea for introducing network pharmacology into the evaluation of the multi-target drugs in internal medicine.

scholarly journals Analysis of the Composition and Anti-Rheumatoid Arthritis Mechanism of Qintengtongbi Decoction Based on Network Pharmacology

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110414
Author(s):  
Guo-Cheng Liang ◽  
Wen-Gui Duan ◽  
Shu-Yin Chen ◽  
Jian-Kang Fang
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathway ◽  
Drug Targets ◽  
Transient Receptor Potential ◽  
Interaction Network ◽  
Receptor Potential ◽  
Transient Receptor Potential Channels ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Integrated Network

Qintengtongbi Decoction (QTTBD) is a traditional prescription for rheumatoid arthritis (RA) treatment in Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, southern China's Guangxi Zhuang Autonomous Region. However, there is not yet any analysis on its active compounds or action mechanism for treating RA. Moreover, the prescription has not been investigated from the perspective of network pharmacology. Therefore, this study aimed to analyze the compounds QTTBD and their potential pharmacological effects and the mechanism by which they treat RA via an integrated network pharmacology approach. With the aid of the relevant database tools and research indices, 188 compounds and 272 related drug targets genes/proteins were collected from QTTBD through the compound-target network, and 175 common gene targets between the QTTBD and RA were obtained by Venn 2.1. Finally, the top 10 gene targets and pathways were identified through the protein–protein interaction network, gene ontology, and KEGG pathway analysis: the gene targets include AKT1, IL6, TP53, VEGFA, MAPK3, TNF, CASP3, JUN, EGF, and EGFR; the pathways include oxytocin signaling pathway, amphetamine addiction, graft-versus-host disease, ovarian steroidogenesis, cGMP-PKG signaling pathway, Rap1 signaling pathway, allograft rejection, cytokine–cytokine receptor interaction, regulation of lipolysis in adipocytes and inflammatory mediator regulation of transient receptor potential channels. Therefore, it is concluded that a network pharmacology-based approach can help reveal and clarify the anti-RA role of QTTBD, and provide a scientific basis for further research into the mechanism.

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