scholarly journals Network Pharmacology and Molecular Docking Study of Zhishi-Baizhu Herb Pair in the Treatment of Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ying Qu ◽  
Xiangyang Yang ◽  
Jingxiang Li ◽  
Shuxin Zhang ◽  
Shiying Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Disease Genes ◽  
Molecular Docking Study ◽  
Cancer Pathogenesis

Objective. This study aimed to investigate the possible mechanism of the Zhishi and Baizhu herb pair in the treatment of gastric cancer by means of network pharmacology and molecular docking and to provide a theoretical basis for experiments and clinical application of traditional Chinese medicine for treating gastric cancer. Methods. The main active chemical components of Zhishi and Baizhu were screened through Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and selected by using the thresholds of oral bioavailability ≥30% and drug-likeness ≥18%. The targets of Zhishi and Baizhu were obtained from TCMSP, Therapeutic Targets Database (TTD), and the DrugBank database. The corresponding genes of the targets were retrieved from the UniProt database, and the gastric cancer targets were obtained from the GeneCards database and TTD. Subsequently, the networks were built between the main drug components, drug targets, and gastric cancer targets. Then, the enrichment analyses of GO and KEGG were applied to predict the potential roles of gastric cancer pathogenesis via the R package clusterProfiler. Finally, molecular docking was used to determine the affinity between the targets and components. Results. Twenty-seven main active components were predicted from the Zhishi-Baizhu herb pair, and a total of 120 intersection genes were screened from 303 potential medicine genes and 1,839 disease genes. The enrichment included the PI3K-Akt and IL-17 signaling pathways, and the network analysis showed that the Zhishi-Baizhu herb pair acted on seven key targets, namely, AKT1, MMP9, IL-6, CCND1, BCL2, MTOR, and MDM2 (where they played a role in treating gastric cancer). Molecular docking showed that luteolin and naringenin could stably bind to the targets. Conclusion. The possible mechanisms of the components of the Zhishi-Baizhu herb pair in treating gastric cancer might be related to luteolin and naringenin, which intervened with the targets AKT1, MMP9, IL-6, CCND1, BCL2, MTOR, and MDM2, and are linked with the PI3K-Akt and IL-17 signaling pathways. This knowledge will lay a solid foundation for further experimental and clinical studies.

scholarly journals Network pharmacology and molecular docking study on the mechanism of colorectal cancer treatment using Xiao-Chai-Hu-Tang

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252508
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Molecular Docking Study

Background and objective We aimed to predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, just as well as to further analyze its anti-CRC material basis and mechanism of action. Methods We adopted Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID) databases to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The common targets were used to construct the “herb-active ingredient-target” network using the Cytoscape 3.8.0 software. Next, we constructed and analyzed protein-to-protein interaction (PPI) using BisoGenet and CytoNCA plug-in in Cytoscape. We then performed Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes using the R package of clusterProfiler. Furthermore, we used the AutoDock Tools software to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results. Results We identified a total of 71 active XCHT ingredients and 20 potential anti-CRC targets. The network analysis revealed quercetin, stigmasterol, kaempferol, baicalein, and acacetin as potential key compounds, and PTGS2, NR3C2, CA2, and MMP1 as potential key targets. The active ingredients of XCHT interacted with most CRC disease targets. We showed that XCHT’s therapeutic effect was attributed to its synergistic action (multi-compound, multi-target, and multi-pathway). Our GO enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. We identified 11 KEGG signaling pathways, including the IL-17, TNF, Toll-like receptor, and NF-kappa B signaling pathways. Our results showed that XCHT could play a role in CRC treatment by regulating different signaling pathways. The molecular docking experiment confirmed the correlation between five core compounds (quercetin, stigmasterol, kaempferol, baicalein, and acacetin) just as well as PTGS2, NR3C2, CA2, and MMP1. Conclusion In this study, we described the potential active ingredients, possible targets, and key biological pathways responsible for the efficacy of XCHT in CRC treatment, providing a theoretical basis for further research.

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 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 Network Pharmacology-Based Strategy for Predicting Active Ingredients and Potential Targets of Coptis chinensis Franchin Polycystic Ovary Syndrome

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jian Xiong Ma ◽  
Miaoyong Ye ◽  
Ke Ma ◽  
Kang Zhou ◽  
Yingying Zhang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Polycystic Ovary Syndrome ◽  
Signaling Pathways ◽  
Polycystic Ovary ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Coptis Chinensis ◽  
Ovary Syndrome

Background. Polycystic ovary syndrome (PCOS) causes low fertility in females. Coptis chinensis (C. chinensis) is used to clear heat and dampness, purify fire, and detoxify in traditional Chinese medicine (TCM). Although C. chinensis has demonstrated efficacy against PCOS in clinical practice, there are no available data regarding the bioactive components of C. chinensis, their targets, and molecular mechanisms underlying their effects. Methods and Results. Network pharmacology was used to analyze the bioactive components of C. chinensis, their targets, and signaling pathways underlying their effects. The TCM systems pharmacology database and analysis platform (TCMSP) was used to screen 14 effective active ingredients and 218 targets of C. chinensis. The GeneCards, OMIM, and PharmGkb databases were used to screen 3517 disease targets for PCOS, and 102 common targets of drugs and diseases were screened using R Cytoscape that was utilized to build a drug-active ingredient-disease target interaction network, and the STRING platform was utilized to construct a common target protein-protein interaction network, including 102 nodes and 221 edges. Key targets of C. chinensis for the treatment of PCOS included JUN, MAPK, IL6, CXCL8, FOS, and IL1B. A total of 123 gene ontology (GO) terms and 129 pathways were acquired by GO and KEGG enrichment analyses. The AGEs/RAGE, TNF, IL-17, MAPK, and HIF-1 signaling pathways were closely related to PCOS and may be the core pathways involved in PCOS. Schrodinger software was used to evaluate the interaction between active components and their targets and explore binding modes. Furthermore, based on the prediction of network pharmacology study, a mouse model of PCOS was established to evaluate the curative role and underlying mechanisms of C. chinensis. The results showed that C. chinensis treatment reversed histopathological damage of the ovary and also ameliorated the mRNA and protein expression levels of the predicted hub targets (MAPK1, CXCL8, IL-6, and IL-1β). These results indicated that WZYZP has a protective effect on spermatogenesis disorder, suggesting that it could be an alternative choice for male infertility therapy. Conclusions. This preliminary study verified the basic pharmacological effects and mechanisms of C. chinensis, a TCM, in the treatment of PCOS. These results indicate that the therapeutic effects of C. chinensis on PCOS may be achieved by regulating the expression of inflammatory factors. This study provides new insights for the systematic exploration of the mechanism of traditional Chinese medicine.

scholarly journals Network Pharmacology‐Based Study on the Active Component and Mechanism of the Anti-Gastric-Cancer Effect of Herba Sarcandrae

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li Han ◽  
Ying Han
Keyword(s):  
Gastric Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Target Genes ◽  
Scientific Basis ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Pathway Network

Background. Herba Sarcandrae is used in the clinical practice of traditional Chinese medicine to deal with gastric cancer. However, there are few studies on its precise mechanism. Method. In this study, a network pharmacological approach was utilized to construct a molecular/target/pathway molecular regulatory network for the anti-gastric-cancer effect of Herba Sarcandrae. The active components of Herba Sarcandrae and their potential mechanisms were explored. Chemical components of the Herba Sarcandrae were identified through a database, and they were evaluated and screened based on oral bioavailability and drug similarity. Results. Genes related to gastric cancer were found in the Gene Expression Omnibus (GEO) database, and gene targets related to anti-gastric-cancer were chosen by comparison. Using annotation, visualization, and a comprehensive discovery database, the function and related pathways of target genes were analyzed and screened. Cytoscape software was utilized to construct a component/target/pathway network for the antitumor effect of Herba Sarcandrae. Finally, 6 drug ingredients and 29 target genes related to gastric cancer were detected. IL-17 signaling pathway, NF-kappa B signaling pathway, and other signaling pathways were significantly enriched. Many signaling pathways that directly act on tumors and indirect pathways inhibit the development of gastric cancer. Conclusion. This study provides a scientific basis for further elucidating the mechanism of the anti-gastric-cancer effect of Herba Sarcandrae.

scholarly journals Study on the Mechanism of Baimai Ointment in the Treatment of Osteoarthritis Based on Network Pharmacology and Molecular Docking with Experimental Verification

2021 ◽  
Vol 12 ◽  
Author(s):  
Yingyin Zhu ◽  
Wanling Zhong ◽  
Jing Peng ◽  
Huichao Wu ◽  
Shouying Du
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Animal Experiments ◽  
Tibetan Medicine ◽  
Blue Staining ◽  
Network Pharmacology ◽  
Enzyme Linked Immunosorbent Assay

Purpose: The external preparation of the Tibetan medicine formula, Baimai ointment (BMO), has great therapeutic effects on osteoarthritis (OA). However, its molecular mechanism remains almost elusive. Here, a comprehensive strategy combining network pharmacology and molecular docking with pharmacological experiments was adopted to reveal the molecular mechanism of BMO against OA.Methods: The traditional Chinese medicine for systems pharmacology (TCMSP) database and analysis platform, traditional Chinese medicine integrated database (TCMID), GeneCards database, and DisGeNET database were used to screen the active components and targets of BMO in treating OA. A component–target (C-T) network was built with the help of Cytoscape, and the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment through STRING. Autodock Tools which was used to dock the key components and key target proteins was analyzed. Animal experiments were performed to verify the key targets of BMO. Hematoxylin–eosin and toluidine blue staining were used to observe the pathology of joints. Protein expression was determined using enzyme-linked immunosorbent assay.Results: Bioactive compounds and targets of BMO and OA were screened. The network analysis revealed that 17-β-estradiol, curcumin, licochalone A, quercetin, and glycyrrhizic acid were the candidate key components, and IL6, tumor necrosis factor (TNF), MAPK1, VEGFA, CXCL8, and IL1B were the candidate key targets in treating OA. The KEGG indicated that the TNF signaling pathway, NF-κB signaling pathway, and HIF-1 signaling pathway were the potential pathways. Molecular docking implied a strong combination between key components and key targets. The pathology and animal experiments showed BMO had great effects on OA via regulating IL6, TNF, MAPK1, VEGFA, CXCL8, and IL1B targets. These findings were consistent with the results obtained from the network pharmacology approach.Conclusion: This study preliminarily illustrated the candidate key components, key targets, and potential pathways of BMO against OA. It also provided a promising method to study the Tibetan medicine formula or external preparations.

Network Pharmacology Analysis on Zhichan Powder in the Treatment of Parkinson's Disease

2020 ◽  
Vol 23 (1) ◽  
pp. 28-40
Author(s):  
Jia Li ◽  
Xinchang Qi ◽  
Yajuan Sun ◽  
Yingyu Zhang ◽  
Jiajun Chen
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Effective Components ◽  
Target Disease

Aim and Objective: Effective components and the mechanism of action of Zhichan powder for the treatment of Parkinson's disease were researched at a systematic level. Materials and Methods: Screening of active components in Zhichan powder for the treatment of Parkinson's disease was conducted using the Traditional Chinese Medicine Systems Pharmacology database, and a medicine-target-disease network was established with computational network pharmacology. Results: By using network pharmacology methods, we identified 18 major active components in Zhichan powder through screening, indicating a connection between chemical components of this Traditional Chinese Medicine and Parkinson’s disease-related targets. Conclusion: The medicine-target-disease system of Zhichan powder established by network pharmacology permitted visualization of clustering and differences among chemical components in this prescription, as well as the complex mechanism of molecular activities among those effective components, relevant targets, pathways, and the disease. Thus, our results provide a new perspective and method for revealing the mechanism of action of Traditional Chinese Medicine prescriptions.

Exploring the mechanisms of Drynariae Rhizoma on treating memory impairment through network pharmacology

2021 ◽  
Author(s):  
Wangmi Liu ◽  
Jiayan Wu
Keyword(s):  
Molecular Docking ◽  
Nerve Growth Factor ◽  
Chinese Medicine ◽  
Growth Factor ◽  
Traditional Chinese Medicine ◽  
Memory Impairment ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Major Health Problem ◽  
Nerve Growth

Abstract Background Memory impairment continues to be a major health problem and increases with age, especially in the elderly population worldwide. However, a causal mechanism has not been clearly identified. Currently, an interaction between bone and brain, the so-called “bone-brain crosstalk,” has emerged. We used a network pharmacology approach to explore the potential mechanisms of Drynariae Rhizoma (DR), a traditional Chinese medicine for fracture treatment, for therapeutic intervention of human conditions associated with memory impairment. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen out the active compounds of DR, and the targets of the active compounds were predicted using PharmMapper. Targets related to memory impairment were downloaded from the DisGeNET database. The compound-target network and protein-protein interaction network were built by NetworkAnalyst and Cytoscape software. Gene ontology analysis and Reactome pathway enrichment analysis were performed using NetworkAnalyst. SYBYL-X software was used to perform molecular docking simulation. Results Our study demonstrated that DR had 7 active compounds. There were 60 target genes related to these active compounds as well as to memory impairment. Signalling by nerve growth factor was among the top 3 enriched Reactome terms. Akt1 was an important signalling hub gene belonging to signalling by nerve growth factor pathway. Molecular docking results showed that the one of the active compounds, xanthogalenol, exhibited acceptable affinities to Akt1. Conclusion This study demonstrated the molecular mechanism that DR may alleviate memory impairment via regulation of Akt1 and signalling by nerve growth factor pathway. These results offer new ideas in searching for novel strategies for the treatment of memory impairment.

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.

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