scholarly journals Network pharmacology integrated molecular docking reveals the bioactive components and potential targets of Morinda officinalis–Lycium barbarum coupled-herbs against oligoasthenozoospermia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Yafei Chen ◽  
Dan Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Protein Kinase ◽  
Signaling Pathway ◽  
Sperm Quality ◽  
Oxidant Stress ◽  
New Drugs ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Lycium Barbarum ◽  
Male Reproductive Function

AbstractOligoasthenozoospermia (OA) is one of the most common types of male infertility affecting sperm count and sperm motility. Unfortunately, it is difficult for existing drugs to fundamentally improve the sperm quality of OA patients, because the pathological mechanism of OA has not been fully elucidated yet. Morinda officinalis–Lycium barbarum coupled-herbs (MOLBCH), as traditional Chinese Medicines, has been widely used for treating OA over thousands of years, but its molecular mechanism is still unclear. For this purpose, we adopted a comprehensive approach integrated network pharmacology and molecular docking to reveal the bioactive components and potential targets of MOLBCH against OA. The results showed that MOLBCH alleviated apoptosis, promoted male reproductive function, and reduced oxidant stress in the treatment of OA. Ohioensin-A, quercetin, beta-sitosterol and sitosterol were the key bioactive components. Androgen receptor (AR), Estrogen receptor (ESR1), Mitogen-activated protein kinase 3 (MAPK3), RAC-alpha serine/threonine-protein kinase (AKT1), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were the core potential targets. PI3K/Akt signaling pathway, prostate cancer, AGE-RAGE signaling pathway in diabetic complications were the most representative pathways. Moreover, molecular docking was performed to validate the strong binding interactions between the obtained core components and targets. These observations provide deeper insight into the pathogenesis of OA and can be used to design new drugs and develop new therapeutic instructions to treat OA.

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

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.

scholarly journals Network Pharmacology to Explore the Molecular Mechanisms of Prunella vulgaris for Treating Hashimoto’s Thyroiditis

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-xiong Gan ◽  
Lin-kun Zhong ◽  
Fei Shen ◽  
Jian-hua Feng ◽  
Ya-yi Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Protein Kinase ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Prunella Vulgaris ◽  
Mitogen Activated Protein

Purpose:Prunella vulgaris (PV), a traditional Chinese medicine, has been used to treat patients with thyroid disease for centuries in China. The purpose of the present study was to investigate its bioactive ingredients and mechanisms against Hashimoto’s thyroiditis (HT) using network pharmacology and molecular docking technology to provide some basis for experimental research.Methods: Ingredients of the PV formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Additionally, HT-related genes were retrieved from the UniProt and GeneCards databases. Cytoscape constructed networks for visualization. A protein–protein interaction (PPI) network analysis was constructed, and a PPI network was built using the Search Tool for the Retrieval of Interacting Genes (STRING) database. These key targets of PV were enriched and analyzed by molecular docking verification, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment.Results: The compound–target network included 11 compounds and 66 target genes. Key targets contained Jun proto-oncogene (JUN), hsp90aa1.1 (AKI), mitogen-activated protein kinase 1 (MAPK1), and tumor protein p53 (TP53). The main pathways included the AGE-RAGE signaling pathway, the TNF signaling pathway, the PI3K–Akt signaling pathway, and the mitogen-activated protein kinase signaling pathway. The molecular docking results revealed that the main compound identified in the Prunella vulgaris was luteolin, followed by kaempferol, which had a strong affinity for HT.Conclusion: Molecular docking studies indicated that luteolin and kaempferol were bioactive compounds of PV and might play an essential role in treating HT by regulating multiple signaling pathways.

scholarly journals Examining the effector mechanisms of Xuebijing Injection on COVID-19 based on network pharmacology

2020 ◽  
Author(s):  
Wenjiang Zheng ◽  
Qian Yan ◽  
Yongshi Ni ◽  
Shaofeng Zhan ◽  
Liuliu Yang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Growth Factor ◽  
Protein Kinase ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Effector Mechanism ◽  
Effector Mechanisms

Abstract Background: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology.Methods: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. Results: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values >40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than -4.0 with those top 10 targets. Conclusion: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

scholarly journals Examining the effector mechanisms of Xuebijing Injection on COVID-19 based on network pharmacology

2020 ◽  
Author(s):  
Wenjiang Zheng ◽  
Qian Yan ◽  
Yongshi Ni ◽  
Shaofeng Zhan ◽  
Liuliu Yang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Growth Factor ◽  
Protein Kinase ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Effector Mechanism ◽  
Effector Mechanisms

Abstract Background: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ onCOVID-19 based on network pharmacology.Methods: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. Results: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values >40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than -4.0 with those top 10 targets. Conclusion: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

scholarly journals Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Wen-jiang Zheng ◽  
Qian Yan ◽  
Yong-shi Ni ◽  
Shao-feng Zhan ◽  
Liu-liu Yang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Growth Factor ◽  
Protein Kinase ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Effector Mechanism ◽  
Effector Mechanisms

Abstract Background Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology. Methods We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. Results We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values > 40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than − 4.0 with those top 10 targets. Conclusion The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

scholarly journals Exploration in the mechanism of fucosterol for the treatment of non-small cell lung cancer based on network pharmacology and molecular docking

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoling Li ◽  
Baixin Lin ◽  
Zhiping Lin ◽  
Yucui Ma ◽  
Qu Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Small Cell Lung Cancer ◽  
Signaling Pathway ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Erk Signaling ◽  
Network Pharmacology ◽  
Protein Interaction Data ◽  
Small Cell Lung

AbstractFucosterol, a sterol isolated from brown algae, has been demonstrated to have anti-cancer properties. However, the effects and underlying molecular mechanism of fucosterol on non-small cell lung cancer remain to be elucidated. In this study, the corresponding targets of fucosterol were obtained from PharmMapper, and NSCLC related targets were gathered from the GeneCards database, and the candidate targets of fucosterol-treated NSCLC were predicted. The mechanism of fucosterol against NSCLC was identified in DAVID6.8 by enrichment analysis of GO and KEGG, and protein–protein interaction data were collected from STRING database. The hub gene GRB2 was further screened out and verified by molecular docking. Moreover, the relationship of GRB2 expression and immune infiltrates were analyzed by the TIMER database. The results of network pharmacology suggest that fucosterol acts against candidate targets, such as MAPK1, EGFR, GRB2, IGF2, MAPK8, and SRC, which regulate biological processes including negative regulation of the apoptotic process, peptidyl-tyrosine phosphorylation, positive regulation of cell proliferation. The Raf/MEK/ERK signaling pathway initiated by GRB2 showed to be significant in treating NSCLC. In conclusion, our study indicates that fucosterol may suppress NSCLC progression by targeting GRB2 activated the Raf/MEK/ERK signaling pathway, which laying a theoretical foundation for further research and providing scientific support for the development of new drugs.

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

Molecular Mechanism of The Effect of Huanglian Jiedu Decoction On Ulcerative Colitis Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Jing Yang ◽  
Chao-Tao Tang ◽  
Ruiri Jin ◽  
Bixia Liu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Signal Pathway ◽  
Intestinal Barrier Function ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Ppi Network ◽  
Active Components

Abstract Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC by means of network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are considered to be very important to PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had good affinity with Hub gene. This study systematically elucidates the "multi-component, multi-target, multi-pathway" mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

scholarly journals Network Pharmacology and Experiment Verification to Explore the Potential Mechanism of Yin-Huo-Tang for Lung Adenocarcinoma Recurrence

2021 ◽  
Author(s):  
Dianna Liu ◽  
Shicheng Lin ◽  
Yuan Li ◽  
Tian Zhou ◽  
Kaiwen Hu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Lung Adenocarcinoma ◽  
Signaling Pathway ◽  
Rna Sequencing ◽  
Network Pharmacology ◽  
Phytochemical Analysis ◽  
Sequencing Analysis ◽  
Lewis Lung ◽  
Hub Genes

Abstract BackgroundLung adenocarcinoma (LUAD) is one of the most common malignancies with a rise in new cases worldwide each year. Recurrence significantly influences the survival in patients with LUAD. Yin-Huo-Tang (YHT) is a classic traditional Chinese prescription, used to prevent lung cancer relapse by “nourishing yin and clearing heat”. MethodsIn this study, the mechanism of YHT in LUAD recurrence was investigated. Firstly, the bioactive compounds-targets network and the protein–protein interaction network were constructed, and functional annotation and pathway enrichment analyses were performed. Pivotal compounds and hub genes were selected from the networks. Subsequently, the effectiveness of YHT was confirmed in lewis lung carcinoma mice. RNA sequencing was used to explore the mRNA expression differences between tumor tissues in the model mouses and YHT-treated mouses. The pathways screened by network pharmacology and RNA sequencing analysis at the same time were considered the most important pathways. At last, qualitative phytochemical analysis, molecular docking technology, PCR and WB analysis were used to validate the pivotal active ingredients, hub genes and main pathways.ResultsThere were 128 active compounds, 419 targets interacting with LUAD recurrence. Network analysis identified 4 pivotal compounds, 28 hub genes and 30 main pathways. Target genes mainly focused on inflammation, metabolism, immune responses and apoptosis. We confirmed that YHT could inhibit the recurrence of lung adenocarcinoma through animal experimental study. Sphingolipid signaling pathway was the common main pathway in network pharmacology and RNA sequencing results. The hub genes related with the sphingolipid signaling pathway was S1PR5. Qualitative phytochemical analysis of the water extract of YHT confirmed the presence of 3 pivotal compounds, namely stigmasterol, nootkatone and ergotamine. The results of molecular docking verified the pivotal compounds of YHT could good affinity with the S1PR5. The PCR and WB analysis verified YHT suppressed lewis lung cancer cells proliferation by inhibiting S1P/S1PR5/Gi/Ras/Raf/MEK/ERK pathway, and inhibited migration through S1P/S1PR5/Gi/PI3K/RAC pathway.ConclusionThe results confirmed the therapeutic effect of YHT on the recurrence of LUAD by multi-component-multi-target mode, the sphingolipid signaling pathway was one of the most relevant potential signaling pathways.

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