scholarly journals Network Pharmacology-Based Prediction of Bioactive Compounds and Potential Targets of Wenjing Decoction for Treatment of Endometriosis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yu-nan Liu ◽  
Xiao-jing Hu ◽  
Bei Liu ◽  
Yu-jie Shang ◽  
Wen-ting Xu ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Inflammatory Disorder

Endometriosis is a chronic estrogen-dependent inflammatory disorder that negatively affects the quality of life in women. The Wenjing decoction (WJD) is a traditional Chinese medicine that has been shown to have a therapeutic effect on endometriosis. Our study systematically explored the mechanism of WJD against endometriosis using a network pharmacology approach. Potentially bioactive compounds of WJD and their possible targets were retrieved from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The protein-protein interaction network and herbs-compounds-genes multinetwork were constructed using Cytoscape for visualization. Subsequently, the signaling pathways of common targets were retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and molecular docking was performed using PyRx software. In total, 48 common targets were screened, such as IL6 and ESR1, which were related to inflammation and the endocrine system. The top five bioactive compounds were quercetin, kaempferol, wogonin, beta-sitosterol, and stigmasterol. KEGG enrichment analysis revealed 65 pathways containing inflammatory- and endocrine-related signaling pathways, such as the “TNF signaling pathway” and the “estrogen signaling pathway.” Taken together, the results of our network pharmacology analysis predicted that certain active ingredients of WJD might treat endometriosis by regulating inflammation and/or endocrine, which provided references for further understanding and exploration of WJD on endometriosis.

scholarly journals Network Pharmacology Study of Heat-Clearing and Detoxifying Traditional Chinese Medicine for Alzheimer's Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hongxing Li ◽  
Xinyue Zhang ◽  
Lili Gu ◽  
Ningzi Wu ◽  
Lingxi Zhang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Chlorogenic Acid ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

This study aims to explore the possible homologous mechanism of 7 frequently‐used herbs for heat-clearing and detoxification in traditional Chinese medicine (HDTCM) for treating Alzheimer's disease (AD), one of the most common types of dementia, based on network pharmacology. Herbs that satisfied the criteria of containing chlorogenic acid, relating to AD and aligning with HDTCM, were simultaneously collected to determine whether they have anti-AD effect based on a survey of the literature. Herb-ingredient-target-disease networks were constructed by collecting information from the TCMSP and GeneCards public databases. The common targets of the herbs and AD were identified for conducting a Gene Ontology (GO) analyses and a Reactome pathway enrichment analysis. The results showed that PTGS1, IL-6, CASP3, and VEGFA were the predicted key gene targets. The IL-4 and IL-13 signaling pathway, the ESR-mediated signaling pathway, and the extranuclear estrogen signaling pathway were the significant pathways associated with the 7 herbs. This study revealed that the analogous anti-AD mechanism of the 7 herbs of HDTCM may be associated with anti-inflammation, which is a common effect of the chlorogenic acid and quercetin components.

scholarly journals Investigating the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease based on network pharmacology

2020 ◽  
Author(s):  
Li-ying Jia ◽  
Jia Li ◽  
Gui-yun Cao ◽  
Zhao-qing Meng ◽  
Lu Gan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology

Abstract Background SheXiang XinTongNing, a commercially available Chinese patent medicine, has been widely used in the treatment of coronary heart disease. However, the mechanisms of SheXiang XinTongNing are still unclear. The aim of this study was to investigate the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease via network analysis. Method The traditional Chinese medicine system pharmacology analysis platform was used to screen the potential active constituents of the six traditional Chinese medicines in SheXiang XinTongNing, and the potential targets were obtained from PharmMapper. The genome annotation database platform was used to screen the candidate targets related to coronary heart disease. Then the drug-components-targets network and protein interaction network were built by Cytoscape 3.6.0 software. Further, GO bio-functional enrichment analysis and KEGG pathway enrichment analysis were performed through annotation, visualization and integrated discovery database. Results Results showed that the drugs-components-targets network contains 104 targets and 62 key components. The protein interaction network consisted of 107 nodes; key targets included Bcl2l1, IGF1, SRC, CASP3, et al. Functionally, the candidate targets were significantly associated with multiple pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, Ras signaling pathway, FoxO signaling pathway, Endocrine resistance. Given the above, the pharmacological activities of SheXiang XinTongNing may be predominantly related to several factors such as cell apoptosis, inflammation and angiogenesis. Conclusion XTN can effectively attenuate the symptoms of coronary heart disease through diverse pathways. The research proves that network pharmacology can successfully reveal the mechanisms of traditional Chinese medicine in a holistic view. Our systematic analysis lays a foundation for further studying.

scholarly journals Systemic Elucidate The Potential Bioactive Compounds and Hypoglycemic Mechanism of Polygonum Multiflorum Based on Network Pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Finally, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

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 Systemic elucidation on the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum based on network pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Thirdly, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Lastly, the part of potential bioactive compounds were under enzyme activity inhibition tests.Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

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 A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Chunli Piao ◽  
Qi Zhang ◽  
De Jin ◽  
Li Wang ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

scholarly journals Systemic elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum based on network pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Finally, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

scholarly journals Study on the Mechanism of Prunella Vulgaris L on Diabetes Mellitus Complicated with Hypertension Based on Network Pharmacology and Molecular Docking Analyses

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinyi Jiao ◽  
Haiying Liu ◽  
Qinan Lu ◽  
Yu Wang ◽  
Yue Zhao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Prunella Vulgaris ◽  
Active Components ◽  
Analysis Platform

The role of traditional Chinese medicine Prunella vulagaris L in the treatment of tumors and inflammation has been widely confirmed. We found that some signaling pathways of Prunella vulgaris L action can also regulate diabetes and hypertension, so we decided to study the active ingredients, potential targets and signaling pathway of Prunrlla vulgaris L, and explore the “multi-target, multi-pathway” molecular mechanism of Prunella vulgaris L on diabetes mellitus complicated with hypertension(DH). Methods. Based on TCMSP(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) and CNKI(China National Knowledge Infrastructure), the components and action targets related to Prunella vulgaris L were screened. The OMIM(Online Mendelian Inheritance in Man) and GeneCards (The human gene database) were used to search for targets related to DH. The “gene - drug - disease” relationship map was drawn by Cytoscape_v3.7.2 plug-in. The target was amplified by the STRING platform, and the “protein - protein” interaction relationship (PPI) network of the interacting target was obtained by the STRING online analysis platform and the Cytoscape_v3.7.2 plug-in. Finally, GO enrichment analysis and KEGG pathway enrichment analysis were conducted on David and Metascape platform to study the co-acting targets. Results. 11 active components, 41 key targets and 16 significant signaling pathways were identified from Prunella vulgaris L. The main active components of Prunella vulgaris L against DH were quercetin and kaumferol, etc, and potential action targets were IL-6 and INS, etc and signaling pathways were AGE-RAGE signaling pathway, TNF signaling pathway, MAPK signaling pathway, PI3K-AKT signaling pathway, etc. It involves in biological processes such as cell proliferation, apoptosis and inflammatory response. Conclusions. The main molecular mechanism of Prunella vulgaris L against DH is that sterols and flavonoids play an active role by affecting TNF signaling pathway, AGE-RAGE signaling pathway, MAPK pathway, PI3K-Akt pathway related targets such as IL-6 and INS.

scholarly journals Synergistic Network Pharmacology for Traditional Chinese Medicine Liangxue Tongyu Formula in Acute Intracerebral Hemorrhagic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Yang Chen ◽  
Ju Dong ◽  
Dongqing Yang ◽  
Qin Qian ◽  
Pengcheng Wang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Rna Seq ◽  
Anti Inflammatory

Background. Nowadays, acute intracerebral hemorrhage stroke (AICH) still causes higher mortality. Liangxue Tongyu Formula (LXTYF), originating from a traditional Chinese medicine (TCM) prescription, is widely used as auxiliary treatment for AICH. Objective. To dig into the multicomponent, multitarget, and multipathway mechanism of LXTYF on treating AICH via network pharmacology and RNA-seq. Methods. Network pharmacology analysis was used by ingredient collection, target exploration and prediction, network construction, and Gene Ontology (GO) and KEGG analysis, with the Cytoscape software and ClusterProfiler package in R. The RNA-seq data of the AICH-rats were analyzed for differential expression and functional enrichments. Herb-Compound-Target-Pathway (H-C-T-P) network was shown to clarify the mechanism of LXTYF for AICH. Results. 76 active ingredients (quercetin, Alanine, kaempferol, etc.) of LXTYF and 376 putative targets to alleviate AICH (PTGS2, PTGS1, ESR1, etc.) were successfully identified. The protein-protein interaction (PPI) network indicated the important role of STAT3. The functional enrichment of GO and KEGG pathway showed that LXTYF is most likely to influence MAPK and PI3K-Akt signaling pathways for AICH treatment. From the RNA-seq of AICH-rats, 583 differential mRNAs were identified and 14 of them were consistent with the putative targets of LXTYF for AICH treatment. The KEGG pathway enrichment also implied that the MAPK signaling pathway was the most correlated one among all the related signaling pathways. Many important targets with expression changes of LXTYF for AICH treatment and their related pathways are great markers of antioxidation, anti-inflammatory, antiapoptosis, and lowering blood pressure, which indicated that LXTYF may play mutiroles in the mechanisms for AICH treatment. Conclusion. The LXTYF attenuates AICH partially by antioxidation, anti-inflammatory, and antiapoptosis and lowers blood pressure roles through regulating the targets involved MAPK, calcium, apoptosis, and TNF signaling pathway, which provide notable clues for further experimental validation.

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