scholarly journals Based on Network Pharmacology to Explore the Mechanisms of Radix Astragali Combined with Prepared Radix Rehmanniain for Treating Osteoporosis

2021 ◽  
Author(s):  
Wenqian Kang ◽  
Chunyu Liu ◽  
Yu Tang ◽  
Zhixin Geng ◽  
Jiahao Zhang ◽  
...  
Keyword(s):  
Protein Interaction Network ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Radix Astragali ◽  
Treatment Of Osteoporosis ◽  
Network Diagram ◽  
In Vivo Experiments

Abstract Background: With the improvement of people's living standards, the aging population in China has gradually increased, and the treatment of osteoporosis (OP) has become a major problem afflicting the medical field. Radix Astragali(RA) and Prepared Radix Rehmannia(PRR) are commonly used Chinese herbal medicines. The combination of them can achieve a synergistic effect in the treatment of osteoporosis. However, its mechanism of action remains uncertain.Objective: This study aims to investigate the possible molecular mechanism of RA combined with PRR in the treatment of OP using an integrated strategy of network pharmacology and experimental validation.Methods: The active ingredients of RA combined with PRR were searched and screened by TCMSP database, and the targets of active ingredients were predicted and supplemented by TCMSP and SwissTargetPrediction databases. The target genes related to OP diseases were searched in GeneCards and OMIM comprehensive databases. The intersection targets of drugs and diseases were imported into String database to obtain the interaction information of intersection target genes. Cytoscape3.7.1 software was used to construct the protein interaction network diagram and "drug component-target-disease" network diagram. Then DAVID database was used for GO gene enrichment analysis and KEGG metabolic pathway analysis. Finally, in vivo experiments were also performed to validate the findings of network pharmacology.Results: A total of 98 active components of RA combined with PRR were finally retrieved and integrated into the TCMSP database, 1700 target genes related to OP were obtained through the disease database, 149 gene targets were obtained by taking the intersection of disease genes, and drug targets, 122 core targets and 514 interaction relationships were obtained after protein interaction network and topology analysis. GO analysis and KEGG pathway enrichment analysis showed that RA combined with PRR intervention for OP mainly through multiple pathways such as PI3K-Akt, MAPK, TNF, Rap1, and Toll-like receptors. In addition, in vivo experiments confirmed that RA combined with PRR could significantly increase bone mineral density, reduce bone spacing, improve bone tissue structure, and improve osteoporosis in ovariectomized rats.Conclusion: In this study, the network pharmacological approach was used to reveal the potential targets and key signal pathways of RA combined with PRR in treating osteoporosis. This study was also verified by animal experiments, which provided a reliable basis for clinical application.

scholarly journals Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minglong Guan ◽  
Lan Guo ◽  
Hengli Ma ◽  
Huimei Wu ◽  
Xiaoyun Fan
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Rosmarinic Acid ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

scholarly journals Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

scholarly journals Identification on the potential mechanism of Radix pueraria on colon cancer based on network pharmacology

2021 ◽  
Author(s):  
Yi Li ◽  
Chunli Zhang ◽  
Xiaohan Ma ◽  
Liuqing Yang ◽  
Huijun Ren
Keyword(s):  
Colon Cancer ◽  
Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
In Vivo Studies ◽  
Network Pharmacology ◽  
Biological Mechanism ◽  
Active Components

Abstract Radix Puerariae (RP), a dry root of the Pueraria lobata (Willd.) Ohwi, is used to treat a variety of diseases, including cancer. Several in vitro and in vivo studies have demonstrated the efficacy of RP in the treatment of colon cancer (CC). However, the biological mechanism of RP in the treatment of colon cancer remains unclear. In this study, the active component of RP and its potential molecular mechanism against CC were studied by network pharmacology and enrichment analysis. The methods adopted included screening of active ingredients of Chinese medicine, prediction of target genes of Chinese medicine and disease, construction of protein interaction network, and GO and KEGG Enrichment Analysis. Finally, the results of network pharmacology were further validated by molecular docking experiments and cell experiments. 8 active constituents and 14 potential protein targets were screened from RP, including EGFR, JAK2 and SRC. The biological mechanism of RP against CC was analyzed by studying the relationship between active components, targets, and enrichment pathway. This provides a basis for understanding the clinical application of RP in CC.

scholarly journals Mechanism of YuPingFeng in the Treatment of COPD Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yunhong Yin ◽  
Jianyu Liu ◽  
Mengyu Zhang ◽  
Rui Li ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Signalling Pathways ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Herbal Formula ◽  
Pathway Enrichment ◽  
Topological Parameters

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

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 Network Pharmacology and Metabolomics Studies on Antimigraine Mechanisms of Da Chuan Xiong Fang (DCXF)

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Shiyu Ma ◽  
Lin Zheng ◽  
Xiao Lin ◽  
Yi Feng ◽  
Ming Yang ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Brain Tissue ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Fatty Acid Transport ◽  
Hub Genes ◽  
Hydroxytryptamine Receptors ◽  
Protein Protein Interaction

Background. Da Chuan Xiong Fang (DCXF) is a traditional Chinese medicine (TCM) formula used to treat migraines. Previously, we uncovered partial mechanisms involved in the therapeutic actions of DCXF on migraines. Methods. In this study, we further elucidated its antimigraine mechanisms in vivo by using an integrated strategy coupling with network pharmacology and metabolomics techniques. Results. Network pharmacology identified 33 genes linked with both migraine and DCXF, most of which were 5-hydroxytryptamine receptors, dopamine, and peptide receptors. The results of GO and KEGG enrichment analysis showed that DCXF significantly regulated tyrosine metabolism, tryptophan metabolism, dopamine metabolic process, glucose transmembrane transport, lipid metabolism, and fatty acid transport. The results of metabolomics analysis found that the metabolism of tryptophan and tyrosine in the brain tissue and energy and lipid metabolism of rats tended towards normal and reached normal levels after administering DCXF. The metabolomics and network pharmacology approaches demonstrated similar antimigraine effects of DCXF on endogenous neurotransmitters and overall trends in serum and brain tissue. Using both approaches, 62 hub genes were identified from the protein-protein interaction (PPI) network of DCXF and gene-metabolite interaction network, with hub genes and different metabolites in serum and brain tissue. The hub genes of DCXF, which were mostly linked with inflammation, might affect mainly neurotransmitters in serum and brain tissue metabolisms. Conclusion. Network pharmacology and metabolomics study may help identify hub genes, metabolites, and possible pathways of disease and treatment. Additionally, two parts of the results were integrated to confirm each other. Their combination may help elucidate the relationship between hub genes and metabolites and provide the further understanding of TCM mechanisms.

scholarly journals Rapid Identification and Systematic Mechanism of Flavonoids from Potentilla freyniana Bornm. Based on UHPLC-Q-Exactive Orbitrap Mass Spectrometry and Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wei Cai ◽  
Kailin Li ◽  
Shihan Qin ◽  
Pei Xiong ◽  
Jie Peng ◽  
...  
Keyword(s):  
High Performance ◽  
Target Genes ◽  
Folk Medicine ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rapid Identification ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Q Exactive ◽  
Orbitrap Ms

Potentilla freyniana Bornm. (P. freyniana), belonging to the family Rosaceae, has been used as a folk medicine in China. However, as we know, the constituents and the systematic elucidation of the mechanism were not fully investigated. Therefore, it is necessary to develop a rapid method using LC-MS and network pharmacology for the detection and identification of constituents and the systematic mechanism of P. freyniana. Firstly, the flavonoids were detected and identified based on ultra-high-performance liquid chromatography coupled with Quadrupole-Exactive Focus Orbitrap MS (UHPLC-Q-Exactive Orbitrap MS). After that, the potential targets of those constituents were obtained by database mining. Then, the core targets were predicted by protein-protein interaction network and network analysis. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out via DAVID. This finding revealed that P. freyniana possessed 43 flavonoids (40 of them were first reported) with 23 core target genes, which are associated with PI3K-Akt, MAPK, TNF signaling pathway, and pathway in cancer. This study demonstrated the multicompound, multitarget, and multimechanism of P. freyniana, which are very beneficial to develop the further study and utilization of this plant including the material basis and quality control research.

scholarly journals Network Pharmacology Approach and Experimental Verification of Huashi Dingtong Decoction Against Knee Osteoarthritis

2020 ◽  
Author(s):  
Ge Hai-Ya ◽  
Yan Lai-Jun ◽  
Zhang Yan ◽  
Zhang Ying-Sheng ◽  
Lai Yu-Yang ◽  
...  
Keyword(s):  
Synovial Fluid ◽  
Knee Osteoarthritis ◽  
Signaling Pathway ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Model Group ◽  
Target Network

Abstract Background: The aim of this study is to clarify the ingredients and targets of HSDTT against KOA by network pharmacology,and to verify the mechanism of HSDTT in treatment of KOA in vivo.Methods: Ingredient-target network for HSDTT and KOA was created to identify the potential targets, protein-protein interaction network was used to find the key targets of HSDTT in treatment for KOA, GO enrichment and KEGG pathway was conducted to illuminate the pathway related to KOA treat by HSDTT. Rat model of KOA was established by joint injection in papain.The morphology of cartilage were assessed by H&E. ELISA was used to detect the contents of inflammation cytokines in synovial fluid and synovium. The expression of the pathway protein were assessed by PCR.Results: The results of network pharmacology demonstrate that there are 440 ingredients of HSDTT against knee osteoarthritis by 478 targets.The KEGG enrichment analysis showed that PI3K-Akt signaling pathway, MAPK signaling pathway were the key pathways for HSDTT to treat KOA. Morphology of cartilage was improved in the HSDTT group when compared with the model group. Our experiment show that HSDTT can reduced the expressions of p38 and p53 in cartilage, increased the expression of collagenⅡ. The contents of IL-1β and TNF-α in the synovium and COX-2 and PGE-2 in synovial fluid were decreased significantly in the HSDTT group when compared with the model group.Conclusions: Our study indicadites that HSDTT is capable to alleviate inflammation and delay the progression of KOA by p38MAPK signaling pathway.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

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