scholarly journals Exploring the mechanism of Danggui Buxue Decoction in regulating atherosclerotic disease network based on integrated pharmacological methods

2021 ◽  
Author(s):  
Hao Xu ◽  
Tianqing Zhang ◽  
Ling He ◽  
Mengxia Yuan ◽  
You Yuan ◽  
...  
Keyword(s):  
Ppi Network ◽  
Model Group ◽  
Local Inflammatory Response ◽  
Matrix Deposition ◽  
Ppi Networks ◽  
Smooth Muscle Proliferation ◽  
Tnf Α ◽  
Disease Protein ◽  
Extracellular Matrix Deposition ◽  
Danggui Buxue Decoction

Objective: To explore the mechanism of Danggui Buxue Decoction (DGBXD) in regulating Atherosclerosis (AS) network based on integrated pharmacological methods. Methods: The active ingredients and targets of DGBXD are obtained from TCMSP database and ETCM. AS-related targets were collected from the Genecards and OMIM databases. The drug-disease protein interaction (PPI) networks were constructed by Cytoscape. Meanwhile, it was used to screen out densely interacting regions, namely clusters. Finally, Gene Ontology (GO) annotations are performed on the targets and genes in the cluster to obtain biological processes, and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations are performed on the targets of the PPI network to obtain signaling pathways. Results: A total of 212 known targets, 265 potential targets and 229 AS genes were obtained. The “DGBXD known-AS PPI network” and “DGBXD-AS PPI Network” were constructed and analyzed. DGBXD can regulate inflammation, platelet activation, endothelial cell apoptosis, oxidative stress, lipid metabolism, vascular smooth muscle proliferation, angiogenesis, TNF, HIF-1, FoxO signaling pathway, etc. The experimental data showed that compared with the model group, the expressions of ICAM-1, VCAM-1 and IL-1β protein and mRNA in the DGBXD group decreased (P<0.05). However, plasma IL-1β, TNF-α and MCP-1 in the DGBXD group were not significantly different from the model group (P>0.05). Conclusion: The mechanism of DGBXD in the treatment of AS may be related to the improvement of extracellular matrix deposition in the blood vessel wall and the anti-vascular local inflammatory response, which may provide a reference for the study of the mechanism of DGBXD.

scholarly journals Molecular mechanism of the anti-inflammatory effects of Sophorae Flavescentis Aiton identified by network pharmacology

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naiqiang Zhu ◽  
Jingyi Hou
Keyword(s):  
Bioactive Compounds ◽  
Topological Analysis ◽  
Network Pharmacology ◽  
No Production ◽  
Ppi Network ◽  
Hub Genes ◽  
Ppi Networks ◽  
Tnf Α ◽  
Cox 2 ◽  
Anti Inflammatory

AbstractInflammation, a protective response against infection and injury, involves a variety of biological processes. Sophorae Flavescentis (Kushen) is a promising Traditional Chinese Medicine (TCM) for treating inflammation, but the pharmacological mechanism of Kushen’s anti-inflammatory effect has not been fully elucidated. The bioactive compounds, predicted targets, and inflammation-related targets of Kushen were obtained from open source databases. The “Component-Target” network and protein–protein interaction (PPI) network were constructed, and hub genes were screened out by topological analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on genes in the PPI network. Furthermore, nitric oxide (NO) production analysis, RT-PCR, and western blot were performed to detect the mRNA and protein expression of hub genes in LPS-induced RAW264.7 cells. An immunofluorescence assay found that NF-κB p65 is translocated. A total of 24 bioactive compounds, 465 predicted targets, and 433 inflammation-related targets were identified and used to construct “Component-Targets” and PPI networks. Then, the five hub genes with the highest values-IL-6, IL-1β, VEGFA, TNF-α, and PTGS2 (COX-2)- were screened out. Enrichment analysis results suggested mainly involved in the NF-κB signaling pathway. Moreover, experiments were performed to verify the predicted results. Kushen may mediate inflammation mainly through the IL-6, IL-1β, VEGFA, TNF-α, and PTGS2 (COX-2), and the NF-κB signaling pathways. This finding will provide clinical guidance for further research on the use of Kushen to treat inflammation.

scholarly journals Uncovering Biological Network Function via Graphlet Degree Signatures

2008 ◽  
Vol 6 ◽  
pp. CIN.S680 ◽  
Author(s):  
Tijana Milenković ◽  
Nataša Pržulj
Keyword(s):  
Protein Function ◽  
Biological Function ◽  
Protein Complexes ◽  
Local Network ◽  
Ppi Network ◽  
Graph Theoretic ◽  
Protein Protein Interaction ◽  
Network Function ◽  
Ppi Networks ◽  
Disease Protein

Motivation Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the entire proteome based on protein-protein interaction (PPI) networks. Since proteins interact to perform a certain function, analyzing structural properties of PPI networks may provide useful clues about the biological function of individual proteins, protein complexes they participate in, and even larger subcellular machines. Results We design a sensitive graph theoretic method for comparing local structures of node neighborhoods that demonstrates that in PPI networks, biological function of a node and its local network structure are closely related. The method summarizes a protein's local topology in a PPI network into the vector of graphlet degrees called the signature of the protein and computes the signature similarities between all protein pairs. We group topologically similar proteins under this measure in a PPI network and show that these protein groups belong to the same protein complexes, perform the same biological functions, are localized in the same subcellular compartments, and have the same tissue expressions. Moreover, we apply our technique on a proteome-scale network data and infer biological function of yet unclassified proteins demonstrating that our method can provide valuable guidelines for future experimental research such as disease protein prediction. Availability Data is available upon request.

A multifunctional substance P-conjugated chitosan hydrochloride hydrogel accelerates full-thickness wound healing by enhancing synchronized vascularization, extracellular matrix deposition, and nerve regeneration

2021 ◽  
Author(s):  
Hao Li ◽  
Mengna Li ◽  
Pei Liu ◽  
Kai-Yang Wang ◽  
Haoyu Fang ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Wound Healing ◽  
Full Thickness ◽  
Matrix Deposition ◽  
Chitosan Hydrochloride ◽  
Reconstructive Microsurgery ◽  
Extracellular Matrix Deposition ◽  
Advanced Biomaterials ◽  
Native Skin ◽  
Full Thickness Wound

Due to the native skin limitations and the complexity of reconstructive microsurgery, advanced biomaterials are urgently required to promote wound healing for severe skin defects caused by accidents and disasters....

scholarly journals Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Bioinformatics Analysis ◽  
Gene Expression Omnibus ◽  
Venn Diagram ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

Effect of Curculigo orchioides on Reflux Esophagitis by Suppressing Proinflammatory Cytokines

2012 ◽  
Vol 40 (06) ◽  
pp. 1241-1255 ◽  
Author(s):  
Sae-Kang Ku ◽  
Jae-Soo Kim ◽  
Young-Bae Seo ◽  
Yong-Ung Kim ◽  
Seung-Lark Hwang ◽  
...  
Keyword(s):  
Reflux Esophagitis ◽  
Group Treatment ◽  
Control Group ◽  
Esophageal Mucosa ◽  
Dependent Manner ◽  
Protective Effects ◽  
Model Group ◽  
Curculigo Orchioides ◽  
Intact Group ◽  
Tnf Α

This study was performed to investigate effects of Curculigo orchioides rhizome (curculiginis rhizome) on acute reflux esophigitis (RE) in rats that are induced by pylorus and forestomach ligation operation. Proinflammatory cytokine, as well as tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6 were all assayed and the expression of TNF-α and COX2 analyzed by RT-PCR. The esophagic tissue damage of reflux esophagitis rat was increased compared to that of normal intact group. However, the esophagic damage percentage from the extract of curculiginis rhizoma (ECR) 600 mg/kg and ECR 300 mg/kg were significantly lower than that of the RE control group. Administration of α-tocopherol (30 mg/kg) and ECR (600 mg/kg, 300 mg/kg, and 150 mg/kg) had a significant effect on the gastric acid pH in rats with induced reflux esophagitis (p < 0.05). The treatment with ECR significantly reduced the production of cytokines TNF-α, IL-1β and IL-6 levels compared to the model group (p < 0.05). The expression of TNF-α and COX2 in the intact esophageal mucosa was low while those of the RE control group were significantly higher due to an inflammatory reaction in the esophagus. Compare to the model group, treatment with α-tocopherol or ECR significantly inhibited the expression levels of COX2 and TNF-α in a dose-dependent manner. These results suggest that anti-inflammatory and protective effects of ECR could attenuate the severity of reflux esophagitis and prevent esophageal mucosal damage.

scholarly journals Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data

2009 ◽  
Vol 7 (44) ◽  
pp. 423-437 ◽  
Author(s):  
Tijana Milenković ◽  
Vesna Memišević ◽  
Anand K. Ganesan ◽  
Nataša Pržulj
Keyword(s):  
Protein Interaction ◽  
Network Topology ◽  
Interaction Network ◽  
Biological Processes ◽  
Cancer Gene ◽  
Cancer Genes ◽  
Clustering Methods ◽  
Ppi Network ◽  
Graph Theoretic ◽  
Ppi Networks

Many real-world phenomena have been described in terms of large networks. Networks have been invaluable models for the understanding of biological systems. Since proteins carry out most biological processes, we focus on analysing protein–protein interaction (PPI) networks. Proteins interact to perform a function. Thus, PPI networks reflect the interconnected nature of biological processes and analysing their structural properties could provide insights into biological function and disease. We have already demonstrated, by using a sensitive graph theoretic method for comparing topologies of node neighbourhoods called ‘graphlet degree signatures’, that proteins with similar surroundings in PPI networks tend to perform the same functions. Here, we explore whether the involvement of genes in cancer suggests the similarity of their topological ‘signatures’ as well. By applying a series of clustering methods to proteins' topological signature similarities, we demonstrate that the obtained clusters are significantly enriched with cancer genes. We apply this methodology to identify novel cancer gene candidates, validating 80 per cent of our predictions in the literature. We also validate predictions biologically by identifying cancer-related negative regulators of melanogenesis identified in our siRNA screen. This is encouraging, since we have done this solely from PPI network topology. We provide clear evidence that PPI network structure around cancer genes is different from the structure around non-cancer genes. Understanding the underlying principles of this phenomenon is an open question, with a potential for increasing our understanding of complex diseases.

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