Analysis of mulberry leaf components in the treatment of diabetes using network pharmacology

Ge, Qi; Chen, Liang; Tang, Min; Zhang, Shu; Liu, Lanlan; Gao, Lu; Ma, Shangshang; Kong, Ming; Yao, Qin; Feng, Fan; Chen, Keping

doi:10.1016/j.ejphar.2018.05.021

Cited by 104 publications

(72 citation statements)

References 35 publications

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“…In addition, these inflammatory cells and cytokines secreted by them can stimulate and activate kidney cells, regulating the expression of chemokines, cytokines, adhesion molecules, and extracellular matrix components, and aggravate the pathological changes of kidney tissue. TNF-α, one of the main regulatory factors, which can induce the production of IL-1β, IL-6, and other cytokines, participates in the process of oxidative stress and inflammation and aggravation of renal tissue damage [36]. IL-6, as an autocrine growth factor of mesangial cells, can significantly stimulate mesangial proliferation.…”

Section: Journal Of Diabetes Researchmentioning

confidence: 99%

Uncovering the Mechanism of Astragalus membranaceus in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Guo

Dai

Gao

et al. 2020

Journal of Diabetes Research

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Background. Diabetic nephropathy (DN), characterized by hyperglycemia, hypertension, proteinuria, and edema, is a unique microvascular complication of diabetes. Traditional Chinese medicine (TCM) Astragalus membranaceus (AM) has been widely used for DN in China while the pharmacological mechanisms are still unclear. This work is aimed at undertaking a network pharmacology analysis to reveal the mechanism of the effects of AM in DN. Materials and Methods. In this study, chemical constituents of AM were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the potential targets of AM were identified using the Therapeutic Target Database (TTD). DisGeNET and GeneCards databases were used to collect DN-related target genes. DN-AM common target protein interaction network was established by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to further explore the DN mechanism and therapeutic effect of AM. The network diagrams of the active component-action target and protein-protein interaction (PPI) networks were constructed using Cytoscape software. Results. A total of 16 active ingredients contained and 78 putative identified target genes were screened from AM, of which 42 overlapped with the targets of DN and were considered potential therapeutic targets. The analysis of the network results showed that the AM activity of component quercetin, formononetin, calycosin, 7-O-methylisomucronulatol, and quercetin have a good binding activity with top ten screened targets, such as VEGFA, TNF, IL-6, MAPK, CCL3, NOS3, PTGS2, IL-1β, JUN, and EGFR. GO and KEGG analyses revealed that these targets were associated with inflammatory response, angiogenesis, oxidative stress reaction, rheumatoid arthritis, and other biological process. Conclusions. This study demonstrated the multicomponent, multitarget, and multichannel characteristics of AM, which provided a novel approach for further research of the mechanism of AM in the treatment of DN.

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Section: Journal Of Diabetes Researchmentioning

confidence: 99%

Uncovering the Mechanism of Astragalus membranaceus in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Guo

Dai

Gao

et al. 2020

Journal of Diabetes Research

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“…Considering adverse effects of drugs, natural products from traditional Chinese medicine like Mulberry leaves have been drawn extensive attentions on preventive and therapeutic interventions for DM (Yan et al, 2016 ). Using network pharmacological analysis, Ge et al found that components of mulberry leaves can relieve the symptoms of diabetes through the action of target proteins in various metabolic pathways (Ge et al, 2018 ). However, the active compound with hypoglycemic activity of mulberry leaves are still unknown.…”

Section: Discussionmentioning

confidence: 99%

Mulberry Leaf Regulates Differentially Expressed Genes in Diabetic Mice Liver Based on RNA-Seq Analysis

Zhang

Chen

et al. 2018

Front. Physiol.

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The pathogenesis of diabetes mellitus is a complicated process involving much gene regulation. The molecular mechanism of mulberry (Morus alba L.) leaf in the treatment of diabetes is not fully understood. In this study, we used the Illumina HiSeq™ 2,500 platform to explore the liver transcriptome of normal mice, STZ-induced diabetic mice, and mulberry leaf-treated diabetic mice, and we obtained 52,542,956, 52,626,414, and 52,780,196 clean reads, respectively. We identified differentially expressed genes (DEGs) during the pathogenesis of diabetes in mice. The functional properties of DEGs were characterized by comparison with the GO and KEGG databases, and the results show that DEGs are mainly involved in the metabolic pathway. qRT-PCR was used to analyse 27 differential genes involved in liver expression in different groups of diabetic mice. Among the DEGs, the expression of Scube1, Spns3, Ly6a, Igf2, and other genes between the control (C) and diabetic control (DC) groups was significantly upregulated; the expression of Grb10, Mup2, and Fasn was significantly downregulated; the expression of the Sqle, Lss, and Irs2 genes between the C group and diabetic group treated with mulberry (DD) was significantly upregulated; the expression of Fabp2, Ly6a, and Grb10 was significantly downregulated; and the expression of Sqle and Lss was significantly upregulated in the DC and DD groups, but Tap1, Igf2, and Spns3 were significantly downregulated. The results of Western blot validation showed that dynamic changes in proteins, such as IGF2, Ly6a, Grb10, and UBD, occurred to regulate the incidence of diabetes by influencing the insulin receptor substrate (IRS) signaling pathway.

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“…However, it is difficult to elucidate the bioactivities of these natural extracts due to the complexity of the molecules and the possibility of interaction between the molecules. The high-throughput, large-scale and parallelism of gene expression microarray technology make it possible to be widely used in drug screening, especially in identifying the authenticity of traditional Chinese medicine (TCM) formulae, screening of effective ingredients, pharmacological mechanism research, and chemical drug synthesis (Gu and Chen, 2014;Ge et al, 2018a;Ge et al, 2018b). Moreover, the employment of microarray gene expression for large-scale screening in cell lines can shorten the screening time, determine the drug targets, and check the toxicity or side effects of drugs (Liu et al, 2015;Carrella et al, 2016;Hong et al, 2018;Rodrigues et al, 2019;Wang et al, 2019b).…”

Section: Microarray In Traditional Medicine Researchmentioning

confidence: 99%

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

et al. 2020

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The development of new drugs is multidisciplinary and systematic work. High-throughput techniques based on "-omics" have driven the discovery of biomarkers in diseases and therapeutic targets of drugs. A transcriptome is the complete set of all RNAs transcribed by certain tissues or cells at a specific stage of development or physiological condition. Transcriptome research can demonstrate gene functions and structures from the whole level and reveal the molecular mechanism of specific biological processes in diseases. Currently, gene expression microarray and high-throughput RNA-sequencing have been widely used in biological, medical, clinical, and drug research. The former has been applied in drug screening and biomarker detection of drugs due to its high throughput, fast detection speed, simple analysis, and relatively low price. With the further development of detection technology and the improvement of analytical methods, the detection flux of RNAseq is much higher but the price is lower, hence it has powerful advantages in detecting biomarkers and drug discovery. Compared with the traditional RNA-seq, scRNA-seq has higher accuracy and efficiency, especially the single-cell level of gene expression pattern analysis can provide more information for drug and biomarker discovery. Therefore, (sc) RNA-seq has broader application prospects, especially in the field of drug discovery. In this overview, we will review the application of these technologies in drug, especially in natural drug and biomarker discovery and development. Emerging applications of scRNA-seq and the third generation RNA-sequencing tools are also discussed.

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Analysis of mulberry leaf components in the treatment of diabetes using network pharmacology

Cited by 104 publications

References 35 publications

Uncovering the Mechanism of Astragalus membranaceus in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Uncovering the Mechanism of Astragalus membranaceus in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Mulberry Leaf Regulates Differentially Expressed Genes in Diabetic Mice Liver Based on RNA-Seq Analysis

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

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