Network Pharmacology: Prediction of Astragalus Membranaceus’ and Cornus Officinalis’ Active Ingredients and Potential Targets to Diabetic Nephropathy

Background. Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus and is a major cause of end-stage kidney disease. Cordyceps sinensis (Cordyceps, Dong Chong Xia Cao) is a widely applied ingredient for treating patients with DN in China, while the molecular mechanisms remain unclear. This study is aimed at revealing the therapeutic mechanisms of Cordyceps in DN by undertaking a network pharmacology analysis. Materials and Methods. In this study, active ingredients and associated target proteins of Cordyceps sinensis were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Swiss Target Prediction platform, then reconfirmed by using PubChem databases. The collection of DN-related target genes was based on DisGeNET and GeneCards databases. A DN-Cordyceps common target interaction network was carried out via the STRING database, and the results were integrated and visualized by utilizing Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to determine the molecular mechanisms and therapeutic effects of Cordyceps on the treatment of DN. Results. Seven active ingredients were screened from Cordyceps, 293 putative target genes were identified, and 85 overlapping targets matched with DN were considered potential therapeutic targets, such as TNF, MAPK1, EGFR, ACE, and CASP3. The results of GO and KEGG analyses revealed that hub targets mainly participated in the AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, PI3K-Akt signaling pathway, and IL-17 signaling pathway. These targets were correlated with inflammatory response, apoptosis, oxidative stress, insulin resistance, and other biological processes. Conclusions. Our study showed that Cordyceps is characterized as multicomponent, multitarget, and multichannel. Cordyceps may play a crucial role in the treatment of DN by targeting TNF, MAPK1, EGFR, ACE, and CASP3 signaling and involved in the inflammatory response, apoptosis, oxidative stress, and insulin resistance.

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

Journal of Diabetes Research ◽

10.1155/2020/5947304 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 3

Author(s):

Ming-Fei Guo ◽

Ya-Ji Dai ◽

Jia-Rong Gao ◽

Pei-Jie Chen

Keyword(s):

Diabetic Nephropathy ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Protein Interaction ◽

Target Genes ◽

Chemical Constituents ◽

Interaction Network ◽

Astragalus Membranaceus ◽

Network Pharmacology ◽

Ppi Networks

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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Based on Network Pharmacology and Molecular Docking to Explore the Underlying Mechanism of Huangqi Gegen Decoction for Treating Diabetic Nephropathy

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/9928282 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Shanshan Ding ◽

Weihao Wang ◽

Xujiao Song ◽

Hao Ma

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Target Genes ◽

Chinese Herb ◽

Underlying Mechanism ◽

Binding Activity ◽

Network Pharmacology ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Core Components

Background. Huangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Therefore, the present study aims to explore the underlying mechanism of HGD for treating diabetic nephropathy (DN). Materials and Methods. Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), UniProt, and SwissTargetPrediction databases were used to search the active ingredients and potential targets of HGD. In addition, multiple disease-related databases were used to collect DN-related targets. Common targets of the protein-protein interaction (PPI) network were established using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. At last, AutoDockVina was used to conduct molecular docking verification for the core components and targets. Results. A total of 27 active ingredients and 354 putative identified target genes were screened from HGD, of which 99 overlapped with the targets of DN and were considered potential therapeutic targets. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, thus delaying the development of DN. The molecular docking results showed that quercetin, formononetin, kaempferol, isorhamnetin, beta-sitosterol had a good binding activity with VEGFA, IL6, TNF, AKT1, and TP53. Conclusion. This study demonstrated that HGD might take part in the treatment of DN through multicomponent, multitarget, and multichannel combined action.

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Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-85980/v1 ◽

2020 ◽

Author(s):

Li-Li Zhang ◽

Lin Han ◽

Xin-Miao Wang ◽

Yu Wei ◽

Jing-Hui Zheng ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Therapeutic Effect ◽

Molecular Mechanisms ◽

Function Analysis ◽

Salvia Miltiorrhiza ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

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Study of the Active Components and Molecular Mechanism of Tripterygium wilfordii in the Treatment of Diabetic Nephropathy

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.664416 ◽

2021 ◽

Vol 8 ◽

Author(s):

Lin Wang ◽

Zheyi Wang ◽

Zhihua Yang ◽

Kang Yang ◽

Hongtao Yang

Keyword(s):

Insulin Resistance ◽

Diabetic Nephropathy ◽

Molecular Mechanism ◽

Biological Process ◽

Venn Diagram ◽

Endothelial Cell Proliferation ◽

Network Pharmacology ◽

Tripterygium Wilfordii ◽

Active Ingredients ◽

Network Diagram

We aimed to explore the active ingredients and molecular mechanism of Tripterygium wilfordii (TW) in the treatment of diabetic nephropathy (DN) through network pharmacology and molecular biology. First, the active ingredients and potential targets of TW were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature materials, and Cytoscape 3.7.2 software was used to construct the active ingredient-target network diagram of TW. Second, the target set of DN was obtained through the disease database, and the potential targets of TW in the treatment of DN were screened through a Venn diagram. A protein interaction network diagram (PPI) was constructed with the help of the String platform and Cytoscape 3.7.2. Third, the ClueGO plug-in tool was used to enrich the GO biological process and the KEGG metabolic pathway. Finally, molecular docking experiments and cell pathway analyses were performed. As a result, a total of 52 active ingredients of TW were screened, and 141 predicted targets and 49 target genes related to DN were identified. The biological process of GO is mediated mainly through the regulation of oxygen metabolism, endothelial cell proliferation, acute inflammation, apoptotic signal transduction pathway, fibroblast proliferation, positive regulation of cyclase activity, adipocyte differentiation and other biological processes. KEGG enrichment analysis showed that the main pathways involved were AGE-RAGE, vascular endothelial growth factor, HIF-1, IL-17, relaxin signalling pathway, TNF, Fc epsilon RI, insulin resistance and other signaling pathways. It can be concluded that TW may treat DN by reducing inflammation, reducing antioxidative stress, regulating immunity, improving vascular disease, reducing insulin resistance, delaying renal fibrosis, repairing podocytes, and reducing cell apoptosis, among others, with multicomponent, multitarget and multisystem characteristics.

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Exploring the mechanisms underlying the therapeutic effect of Salvia miltiorrhiza on diabetic nephropathy using network pharmacology and molecular docking

Bioscience Reports ◽

10.1042/bsr20203520 ◽

2021 ◽

Author(s):

Lili Zhang ◽

Lin Han ◽

Xinmiao Wang ◽

Yu Wei ◽

Jinghui Zheng ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Therapeutic Effect ◽

Function Analysis ◽

Salvia Miltiorrhiza ◽

Tanshinone Iia ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Active Ingredients

The mechanisms underlying the therapeutic effect of Salvia miltiorrhiza (SM) on diabetic nephropathy (DN) were examined using a systematic network pharmacology approach and molecular docking. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to screen active ingredients of SM. Targets were obtained using the SwissTargetPrediction and TCMSP databases. Proteins related to DN were retrieved from the GeneCards and DisGeNET databases. A protein–protein interaction (PPI) network was constructed using common SM/DN targets in the STRING database. The Metascape platform was used for GO function analysis, and the Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for network mapping. Sixty-six active ingredients and 189 targets of SM were found. Sixty-four targets overlapped with DN-related proteins. The PPI network revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the 10 most relevant targets. Go and KEGG analyses revealed that the common targets of DN and SM were mainly involved in advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that potential DN-related targets, includingTNF, NOS2, and AKT1, more stably bound with salvianolic acid B than with tanshinone IIA. In conclusion, this study revealed the active components and potential molecular therapeutic mechanisms of SM in DN and provides a reference for the wide application of SM in clinically managing DN.

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Network Pharmacology-Based Analysis on the Mechanism of Drug Pair of Astragalus Membranaceus and Acorus Tatarinowii in the Treatment of Alzheimer’s Disease

10.3233/atde210250 ◽

2021 ◽

Author(s):

Xiuting Huang ◽

Xiujin Zhang ◽

Xiangning Li ◽

Haozhen Wang ◽

Chen Lu ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Enrichment Analysis ◽

Astragalus Membranaceus ◽

Network Pharmacology ◽

Active Ingredients ◽

Drug Pair ◽

Target Proteins ◽

High Position ◽

Acorus Tatarinowii

Alzheimer’s disease (AD) is a degenerative disease of central nervous system, which seriously threatens the life and health of the elderly people. It has been for long time that Traditional Chinese medicine (TCM) treatment for AD is effective. This study analyzed the potential target and molecular mechanism of the most often used drug pair of Astragalus membranaceus and Acorus tatarinowii to treat AD by network pharmacological method. Firstly, the method was performed to screen and sort out the active ingredients with good ADME properties and drug targets of Astragalus membranaceus and Acorus tatarinowii. Then, we searched for the disease targets related to AD, followed by the construction of the “active ingredients-target-disease” network. We implemented GO enrichment analysis and KEGG pathway enrichment analysis of related overlapped target proteins, and then constructed the “target-pathway” network diagram. Finally, the above overlapped target proteins are mapped to build a PPI high-position protein interoperability network, and we conducted the network topology analysis to screen out the core targets of Astragalus membranaceus-Acorus tatarinowii drug pair in the treatment of AD. According to network pharmacology, this research predicted the potential targets of the drug pair of Astragalus membranaceus and Acorus tatarinowii in the treatment of AD, and explored that Astragalus membranaceus-Acorus tatarinowii drug pair in the treatment of AD was the overall systematic regulating action of “multiple-ingredients, multiple-target and multiple-pathway”. It affords the reference for understanding the pathogenesis of AD and exploring new therapeutic methods and drug development in the future.

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Research on the Potential Mechanism of Chuanxiong Rhizoma on Treating Diabetic Nephropathy Based on Network Pharmacology

10.21203/rs.3.rs-18492/v1 ◽

2020 ◽

Author(s):

Shanshan Hu ◽

Siteng Chen ◽

Zhilei Li ◽

Yuhang Wang ◽

Yong Wang

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Genomic Analysis ◽

Interaction Network ◽

Network Pharmacology ◽

Active Ingredients ◽

Docking Analysis ◽

Kegg Pathways ◽

Binding Forces ◽

Analysis Platform

Abstract Background: Chuanxiong Rhizoma is one of the traditional Chinese medicines which have been used for years in the treatment of diabetic nephropathy (DN). However, the mechanism of Chuanxiong Rhizoma in DN has not yet been fully understood. Methods: We performed network pharmacology to construct targeted proteins interaction network of Chuanxiong Rhizoma. Active ingredients were acquired from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. DRUGBANK database was used to predict targeted proteins of Chuanxiong Rhizoma. Gene ontology (GO) biological process analyses and KEGG pathway enrichment analyses were also performed for functional prediction of the targeted proteins. Molecular docking was applied for evaluating the drug interactions between hub targets and active ingredients. Results: Twenty-eight targets fished by 6 active ingredients of Chuanxiong Rhizoma were obtained in the study. The top 10 significant GO analyses, as well as 6 KEGG pathways, were enriched for genomic analysis. We also acquired 1366 differentially expressed genes associated with DN from GSE30528 dataset, including five targeted genes: KCNH2, NCOA1, KDR, NR3C2 and ADRB2. Molecular docking analysis successfully combined KCNH2, NCOA1, KDR and ADRB2 to Myricanone with docking scores from 4.61 to 6.28. NR3C2 also displayed good binding forces (8.13 and 8.34) with Wallichilide and Sitosterol, revealing good binding forces to active compounds of Chuanxiong Rhizoma. Conclusions: Chuanxiong Rhizoma might take part in the treatment of DN through pathways associated with steroid hormone, estrogen, thyroid hormone and IL-17. KCNH2, NCOA1, KDR, ADRB2 and NR3C2 were proved to be the hub targets closely related to corresponding active ingredients of Chuanxiong Rhizoma.

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Network pharmacology combined with metabolomics to study the mechanism of Shenyan Kangfu Tablets in the treatment of diabetic nephropathy

Journal of Ethnopharmacology ◽

10.1016/j.jep.2021.113817 ◽

2021 ◽

Vol 270 ◽

pp. 113817

Author(s):

Xiaoli Wang ◽

Qiaoyu He ◽

Qian Chen ◽

Beibei Xue ◽

Jia Wang ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Network Pharmacology

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Network pharmacology and molecular docking study on the active ingredients of qidengmingmu capsule for the treatment of diabetic retinopathy

Scientific Reports ◽

10.1038/s41598-021-86914-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mingxu Zhang ◽

Jiawei Yang ◽

Xiulan Zhao ◽

Ying Zhao ◽

Siquan Zhu

Keyword(s):

Diabetic Retinopathy ◽

Molecular Docking ◽

Molecular Mechanisms ◽

Hypoxia Inducible Factor ◽

Enrichment Analysis ◽

Docking Study ◽

Network Pharmacology ◽

Biological Processes ◽

Active Ingredients ◽

Molecular Docking Study

AbstractDiabetic retinopathy (DR) is a leading cause of irreversible blindness globally. Qidengmingmu Capsule (QC) is a Chinese patent medicine used to treat DR, but the molecular mechanism of the treatment remains unknown. In this study, we identified and validated potential molecular mechanisms involved in the treatment of DR with QC via network pharmacology and molecular docking methods. The results of Ingredient-DR Target Network showed that 134 common targets and 20 active ingredients of QC were involved. According to the results of enrichment analysis, 2307 biological processes and 40 pathways were related to the treatment effects. Most of these processes and pathways were important for cell survival and were associated with many key factors in DR, such as vascular endothelial growth factor-A (VEGFA), hypoxia-inducible factor-1A (HIF-1Α), and tumor necrosis factor-α (TNFα). Based on the results of the PPI network and KEGG enrichment analyses, we selected AKT1, HIF-1α, VEGFA, TNFα and their corresponding active ingredients for molecular docking. According to the molecular docking results, several key targets of DR (including AKT1, HIF-1α, VEGFA, and TNFα) can form stable bonds with the corresponding active ingredients of QC. In conclusion, through network pharmacology methods, we found that potential biological mechanisms involved in the alleviation of DR by QC are related to multiple biological processes and signaling pathways. The molecular docking results also provide us with sound directions for further experiments.

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