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      Network Pharmacology Analysis of ZiShenWan for Diabetic Nephropathy and Experimental Verification of Its Anti-Inflammatory Mechanism

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          Diabetic nephropathy (DN) is the leading cause of end-stage renal disease (ESRD). The inflammatory response plays a critical role in DN. ZiShenWan (ZSW) is a classical Chinese medicinal formula with remarkable clinical therapeutic effects on DN, but its pharmacological action mechanisms remain unclear.


          In this study, a network pharmacology approach was applied to investigate the pharmacological mechanisms of ZSW in DN therapy. Based on the results of network analysis, the core targets and signaling pathways related to anti-inflammatory effect were verified via experiments in vivo.


          The candidate chemical ingredients of ZSW as well as its putative targets and known therapeutic targets of DN were acquired from appropriate databases. The “herb-ingredient-target” network for ZSW in DN treatment was established. The protein–protein interaction (PPI) network of potential targets was constructed to screen the core targets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. In addition to biochemical and pathological indicators, the core targets and signaling pathways associated with inflammation were partially validated in db/db mice at molecular level.


          A total of 56 active ingredients in ZSW and 166 DN-related targets were selected from databases. A high proportion of core targets and top signaling pathways participate in inflammation. ZSW markedly alleviated renal injuries pathologically and regulated related biomarkers. In particular, ZSW significantly inhibited the exaggerated release of inflammatory cytokines such as interleukin (IL)-1β, IL-6, tumor necrosis factor receptor (TNF)-ɑ, and monocyte chemotactic protein (MCP)-1 as well as regulating p38 mitogen-activated protein kinases (MAPK) and phosphoinositide 3-kinase (PI3K)–protein kinase B (Akt) signaling pathways in db/db mice.


          This study first comprehensively investigated the active ingredients, potential targets, and molecular mechanism of ZSW as a therapy for DN. ZSW achieved renoprotective effects in DN via regulation of multiple targets and signaling pathways, especially by alleviating inflammation. Results indicate that ZSW is a promising multi-target therapeutic approach for DN treatment.

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          Most cited references 57

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Is Open Access

            DrugBank 5.0: a major update to the DrugBank database for 2018

            Abstract DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year’s update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education.
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              The genetic association database.

               S Wang,  K Barnes,  K. Becker (2004)

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                15 April 2021
                : 15
                : 1577-1594
                [1 ]Department of Nephrology, Dong Fang Hospital, Beijing University of Chinese Medicine , Beijing, 100078, People’s Republic of China
                [2 ]Second Clinical Medical College, Beijing University of Chinese Medicine , Beijing, 100078, People’s Republic of China
                [3 ]Key Laboratory of Health Cultivation of the Ministry of Education, Beijing University of Chinese Medicine , Beijing, 100029, People’s Republic of China
                [4 ]Technology Department, Beijing University of Chinese Medicine , Beijing, 100029, People’s Republic of China
                Author notes
                Correspondence: Tonghua Liu Key Laboratory of Health Cultivation of the Ministry of Education, Beijing University of Chinese Medicine , 11 Bei San Huan Dong Lu, Chaoyang, Beijing, 100029, People’s Republic of ChinaTel +8601064286426Fax +8601064213817 Email thliu@vip.163.com
                © 2021 Guo et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 11, Tables: 7, References: 58, Pages: 18
                Original Research


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