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      Drug Design, Development and Therapy (submit here)

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      Network Pharmacology Analysis of Hewei Jiangni Granule for Gastroesophageal Reflux Disease and Experimental Verification of Its Anti-Neurogenic Inflammation Mechanism


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          Proton pump inhibitors, as the first-line drugs for treating gastroesophageal reflux disease (GERD), are unable to completely relieve patients’ symptoms and patients are prone to recurrence after prolonged drug withdrawal. Thus, it is crucial to find herbal medicines as a complementary and alternative treatment. Hewei Jiangni granule (HWJNG) is a classical Chinese medicinal formula with clinical therapeutic effects on GERD, but its pharmacological mechanism of action remains unclear. This study aimed to explore and then verify the pharmacological mechanisms of HWJNG in GERD therapy.


          A network pharmacology approach was applied to explore and then verify the pharmacological mechanisms of HWJNG in GERD therapy. The active ingredients of HWJNG, as well as therapeutic targets of GERD were acquired from specialized databases. The “herb-ingredient-gene-target” network for HWJNG in GERD treatment was built. The protein–protein interaction (PPI) network was constructed to screen the core coincident targets. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The core targets and signaling pathways associated with the anti-neurogenic inflammatory effect were partially verified via experiments in vivo at molecular level.


          In total, 179 chemical ingredients in HWJNG and 298 intersection targets between GERD and HWJNG were selected from databases. A large proportion of core targets and top signaling pathways were involved in neurogenic inflammation. HWJNG significantly alleviated pathological injuries of esophagus and reversed dilated intracellular spaces. Additionally, HWJNG markedly inhibited the excessive release of inflammatory cytokines such as interleukin (IL)-1β, IL-6, tumor necrosis factor receptor (TNF-a), as well as regulated stimulation sensors including transient receptor potential vanilloid type 1 (TRPV1) and its related neuroinflammatory mediators in GERD mice.


          HWJNG is a promising therapeutic strategy for GERD treatment via regulation of multiple targets and pathways, its effects in alleviating neurogenic inflammation are especially acknowledged.

          Most cited references47

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          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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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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              TCMSP: a database of systems pharmacology for drug discovery from herbal medicines

              Background Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. Description The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski’s rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. Conclusions The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                05 May 2022
                : 16
                : 1349-1363
                [1 ]Second Clinical Medical College, Beijing University of Chinese Medicine , Beijing, People’s Republic of China
                [2 ]Department of Gastroenterology, Dongfang Hospital, Beijing University of Chinese Medicine , Beijing, People’s Republic of China
                [3 ]Department of Pharmacotherapy and Oriental Medicine, School of Pharmacy, Hyogo University of Health Sciences , Hyogo, Japan
                Author notes
                Correspondence: Junxiang Li; Xiaohong Li, Department of Gastroenterology, Dongfang Hospital, Beijing University of Chinese Medicine , No. 6, 1st Section Fangxingyuan, Fangzhuang, Fengtai District, Beijing, 100078, People’s Republic of China, Email junxiangli1226@126.com; lxhktxz@163.com

                These authors contributed equally to this work

                Author information
                © 2022 Cheng 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).

                : 25 November 2021
                : 27 April 2022
                Page count
                Figures: 7, Tables: 2, References: 47, Pages: 15
                Funded by: National Natural Science Foundation of China, open-funder-registry 10.13039/501100001809;
                Funded by: Key Projects of Beijing University of Traditional Chinese Medicine;
                Funded by: Beijing Science and Technology Program Project-Capital characteristics Project;
                This work was supported by National Natural Science Foundation of China (81803907); Key Projects of Beijing University of Traditional Chinese Medicine (No. 2020-JYB-ZDGG-128) and Beijing Science and Technology Program Project-Capital characteristics Project (Z181100001718067).
                Original Research

                Pharmacology & Pharmaceutical medicine
                hewei jiangni granule,gastroesophageal reflux disease,network pharmacology,neurogenic inflammation


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