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      Network Pharmacology-Based Identification of the Mechanisms of Shen-Qi Compound Formula in Treating Diabetes Mellitus

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          Abstract

          Aim

          The purpose of this research is to identify the mechanisms of Shen-Qi compound formula (SQC), a traditional Chinese medicine (TCM), for treating diabetes mellitus (DM) using system pharmacology.

          Methods

          The active components and therapeutic targets were identified, and these targets were analyzed using gene ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) analysis. Finally, an integrated pathway was constructed to show the mechanisms of SQC.

          Results

          A total of 282 active components and 195 targets were identified through a database search. The component-target network was constructed, and the key components were screened out according to their degree. Through the GO, PPI, and KEGG analyses, the mechanism network of SQC treating DM was constructed.

          Conclusions

          This study shows that the mechanisms of SQC treating DM are related to various pathways and targets. This study provides a good foundation and basis for further in-depth verification and clinical application.

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          Most cited references95

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          Gene Ontology: tool for the unification of biology

          Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)
          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            GeneCards: integrating information about genes, proteins and diseases.

            M Rebhan (1997)
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              SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping

              Yang Ping Wu, Feilong Zhang, Kuo Yang … (2018)
              Abstract Recently, the pharmaceutical industry has heavily emphasized phenotypic drug discovery (PDD), which relies primarily on knowledge about phenotype changes associated with diseases. Traditional Chinese medicine (TCM) provides a massive amount of information on natural products and the clinical symptoms they are used to treat, which are the observable disease phenotypes that are crucial for clinical diagnosis and treatment. Curating knowledge of TCM symptoms and their relationships to herbs and diseases will provide both candidate leads and screening directions for evidence-based PDD programs. Therefore, we present SymMap, an integrative database of traditional Chinese medicine enhanced by sym ptom map ping. We manually curated 1717 TCM symptoms and related them to 499 herbs and 961 symptoms used in modern medicine based on a committee of 17 leading experts practicing TCM. Next, we collected 5235 diseases associated with these symptoms, 19 595 herbal constituents (ingredients) and 4302 target genes, and built a large heterogeneous network containing all of these components. Thus, SymMap integrates TCM with modern medicine in common aspects at both the phenotypic and molecular levels. Furthermore, we inferred all pairwise relationships among SymMap components using statistical tests to give pharmaceutical scientists the ability to rank and filter promising results to guide drug discovery. The SymMap database can be accessed at http://www.symmap.org/ and https://www.bioinfo.org/symmap.
              Article 0 comments Cited 214 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Chunguang Xie:
                ORCID: https://orcid.org/0000-0001-9120-8605
                Journal
                Journal ID (nlm-ta): Evid Based Complement Alternat Med
                Journal ID (iso-abbrev): Evid Based Complement Alternat Med
                Journal ID (publisher-id): ECAM
                Title: Evidence-based Complementary and Alternative Medicine : eCAM
                Publisher: Hindawi
                ISSN (Print): 1741-427X
                ISSN (Electronic): 1741-4288
                Publication date Collection: 2020
                Publication date (Electronic): 4 June 2020
                Publication date PMC-release: 4 June 2020
                Volume: 2020
                Electronic Location Identifier: 5798764
                Affiliations
                1Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610072, China
                2Department of Gastroenterology, Tongde Hospital of Zhejiang Province, Hangzhou 310012, China
                Author notes

                Academic Editor: XiuMin Li

                Author information
                https://orcid.org/0000-0003-1524-6452
                https://orcid.org/0000-0003-3164-8312
                https://orcid.org/0000-0001-9120-8605
                Article
                DOI: 10.1155/2020/5798764
                PMC ID: 7292981
                SO-VID: 608f1389-a65f-4cde-a704-5099e5e21823
                Copyright © Copyright © 2020 Zhipeng Hu et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 21 October 2019
                Date revision received : 20 February 2020
                Date accepted : 9 April 2020
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 81774302
                Award ID: 81703953
                Funded by: Department of Science and Technology of Sichuan Province
                Award ID: 2019YFS0022
                Categories
                Subject: Research Article

                ScienceOpen disciplines: Complementary & Alternative medicine
                Data availability:
                ScienceOpen disciplines: Complementary & Alternative medicine

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