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      A Network Pharmacology Approach to Investigate the Active Compounds and Mechanisms of Musk for Ischemic Stroke

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          Abstract

          Objectives

          This study aims to study the material basis and effective mechanism of musk for ischemic stroke (IS) based on the network pharmacology approach.

          Methods

          We collected the chemical components and target gene of musk from the BATMAN-TCM analytical platform and identified ischemic stroke-related targets from the following databases: DisGeNET, NCBI-Gene, HPO, OMIM, DrugBank, and TTD. The targets of musk and IS were uploaded to the String database to construct the protein-protein interaction (PPI) network, and then, the key targets were analyzed by topological methods. At last, the function biological process and signaling pathways of key targets were carried out by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and cluster analysis by using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server and Metascape platform.

          Results

          A total of 29 active compounds involving 1081 predicted targets were identified in musk and there were 1104 IS-related targets. And 88 key targets of musk for IS were obtained including AKT1, MAPK1/3, TP53, TNF, SRC, FOS, CASP3, JUN, NOS3, and IL1B. The GO and KEGG enrichment analysis suggested that these key targets are mainly involved in multiple pathways which participated in TNF signaling pathway, estrogen signaling pathway, prolactin signaling pathway, neurotrophin signaling pathway, T-cell receptor signaling pathway, cAMP signaling pathway, FoxO signaling pathway, and HIF1 signaling pathway.

          Conclusion

          This study revealed that the effective mechanisms of musk against IS would be associated with the regulation of apoptosis, inflammatory response, and gene transcription.

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          Most cited references52

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          Gene Ontology: tool for the unification of biology

          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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            DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

            The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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              Network pharmacology.

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                Author and article information

                Contributors
                Journal
                Evid Based Complement Alternat Med
                Evid Based Complement Alternat Med
                ECAM
                Evidence-based Complementary and Alternative Medicine : eCAM
                Hindawi
                1741-427X
                1741-4288
                2020
                3 July 2020
                3 July 2020
                : 2020
                : 4063180
                Affiliations
                1The Second Clinical School, Guangzhou University of Chinese Medicine, Guangzhou, China
                2The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
                3State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
                4Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
                Author notes

                Academic Editor: Manel Santafe

                Author information
                https://orcid.org/0000-0001-6289-2639
                https://orcid.org/0000-0003-1254-6732
                Article
                10.1155/2020/4063180
                7354650
                32714405
                f5fa2265-d551-496a-9bf5-b7f394575f55
                Copyright © 2020 Changlin Zhang et al.

                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
                : 17 March 2020
                : 14 May 2020
                : 10 June 2020
                Funding
                Funded by: Guangzhou Basic Research Plan of the People's Livelihood Science and Technology
                Award ID: 18
                Funded by: Guangdong Provincial Hospital of Traditional Chinese Medicine
                Award ID: YN2019MJ07
                Funded by: State Key Laboratory of Dampness Syndrome of Chinese Medicine
                Award ID: [2020] No. 20
                Funded by: Special Project of Guangdong Province Key Laboratory of TCM Emergency Research
                Award ID: [2017] No. 83
                Categories
                Research Article

                Complementary & Alternative medicine
                Complementary & Alternative medicine

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