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      Network pharmacology and in vitro experimental verification to explore the mechanism of Sanhua decoction in the treatment of ischaemic stroke

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          Abstract

          Context

          Stroke is an illness with high morbidity, disability and mortality that presents a major clinical challenge. Sanhua decoction (SHD) has been widely used to treat ischaemic stroke in the clinic. However, the potential mechanism of SHD remains unknown.

          Objective

          To elucidate the multitarget mechanism of SHD in ischaemic stroke through network pharmacology and bioinformatics analyses.

          Materials and methods

          Network pharmacology and experimental validation approach was used to investigate the bioactive ingredients, critical targets and potential mechanisms of SHD against ischaemic stroke. Four herbal names of SHD, ‘ischemic stroke’ or ‘stroke’ was used as a keyword to search the relevant databases. SH-SY5Y cells were treated with various concentrations of SHD (12.5, 25, 50 or 100 μg/mL) for 4 h, exposed to oxygen and glucose deprivation (OGD) for 1 h, then reoxygenation for 24 h. The cell viability was detected by MTT, the lactate dehydrogenase (LDH) was evaluated by ELISA, and protein expression was detected by western blots.

          Results

          SHD treatment increased the survival rate from 65.9 ± 4.3 to 85.56 ± 5.7%. The median effective dose (ED 50) was 47.1 μg/mL, the LDH decreased from 288.0 ± 12.0 to 122.8 ± 9.1 U/L and the cell apoptosis rate decreased from 33.6 ± 1.8 to 16.3 ± 1.2%. Western blot analysis revealed that SHD increased the levels of p-PI3k, p-Akt and p-CREB1, and decreased the expression of TNF-α and IL-6.

          Discussion and conclusions

          This study suggests that SHD protects against cerebral ischaemic injury via regulation of the PI3K/Akt/CREB1 and TNF pathways.

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          Most cited references51

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            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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              AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Pharm Biol
                Pharm Biol
                Pharmaceutical Biology
                Taylor & Francis
                1388-0209
                1744-5116
                5 January 2022
                2022
                5 January 2022
                : 60
                : 1
                : 119-130
                Affiliations
                [a ]Department of Pharmacy, Xijing Hospital, Fourth Military Medical University , Xi'an, Shaanxi, China
                [b ]Department of Emergency, Xijing Hospital, Fourth Military Medical University , Xi'an, Shaanxi, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Supplemental data for this article can be accessed here .

                CONTACT Jingwen Wang wangjingwen8021@ 123456163.com
                Yi Ding dingyi.007@ 123456163.com Department of Pharmacy, Xijing Hospital, Fourth Military Medical University , Xi’an 710032, Shaanxi Province, China
                Article
                2019281
                10.1080/13880209.2021.2019281
                8741256
                34985385
                445aa040-9871-423e-87d6-13aeea631867
                © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 8, Tables: 3, Pages: 12, Words: 7294
                Categories
                Research Article
                Research Article

                cerebral ischaemia,cell viability,sh-sy5y cells,molecular docking

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