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      Molecular mechanism of reproductive toxicity induced by Tripterygium Wilfordii based on network pharmacology

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          Abstract

          To explore the possible molecular mechanism of reproductive toxicity of Tripterygium wilfordii from the perspective of network pharmacology and bioinformatics.

          The compounds of T wilfordii were obtained by querying the relevant Chinese medicine database, the effective compounds were screened and the corresponding targets were obtained, and then compared with the reproductive toxicities related to disease targets obtained from the disease gene database to infer the potential toxic targets of reproductive toxicity of T wilfordii. Then, the key targets of reproductive toxicity of T wilfordii were screened using Search Tool for the Retrieval of Interacting Genes/Protein and Cytoscape. The gene ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, as well as module analysis, were performed on the key targets using Database for Annotation, Visualization, and Integrated Discovery and Cytoscape, respectively. Finally, the network between effective compounds-toxic targets was conducted to see how the compounds interacted.

          A total of 48 effective compounds and 482 potential toxic targets related to the reproductive toxicity of T wilfordii were screened. The enrichment analysis results showed that the key targets were mainly enriched in biological processes such as response to drug, ionotropic glutamate receptor signaling pathway, and KEGG pathways such as neuroactive ligand-receptor interaction, cAMP signaling pathway. In the protein-protein interaction network of potential toxic targets, there were 78 key targets such as TP53, INS, IL6, AGT, ADCY3, and so on. Enrichment analysis of the top module with 19 genes from module analysis indicated that T wilfordii might cause reproductive toxicity by gene ontology terms and KEGG pathways such as regulation of vasoconstriction, G-protein coupled receptor signaling pathway, inflammatory response, cAMP signaling pathway, and so on. In the network between effective compounds of T wilfordii and key targets, there were 5 compounds with high degree including Tingenone, Wilfordic Acid, Abruslactone A, Nobilin, and Wilforlide B.

          The complex molecular mechanism of reproductive toxicity of T wilfordii can be preliminarily elucidated with the help of the network pharmacology method, and the analysis results can provide some reference for the further mechanism research of reproductive toxicity of T wilfordii.

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          Most cited references35

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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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            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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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MEDI
                Medicine
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0025-7974
                1536-5964
                09 July 2021
                09 July 2021
                : 100
                : 27
                : e26197
                Affiliations
                [a ]Department of Rheumatology and Immunology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
                [b ]National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
                [c ]Tianjin Key Laboratory of Translational Research of TCM Prescription and Syndrome, Tianjin, China.
                Author notes
                []Correspondence: Yuanhao Wu, Department of Rheumatology and Immunology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China (e-mail: doctor.wuyh@ 123456gmail.com ).
                Article
                MD-D-20-11631 26197
                10.1097/MD.0000000000026197
                8270632
                34232166
                66aa7f86-e04e-4e29-9f90-41208125fa97
                Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0

                History
                : 22 December 2020
                : 11 May 2021
                : 12 May 2021
                Funding
                Funded by: Scientific Research Project of Tianjin Municipal Commission of Education
                Award ID: 2019ZD12
                Award Recipient : Not Applicable
                Funded by: High-level Talent Selection and Training Project of Tianjin Health and Family Planning Industry
                Award ID: 02005wuyuanhao
                Award Recipient : Not Applicable
                Funded by: National Natural Science Foundation of China
                Award ID: 81673927
                Award Recipient : Not Applicable
                Categories
                7200
                Research Article
                Observational Study
                Custom metadata
                TRUE

                molecular mechanism,network pharmacology,reproductive toxicity,tripterygium wilfordii

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