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      Study on the Mechanism of the Danggui–Chuanxiong Herb Pair on Treating Thrombus through Network Pharmacology and Zebrafish Models

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          Abstract

          Danggui–Chuanxiong (DC) is a commonly used nourishing and activating blood medicine pair in many gynecological prescriptions and modern Chinese medicine. However, its activating blood mechanism has not been clearly elucidated. Our research aimed at investigating the activating blood mechanisms of DC using network pharmacology and zebrafish experiments. Network pharmacology was used to excavate the potential targets and mechanisms of DC in treating thrombus. The antithrombotic, anti-inflammatory, antioxidant, and vasculogenesis activities of DC and the main components of DC, ferulic acid (DC2), ligustilide (DC7), and levistilide A (DC17), were evaluated by zebrafish models in vivo. A total of 24 compounds were selected as the active ingredients with favorable pharmacological parameters for this herb pair. A total of 89 targets and 18 pathways related to the thrombus process were gathered for active compounds. The genes, TNF, CXCR4, IL2, ESR1, FGF2, HIF1A, CXCL8, AR, FOS, MMP2, MMP9, STAT3, and RHOA, might be the main targets for this herb pair to exert cardiovascular activity from the analysis of protein–protein interaction and KEGG pathway results, which were mainly related to inflammation, vasculogenesis, immunity, hormones, and so forth. The zebrafish experiment results showed that DC had antithrombotic, anti-inflammatory, antioxidant, and vasculogenesis activities. The main compounds had different effects of zebrafish activities. Especially, the antithrombotic activity of the DC17H group, anti-inflammatory activities of DCH and DC2H groups, antioxidant activities of DCM, DCH, DC2, DC7, and DC17 groups, and vasculogenesis activities of DCM, DCH, and DC2 groups were stronger than those of the positive group. The integrated method coupled zebrafish models with network pharmacology provided the insights into the mechanisms of DC in treating thrombus.

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          Most cited references 60

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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.
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              Estrogen receptors and human disease.

              Estrogens influence many physiological processes in mammals, including but not limited to reproduction, cardiovascular health, bone integrity, cognition, and behavior. Given this widespread role for estrogen in human physiology, it is not surprising that estrogen is also implicated in the development or progression of numerous diseases, which include but are not limited to various types of cancer (breast, ovarian, colorectal, prostate, endometrial), osteoporosis, neurodegenerative diseases, cardiovascular disease, insulin resistance, lupus erythematosus, endometriosis, and obesity. In many of these diseases, estrogen mediates its effects through the estrogen receptor (ER), which serves as the basis for many therapeutic interventions. This Review will describe diseases in which estrogen, through the ER, plays a role in the development or severity of disease.
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                Author and article information

                Journal
                ACS Omega
                ACS Omega
                ao
                acsodf
                ACS Omega
                American Chemical Society
                2470-1343
                25 May 2021
                08 June 2021
                : 6
                : 22
                : 14677-14691
                Affiliations
                []Engineering Research Center of Zebrafish Models for Human Diseases and Drug Screening of Shandong Province, Key Laboratory for Biosensor of Shandong Province, Biology Institute, Qilu University of Technology, Shandong Academy of Sciences , Jinan 250103, China
                []State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences , Jinan 250353, China
                [§ ]Bioengineering Technology Innovation Center of Shandong Province , Heze 274000, China
                Author notes
                [* ]Email: lixb@ 123456sdas.org . Phone: +86 0531 82605331.
                [* ]Email: liukechun2000@ 123456163.com . Phone: +86 0531 82605331.
                Article
                10.1021/acsomega.1c01847
                8190889
                © 2021 The Authors. Published by American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                Funding
                Funded by: China Postdoctoral Science Foundation, doi 10.13039/501100002858;
                Award ID: 2019M662418
                Funded by: State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, doi NA;
                Award ID: ZZ20190406
                Funded by: Major Project of Bioengineering Technology Innovation Center of Shandong Province, doi NA;
                Award ID: 2019JSWGCCXZX003
                Funded by: Major Project of Bioengineering Technology Innovation Center of Shandong Province, doi NA;
                Award ID: 2018JGX114
                Funded by: Qilu University of Technology, doi 10.13039/501100014890;
                Award ID: 2020KJC-ZD08
                Funded by: Natural Science Foundation of Shandong Province, doi 10.13039/501100007129;
                Award ID: ZR2020QD103
                Funded by: Shandong Province, doi 10.13039/501100003091;
                Award ID: 202002047
                Funded by: China Postdoctoral Science Foundation, doi 10.13039/501100002858;
                Award ID: 2020M672100
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