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      Network pharmacology-based identifcation of potential targets of the flower of Trollius chinensis Bunge acting on anti-inflammatory effectss

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          Abstract

          The flower of Trollius chinensis Bunge was widely used for the treatment of inflammation-related diseases in traditional Chinese medicine (TCM). In order to clarify the anti-inflammatory mechanism of this Chinese herbs, a comprehensive network pharmacology strategy that consists of three sequential modules (pharmacophore matching, enrichment analysis and molecular docking.) was carried out. As a result, Apoptosis signal-regulating kinase 1 (ASK1), Janus kinase 1 (JAK1), c-Jun N-terminal kinases (JNKs), transforming protein p21 (HRas) and mitogen-activated protein kinase 14 (p38α) that related to the anti-inflammatory effect were filtered out. In further molecular dynamics (MD) simulation, the conformation of CID21578038 and CID20055288 were found stable in the protein ASK1 and JNKs respectively. The current investigation revealed that two effective compounds in the flower of Trollius chinensis Bunge played a crucial role in the process of inflammation by targeting ASK1 and JNKs, the comprehensive strategy can serve as a universal method to guide in illuminating the mechanism of the prescription of traditional Chinese medicine by identifying the pathways or targets.

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          Most cited references33

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          PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach

          In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper.
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            p38 MAP kinases: key signalling molecules as therapeutic targets for inflammatory diseases.

            The p38 MAP kinases are a family of serine/threonine protein kinases that play important roles in cellular responses to external stress signals. Since their identification about 10 years ago, much has been learned of the activation and regulation of the p38 MAP kinase pathways. Inhibitors of two members of the p38 family have been shown to have anti-inflammatory effects in preclinical disease models, primarily through the inhibition of the expression of inflammatory mediators. Several promising compounds have also progressed to clinical trials. In this review, we provide an overview of the role of p38 MAP kinases in stress-activated pathways and the progress towards clinical development of p38 MAP kinase inhibitors in the treatment of inflammatory diseases.
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              Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery.

              The search for new compounds with a given biological activity requires enormous effort in terms of manpower and cost. This effort arises from the large number of compounds that need to be synthesized and subsequently biologically evaluated. For this reason the pharmaceutical industry has shown great interest in theoretical methods that enable the rational design of pharmaceutical agents. In the last years bioinformatics has experienced a great evolution due to the development of specialized software and to the increasing computer power. The codification of the structural information of molecules through molecular descriptors and the subsequent data analysis allow establishing QSAR models (Quantitative Structure-Activity Relationship) that can be applied to the design and the virtual screening of new drugs. The development of sophisticated Docking methodologies also allows a more accurate predict of the biological activity of molecules. Moreover, through this type of computational techniques and theoretical approaches, it is possible to develop explanatory hypothesis on the mechanism of action of drugs. This work provides a brief description of a series of studies implemented in the software MOE (Molecular Operating Environment) with particular attention to the medicinal chemistry aspects.
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                Author and article information

                Contributors
                fhmeng@cmu.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                30 May 2019
                30 May 2019
                2019
                : 9
                : 8109
                Affiliations
                ISNI 0000 0000 9678 1884, GRID grid.412449.e, School of Pharmacy, , China Medical University, ; Liaoning, 110122 China
                Article
                44538
                10.1038/s41598-019-44538-z
                6542797
                31147584
                9f7a611d-7dbe-423d-91ab-f0c79e9c4a7e
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 November 2018
                : 14 May 2019
                Funding
                Funded by: National Natural Science Foundation of China 31600278
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 81573687
                Award ID: 81274182
                Award Recipient :
                Categories
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                © The Author(s) 2019

                Uncategorized
                computational biology and bioinformatics,immunological disorders
                Uncategorized
                computational biology and bioinformatics, immunological disorders

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