12
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A network pharmacology approach to explore the mechanisms of Erxian decoction in polycystic ovary syndrome

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Polycystic ovary syndrome (PCOS) significantly affects women’s health and well-being. To explore the pharmacological basis of the Erxian decoction (EXD) action in PCOS therapy, a network interaction analysis was conducted at the molecular level.

          Methods

          The active elements of EXD were identified according to the oral bioavailability and drug-likeness filters from three databases: traditional Chinese medicine system pharmacology analysis platform, TCM@taiwan and TCMID, and their potential targets were also identified. Genes associated with PCOS and established protein–protein interaction networks were mined from the NCBI database. Finally, significant pathways and functions of these networks were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to determine the mechanism of action of EXD.

          Results

          Seventy active compounds were obtained from 981 ingredients present in the EXD decoction, corresponding to 247 targets. In addition, 262 genes were found to be closely related with PCOS, of which 50 overlapped with EXD and were thus considered therapeutically relevant. Pathway enrichment analysis identified PI3k-Akt, insulin resistance, Toll-like receptor, MAPK and AGE-RAGE from a total of 15 significant pathways in PCOS and its treatment.

          Conclusions

          EXD can effectively improve the symptoms of PCOS and our systemic pharmacological analysis lays the experimental foundation for further clinical applications of EXD.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Random forest: a classification and regression tool for compound classification and QSAR modeling.

            A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples of the training data and random feature selection in tree induction. Prediction is made by aggregating (majority vote or averaging) the predictions of the ensemble. We built predictive models for six cheminformatics data sets. Our analysis demonstrates that Random Forest is a powerful tool capable of delivering performance that is among the most accurate methods to date. We also present three additional features of Random Forest: built-in performance assessment, a measure of relative importance of descriptors, and a measure of compound similarity that is weighted by the relative importance of descriptors. It is the combination of relatively high prediction accuracy and its collection of desired features that makes Random Forest uniquely suited for modeling in cheminformatics.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              UniProt: the universal protein knowledgebase

              Nucleic Acids Research (2017) 45: D158–D169, https://doi.org/10.1093/nar/gkw1099 The authors wish to make the following correction to their article. Co-author Alexandre Renaux affiliated with the EMBL-EBI was mistakenly omitted from the list of authors. His name has been added to the full list of authors in the Acknowledgement section of the published article.
                Bookmark

                Author and article information

                Contributors
                liulihong024@163.com
                15949900879@163.com
                724283737@qq.com
                893813795@qq.com
                447274347@qq.com
                275492280@qq.com
                123@163.com
                1019871322@qq.com
                fcaihao@163.com
                Journal
                Chin Med
                Chin Med
                Chinese Medicine
                BioMed Central (London )
                1749-8546
                29 August 2018
                29 August 2018
                2018
                : 13
                : 46
                Affiliations
                [1 ]ISNI 0000 0000 9860 0426, GRID grid.454145.5, Department of Gynecological Ward, The Third Affiliated Hospital, , Jinzhou Medical University, ; Jinzhou, China
                [2 ]Liaoning Provincial Key Laboratory of Follicle Development and Reproductive Health (Office of Science and Technology), Jinzhou, China
                [3 ]ISNI 0000 0000 9860 0426, GRID grid.454145.5, Library Department, , Jinzhou Medical University, ; Jinzhou, China
                [4 ]ISNI 0000 0000 9860 0426, GRID grid.454145.5, Department of Gynecological Ward, The First Affiliated Hospital, , Jinzhou Medical University, ; Jinzhou, China
                Author information
                http://orcid.org/0000-0003-2039-1312
                Article
                201
                10.1186/s13020-018-0201-1
                6114271
                30181771
                552298ec-2801-4748-8418-85c3c8a7460f
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 May 2018
                : 18 August 2018
                Funding
                Funded by: Project supported by the Natural Science Foundation of Liaoning pvovince,China
                Award ID: 20170540373
                Award Recipient :
                Funded by: Project supported by the Jinzhou Foundation for Science and Technology, China
                Award ID: 16B1G35
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Complementary & Alternative medicine
                system pharmacology,erxian decoction,polycystic ovary syndrome,pharmacological mechanism,targets

                Comments

                Comment on this article