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TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations
With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the “compounds-proteins/genes-diseases” network, and revealing the regulation princ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460194/ https://www.ncbi.nlm.nih.gov/pubmed/28588237 http://dx.doi.org/10.1038/s41598-017-03039-7 |
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author | Zhang, Run-zhi Yu, Shao-jun Bai, Hong Ning, Kang |
author_facet | Zhang, Run-zhi Yu, Shao-jun Bai, Hong Ning, Kang |
author_sort | Zhang, Run-zhi |
collection | PubMed |
description | With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the “compounds-proteins/genes-diseases” network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database. |
format | Online Article Text |
id | pubmed-5460194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54601942017-06-06 TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations Zhang, Run-zhi Yu, Shao-jun Bai, Hong Ning, Kang Sci Rep Article With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the “compounds-proteins/genes-diseases” network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database. Nature Publishing Group UK 2017-06-06 /pmc/articles/PMC5460194/ /pubmed/28588237 http://dx.doi.org/10.1038/s41598-017-03039-7 Text en © The Author(s) 2017 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/. |
spellingShingle | Article Zhang, Run-zhi Yu, Shao-jun Bai, Hong Ning, Kang TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title | TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title_full | TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title_fullStr | TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title_full_unstemmed | TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title_short | TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations |
title_sort | tcm-mesh: the database and analytical system for network pharmacology analysis for tcm preparations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460194/ https://www.ncbi.nlm.nih.gov/pubmed/28588237 http://dx.doi.org/10.1038/s41598-017-03039-7 |
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