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KampoDB, database of predicted targets and functional annotations of natural medicines

Natural medicines (i.e., herbal medicines, traditional formulas) are useful for treatment of multifactorial and chronic diseases. Here, we present KampoDB (http://wakanmoview.inm.u-toyama.ac.jp/kampo/), a novel platform for the analysis of natural medicines, which provides various useful scientific...

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Autores principales: Sawada, Ryusuke, Iwata, Michio, Umezaki, Masahito, Usui, Yoshihiko, Kobayashi, Toshikazu, Kubono, Takaki, Hayashi, Shusaku, Kadowaki, Makoto, Yamanishi, Yoshihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060122/
https://www.ncbi.nlm.nih.gov/pubmed/30046160
http://dx.doi.org/10.1038/s41598-018-29516-1
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author Sawada, Ryusuke
Iwata, Michio
Umezaki, Masahito
Usui, Yoshihiko
Kobayashi, Toshikazu
Kubono, Takaki
Hayashi, Shusaku
Kadowaki, Makoto
Yamanishi, Yoshihiro
author_facet Sawada, Ryusuke
Iwata, Michio
Umezaki, Masahito
Usui, Yoshihiko
Kobayashi, Toshikazu
Kubono, Takaki
Hayashi, Shusaku
Kadowaki, Makoto
Yamanishi, Yoshihiro
author_sort Sawada, Ryusuke
collection PubMed
description Natural medicines (i.e., herbal medicines, traditional formulas) are useful for treatment of multifactorial and chronic diseases. Here, we present KampoDB (http://wakanmoview.inm.u-toyama.ac.jp/kampo/), a novel platform for the analysis of natural medicines, which provides various useful scientific resources on Japanese traditional formulas Kampo medicines, constituent herbal drugs, constituent compounds, and target proteins of these constituent compounds. Potential target proteins of these constituent compounds were predicted by docking simulations and machine learning methods based on large-scale omics data (e.g., genome, proteome, metabolome, interactome). The current version of KampoDB contains 42 Kampo medicines, 54 crude drugs, 1230 constituent compounds, 460 known target proteins, and 1369 potential target proteins, and has functional annotations for biological pathways and molecular functions. KampoDB is useful for mode-of-action analysis of natural medicines and prediction of new indications for a wide range of diseases.
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spelling pubmed-60601222018-07-31 KampoDB, database of predicted targets and functional annotations of natural medicines Sawada, Ryusuke Iwata, Michio Umezaki, Masahito Usui, Yoshihiko Kobayashi, Toshikazu Kubono, Takaki Hayashi, Shusaku Kadowaki, Makoto Yamanishi, Yoshihiro Sci Rep Article Natural medicines (i.e., herbal medicines, traditional formulas) are useful for treatment of multifactorial and chronic diseases. Here, we present KampoDB (http://wakanmoview.inm.u-toyama.ac.jp/kampo/), a novel platform for the analysis of natural medicines, which provides various useful scientific resources on Japanese traditional formulas Kampo medicines, constituent herbal drugs, constituent compounds, and target proteins of these constituent compounds. Potential target proteins of these constituent compounds were predicted by docking simulations and machine learning methods based on large-scale omics data (e.g., genome, proteome, metabolome, interactome). The current version of KampoDB contains 42 Kampo medicines, 54 crude drugs, 1230 constituent compounds, 460 known target proteins, and 1369 potential target proteins, and has functional annotations for biological pathways and molecular functions. KampoDB is useful for mode-of-action analysis of natural medicines and prediction of new indications for a wide range of diseases. Nature Publishing Group UK 2018-07-25 /pmc/articles/PMC6060122/ /pubmed/30046160 http://dx.doi.org/10.1038/s41598-018-29516-1 Text en © The Author(s) 2018 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
Sawada, Ryusuke
Iwata, Michio
Umezaki, Masahito
Usui, Yoshihiko
Kobayashi, Toshikazu
Kubono, Takaki
Hayashi, Shusaku
Kadowaki, Makoto
Yamanishi, Yoshihiro
KampoDB, database of predicted targets and functional annotations of natural medicines
title KampoDB, database of predicted targets and functional annotations of natural medicines
title_full KampoDB, database of predicted targets and functional annotations of natural medicines
title_fullStr KampoDB, database of predicted targets and functional annotations of natural medicines
title_full_unstemmed KampoDB, database of predicted targets and functional annotations of natural medicines
title_short KampoDB, database of predicted targets and functional annotations of natural medicines
title_sort kampodb, database of predicted targets and functional annotations of natural medicines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060122/
https://www.ncbi.nlm.nih.gov/pubmed/30046160
http://dx.doi.org/10.1038/s41598-018-29516-1
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