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Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae

BACKGROUND: Traditional Chinese Medicine (TCM) is characterized by the wide use of herbal formulae, which are capable of systematically treating diseases determined by interactions among various herbs. However, the combination rule of TCM herbal formulae remains a mystery due to the lack of appropri...

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Autores principales: Li, Shao, Zhang, Bo, Jiang, Duo, Wei, Yingying, Zhang, Ningbo
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024874/
https://www.ncbi.nlm.nih.gov/pubmed/21172056
http://dx.doi.org/10.1186/1471-2105-11-S11-S6
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author Li, Shao
Zhang, Bo
Jiang, Duo
Wei, Yingying
Zhang, Ningbo
author_facet Li, Shao
Zhang, Bo
Jiang, Duo
Wei, Yingying
Zhang, Ningbo
author_sort Li, Shao
collection PubMed
description BACKGROUND: Traditional Chinese Medicine (TCM) is characterized by the wide use of herbal formulae, which are capable of systematically treating diseases determined by interactions among various herbs. However, the combination rule of TCM herbal formulae remains a mystery due to the lack of appropriate methods. METHODS: From a network perspective, we established a method called Distance-based Mutual Information Model (DMIM) to identify useful relationships among herbs in numerous herbal formulae. DMIM combines mutual information entropy and “between-herb-distance” to score herb interactions and construct herb network. To evaluate the efficacy of the DMIM-extracted herb network, we conducted in vitro assays to measure the activities of strongly connected herbs and herb pairs. Moreover, using the networked Liu-wei-di-huang (LWDH) formula as an example, we proposed a novel concept of “co-module” across herb-biomolecule-disease multilayer networks to explore the potential combination mechanism of herbal formulae. RESULTS: DMIM, when used for retrieving herb pairs, achieves a good balance among the herb’s frequency, independence, and distance in herbal formulae. A herb network constructed by DMIM from 3865 Collaterals-related herbal formulae can not only nicely recover traditionally-defined herb pairs and formulae, but also generate novel anti-angiogenic herb ingredients (e.g. Vitexicarpin with IC50=3.2 μM, and Timosaponin A-III with IC50=3.4 μM) as well as herb pairs with synergistic or antagonistic effects. Based on gene and phenotype information associated with both LWDH herbs and LWDH-treated diseases, we found that LWDH-treated diseases show high phenotype similarity and identified certain “co-modules” enriched in cancer pathways and neuro-endocrine-immune pathways, which may be responsible for the action of treating different diseases by the same LWDH formula. CONCLUSIONS: DMIM is a powerful method to identify the combination rule of herbal formulae and lead to new discoveries. We also provide the first evidence that the co-module across multilayer networks may underlie the combination mechanism of herbal formulae and demonstrate the potential of network biology approaches in the studies of TCM.
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spelling pubmed-30248742011-01-22 Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae Li, Shao Zhang, Bo Jiang, Duo Wei, Yingying Zhang, Ningbo BMC Bioinformatics Research BACKGROUND: Traditional Chinese Medicine (TCM) is characterized by the wide use of herbal formulae, which are capable of systematically treating diseases determined by interactions among various herbs. However, the combination rule of TCM herbal formulae remains a mystery due to the lack of appropriate methods. METHODS: From a network perspective, we established a method called Distance-based Mutual Information Model (DMIM) to identify useful relationships among herbs in numerous herbal formulae. DMIM combines mutual information entropy and “between-herb-distance” to score herb interactions and construct herb network. To evaluate the efficacy of the DMIM-extracted herb network, we conducted in vitro assays to measure the activities of strongly connected herbs and herb pairs. Moreover, using the networked Liu-wei-di-huang (LWDH) formula as an example, we proposed a novel concept of “co-module” across herb-biomolecule-disease multilayer networks to explore the potential combination mechanism of herbal formulae. RESULTS: DMIM, when used for retrieving herb pairs, achieves a good balance among the herb’s frequency, independence, and distance in herbal formulae. A herb network constructed by DMIM from 3865 Collaterals-related herbal formulae can not only nicely recover traditionally-defined herb pairs and formulae, but also generate novel anti-angiogenic herb ingredients (e.g. Vitexicarpin with IC50=3.2 μM, and Timosaponin A-III with IC50=3.4 μM) as well as herb pairs with synergistic or antagonistic effects. Based on gene and phenotype information associated with both LWDH herbs and LWDH-treated diseases, we found that LWDH-treated diseases show high phenotype similarity and identified certain “co-modules” enriched in cancer pathways and neuro-endocrine-immune pathways, which may be responsible for the action of treating different diseases by the same LWDH formula. CONCLUSIONS: DMIM is a powerful method to identify the combination rule of herbal formulae and lead to new discoveries. We also provide the first evidence that the co-module across multilayer networks may underlie the combination mechanism of herbal formulae and demonstrate the potential of network biology approaches in the studies of TCM. BioMed Central 2010-12-14 /pmc/articles/PMC3024874/ /pubmed/21172056 http://dx.doi.org/10.1186/1471-2105-11-S11-S6 Text en Copyright ©2010 Li et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Li, Shao
Zhang, Bo
Jiang, Duo
Wei, Yingying
Zhang, Ningbo
Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title_full Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title_fullStr Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title_full_unstemmed Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title_short Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae
title_sort herb network construction and co-module analysis for uncovering the combination rule of traditional chinese herbal formulae
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024874/
https://www.ncbi.nlm.nih.gov/pubmed/21172056
http://dx.doi.org/10.1186/1471-2105-11-S11-S6
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