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Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer

Epigallocatechin-3-gallate (EGCG), a bioactive compound in green tea, is the most abundant and biologically active catechin, and it exerts multiple effects in humans through mechanisms that remain to be clarified. The present study used bioinformatics to identify possible mechanisms by which EGCG re...

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Detalles Bibliográficos
Autores principales: Song, Xinqiang, Zhang, Mu, Chen, Lei, Lin, Qingsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492114/
https://www.ncbi.nlm.nih.gov/pubmed/28713815
http://dx.doi.org/10.3389/fmolb.2017.00043
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author Song, Xinqiang
Zhang, Mu
Chen, Lei
Lin, Qingsong
author_facet Song, Xinqiang
Zhang, Mu
Chen, Lei
Lin, Qingsong
author_sort Song, Xinqiang
collection PubMed
description Epigallocatechin-3-gallate (EGCG), a bioactive compound in green tea, is the most abundant and biologically active catechin, and it exerts multiple effects in humans through mechanisms that remain to be clarified. The present study used bioinformatics to identify possible mechanisms by which EGCG reduces risk of breast cancer. Possible human protein targets of EGCG were identified in the PubChem database, possible human gene targets were identified in the NCBI database, and then both sets of targets were analyzed using Ingenuity Pathway Analysis to predict molecular networks affected by EGCG in breast cancer. The results suggest that signaling proteins affected by EGCG in breast cancer, which include JUN, FADD, NFKB1, Bcl-2, GNAO1, and MMP14, are involved primarily in cell death and survival; DNA replication, recombination and repair; and the cell cycle. The main networks affected by EGCG are predicted to involve the cell cycle; cellular assembly and organization; DNA replication, recombination and repair; and cell death and survival. These results identify several specific proteins and pathways that may be affected by EGCG in breast cancer, and they illustrate the power of integrative bioinformatics and chemical fragment analysis for focusing mechanistic studies.
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spelling pubmed-54921142017-07-14 Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer Song, Xinqiang Zhang, Mu Chen, Lei Lin, Qingsong Front Mol Biosci Molecular Biosciences Epigallocatechin-3-gallate (EGCG), a bioactive compound in green tea, is the most abundant and biologically active catechin, and it exerts multiple effects in humans through mechanisms that remain to be clarified. The present study used bioinformatics to identify possible mechanisms by which EGCG reduces risk of breast cancer. Possible human protein targets of EGCG were identified in the PubChem database, possible human gene targets were identified in the NCBI database, and then both sets of targets were analyzed using Ingenuity Pathway Analysis to predict molecular networks affected by EGCG in breast cancer. The results suggest that signaling proteins affected by EGCG in breast cancer, which include JUN, FADD, NFKB1, Bcl-2, GNAO1, and MMP14, are involved primarily in cell death and survival; DNA replication, recombination and repair; and the cell cycle. The main networks affected by EGCG are predicted to involve the cell cycle; cellular assembly and organization; DNA replication, recombination and repair; and cell death and survival. These results identify several specific proteins and pathways that may be affected by EGCG in breast cancer, and they illustrate the power of integrative bioinformatics and chemical fragment analysis for focusing mechanistic studies. Frontiers Media S.A. 2017-06-30 /pmc/articles/PMC5492114/ /pubmed/28713815 http://dx.doi.org/10.3389/fmolb.2017.00043 Text en Copyright © 2017 Song, Zhang, Chen and Lin. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Song, Xinqiang
Zhang, Mu
Chen, Lei
Lin, Qingsong
Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title_full Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title_fullStr Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title_full_unstemmed Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title_short Bioinformatic Prediction of Possible Targets and Mechanisms of Action of the Green Tea Compound Epigallocatechin-3-Gallate Against Breast Cancer
title_sort bioinformatic prediction of possible targets and mechanisms of action of the green tea compound epigallocatechin-3-gallate against breast cancer
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492114/
https://www.ncbi.nlm.nih.gov/pubmed/28713815
http://dx.doi.org/10.3389/fmolb.2017.00043
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