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

Xinqiang Song,Mu Zhang,Lei Chen,Q. Lin

Published 2017 in Frontiers in Molecular Biosciences

ABSTRACT

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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