Open AccessBioinformatics Analysis on Molecular Mechanism of Green Tea Compound Epigallocatechin‐3‐Gallate Against Ovarian Cancer
Author(s) -
Xinqiang S,
Mu Z,
Lei C,
Mun LY
Publication year - 2017
Publication title -
clinical and translational science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.303
H-Index - 44
eISSN - 1752-8062
pISSN - 1752-8054
DOI - 10.1111/cts.12470
Subject(s) - pubchem , fadd , mechanism (biology) , ovarian cancer , computational biology , biology , cancer , cancer research , chemistry , bioinformatics , biochemistry , genetics , apoptosis , programmed cell death , caspase , philosophy , epistemology
Epigallocatechin‐3‐gallate (EGCG) is the most abundant and biologically active catechin in green tea, 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 the risk of ovarian cancer. Possible human protein targets of EGCG were identified in the PubChem database, possible human gene targets were identified in the National Center for Biotechnology Information database, and then both sets of targets were analyzed using Ingenuity Pathway Analysis (IPA). The results suggest that signaling proteins affected by EGCG in ovarian cancer, which include JUN, FADD, NFKB1, Bcl‐2, HIF1α, and MMP, are involved primarily in cell cycle, cellular assembly and organization, DNA replication, etc. These results identify several specific proteins and pathways that may be affected by EGCG in ovarian cancer, and they illustrate the power of integrative informatics and chemical fragment analysis for focusing mechanistic studies.