TY - CHAP
T1 - Combining computational and experimental methods for identifying molecular targets of phytochemicals
AU - Bode, Ann M.
AU - Dong, Zigang
N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - Targeting specific and multiple cancer genes, signaling proteins, and transcription factors to prevent cancer is now considered to be the most effective means to prevent cancer. Proteins that bind to a specific DNA gene sequence and act to initiate transcription of the distinct protein gene product are referred to as transcription factors. Transcription factors such as activator protein-1 (AP-1), nuclear factor-kappaB (NF-κB), p53, nuclear factor of activated T cells (NFAT), and cAMP response element-binding (CREB) protein have been shown to play a critical role in carcinogenesis and all are regulated by the mitogen-activated protein (MAP) kinase cascades. The activation of these or other transcription factors results in transcription of genes that encode proteins that regulate a multitude of cellular responses including apoptosis, differentiation, development, inflammation, and proliferation. Nutrients and dietary factors have attracted a great deal of interest because of their perceived ability to act as highly effective chemopreventive agents by targeting protein kinases and/or transcription factors, with very few adverse side effects. In the last few years, we have successfully combined computational biology and experimental validation to identify specific molecular targets of a variety of nutrients/phytochemicals, including EGCG, [6]-gingerol, resveratrol, and various flavonoids such as kaempherol, quercetin, and myricetin, to prevent cancer. Understanding the precise molecular mechanisms of these and other nutrients in preventing cancer may reveal key molecular targets for the development of more effective, less toxic anticancer agents ultimately leading to the eradication of cancer as a life-threatening disease. This chapter details the computational methods and software combined with experimental validation methods to successfully identify molecular targets of any phytochemical or nutrient, and also provides citations of examples for the reader's reference.
AB - Targeting specific and multiple cancer genes, signaling proteins, and transcription factors to prevent cancer is now considered to be the most effective means to prevent cancer. Proteins that bind to a specific DNA gene sequence and act to initiate transcription of the distinct protein gene product are referred to as transcription factors. Transcription factors such as activator protein-1 (AP-1), nuclear factor-kappaB (NF-κB), p53, nuclear factor of activated T cells (NFAT), and cAMP response element-binding (CREB) protein have been shown to play a critical role in carcinogenesis and all are regulated by the mitogen-activated protein (MAP) kinase cascades. The activation of these or other transcription factors results in transcription of genes that encode proteins that regulate a multitude of cellular responses including apoptosis, differentiation, development, inflammation, and proliferation. Nutrients and dietary factors have attracted a great deal of interest because of their perceived ability to act as highly effective chemopreventive agents by targeting protein kinases and/or transcription factors, with very few adverse side effects. In the last few years, we have successfully combined computational biology and experimental validation to identify specific molecular targets of a variety of nutrients/phytochemicals, including EGCG, [6]-gingerol, resveratrol, and various flavonoids such as kaempherol, quercetin, and myricetin, to prevent cancer. Understanding the precise molecular mechanisms of these and other nutrients in preventing cancer may reveal key molecular targets for the development of more effective, less toxic anticancer agents ultimately leading to the eradication of cancer as a life-threatening disease. This chapter details the computational methods and software combined with experimental validation methods to successfully identify molecular targets of any phytochemical or nutrient, and also provides citations of examples for the reader's reference.
KW - Computational biology
KW - Dietary factor
KW - In silico screening
KW - Molecular target
KW - Nutrient
KW - Phytochemical
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U2 - 10.1007/978-1-4614-9227-6_1
DO - 10.1007/978-1-4614-9227-6_1
M3 - Chapter
AN - SCOPUS:84891792219
SN - 9781461492269
T3 - Methods in Pharmacology and Toxicology
SP - 1
EP - 32
BT - Cancer Prevention
PB - Humana Press Inc.
ER -