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Network Insights into the Genes Regulated by Hepatocyte Nuclear Factor 4 in Response to Drug Induced Perturbations: A Review
Author(s) -
Asfar S. Azmi,
Ginny Bao,
Jiankun Gao,
Ramzi M. Mohammad,
Fazlul H. Sarkar
Publication year - 2013
Publication title -
current drug discovery technologies
Language(s) - English
Resource type - Journals
eISSN - 1875-6220
pISSN - 1570-1638
DOI - 10.2174/1570163811310020007
Subject(s) - druggability , transcription factor , computational biology , drug discovery , biology , drug repositioning , phenotypic screening , function (biology) , drug , phenotype , gene , bioinformatics , microbiology and biotechnology , pharmacology , biochemistry
Transcription factors (TFs) play central role in normal cellular physiology and their aberrant expression is linked to different diseases. Hepatocyte Nuclear Factors (HNFs) are TFs that have been recognized to play multiple roles in liver physiology. Emerging research has highlighted their function in the sustenance of solid tumors, indicating that HNFs could serve as possible therapeutic targets in cancer. Although, there have been many attempts to develop HNF targeted drugs, the myriad downstream targets associated with these transcription factors, some of which are critical for normal cell homeostasis, led to the realization that HNFs are not easily druggable. Therefore, identifying and optimizing drugs that can selectively inactivate HNFs is a challenge to the pharmaceutical industry. To achieve this, a more in-depth understanding is required of the HNFs binding partners, the protein interaction networks it regulates and the resulting phenotype. This calls for network analysis of the pathways regulated by HNFs and how chemical perturbations can selectively activate or suppress their functions. Network biology is an emerging field of research that is finding applications in cancer drug discovery. Specifically, network pharmacology is cementing its position in cancer research and has various applications such as biomarker identification, in determining synergistic drug pairs and in drug repurposing. Developing a network understanding of HNFs, the target it hits and responses thereof can enhance our ability to design drugs against these TFs. This article reviews how network pharmacology can help in the identification of druggable avenues in TFs and also allow the selection of drugs and their synergistic pairs against HNFs for cancer therapy.

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