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A possible strategy against head and neck cancer:in silicoinvestigation of three-in-one inhibitors

Authors: Yung-An, Tsou; Kuan-Chung, Chen; Su-Sen, Chang; Yeong-Ray, Wen; Calvin Yu-Chian, Chen;

A possible strategy against head and neck cancer:in silicoinvestigation of three-in-one inhibitors

Abstract

Overexpression of epidermal growth factor receptor (EGFR), Her2, and uroporphyrinogen decarboxylase (UROD) occurs in a variety of malignant tumor tissues. UROD has potential to modulate tumor response of radiotherapy for head and neck cancer, and EGFR and Her2 are common drug targets for the treatment of head and neck cancer. This study attempts to find a possible lead compound backbone from TCM Database@Taiwan ( http://tcm.cmu.edu.tw/ ) for EGFR, Her2, and UROD proteins against head and neck cancer using computational techniques. Possible traditional Chinese medicine (TCM) lead compounds had potential binding affinities with EGFR, Her2, and UROD proteins. The candidates formed stable interactions with residues Arg803, Thr854 in EGFR, residues Thr862, Asp863 in Her2 protein, and residues Arg37, Arg41 in UROD protein, which are key residues in the binding or catalytic domain of EGFR, Her2, and UROD proteins. Thus, the TCM candidates indicated a possible molecule backbone for evolving potential inhibitors for three drug target proteins against head and neck cancer.

Keywords

Models, Molecular, Databases, Factual, Molecular Structure, Receptor, ErbB-2, Taiwan, Antineoplastic Agents, Molecular Dynamics Simulation, Protein Structure, Tertiary, ErbB Receptors, Head and Neck Neoplasms, Humans, Uroporphyrinogen Decarboxylase, Computer Simulation, Enzyme Inhibitors, Medicine, Chinese Traditional, Protein Binding

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Top 10%
Related to Research communities
Cancer Research