Binding mode prediction and inhibitor design of anti-influenza virus diketo acids targeting metalloenzyme RNA polymerase by molecular docking

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Title	Binding mode prediction and inhibitor design of anti-influenza virus diketo acids targeting metalloenzyme RNA polymerase by molecular docking
Authors	Yoshinobu Ishikawa* & Satoshi Fujii
Affiliation	School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka 422-8526, Japan
Email	ishi206@u-shizuoka-ken.ac.jp; *Corresponding author
Phone & Fax	+81 54 264 5645
Article Type	Hypothesis
Date	Received May 19, 2011; Accepted May 21, 2011; Published June 06, 2011
Abstract	Influenza is a yearly seasonal threat and major cause of mortality, particularly in children and the elderly. Although neuraminidase inhibitors and M2 protein blockers are used for medication, drug resistance has gradually emerged. Thus, the development of effective anti-influenza drugs targeting different constituent proteins of the virus is urgently desired. In this light, we carried out molecular docking to predict the binding modes of anti-influenza diketo acid inhibitors in the active site of the PAN subunit of the metalloenzyme RNA polymerase of influenza virus. The calculations suggested that the dianionic forms of the diketo acids should chelate the dinuclear manganese center as dinucleating ligands and sequester it. They also indicated that the diketo acid derivatives with larger hydrophobic substituents should block a hydrophobic cavity in the active site more tightly. These assumptions could adequately explain the enzyme inhibition by these compounds. Furthermore, we designed potential inhibitors by lead optimization of a diketo acid inhibitor from the thermodynamic points of view. Molecular docking results showed that the newly designed diketo acid derivatives might inhibit the metalloenzyme RNA polymerase more strongly than the lead inhibitor.
Keywords	Influenza, RNA polymerase, Metalloenzyme, Diketo acid, Molecular docking, Drug design
Citation	Ishikawa & Fujii. Bioinformation 6(6): 221-225 (2011)
Edited by	P Kangueane
ISSN	0973-2063
Publisher	Biomedical Informatics
License	This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.