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Consensus Scoring Approach To Identify the Inhibitors of AMP-Activated Protein Kinase α2 with Virtual Screening

Authors :
Hwangseo Park
Jae-Won Eom
Yang-Hee Kim
Source :
Journal of Chemical Information and Modeling. 54:2139-2146
Publication Year :
2014
Publisher :
American Chemical Society (ACS), 2014.

Abstract

Due to the involvement in the ischemic damage in the brain, 5'-adenosine monophosphate-activated protein kinase subunit α2 (AMPK2) serves as a promising target for the development of new medicines for stroke. Despite such a pharmaceutical importance, only a few small-molecule inhibitors have been reported so far. We aim in this study to identify a new class of AMPK2 inhibitors based on the structure-based virtual screening with docking simulations. To take advantage of and supplement the deficiencies of force field-based and empirical scoring functions, a consensus scoring method is employed to select the putative inhibitors by the combined use of AutoDock and FlexX programs. Prior to the virtual screening with docking simulations, both scoring functions are modified by implementing the molecular solvation free energy term to enhance the accuracy in estimating the protein-ligand binding affinity. As a consequence of the consensus virtual screening with the two modified scoring functions, we find seven structurally diverse AMPK2 inhibitors with micromolar inhibitory activity. Detailed binding mode analyses indicate that all these inhibitors can be stabilized in the ATP-binding pocket through the simultaneous establishment of the multiple hydrogen bonds and hydrophobic interactions. It is also found that a high inhibitory activity can be achieved by the reduction of desolvation cost for the inhibitor as well as by the strengthening of the enzyme-inhibitor interactions. Thus, the results of the present study demonstrate the outperformance of consensus scoring with the force field-based and empirical scoring functions that are modified to include the effects of ligand solvation on protein-ligand docking.

Details

ISSN :
1549960X and 15499596
Volume :
54
Database :
OpenAIRE
Journal :
Journal of Chemical Information and Modeling
Accession number :
edsair.doi.dedup.....017d3cd72a59b7afcb1985503def04ef