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Discovery of α-glucosidase inhibitors has been actively pursued with the aim to develop therapeutics for the treatment of diabetes and the other carbohydrate mediated diseases. As a method for the discovery of new novel inhibitors of α-glucosidase, we have addressed the performance of the computer-aided drug design protocol involving the homology modeling of α-glucosidase and the structure-based virtual screening with the two docking tools: FlexX and the automated and improved AutoDock implementing the effects of ligand solvation in the scoring function. The homology modeling of α-glucosidase from baker’s yeast provides a high-quality 3-D structure enabling the structure-based inhibitor design. Of the two docking programs under consideration, AutoDock is found to be more accurate than FlexX in terms of scoring putative ligands to the extent of 5-fold enhancement of hit rate in database screening when 1% of database coverage is used as a cutoff. A detailed binding mode analysis of the known inhibitors shows that they can be stabilized in the active site of αglucosidase through the simultaneous establishment of the multiple hydrogen bond and hydrophobic interactions. The present study demonstrates the usefulness of the automated AutoDock program with the improved scoring function as a docking tool for virtual screening of new α-glucosidase inhibitors as well as for binding mode analysis to elucidate the activities of known inhibitors.

Toward the Virtual Screening of α-Glucosidase Inhibitors with the Homology-Modeled Protein Structure