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BioMed Research International
Volume 2013 (2013), Article ID 236850, 8 pages
http://dx.doi.org/10.1155/2013/236850
Research Article

Exploring Different Virtual Screening Strategies for Acetylcholinesterase Inhibitors

Department of Pharmaceutical Sciences, Birla Institute of Technology, Mesra, Ranchi 835215, India

Received 11 April 2013; Revised 12 August 2013; Accepted 4 September 2013

Academic Editor: J. Guy Guillemette

Copyright © 2013 Nibha Mishra and Arijit Basu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The virtual screening problems associated with acetylcholinesterase (AChE) inhibitors were explored using multiple shape, and structure-based modeling strategies. The employed strategies include molecular docking, similarity search, and pharmacophore modeling. A subset from directory of useful decoys (DUD) related to AChE inhibitors was considered, which consists of 105 known inhibitors and 3732 decoys. Statistical quality of the models was evaluated by enrichment factor (EF) metrics and receiver operating curve (ROC) analysis. The results revealed that electrostatic similarity search protocol using EON (ET_combo) outperformed all other protocols with outstanding enrichment of 95% in top 1% and 2% of the dataset with an AUC of 0.958. Satisfactory performance was also observed for shape-based similarity search protocol using ROCS and PHASE. In contrast, the molecular docking protocol performed poorly with enrichment factors 30% in all cases. The shape- and electrostatic-based similarity search protocol emerged as a plausible solution for virtual screening of AChE inhibitors.