Pharmacophore modeling and virtual screening for the discovery of new fatty acid amide hydrolase inhibitors

A predictive pharmacophore model has been generated from a series of diverse fatty acid amide hydrolase (FAAH) inhibitors and the optimal pharmacophore model applied in virtual screening. The pharmacophore model was based on a training set of 21 compounds carefully selected from the published literatures. The optimal model Hypo-1 included four features (two hydrogen-bond acceptor units, one aromatic hydrophobic unit and one aromatic ring unit) and two excluded volumes. Cross-validation of the model confirmed that Hypo-1 was not generated by chance correlation. A large test set of 55 compounds showed that Hypo-1 performed well in classifying highly active and less active FAAH inhibitors. Superimposition analysis of the FAAH X-ray crystal structure and the pharmacophore Hypo-1 further validated the adequacy of the model. Virtual screening generated a total of 976 hits from the Zinc Natural Products database, a hit rate of 1.04% and enrichment of 83.89. The acceptable hit rate further supports the use of Hypo-1 as a 3D query tool for virtual screening.