ERG2, emopamil binding protein (EBP), and sigma-1 receptor (sigma(1)) are enzymes of sterol metabolism and an enzyme-related protein, respectively, that share high affinity for various structurally diverse compounds. To discover novel high-affinity ligands, pharmacophore models were built with Catalyst based upon a series of 23 structurally diverse chemicals exhibiting K(i) values from 10 pM to 100 microM for all three proteins. In virtual screening experiments, we retrieved drugs that were previously reported to bind to one or several of these proteins and also tested 11 new hits experimentally, of which three, among them raloxifene, had affinities for sigma(1) or EBP of <60 nM. When used to search a database of 3525 biochemicals of intermediary metabolism, a slightly modified ERG2 pharmacophore model successfully retrieved 10 substrate candidates among the top 28 hits. Our results indicate that inhibitor-based pharmacophore models for sigma(1), ERG2, and EBP can be used to screen drug and metabolite databases for chemically diverse compounds and putative endogenous ligands.

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Different methods of virtual screening as a tool for lead structure discovery are described. They range from structure based docking procedures to ligand based methods such as the chemical features based pharmacophore hypothesis approach. A review on several successful applications of virtual screening is given. Different approaches have been described to derive pharmacophore models, which were subsequently used for 3D database searching. The studies so far published cover a wide range of pharmacological applications. The results hereby obtained clearly indicate that focused assessment of corporate databases by virtual screening using well validated pharmacophore models yield to a significant improvement in lead structure determination compared to high throughput screening.

A conformation-activity relationship study of 5-HT3 receptor antagonists was used to define a pharmacophore and receptor map to qualitatively account for their activity. The design and synthesis of specific keto-amino-indole derivatives that are potent 5-HT3 receptor antagonists gave some support to the model.

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