Lead Generation Using Pharmacophore Mapping and Three-Dimensional Database Searching: Application to Muscarinic M3 Receptor Antagonists

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Abstract
By using a pharmacophore model, a geometrical representation of the features necessary for molecules to show a particular biological activity, it is possible to search databases containing the 3D structures of molecules and identify novel compounds which may possess this activity. We describe our experiences of establishing a working 3D database system and its use in rational drug design. By using muscarinic M3 receptor antagonists as an example, we show that it is possible to identify potent novel lead compounds using this approach. Pharmacophore generation based on the structures of known M3 receptor antagonists, 3D database searching, and medium-throughput screening were used to identify candidate compounds. Three compounds were chosen to define the pharmacophore: a lung-selective M3 antagonist patented by Pfizer and two Astra compounds which show affinity at the M3 receptor. From these, a pharmacophore model was generated, using the program DISCO, and this was used subsequently to search a UNITY 3D database of proprietary compounds; 172 compounds were found to fit the pharmacophore. These compounds were then screened, and 1-[2-(2-(diethylamino)ethoxy)phenyl]-2-phenylethanone (pA2 6.67) was identified as the best hit, with N-[2-(piperidin-1-ylmethyl)cycohexyl]-2-propoxybenzamide (pA2 4.83) and phenylcarbamic acid 2-(morpholin-4-ylmethyl)cyclohexyl ester (pA2 5.54) demonstrating lower activity. As well as its potency, 1-[2-(2-(diethylamino)ethoxy)phenyl]-2-phenylethanone is a simple structure with limited similarity to existing M3 receptor antagonists.