A rapid computational method for lead evolution: Description and application to alpha(1)-adrenergic antagonists

The high failure rate of drugs in the development phase requires a strategy to reduce risks by generating lead candidates from different chemical clas ses. We describe a new three-dimensional computational approach for lead ev olution, based on multiple pharmacophore hypotheses. Using full conformatio nal models for both active and inactive compounds, a large number of pharma cophore hypotheses are analyzed to select the set or "ensemble" of hypothes es that, when combined, is most able to discriminate between active and ina ctive molecules. The ensemble hypothesis is then used to search virtual che mical libraries to identify compounds for synthesis. This method is very ra pid, allowing very large virtual libraries on the order of a million compou nds to be filtered efficiently. In applying this method to alpha(1)-adrener gic receptor ligands, we have demonstrated lead evolution from heterocyclic alpha(1)-adrenergic receptor ligands to highly dissimilar active N-substit uted glycine compounds. Our results also show that the active N-substituted glycines are part of our smaller filtered library and thus could have been identified by synthesizing only a portion of the N-substituted glycine lib rary.