PHASE: A Novel Approach to Pharmacophore Modeling and 3D Database Searching

Abstract

Pharmacophore modeling and 3D database searching are now recognized as integral components of lead discovery and lead optimization, and the continuing need for improved pharmacophore‐based tools has driven the development of PHASE. By employing a novel, tree‐based partitioning algorithm, PHASE exhaustively identifies spatial arrangements of functional groups that are common and essential to the biologic activity of a set of high affinity ligands. These pharmacophore hypotheses are validated in a number of ways, including their ability to: (i) rationalize the binding affinities of a training set of molecules of varying activity, (ii) successfully predict the affinities of a test set of molecules, and (iii) selectively retrieve known actives from a database of drug‐like molecules. In addition, PHASE uniquely offers the ability to distinguish multiple binding modes through a bi‐directional clustering approach applied to bit string representations of the ligand/hypothesis space.