SIMILARITY MEASURES FOR RATIONAL SET SELECTION AND ANALYSIS OF COMBINATORIAL LIBRARIES - THE DIVERSE PROPERTY-DERIVED (DPD) APPROACH

The generation of new chemical leads for biological targets is a very challenging task for researchers in the pharmaceutical industry. The d esign of representative screening sets and combinatorial libraries is central to achieving this objective. In this paper, we describe a nove l molecular descriptor, the Diverse Property-Derived (DPD) code, that contains information about key molecular and physicochemical propertie s of a molecule. The utility of this descriptor is explored through it s application for the selection of a maximally diverse representative screening set, through the selection of secondary screening sets to ob tain more information concerning the structure-activity relationships (SAR) of a particular target receptor, and through the profiling of co mbinatorial libraries. The usefulness of physicochemical/molecular pro perty descriptors, such as the DPD code, is discussed critically.