Extraction of pharmacophore information from high-throughput screens

Two major advances have been made in the computational perception and utilization of pharmacophores in compound libraries, both real and virtual. Firstly, a hierarchical set of filtering calculations has emerged that can be used to efficiently partition a library into a trial set of pharmacophores. This sequential filtering permits large libraries to be efficiently processed, as well as compounds judged as 'hits' to be analyzed in great detail. Secondly, new and extended methods of QSAR (quantitative structure-activity relationship) analysis have evolved to translate pharmacophore information into QSAR models that, in turn, can be used as virtual high-throughput screens for activity profiling of a library.