In the present study we investigate whether augmentation of pharmacophores with 
excluded (ligand-inaccessible) volumes can condense the lengthy unspecific hit 
lists often obtained in 3D-database searching. Our pharmacophores contained 
hydrophobic features defined by the hormone, hydrogen bond donor and acceptor 
features of the liganded rat THR-alpha X-ray structure, and excluded volumes 
located at the positions and scaled according to the sizes of atoms delineating 
the binding cavity. We now show, for the first time, that it is perfectly 
feasible with the Catalyst software to search, in 1-2 h, medium-sized databases 
such as Maybridge (with 5 x 10(5) compounds registered as multiple conformers) 
with pharmacophores containing numerous (approximately 10(2)) excluded volumes. 
The excluded volumes did not slow the search significantly; for pharmacophores 
containing more features they also reduced the size of the hit list the most. 
For example, with a 7-feature pharmacophore, the Maybridge hit list shrank from 
4 to 1. The single remaining compound was subsequently shown to bind to 
THR-alpha with an IC50 of 69 microM. Thus, we conclude that structure-based 
pharmacophores augmented with numerous excluded volumes can effectively prune 
and focus hit lists. The performance of multiple excluded volume-supplemented 
structure-based pharmacophores in 3D-database mining as implemented with the 
Catalyst software compares very favorably with other published procedures, with 
respect to speed, specificity, and ease of use.