To design diverse combinatorial libraries or to select diverse compounds to augment a screening collection, computational chemists frequently reject compounds that are > or =0.85 similar to one already chosen for the combinatorial library or in the screening set. Using Daylight fingerprints, this report shows that for IC(50) values determined as a follow-up to 115 high-throughput screening assays, there is only a 30% chance that a compound that is > or = 0.85 (Tanimoto) similar to an active is itself active. Although this enrichment is greater than that found with random screening and docking to three-dimensional structures, this low fraction of actives within similar compounds occurs not only because of deficiencies in the Daylight fingerprints and Tanimoto similarity calculations but also because similar compounds do not necessarily interact with the target macromolecule in similar ways. The current study emphasizes the statistical or probabilistic nature of library design and that perfect results cannot be expected.

The authors report the development of a high-throughput screen for inhibitors of Streptococcus pneumoniae transcription and translation (TT) using a luciferase reporter, and the secondary assays used to determine the biochemical spectrum of activity and bacterial specificity. More than 220,000 compounds were screened in mixtures of 10 compounds per well, with 10,000 picks selected for further study. False-positive hits from inhibition of luciferase activity were an extremely common artifact. After filtering luciferase inhibitors and several known classes of antibiotics, approximately 50 hits remained. These compounds were examined for their ability to inhibit Escherichia coli TT, uncoupled S. pneumoniae translation or transcription, rabbit reticulocyte translation, and in vitro toxicity in human and bacterial cells. One of these compounds had the desired profile of broad-spectrum biochemical activity in bacteria and selectivity versus mammalian biochemical and whole-cell assays.

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