Small-Molecule Library Subset Screening as an Aid for Accelerating Lead Identification. (June 2014)

• Record Type: Journal Article
• Authors: Beresini, Maureen H.; Liu, Yichin; Dawes, Timothy D.; Clark, Kevin R.; Orren, Linda; Schmidt, Stephen; Turincio, Rebecca; Jones, Steven W.; Rodriguez, Richard A.; Thana, Peter; Hascall, Daniel; Gross, Daniel P.; Skelton, Nicholas J.
• Is Part Of: Journal of biomolecular screening. Volume 19:Number 5(2014)
• Page Start: 758
• Page End: 770
• Publication Date: 2014-06
• Subjects: high-throughput screening -- library subset -- compound library -- molecular diversity; Drugs -- Analysis -- Periodicals; Drugs -- Testing -- Periodicals; Biomolecules -- Analysis -- Periodicals; 572.36
• DOI: 10.1177/1087057114522515
• Languages: English
• ISSNs: 1087-0571

Abstract

Several small-compound library subsets (14, 000 to 56, 000) have been established to complement screening of a larger Genentech corporate library (~1, 300, 000). Two validation sets (~1% of the total library) containing compounds representative of the main library were chosen by selection of plates or individual compounds. Use of these subsets guided selection of assay configuration, validated assay reproducibility, and provided estimates of hit rates expected from our full library. A larger diversity subset representing the scaffold diversity of the full library (3.4% of the total) was designed for screening more challenging targets with limited reagent availability or low-throughput assays. Retrospective analysis of this subset showed hit rates similar to those of the main library while recovering a higher proportion of hit scaffolds. Finally, a property-restricted diversity set called the "in-between library" was established to identify ligand-efficient compounds of molecular size between those typically found in fragment and high-throughput screening libraries. It was screened at fivefold higher concentrations than the main library to facilitate identification of less potent yet ligand-efficient compounds. Taken together, this work underscores the value of generating multiple purpose-focused, diversity-based library subsets that are designed using computational approaches coupled with internal screening data analyses to accelerate the lead discovery process.