Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries.

Inglese J, Auld DS, Jadhav A, Johnson RL, Simeonov A, Yasgar A, Zheng W, Austin CP
Proceedings of the National Academy of Sciences of the United States of America - vol. 103 11473-11478 (2006)

Proceedings of the National Academy of Sciences of the United States of America

High-throughput screening (HTS) of chemical compounds to identify modulators of molecular targets is a mainstay of pharmaceutical development. Increasingly, HTS is being used to identify chemical probes of gene, pathway, and cell functions, with the ultimate goal of comprehensively delineating relationships between chemical structures and biological activities. Achieving this goal will require methodologies that efficiently generate pharmacological data from the primary screen and reliably profile the range of biological activities associated with large chemical libraries. Traditional HTS, which tests compounds at a single concentration, is not suited to this task, because HTS is burdened by frequent false positives and false negatives and requires extensive follow-up testing. We have developed a paradigm, quantitative HTS (qHTS), tested with the enzyme pyruvate kinase, to generate concentration-response curves for >60,000 compounds in a single experiment. We show that this method is precise, refractory to variations in sample preparation, and identifies compounds with a wide range of activities. Concentration-response curves were classified to rapidly identify pyruvate kinase activators and inhibitors with a variety of potencies and efficacies and elucidate structure-activity relationships directly from the primary screen. Comparison of qHTS with traditional single-concentration HTS revealed a high prevalence of false negatives in the single-point screen. This study demonstrates the feasibility of qHTS for accurately profiling every compound in large chemical libraries (>10(5) compounds). qHTS produces rich data sets that can be immediately mined for reliable biological activities, thereby providing a platform for chemical genomics and accelerating the identification of leads for drug discovery.