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定量高通量筛选:一种基于滴定的方法,可有效识别大型化学文库中的生物活性。

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

作者信息

Inglese James, Auld Douglas S, Jadhav Ajit, Johnson Ronald L, Simeonov Anton, Yasgar Adam, Zheng Wei, Austin Christopher P

机构信息

NIH Chemical Genomics Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-3370, USA.

出版信息

Proc Natl Acad Sci U S A. 2006 Aug 1;103(31):11473-8. doi: 10.1073/pnas.0604348103. Epub 2006 Jul 24.

Abstract

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.

摘要

通过高通量筛选(HTS)化学化合物以鉴定分子靶点调节剂是药物研发的主要手段。越来越多地,HTS被用于鉴定基因、信号通路和细胞功能的化学探针,其最终目标是全面描绘化学结构与生物活性之间的关系。要实现这一目标,需要能够从初筛中高效生成药理学数据并可靠地描绘与大型化学文库相关的生物活性范围的方法。传统的HTS在单一浓度下测试化合物,并不适合这项任务,因为HTS常受到频繁的假阳性和假阴性的困扰,并且需要大量的后续测试。我们已经开发了一种模式,即定量HTS(qHTS),并用丙酮酸激酶进行了测试,以便在一次实验中为超过60,000种化合物生成浓度-反应曲线。我们表明,这种方法精确,对样品制备的变化具有抗性,并且能够鉴定出具有广泛活性的化合物。对浓度-反应曲线进行分类,以快速鉴定具有各种效力和效能的丙酮酸激酶激活剂和抑制剂,并直接从初筛中阐明构效关系。将qHTS与传统的单浓度HTS进行比较,发现在单点筛选中假阴性的发生率很高。这项研究证明了qHTS用于准确描绘大型化学文库(>10^5种化合物)中每种化合物的可行性。qHTS产生丰富的数据集,可以立即挖掘以获取可靠的生物活性,从而为化学基因组学提供一个平台,并加速药物发现先导物的鉴定。

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