Hu Huabin, Yi Xiangyan, Xue Lian, Baell Jonathan B
Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, BMC, Box 596, Uppsala SE-751 24, Sweden.
Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia.
JACS Au. 2024 Nov 25;4(12):4883-4891. doi: 10.1021/jacsau.4c00851. eCollection 2024 Dec 23.
High-throughput screening (HTS) is a crucial technique for identifying potential hits to fuel drug discovery pipelines. However, this process naturally concentrates nuisance compounds that are not optimizable yet signal positively in a convincing manner. To be able to understand what types of nuisance compounds a particular assay is sensitive to, would be of great utility in being able to prioritize progressable over nonprogressable screening hits. In this study, we present a carefully compiled set of over 100 nuisance compounds that are known to interfere with assay readouts in either phenotypic or target-based screenings. Readily accessible in an assay-ready screening plate, we believe this nuisance compound set will be of great interest to the research community, helping to establish high-quality HTS assays and identify promising, optimizable hits.
高通量筛选(HTS)是一种关键技术,用于识别潜在的命中物以推动药物研发流程。然而,这个过程自然会富集那些虽无法优化但能以令人信服的方式给出阳性信号的干扰化合物。能够了解特定检测方法对哪些类型的干扰化合物敏感,对于区分可推进的筛选命中物和不可推进的筛选命中物具有极大的实用价值。在本研究中,我们精心汇编了一组超过100种的干扰化合物,已知这些化合物会在表型筛选或基于靶点的筛选中干扰检测读数。该干扰化合物集以易于用于检测的筛选板形式提供,我们相信它将引起研究界的极大兴趣,有助于建立高质量的高通量筛选检测方法,并识别出有前景、可优化的命中物。