用于常规筛查的强大 CETSA 数据分析自动化工作流程。

IF 2.7 4区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

SLAS Discovery Pub Date : 2024-07-01 DOI:10.1016/j.slasd.2024.100172

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引用次数: 0

摘要

细胞热转移分析法（CETSA）可以在细胞环境中研究蛋白质与配体之间的相互作用。它能在相关生理环境中提供有关小分子和大分子配体结合亲和力和特异性的宝贵信息，因此是药物发现的独特工具。虽然已有高通量实验室协议可用于扩大 CETSA 的规模，但后续的数据分析和质量控制仍然十分费力，并限制了实验通量。在此，我们介绍了一种可扩展且稳健的数据分析工作流程，可将 CETSA 集成到常规高通量筛选（HT-CETSA）中。这一新的工作流程实现了数据分析自动化，并结合了质量控制（QC），包括离群点检测、样品和平板质量控制以及结果分流。我们描述了这一工作流程，展示了它对典型实验伪影的稳健性，显示了缩放效应，并讨论了数据分析自动化对消除人工数据处理步骤的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A robust CETSA data analysis automation workflow for routine screening

The Cellular Thermal Shift Assay (CETSA) enables the study of protein-ligand interactions in a cellular context. It provides valuable information on the binding affinity and specificity of both small and large molecule ligands in a relevant physiological context, hence forming a unique tool in drug discovery. Though high-throughput lab protocols exist for scaling up CETSA, subsequent data analysis and quality control remain laborious and limit experimental throughput. Here, we introduce a scalable and robust data analysis workflow which allows integration of CETSA into routine high throughput screening (HT-CETSA). This new workflow automates data analysis and incorporates quality control (QC), including outlier detection, sample and plate QC, and result triage. We describe the workflow and show its robustness against typical experimental artifacts, show scaling effects, and discuss the impact of data analysis automation by eliminating manual data processing steps.

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来源期刊

SLAS Discovery Chemistry-Analytical Chemistry

CiteScore

7.00

自引率

3.20%

发文量

审稿时长

39 days

期刊介绍： Advancing Life Sciences R&D: SLAS Discovery reports how scientists develop and utilize novel technologies and/or approaches to provide and characterize chemical and biological tools to understand and treat human disease. SLAS Discovery is a peer-reviewed journal that publishes scientific reports that enable and improve target validation, evaluate current drug discovery technologies, provide novel research tools, and incorporate research approaches that enhance depth of knowledge and drug discovery success. SLAS Discovery emphasizes scientific and technical advances in target identification/validation (including chemical probes, RNA silencing, gene editing technologies); biomarker discovery; assay development; virtual, medium- or high-throughput screening (biochemical and biological, biophysical, phenotypic, toxicological, ADME); lead generation/optimization; chemical biology; and informatics (data analysis, image analysis, statistics, bio- and chemo-informatics). Review articles on target biology, new paradigms in drug discovery and advances in drug discovery technologies. SLAS Discovery is of particular interest to those involved in analytical chemistry, applied microbiology, automation, biochemistry, bioengineering, biomedical optics, biotechnology, bioinformatics, cell biology, DNA science and technology, genetics, information technology, medicinal chemistry, molecular biology, natural products chemistry, organic chemistry, pharmacology, spectroscopy, and toxicology. SLAS Discovery is a member of the Committee on Publication Ethics (COPE) and was published previously (1996-2016) as the Journal of Biomolecular Screening (JBS).