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通过时分辨和剂量分辨蛋白质组学解析药物作用和蛋白质修饰。

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics.

机构信息

Proteomics and Bioanalytics, Department of Molecular Life Sciences, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

German Cancer Consortium, Partner Site Munich, 80336 Munich, Germany.

出版信息

Science. 2023 Apr 7;380(6640):93-101. doi: 10.1126/science.ade3925. Epub 2023 Mar 16.

Abstract

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

摘要

虽然大多数癌症药物通过改变翻译后修饰(PTM)来调节细胞通路的活性,但对于药物调节的 PTM 的程度以及时间和剂量反应特征知之甚少。在这项工作中,我们引入了一种称为 decryptM 的蛋白质组学测定方法,该方法可定量测定细胞中数千种 PTM 的药物-PTM 调节,以阐明靶标结合和药物作用机制。示例包括检测化疗药物引起的 DNA 损伤,鉴定激酶抑制剂的药物特异性 PTM 特征,以及证明利妥昔单抗通过过度激活 B 细胞受体信号杀死 CD20 阳性 B 细胞。在 13 种细胞系中的 31 种癌症药物的 decryptM 分析表明了该方法的广泛适用性。生成的 180 万个剂量反应曲线作为 ProteomicsDB 中的交互式分子资源提供。

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