Jing Hui, Richardson Paul L, Potts Gregory K, Senaweera Sameera, Marin Violeta L, McClure Ryan A, Banlasan Adam, Tang Hua, Kath James E, Patel Shitalben, Torrent Maricel, Ma Renze, Williams Jon D
Discovery Research, AbbVie, Inc., 1 North Waukegan Rd., North Chicago, Illinois 60064, United States.
J Proteome Res. 2025 Feb 7;24(2):537-549. doi: 10.1021/acs.jproteome.4c00696. Epub 2025 Jan 27.
Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis. The streamlined process significantly reduced both the overall and hands-on time needed for sample preparation. Additionally, we developed a data-independent acquisition-mass spectrometry (DIA-MS) method to establish an efficient label-free quantitative chemical proteomic kinome profiling workflow. DIA-MS yielded a coverage of ∼380 kinases, a > 60% increase compared to using a data-dependent acquisition (DDA)-MS method, and provided reproducible target profiling of the kinase inhibitor dasatinib. We further showcased the applicability of this AC-MS workflow for assessing the selectivity of two clinical-stage CDK9 inhibitors against ∼250 probe-enriched kinases. Our study here provides a roadmap for efficient target engagement and selectivity profiling in native cell or tissue lysates using AC-MS.
亲和捕获(AC)与基于质谱(MS)的蛋白质组学相结合,在整个药物发现流程中被广泛应用,以确定小分子靶点的选择性和结合情况。然而,繁琐的样品制备步骤和耗时的质谱采集过程限制了其在高通量形式中的应用。在此,我们报告了一种自动化工作流程,该流程采用生物素化探针和链霉亲和素磁珠,以96孔板形式富集小分子靶点,最后直接从EvoSep固相萃取尖端取样用于液相色谱(LC)-串联质谱(MS/MS)分析。简化后的流程显著减少了样品制备所需的总时间和实际操作时间。此外,我们开发了一种数据非依赖采集质谱(DIA-MS)方法,以建立一种高效的无标记定量化学蛋白质组激酶组分析工作流程。DIA-MS覆盖了约380种激酶,与使用数据依赖采集(DDA)-MS方法相比增加了60%以上,并提供了激酶抑制剂达沙替尼可重复的靶点分析。我们进一步展示了这种AC-MS工作流程在评估两种临床阶段CDK9抑制剂对约250种探针富集激酶的选择性方面的适用性。我们在此的研究为使用AC-MS在天然细胞或组织裂解物中进行高效的靶点结合和选择性分析提供了路线图。