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Automated High-Throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition.
- Source :
-
Journal of proteome research [J Proteome Res] 2025 Feb 07; Vol. 24 (2), pp. 537-549. Date of Electronic Publication: 2025 Jan 27. - Publication Year :
- 2025
-
Abstract
- 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.
- Subjects :
- Humans
Chromatography, Liquid methods
Protein Kinase Inhibitors pharmacology
Streptavidin chemistry
Drug Discovery methods
Workflow
Solid Phase Extraction methods
Biotinylation
Proteomics methods
Tandem Mass Spectrometry methods
Dasatinib pharmacology
High-Throughput Screening Assays methods
Subjects
Details
- Language :
- English
- ISSN :
- 1535-3907
- Volume :
- 24
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Journal of proteome research
- Publication Type :
- Academic Journal
- Accession number :
- 39869306
- Full Text :
- https://doi.org/10.1021/acs.jproteome.4c00696