Automated High-Throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition
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.
Authors
- Renze Ma (ORCID: https://orcid.org/0000-0003-0437-351X)
- Hua Tang (ORCID: https://orcid.org/0000-0001-6886-7450)
- James E. Kath (ORCID: https://orcid.org/0000-0003-3767-9822)
- Jon D. Williams (ORCID: https://orcid.org/0000-0001-9873-4165)
- Gregory K. Potts (ORCID: https://orcid.org/0000-0003-0542-9781)
- Violeta L. Marin
- Hui Jing (ORCID: https://orcid.org/0000-0002-2129-7937)
- Shitalben Patel (ORCID: https://orcid.org/0000-0003-3710-0497)
- Sameera Senaweera (ORCID: https://orcid.org/0000-0002-2113-5970)
- Ryan A. McClure (ORCID: https://orcid.org/0000-0002-0163-9290)
- Paul L. Richardson (ORCID: https://orcid.org/0000-0001-5526-8168)
- Maricel Torrent
- Adam Banlasan
Institutions
- AbbVie (United States) (US)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1021/acs.jproteome.4c00696
- Citations
- 1
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.76
Funders
- AbbVie