Proteomics

Dataset Information

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End-to-end Throughput Chemical Proteomics for Photoaffinity Labeling Target Engagement and Deconvolution


ABSTRACT: Photoaffinity labeling (PAL) methodologies have proven to be a critical tool for the unbiased deconvolution of protein-ligand binding events in complex biological systems. However, like other chemical proteomic workflows, it is limited by time-intensive sample manipulations and data acquisition techniques. Here, we describe an approach to address this challenge through the innovation of a carboxylate bead-based protein cleanup procedure to isolate protein and coupling it to plate-based, proteomic sample processing as a semi-automated solution. Combining this with label-free, data-independent acquisition (DIA) sample analysis led to improvements on a workflow time per sample basis over current standard practices. This unified strategy for processing and analyzing these complex samples could greatly facilitate drug discovery efforts and open new opportunities in chemical proteomics.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Myeloid Leukocyte, T Cell, Kidney

DISEASE(S): Chronic Myeloid Leukemia,Lymphoma

SUBMITTER: Sheldon Cheung  

LAB HEAD: Sheldon Cheung

PROVIDER: PXD054514 | Pride | 2024-10-08

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
Dasatinib_PAL_A1.raw Raw
Dasatinib_PAL_A2.raw Raw
Dasatinib_PAL_A3.raw Raw
Dasatinib_PAL_A4.raw Raw
Dasatinib_PAL_A5.raw Raw
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