MassIVE MSV000099486

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Ultra-High-Throughput LC-MS Method for Targeted Protein Degradation Compound Screening Using the Orbitrap Astral Mass Spectrometer

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Description

High-throughput proteomics analysis is crucial for targeted protein degradation (TPD) compound screening. Here, we developed a 300 sample per day (SPD) LC-MS method using the Orbitrap Astral mass spectrometer for ultra-high-throughput TPD compound screening. We identified close to 8,000 protein groups from a single cell line with a coefficient of variance (CV) of less than 10%, highlighting the deep proteome coverage and method reproducibility even at 300 SPD. To evaluate the quantitation accuracy of this method, we further mixed the digests from two or three species at different ratios. Our three-proteome mixture results demonstrated highly accurate quantitation for proteins with both small and large fold changes. Moreover, our two-proteome mixture experiment, where 20 to 160 ng of yeast digest was spiked into 200 ng of HeLa digest, showed an R2 of 0.999 for the yeast proteome, underscoring the quantitation accuracy of the method. Utilizing this workflow, we studied dose-dependent protein degradation patterns induced by pomalidomide, iberdomide, and mezigdomide. Our results indicate that mezigdomide may possess enhanced efficacy in T cells by degrading additional proteins such as IKZF2, thereby boosting anti-cancer immunity. Together, we developed an ultra-high-throughput LC-MS method with excellent proteome coverage and quantitation accuracy that is highly suitable for chemoproteomics screening of drug libraries. [doi:10.25345/C54T6FG7B] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: benchmark ; targeted protein degradation ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Jin Wang, Baylor College of Medicine, Houston TX, USA
Submitting User: jinwang
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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
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