4.8 Article

Reimagining high-throughput profiling of reactive cysteines for cell-based screening of large electrophile libraries

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NATURE BIOTECHNOLOGY
卷 39, 期 5, 页码 630-641

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NATURE PORTFOLIO
DOI: 10.1038/s41587-020-00778-3

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资金

  1. Google Ventures
  2. Third Rock Ventures
  3. NIH [GM67945, CA231991, CA217809]
  4. Dana-Farber Cancer Institute Claudia Adams Barr Program for Innovative Cancer Research Award
  5. Hale Family Center for Pancreatic Cancer Research

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This study presents a redesigned workflow called streamlined cysteine activity-based protein profiling (SLC-ABPP) for measuring amino acid side-chain reactivity, which significantly improves sample throughput. The method has been successfully applied to identify proteome-wide targets of various covalent inhibitors, while also creating a resource of cysteine reactivity data for further research.
Current methods used for measuring amino acid side-chain reactivity lack the throughput needed to screen large chemical libraries for interactions across the proteome. Here we redesigned the workflow for activity-based protein profiling of reactive cysteine residues by using a smaller desthiobiotin-based probe, sample multiplexing, reduced protein starting amounts and software to boost data acquisition in real time on the mass spectrometer. Our method, streamlined cysteine activity-based protein profiling (SLC-ABPP), achieved a 42-fold improvement in sample throughput, corresponding to profiling library members at a depth of >8,000 reactive cysteine sites at 18 min per compound. We applied it to identify proteome-wide targets of covalent inhibitors to mutant Kirsten rat sarcoma (KRAS)(G12C) and Bruton's tyrosine kinase (BTK). In addition, we created a resource of cysteine reactivity to 285 electrophiles in three human cell lines, which includes >20,000 cysteines from >6,000 proteins per line. The goal of proteome-wide profiling of cysteine reactivity across thousand-member libraries under several cellular contexts is now within reach. An improved workflow enables a 42-fold higher throughput of activity-based protein profiling.

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