MassIVE MSV000099688

Partial Public PXD070048

High Coverage and Quantitative Small Molecule Binding Site Discovery with Silyl Ether Enabled Quantitative Chemoproteomics

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Description

Most therapeutics are small molecules that function by interacting with specific protein targets. Consequently, delineating the protein targets, including the specific binding sites, for chemical probes and clinical candidates is essential to ensure potent on-target activity and to minimize engagement of unfavorable off-targets. The pairing of mass spectrometry-based chemoproteomics with photoaffinity labeling (PAL) has emerged as a favored approach to generate proteome-wide target engagement maps for reversible compounds. However, a key limitation of most PAL-based proteomic platforms is the absence of strategies that report precise binding sites and enable direct head-to-head comparisons of relative target engagement at these sites by different lead compounds. This gap stems from a confluence of factors including the complex fragmentation patterns for crosslinked peptides, poor recovery of peptides crosslinked with large hydrophobic molecules, and modification masses that differ between molecules of interest (MOI). To address these challenges, here we establish the Silyl Ether Enables Chemoproteomic Interaction and Target Engagement (SEE-CITE) approach. SEE- CITE incorporates a fully functionalized chemically cleavable photocrosslinking handle that enables precise site-of-labeling identification and head-to-head comparisons of relative binding site engagement by chemically diverse compounds. To ensure high confidence localization of labeled residues, we also enabled enhanced mapping of photocrosslinked sites by extending the MSFragger algorithm of the FragPipe computational platform to report localization scores customized for PAL and SEE-CITE data. By benchmarking SEE-CITE using scout fragments and analogues of the FDA approved kinase inhibitors, dasatinib and asciminib, we identify known and novel binding sites, including for high impact targets, such as BCR-ABL1, RTN4, and COX5A. [doi:10.25345/C51Z4262G] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: photocrosslinking ; interactome ; diazirine ; silyl ether ; chemoproteomics ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Keriann Backus, Ph.D., UCLA, United States of America
Submitting User: chaudngo
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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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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 peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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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.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

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.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.