Improved drug target deconvolution with PISA‐DIA using an extended, overlapping temperature gradient

Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data‐independent acquisition mass spectrometry (DIA‐MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Ass...

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Published in:Proteomics (Weinheim) 2024-08, Vol.24 (16), p.e2300644-n/a
Main Authors: Emery‐Corbin, Samantha J., Yousef, Jumana M., Adhikari, Subash, Sumardy, Fransisca, Nhu, Duong, Delft, Mark F., Lessene, Guillaume, Dziekan, Jerzy, Webb, Andrew I., Dagley, Laura F.
Format: Article
Language:English
Subjects:
data independent acquisition (DIA)
Deconvolution
Design of experiments
Experimental design
Mass spectrometry
Mass spectroscopy
Melt temperature
Multiplexing
protein stability
Proteins
Proteome Integral Solubility Alteration
Proteomes
proteomics
Reagents
Target acquisition
target engagement
Temperature
Temperature gradients
Therapeutic targets
thermal proteome profiling
Workflow
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Summary:Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data‐independent acquisition mass spectrometry (DIA‐MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay “CETSA”) workflows typically employ multiplexing reagents reliant on data‐dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label‐free DIA approach (PISA‐DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA‐MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA‐DIA design has superior proteome coverage as compared to using tandem‐mass tags (TMT) necessitating DDA‐MS analysis. Importantly, we demonstrate our PISA‐DIA approach has the quantitative and statistical rigor using A‐1331852, a specific inhibitor of BCL‐xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA‐DIA workflow to identify BCL‐xL. We assert our novel overlapping gradient PISA‐DIA‐MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.
ISSN:1615-9853
1615-9861
1615-9861
DOI:10.1002/pmic.202300644