反褶积
药品
药物靶点
温度梯度
化学
计算生物学
生物系统
色谱法
物理
计算机科学
医学
算法
生物
药理学
生物化学
气象学
作者
Samantha J. Emery‐Corbin,Jumana M. Yousef,Subash Adhikari,Fransisca Sumardy,Duong Nhu,Mark F. van Delft,Guillaume Lessène,Jerzy Michal Dziekan,Andrew Ian Webb,Laura F. Dagley
出处
期刊:Proteomics
[Wiley]
日期:2024-05-20
卷期号:24 (16): e2300644-e2300644
被引量:8
标识
DOI:10.1002/pmic.202300644
摘要
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.
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