Advanced Technology and Biology Division, the Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia.
Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia.
Proteomics. 2024 Aug;24(16):e2300644. doi: 10.1002/pmic.202300644. Epub 2024 May 20.
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.
热蛋白质组分析(TPP)是药物靶点解析的有力工具。最近,数据非依赖性采集质谱(DIA-MS)方法在蛋白质组数据的深度和缺失方面显示出了显著的改进,但传统的 TPP(也称为 CEllular Thermal Shift Assay“CETSA”)工作流程通常采用依赖于数据依赖性采集(DDA)的多重试剂。在此,我们介绍了一种新的实验设计,用于通过无标签 DIA 方法(PISA-DIA)实现蛋白质组整体可溶性变化。我们强调了使用多个重叠热梯度和 DIA-MS 获得的蛋白质组覆盖范围和灵敏度,这最大限度地提高了 PISA 样品拼接的效率,并防止了在高熔点存在的缺失蛋白质靶标。我们证明,与使用串联质量标签(TMT)需要 DDA-MS 分析相比,我们扩展的 PISA-DIA 设计具有更高的蛋白质组覆盖范围。重要的是,我们使用特定的 BCL-xL 抑制剂 A-1331852 证明了我们的 PISA-DIA 方法具有定量和统计学严谨性。由于该蛋白质靶标的熔点较高,我们利用我们扩展的多个梯度 PISA-DIA 工作流程来鉴定 BCL-xL。我们断言我们新颖的重叠梯度 PISA-DIA-MS 方法非常适合进行无偏药物靶点解析,跨越了很大的温度范围,同时最小化了梯度之间的目标缺失,增加了解析新型化合物的蛋白质靶标的可能性。