<HashMap><database>iProX</database><scores/><additional><omics_type>Proteomics</omics_type><submitter>Wen Gao</submitter><species>Homo Sapiens</species><full_dataset_link>http://www.iprox.org/page/project.html?id=IPX0012605000</full_dataset_link><submitter_email>gw_cpu@126.com</submitter_email><submitter_affiliation>China Pharmaceutical University</submitter_affiliation><sample_protocol></sample_protocol><repository>iProX</repository><data_protocol></data_protocol><pubmed_abstract>&lt;h4>Background&lt;/h4>Thermal stability-based proteomic strategies, including thermal proteome profiling (TPP) and proteome integral solubility alteration (PISA), enable proteome-wide target identification but predominantly analyze soluble proteins, overlooking heat-induced aggregates that may contain informative targets. Conventional denaturants used for solubilization of these precipitates offer limited performance and compatibility. Here, we developed a deep eutectic solvent (DES)-assisted reverse PISA (DrPISA) strategy to enhance insoluble proteome accessibility and improve detection sensitivity for subtle thermal stability alterations.&lt;h4>Results&lt;/h4>A systematic evaluation of 65 DES formulations identified DES-48 (l-proline:glycerol:water, 1:1:4) as an optimal solubilization reagent for heat-aggregated proteomes, delivering up to 71.7% more identified proteins than GuHCl and 23.5% more than urea, together with 80.6% fully cleaved peptides and excellent quantitative reproducibility. Integrating DES-48 into a reverse PISA workflow enabled sensitive detection of early-stage aggregation events not captured in soluble-focused assays. Across five reference compounds, DrPISA reproducibly recovered known targets and increased kinase coverage, identifying 45 kinases among 1142 quantified proteins, including marginal kinase responses in staurosporine-treated samples undetectable by conventional PISA. A simplified six-temperature dimethyl labeling workflow was applied, pooling samples from six discrete heat treatments prior to isotopic labeling and quantitative mass spectrometry, reducing reagent consumption and MS acquisition time by more than 50%. Application to celastrol identified LULL1 as a previously under-recognized interacting protein, illustrating the biological insights gained by expanding target coverage into aggregated fractions.&lt;h4>Significance&lt;/h4>DrPISA extends thermal profiling to insoluble fractions with improved performance over conventional workflows, offering a scalable approach for high-sensitivity target deconvolution. The introduction of DES-48 enables enhanced recovery and quantification of heat-aggregated proteins, broadening the analytical scope of chemical proteomics. These advances establish DrPISA as a practical and complementary strategy for expanding the discoverable drug-protein interaction landscape.</pubmed_abstract><pubmed_title>DrPISA: Deep eutectic solvent-assisted reverse proteome-integrated solubility alteration for high-sensitivity drug target identification.</pubmed_title><pubmed_authors>Yang Liu L, Ma Tian-Bo TB, Guo Chen-Wan CW, Yu Run-Bo RB, Li Ping P, Yang Hua H, Gao Wen W</pubmed_authors></additional><is_claimable>false</is_claimable><name>DrPISA: Deep Eutectic Solvent-Assisted Reverse Proteome-Integrated Solubility Alteration for High-Sensitivity Drug Target Identification</name><description>Existing thermal shift-based mass spectrometry approaches, such as TPP and PISA, focus mainly on soluble fractions, often neglecting the insoluble pellet, limiting comprehensive drug–target profiling. In this work, we developed DrPISA (deep eutectic solvent-assisted reverse PISA), a novel strategy that enables direct analysis of protein precipitates by integrating optimized deep eutectic solvents (DESs) into the PISA framework. Combined with LC-MS/MS, DrPISA demonstrated broad applicability across multiple model compounds, including methotrexate (MTX), cyclosporin A (CsA), geldanamycin (GA), panobinostat (PAN), and staurosporine (STS), as well as a natural product celastrol (CEL), highlighting its potential in target identification for bioactive natural products.</description><dates><publication>Mon Jul 14 00:00:00 BST 2025</publication></dates><accession>PXD066145</accession><cross_references><TAXONOMY>9606</TAXONOMY><pubmed>41791814</pubmed></cross_references></HashMap>