Targeting G†Protein-Coupled Receptors by Capture Compound Mass Spectrometry: A Case Study with Sertindole.

Unbiased chemoproteomic profiling of small-molecule interactions with endogenous proteins is important for drug discovery. For meaningful results, all protein classes have to be tractable, including G protein-coupled receptors (GPCRs). These receptors are hardly tractable by affinity pulldown from lysates. We report a capture compound (CC)-based strategy to target and identify GPCRs directly from living cells. We synthesized CCs with sertindole attached to the CC scaffold in different orientations to target the dopamine D2 receptor (DRD2) heterologously expressed in HEK 293 cells. The structure-activity relationship of sertindole for DRD2 binding was reflected in the activities of the sertindole CCs in radioligand displacement, cell-based assays, and capture compound mass spectrometry (CCMS). The activity pattern was rationalized by molecular modelling. The most-active CC showed activities very similar to that of unmodified sertindole. A concentration of DRD2 in living cells well below 100 fmol used as an experimental input was sufficient for unambiguous identification of captured DRD2 by mass spectrometry. Our new CCMS workflow broadens the arsenal of chemoproteomic technologies to close a critical gap for the comprehensive characterization of drug-protein interactions.

Disease- and sex-specific differences in patients with heart valve disease: a proteome study.

Pressure overload in patients with aortic valve stenosis and volume overload in mitral valve regurgitation trigger specific forms of cardiac remodeling; however, little is known about similarities and differences in myocardial proteome regulation. We performed proteome profiling of 75 human left ventricular myocardial biopsies (aortic stenosis = 41, mitral regurgitation = 17, and controls = 17) using high-resolution tandem mass spectrometry next to clinical and hemodynamic parameter acquisition. In patients of both disease groups, proteins related to ECM and cytoskeleton were more abundant, whereas those related to energy metabolism and proteostasis were less abundant compared with controls. In addition, disease group-specific and sex-specific differences have been observed. Male patients with aortic stenosis showed more proteins related to fibrosis and less to energy metabolism, whereas female patients showed strong reduction in proteostasis-related proteins. Clinical imaging was in line with proteomic findings, showing elevation of fibrosis in both patient groups and sex differences. Disease- and sex-specific proteomic profiles provide insight into cardiac remodeling in patients with heart valve disease and might help improve the understanding of molecular mechanisms and the development of individualized treatment strategies.

Comprehensive micro-scaled proteome and phosphoproteome characterization of archived retrospective cancer repositories.

Formalin-fixed paraffin-embedded (FFPE) tissues are a valuable resource for retrospective clinical studies. Here, we evaluate the feasibility of (phospho-)proteomics on FFPE lung tissue regarding protein extraction, quantification, pre-analytics, and sample size. After comparing protein extraction protocols, we use the best-performing protocol for the acquisition of deep (phospho-)proteomes from lung squamous cell and adenocarcinoma with >8,000 quantified proteins and >14,000 phosphosites with a tandem mass tag (TMT) approach. With a microscaled approach, we quantify 7,000 phosphosites, enabling the analysis of FFPE biopsies with limited tissue amounts. We also investigate the influence of pre-analytical variables including fixation time and heat-assisted de-crosslinking on protein extraction efficiency and proteome coverage. Our improved workflows provide quantitative information on protein abundance and phosphosite regulation for the most relevant oncogenes, tumor suppressors, and signaling pathways in lung cancer. Finally, we present general guidelines to which methods are best suited for different applications, highlighting TMT methods for comprehensive (phospho-)proteome profiling for focused clinical studies and label-free methods for large cohorts.