Project description:Existing thermal shift-based mass spectrometry approaches are able to identify target proteins without chemical modification of the ligand, but they are suffering from complicated workflows with limited throughput. Herein, we present a new thermal shift-based method, termed matrix thermal shift assay (mTSA), for fast deconvolution of ligand-binding targets and binding affinities at the proteome level. In mTSA, a sample matrix, treated horizontally with five different compound concentrations and vertically with five technical replicates of each condition, was denatured at a single temperature to induce protein precipitation, and then, data-independent acquisition was employed for quick protein quantification. Compared with previous thermal shift assays, the analysis throughput of mTSA was significantly improved, but the costs as well as efforts were reduced. More importantly, the matrix experiment design allowed simultaneous computation of the statistical significance and fitting of the dose–response profiles, which can be combined to enable a more accurate identification of target proteins, as well as reporting binding affinities between the ligand and individual targets. Using a pan-specific kinase inhibitor, staurosporine, we demonstrated a 36% improvement in screening sensitivity over the traditional thermal proteome profiling (TPP) and a comparable sensitivity with a latest two-dimensional TPP. Finally, mTSA was successfully applied to delineate the target landscape of perfluorooctanesulfonic acid (PFOS), a persistent organic pollutant that is hard to perform modification on, and revealed several potential targets that might account for the toxicities of PFOS.
Project description:Detecting target engagement is a major challenge in drug discovery. To this end, thermal proteome profiling (TPP) offers unbiased assessment of system-wide ligand-protein interactions. However, its most sensitive assay format lacks statistical methods with false discovery rate-control. Here, we present FILIP, a functional data analysis approach and showcase its performance on several TPP-datasets probing epigenetic drugs. This leads us to identify drug off-targets which we validate in vitro.
Project description:In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to characterize compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified 1.498 million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.
Project description:The target deconvolution of MMV897615 was evaluated using thermal proteome profiling (TPP), a chemical proteomics approach based on the stabilisation of protein targets upon ligand binding. In these TPP experiments we used a whole-cell strategy, exposing cells rather than lysates to the drug
Project description:Thermal proteome profiling analysis of ESO26-R248W esophageal adenocarcinoma cells treated with NSC59984 to identify targets of the inhibitor. Experimental details can be found in the meta data file.