High-throughput drug discovery is highly dependent on the targets available to accelerate the process of candidates screening. Traditional chemical proteomics approaches for the screening of drug targets usually require the immobilization/modification of the drug molecules to pull down the interacting proteins. Recently, energetics-based proteomics methods provide an alternative way to study drug–protein interaction by using complex cell lysate directly without any modification of the drugs. In this study, we developed a novel energetics-based proteomics strategy, the solvent-induced protein precipitation (SIP) approach, to profile the interaction of drugs with their target proteins by using quantitative proteomics. The method is easy to use for any laboratory with the common chemical reagents of acetone, ethanol, and acetic acid. The SIP approach was able to identify the well-known protein targets of methotrexate, SNS-032, and a pan-kinase inhibitor of staurosporine in cell lysate. We further applied this approach to discover the off-targets of geldanamycin. Three known protein targets of the HSP90 family were successfully identified, and several potential off-targets including NADH dehydrogenase subunits NDUFV1 and NDUFAB1 were identified for the first time, and the NDUFV1 was validated by using Western blotting. In addition, this approach was capable of evaluating the affinity of the drug–target interaction. The data collectively proved that our approach provides a powerful platform for drug target discovery.
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.
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