Thermal proteome profiling monitors ligand interactions with cellular membrane proteins.

We extended thermal proteome profiling to detect transmembrane protein-small molecule interactions in cultured human cells. When we assessed the effects of detergents on ATP-binding profiles, we observed shifts in denaturation temperature for ATP-binding transmembrane proteins. We also observed cellular thermal shifts in pervanadate-induced T cell-receptor signaling, delineating the membrane target CD45 and components of the downstream pathway, and with drugs affecting the transmembrane transporters ATP1A1 and MDR1.

Tracking cancer drugs in living cells by thermal profiling of the proteome.

The thermal stability of proteins can be used to assess ligand binding in living cells. We have generalized this concept by determining the thermal profiles of more than 7000 proteins in human cells by means of mass spectrometry. Monitoring the effects of small-molecule ligands on the profiles delineated more than 50 targets for the kinase inhibitor staurosporine. We identified the heme biosynthesis enzyme ferrochelatase as a target of kinase inhibitors and suggest that its inhibition causes the phototoxicity observed with vemurafenib and alectinib. Thermal shifts were also observed for downstream effectors of drug treatment. In live cells, dasatinib induced shifts in BCR-ABL pathway proteins, including CRK/CRKL. Thermal proteome profiling provides an unbiased measure of drug-target engagement and facilitates identification of markers for drug efficacy and toxicity.

Quantifying small molecule-induced changes in cellular protein expression and posttranslational modifications using isobaric mass tags.

Proteomics enables the comprehensive analysis of cellular perturbations induced by bioactive small molecules and contributes to our understanding of the mechanisms by which drugs elicit their activity in disease situations. Here we describe a quantitative proteomics approach to study dose-dependent changes in protein expression and posttranslational protein modifications in human promyelocytic leukemia cells in response to inhibition of histone deacetylases by Vorinostat. The method employs isobaric mass tags (tandem mass tags, TMT) to enable the multiplexed quantitative analysis of up to six samples and antibodies directed against acetylated lysine residues for immunoenrichment of TMT-encoded acetylated peptides.

Ion coalescence of neutron encoded TMT 10-plex reporter ions.

Isobaric mass tag-based quantitative proteomics strategies such as iTRAQ and TMT utilize reporter ions in the low mass range of tandem MS spectra for relative quantification. The recent extension of TMT multiplexing to 10 conditions has been enabled by utilizing neutron encoded tags with reporter ion m/z differences of 6 mDa. The baseline resolution of these closely spaced tags is possible due to the high resolving power of current day mass spectrometers. In this work we evaluated the performance of the TMT10 isobaric mass tags on the Q Exactive Orbitrap mass spectrometers for the first time and demonstrated comparable quantification accuracy and precision to what can be achieved on the Orbitrap Elite mass spectrometers. However, we discovered, upon analysis of complex proteomics samples on the Q Exactive Orbitrap mass spectrometers, that the proximate TMT10 reporter ion pairs become prone to coalescence. The fusion of the different reporter ion signals into a single measurable entity has a detrimental effect on peptide and protein quantification. We established that the main reason for coalescence is the commonly accepted maximum ion target for MS2 spectra of 1e6 on the Q Exactive instruments. The coalescence artifact was completely removed by lowering the maximum ion target for MS2 spectra from 1e6 to 2e5 without any losses in identification depth or quantification quality of proteins.

Affinity profiling of the cellular kinome for the nucleotide cofactors ATP, ADP, and GTP.

Most kinase inhibitor drugs target the binding site of the nucleotide cosubstrate ATP. The high intracellular concentration of ATP can strongly affect inhibitor potency and selectivity depending on the affinity of the target kinase for ATP. Here we used a defined chemoproteomics system based on competition-binding assays in cell extracts from Jurkat and SK-MEL-28 cells with immobilized ATP mimetics (kinobeads). This system enabled us to assess the affinities of more than 200 kinases for the cellular nucleotide cofactors ATP, ADP, and GTP and the effects of the divalent metal ions Mg(2+) and Mn(2+). The affinity values determined in this system were largely consistent across the two cell lines, indicating no major dependence on kinase expression levels. Kinase-ATP affinities range from low micromolar to millimolar, which has profound consequences for the prediction of cellular effects from inhibitor selectivity profiles. Only a small number of kinases including CK2, MEK, and BRAF exhibited affinity for GTP. This extensive and consistent data set of kinase-nucleotide affinities, determined for native enzymes under defined experimental conditions, will represent a useful resource for kinase drug discovery.

Unbiased detection of posttranslational modifications using mass spectrometry.

A major challenge in proteomics is to fully identify and characterize posttranslational modification (PTM) patterns present at any given time in cells, tissues, and organisms. Currently, the most frequently used method for identifying PTMs is tandem mass spectrometry combined with searching a protein sequence database. Although, database searching has been highly successful for the identification of proteins, it has a number of significant drawbacks for identification of modifications. The user needs to specify all expected modifications, and the search engine needs to consider all possible combinations of these modifications for all peptide sequences. If several potential modifications are considered, the search can take much longer than the data acquisition, creating a bottleneck in high-throughput analysis. In addition, the many possible assignments that need to be tested increase the noise and require better quality data for confident identification of modifications. Here, we describe a method for identifying both known and unknown PTM using mass spectrometry that does not suffer from these problems. The method is based on the observation that, in many samples, peptides are usually present both with and without modifications. By identifying the unmodified peptide with conventional database searches, the modified species of the peptide can be identified by searching for peptides with common and similar fragments as the unmodified peptide. After identifying both the modified and unmodified peptide, the elemental composition of the modification can be deduced if the mass accuracy of the precursor ion is sufficiently high.