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 <i>m</i>/<i>z</i> 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

Measuring and Managing Ratio Compression for Accurate iTRAQ/TMT Quantification

Isobaric mass tagging (e.g., TMT and iTRAQ) is a precise and sensitive multiplexed peptide/protein quantification technique in mass spectrometry. However, accurate quantification of complex proteomic samples is impaired by cofragmentation of peptides, leading to systematic underestimation of quantitative ratios. Label-free quantification strategies do not suffer from such an accuracy bias but cannot be multiplexed and are less precise. Here, we compared protein quantification results obtained with these methods for a chemoproteomic competition binding experiment and evaluated the utility of measures of spectrum purity in survey spectra for estimating the impact of cofragmentation on measured TMT-ratios. While applying stringent interference filters enables substantially more accurate TMT quantification, this came at the expense of 30%–60% fewer proteins quantified. We devised an algorithm that corrects experimental TMT ratios on the basis of determined peptide interference levels. The quantification accuracy achieved with this correction was comparable to that obtained with stringent spectrum filters but limited the loss in coverage to <10%. The generic applicability of the fold change correction algorithm was further demonstrated by spiking of chemoproteomics samples into excess amounts of <i>E. coli</i> tryptic digests

Chemical Proteomic Analysis Reveals the Drugability of the Kinome of <i>Trypanosoma brucei</i>

The protozoan parasite <i>Trypanosoma brucei</i> is the causative agent of African sleeping sickness, and there is an urgent unmet need for improved treatments. Parasite protein kinases are attractive drug targets, provided that the host and parasite kinomes are sufficiently divergent to allow specific inhibition to be achieved. Current drug discovery efforts are hampered by the fact that comprehensive assay panels for parasite targets have not yet been developed. Here, we employ a kinase-focused chemoproteomics strategy that enables the simultaneous profiling of kinase inhibitor potencies against more than 50 endogenously expressed <i>T. brucei</i> kinases in parasite cell extracts. The data reveal that <i>T. brucei</i> kinases are sensitive to typical kinase inhibitors with nanomolar potency and demonstrate the potential for the development of species-specific inhibitors

Interrogating the Druggability of the 2‑Oxoglutarate-Dependent Dioxygenase Target Class by Chemical Proteomics

The 2-oxoglutarate-dependent dioxygenase target class comprises around 60 enzymes including several subfamilies with relevance to human disease, such as the prolyl hydroxylases and the Jumonji-type lysine demethylases. Current drug discovery approaches are largely based on small molecule inhibitors targeting the iron/2-oxoglutarate cofactor binding site. We have devised a chemoproteomics approach based on a combination of unselective active-site ligands tethered to beads, enabling affinity capturing of around 40 different dioxygenase enzymes from human cells. Mass-spectrometry-based quantification of bead-bound enzymes using a free-ligand competition-binding format enabled the comprehensive determination of affinities for the cosubstrate 2-oxoglutarate and for oncometabolites such as 2-hydroxyglutarate. We also profiled a set of representative drug-like inhibitor compounds. The results indicate that intracellular competition by endogenous cofactors and high active site similarity present substantial challenges for drug discovery for this target class