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Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry

Abstract

The direct detection of drug-protein interactions in living cells is a major challenge in drug discovery research. Recently, we introduced an approach termed thermal proteome profiling (TPP), which enables the monitoring of changes in protein thermal stability across the proteome using quantitative mass spectrometry. We determined the intracellular thermal profiles for up to 7,000 proteins, and by comparing profiles derived from cultured mammalian cells in the presence or absence of a drug we showed that it was possible to identify direct and indirect targets of drugs in living cells in an unbiased manner. Here we demonstrate the complete workflow using the histone deacetylase inhibitor panobinostat. The key to this approach is the use of isobaric tandem mass tag 10-plex (TMT10) reagents to label digested protein samples corresponding to each temperature point in the melting curve so that the samples can be analyzed by multiplexed quantitative mass spectrometry. Important steps in the bioinformatic analysis include data normalization, melting curve fitting and statistical significance determination of compound concentration-dependent changes in protein stability. All analysis tools are made freely available as R and Python packages. The workflow can be completed in 2 weeks.

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Figure 1: Schematic representation of TPP experiments.
Figure 2: Workflow for the isobarQuant Python package.
Figure 3: Operational workflow breakdown.
Figure 4: Example tables required to analyze TPP-TR data using the TPP package.
Figure 5: Example tables required to analyze TPP-CCR data using the TPP package.
Figure 6: Panobinostat TPP-TR experiment.
Figure 7: Panobinostat TPP-CCR experiment.

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Acknowledgements

We thank M. Jundt, K. Kammerer, M. Klös-Hudak, M. Paulmann and T. Rudi for expert technical assistance; F. Weisbrodt for help with the figures; and R. Heinkel for expert advice regarding packaging of the isobarQuant software. We are grateful to G. Neubauer for discussions and support.

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Authors

Contributions

H.F., D.C., T.M., F.B.M.R., W.H. and M.M.S. conceived the project and wrote the manuscript; M.M.S., F.B.M.R., T.W., M.B. and G.D. designed the mass spectrometry experiments; T.W. and I.T. conducted and supervised the experiments; H.F., T.M., D.C., G.M.A.S., T.W., C.D., F.B.M.R. and M.M.S. analyzed proteomics data; T.M. and G.M.A.S. developed the isobarQuant package; D.C., H.F., C.D., S.G. and W.H. developed the TPP package; T.W., I.T., G.M.A.S., M.B. and G.D. contributed to the manuscript.

Corresponding authors

Correspondence to Friedrich B M Reinhard or Wolfgang Huber or Mikhail M Savitski.

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Competing interests

H.F., T.M., G.M.A.S., T.W., I.T., C.D., S.G., M.B., G.D., F.B.M.R. and M.M.S. are employees and/or shareholders of Cellzome and GlaxoSmithKline.

Supplementary information

Supplementary Text and Figures

Supplementary Methods and Supplementary Manual (PDF 3363 kb)

Supplementary Data 1

Results output of the TPP package of the analysis of the TPP-TR panobinostat experiment. (XLSX 9553 kb)

Supplementary Data 2

Results output of the TPP package of the analysis of the TPP-CCR panobinostat experiment. (XLSX 2330 kb)

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Franken, H., Mathieson, T., Childs, D. et al. Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry. Nat Protoc 10, 1567–1593 (2015). https://doi.org/10.1038/nprot.2015.101

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