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Thermal proteome profiling: unbiased assessment of protein state through heat-induced stability changes

Overview of attention for article published in Proteome Science, June 2017
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Title
Thermal proteome profiling: unbiased assessment of protein state through heat-induced stability changes
Published in
Proteome Science, June 2017
DOI 10.1186/s12953-017-0122-4
Pubmed ID
Authors

André Mateus, Tomi A. Määttä, Mikhail M. Savitski

Abstract

In recent years, phenotypic-based screens have become increasingly popular in drug discovery. A major challenge of this approach is that it does not provide information about the mechanism of action of the hits. This has led to the development of multiple strategies for target deconvolution. Thermal proteome profiling (TPP) allows for an unbiased search of drug targets and can be applied in living cells without requiring compound labeling. TPP is based on the principle that proteins become more resistant to heat-induced unfolding when complexed with a ligand, e.g., the hit compound from a phenotypic screen. The melting proteome is also sensitive to other intracellular events, such as levels of metabolites, post-translational modifications and protein-protein interactions. In this review, we describe the principles of this approach, review the method and its developments, and discuss its current and future applications. While proteomics has generally focused on measuring relative protein concentrations, TPP provides a novel approach to gather complementary information on protein stability not present in expression datasets. Therefore, this strategy has great potential not only for drug discovery, but also for answering fundamental biological questions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 291 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 291 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 22%
Researcher 58 20%
Student > Master 37 13%
Student > Bachelor 29 10%
Student > Doctoral Student 16 5%
Other 28 10%
Unknown 59 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 101 35%
Agricultural and Biological Sciences 46 16%
Chemistry 40 14%
Pharmacology, Toxicology and Pharmaceutical Science 10 3%
Medicine and Dentistry 6 2%
Other 17 6%
Unknown 71 24%