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A computational method for detection of ligand-binding proteins from dose range thermal proteome profiles.


ABSTRACT: Detecting ligand-protein interactions in living cells is a fundamental challenge in molecular biology and drug research. Proteome-wide profiling of thermal stability as a function of ligand concentration promises to tackle this challenge. However, current data analysis strategies use preset thresholds that can lead to suboptimal sensitivity/specificity tradeoffs and limited comparability across datasets. Here, we present a method based on statistical hypothesis testing on curves, which provides control of the false discovery rate. We apply it to several datasets probing epigenetic drugs and a metabolite. This leads us to detect off-target drug engagement, including the finding that the HDAC8 inhibitor PCI-34051 and its analog BRD-3811 bind to and inhibit leucine aminopeptidase 3. An implementation is available as an R package from Bioconductor ( https://bioconductor.org/packages/TPP2D ). We hope that our method will facilitate prioritizing targets from thermal profiling experiments.

SUBMITTER: Kurzawa N 

PROVIDER: S-EPMC7666118 | biostudies-literature |

REPOSITORIES: biostudies-literature

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