Proteomics

Dataset Information

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Robust ligand-protein interaction inference reveals off-targets of epigenetic drugs

ABSTRACT: Detecting target engagement is a major challenge in drug discovery. To this end, thermal proteome profiling (TPP) offers unbiased assessment of system-wide ligand-protein interactions. However, its most sensitive assay format lacks statistical methods with false discovery rate-control. Here, we present FILIP, a functional data analysis approach and showcase its performance on several TPP-datasets probing epigenetic drugs. This leads us to identify drug off-targets which we validate in vitro.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): T Cell, Hepatocyte, Monocyte, Cell Culture

SUBMITTER: Nils Kurzawa  

LAB HEAD: Marcus Bantscheff

PROVIDER: PXD016640 | Pride | 2020-10-29

REPOSITORIES: Pride

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Publications

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

Kurzawa Nils N   Becher Isabelle I   Sridharan Sindhuja S   Franken Holger H   Mateus André A   Anders Simon S   Bantscheff Marcus M   Huber Wolfgang W   Savitski Mikhail M MM  

Nature communications 20201113 1

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  ...[more]

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