ArticleNature communications2020
A computational method for detection of ligand-binding proteins from dose range thermal proteome profiles.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 31 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 citing papers in PubMed, 53 citations in OpenAlex.
- DT-TRAP enables accurate target recognition via simplified dosing and low-temperature incubation.Journal of pharmaceutical analysis · 2026Article
- Global protein-ligand binding affinity profiling via photocatalytic labeling.Nature communications · 2026Article
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- Systematic screen uncovers regulator contributions to chemical cues in Escherichia coli.PLoS biology · 2025Article
- Human gut bacteria bioaccumulate per- and polyfluoroalkyl substances.Nature microbiology · 2025Article
- Uncovering nitroxoline activity spectrum, mode of action and resistance across Gram-negative bacteria.Nature communications · 2025Article
- TargetSeeker-MS: A Bayesian Inference Approach for Drug-Target Discovery Using Protein Fractionation Coupled to Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2025Article
- A multi-strategy antimicrobial discovery approach reveals new ways to treat Chlamydia.PLoS biology · 2025Article
- Characterizing protein-protein interactions with thermal proteome profiling.Current opinion in structural biology · 2024Review
- GPMelt: A hierarchical Gaussian process framework to explore the dark meltome of thermal proteome profiling experiments.PLoS computational biology · 2024Article
- Stability-based approaches in chemoproteomics.Expert reviews in molecular medicine · 2024Review
- Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition.Molecular systems biology · 2024Article
- IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data.Briefings in bioinformatics · 2024Article
- Experimental and data analysis advances in thermal proteome profiling.Cell reports methods · 2024Review
- Thermal proteome profiling unveils protein targets of deoxycholic acid in living neuronal cells.Advanced biotechnology · 2023Article
- CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves.Nature communications · 2023Article
- Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions.Cell chemical biology · 2023Article
- Systematic analysis of drug combinations against Gram-positive bacteria.Nature microbiology · 2023Article
- D-amino acids signal a stress-dependent run-away response in Vibrio cholerae.Nature microbiology · 2023Article
- Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays.Communications chemistry · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.