ArticleACS pharmacology & translational science2024
Determination of Protein-Ligand Binding Affinities by Thermal Shift Assay.
Article in ACS pharmacology & translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Identification of quinoline scaffolds against emerging drug target glycerophosphodiester phosphodiesterase fromRSC advances · 2026Article
- Cryo-EM reveals thatProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Component A2 is a redox-sensitive archaeal ATPase activated by methyl-coenzyme M reductase.Current biology : CB · 2026Article
- Component A2 is a redox-sensitive archaeal ATPase activated by methyl-coenzyme M reductase.bioRxiv : the preprint server for biology · 2026Article
- Measuring Protein-Ligand Binding by Thermal Shift Assay.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Design, synthesis and profiling of highly potent antivirals targeting emerging drug-resistant HIV-1 variants.bioRxiv : the preprint server for biology · 2025Article
- Surface Density of Mono- and Trivalent High-Mannan-Derived Targeting Structures with Different Affinities Impacts Cellular Uptake of Human Serum Albumin-Derived Nanocarriers.Biomacromolecules · 2025Article
- Discovery, Optimization, and Evaluation of Non-Nucleoside SARS-CoV-2 NSP14 Inhibitors.Journal of medicinal chemistry · 2025Article
- Expanding the bioanalytical application of β-hydroxybutyrate binding proteins through characterization of their metabolite interactions and site-directed mutagenesis.Protein science : a publication of the Protein Society · 2025Article
- Thermal shift assay to identify ligands for bacterial sensor proteins.FEMS microbiology reviews · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Quantification of protein-ligand interactions is crucial for understanding the protein's biological function and for drug discovery. In this study, we employed three distinct approaches for determination of protein-ligand binding affinities by a thermal shift assay using a single ligand concentration. We present the results of the comparison of the performance of the conventional curve fitting (CF) method and two newly introduced methods - assuming zero heat capacity change across small temperature ranges (ZHC) and utilizing the unfolding equilibrium constant (UEC); the latter has the advantage of reducing calculations by obtaining the unfolding equilibrium constant directly from the experimental data. Our results highlight superior performance of the ZHC and UEC methods over the conventional CF method in estimating the binding affinity, irrespective of the ligand concentration. In addition, we evaluated how the new methods can be applied to high-throughput screening for potential binders, when the enthalpy (Δ
Identifiers
What OpenQuestion holds
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.