Evidence map›Paper›PMID 29930256›Full record

ArticleScientific reports2018

A widely-applicable high-throughput cellular thermal shift assay (CETSA) using split Nano Luciferase.

Natalia J Martinez, Rosita R Asawa, Matthew G Cyr, Alexey Zakharov, Daniel J Urban, Jacob S Roth, Eric Wallgren, Carleen Klumpp-Thomas, Nathan P Coussens, Ganesha Rai and 5 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
9.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 122 citations in OpenAlex.

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  16. The Mac1 ADP-ribosylhydrolase is a Therapeutic Target for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025
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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 1 institution in 1 country.

Natalia J MartinezNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Rosita R AsawaNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Matthew G CyrNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Alexey ZakharovNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Daniel J UrbanNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Jacob S RothNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Eric WallgrenNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Carleen Klumpp-ThomasNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Nathan P CoussensNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Ganesha RaiNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Shyh-Ming YangNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Matthew D HallNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.ORCID 0000-0002-5073-442X
Juan J MaruganNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Anton SimeonovNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA.
Mark J HendersonNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, 20850, USA. mark.henderson2@nih.gov.ORCID 0000-0001-8590-7338
National Institutes of Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of the interactions between a drug and its protein target in a physiologically relevant cellular environment constitutes a major challenge in the pre-clinical drug discovery space. The Cellular Thermal Shift Assay (CETSA) enables such an assessment by quantifying the changes in the thermal stability of proteins upon ligand binding in intact cells. Here, we present the development and validation of a homogeneous, standardized, target-independent, and high-throughput (384- and 1536-well formats) CETSA platform that uses a split Nano Luciferase approach (SplitLuc CETSA). The broad applicability of the assay was demonstrated for diverse targets, and its performance was compared with independent biochemical and cell-based readouts using a set of well-characterized inhibitors. Moreover, we investigated the utility of the platform as a primary assay for high-throughput screening. The SplitLuc CETSA presented here enables target engagement studies for medium and high-throughput applications. Additionally, it provides a rapid assay development and screening platform for targets where phenotypic or other cell-based assays are not readily available.

Indexed as

Antineoplastic AgentsCyclin-Dependent Kinase 9Drug DiscoveryEnzyme StabilityHEK293 CellsHeLa CellsHigh-Throughput Screening AssaysHT29 CellsHumansL-Lactate DehydrogenaseLuciferasesNanotechnologyProtein BindingProtein Kinase InhibitorsAntineoplastic AgentsCyclin-Dependent Kinase 9LDHA protein, humanL-Lactate DehydrogenaseLuciferasesProtein Kinase Inhibitors

Identifiers

PMID29930256
PMCPMC6013488
OpenAlexW2808681120

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.