Evidence map›Paper›PMID 42446647›Full record

ArticleChemical research in toxicology2026

Screening the Tox21 Compound Library for Chemicals That Stimulate the Adrenergic β1 Receptor.

Precious A Adesina, Li Zhang, Chainarong Sukhawanit, Savannah Wood, Jinghua Zhao, Zoe Li, Srilatha Sakamuru, Stephen S Ferguson, Jui-Hua Hsieh, David M Reif and 2 more

Abstract read
In one paragraph

Article in Chemical research in toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Precious A AdesinaDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Li ZhangDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Chainarong SukhawanitDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Savannah WoodDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Jinghua ZhaoDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Zoe LiDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.
Srilatha SakamuruDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.ORCID 0000-0002-9693-1832
Stephen S FergusonDivision of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina27709, United States.ORCID 0000-0003-3172-8347
Jui-Hua HsiehDivision of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina27709, United States.ORCID 0000-0003-1620-1571
David M ReifDivision of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina27709, United States.
Ruili HuangDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.ORCID 0000-0001-8886-8311
Menghang XiaDivision of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland20892, United States.ORCID 0000-0001-7285-8469

Funding

NIEHS NIH HHS NTR 12003
6 · The paper itself

Abstract

Beta-1 adrenergic receptors (ADRβ1) are critical regulators of cardiac function; however, the potential modulation of ADRβ1 by environmental chemicals remains largely underexplored, raising concerns about unintended impacts on cardiovascular health. We applied a quantitative high-throughput screening (qHTS) approach to identify ADRβ1 agonists within the Tox21 10K compound library, which includes environmental chemicals, pharmaceuticals, industrial agents, and consumer products, using an HTRF-based cAMP assay in ADRβ1-overexpressing HEK293 cells. Primary screening of 8,947 unique compounds identified 118 potential ADRβ1 agonists. Among these, 94 were confirmed and further evaluated for β-adrenergic receptor subtype selectivity (ADRβ2 and ADRβ3) and hERG channel inhibition to assess potential cardiotoxicity liability. Known ADRβ1 agonists, isoproterenol (EC50, 0.91 nM) and dobutamine (EC50, 10 nM), were identified, supporting the validity of the assay. In addition, several compounds with limited prior ADRβ1-specific characterization, such as GR 103691 and N,N'-dibenzylethane-1,2-diamine, demonstrated subtype-selective or mixed agonist profiles, with some exhibiting minimal hERG inhibition. These findings expand the catalog of ADRβ1 modulators and demonstrate the utility of qHTS for identifying chemicals that may affect cardiovascular signaling pathways.

Indexed as

Adrenergic beta-1 Receptor AgonistsReceptors, Adrenergic, beta-1Small Molecule LibrariesDrug Evaluation, PreclinicalHEK293 CellsHigh-Throughput Screening AssaysHumansMolecular StructureAdrenergic beta-1 Receptor AgonistsReceptors, Adrenergic, beta-1Small Molecule Libraries

Identifiers

PMID42446647
PMCPMC13488611

What OpenQuestion holds

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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.