Evidence map›Paper›PMID 40934869›Full record

ArticleJournal of chemical information and modeling2025

Virtual Compound Screening for Discovery of Dopamine D1 Receptor Biased Allosteric Modulators.

Yang Zhou, William C Wetsel, Steven H Olson, Lawrence S Barak

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Yang ZhouDepartment of Cell Biology, Duke University Medical Center, Durham, North Carolina 27710, United States.
William C WetselDepartments of Psychiatry and Behavioral Sciences, Cell Biology, and Neurobiology, Duke University Medical Center, Durham, North Carolina 27710, United States.
Steven H OlsonConrad Prebys Center for Chemical Genomics at Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California 92037, United States.
Lawrence S BarakDepartment of Cell Biology, Duke University Medical Center, Durham, North Carolina 27710, United States.ORCID 0000-0002-9170-2141

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dopamine D1 receptor (D1R) is a therapeutic target for a variety of central nervous system disorders including Parkinson's disease (PD). Challenges thus arise in the development of safer D1R therapies in limiting off-target drug activity. This issue is particularly relevant to PD therapy, where L-DOPA has been the "gold standard" drug for decades despite a problematic side-effect profile. Recent studies of G-protein and β-arrestin functionally selective signaling offer new strategies for developing superior D1R orthosteric and allosteric compounds with fewer side effects. We designed a desktop-computer drug-screening platform to examine large virtual chemical libraries for allosteric compounds binding D1R intracellular loop 2 (ICL2) determinants. Two structurally distinct hits were strong enhancers of dopamine-induced β-arrestin recruitment and inhibitors of dopamine-induced G-protein activation. The lead candidate DUSBI-A3 was highly selective for D1R over closely related dopamine receptors when assessed by β-arrestin activation, providing proof-of-concept for pursuing D1R selective, biased compounds in the treatment of PD.

Indexed as

Drug DiscoveryReceptors, Dopamine D1User-Computer InterfaceAllosteric Regulationbeta-ArrestinsDrug Evaluation, PreclinicalHumansSmall Molecule Librariesbeta-ArrestinsReceptors, Dopamine D1Small Molecule Libraries

Identifiers

PMID40934869
PMCPMC12478865

What Socratic holds

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LicenceCC BY
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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 Socratic graph.