ArticleACS central science2018
Chemogenetic Approach Using Ni(II) Complex-Agonist Conjugates Allows Selective Activation of Class A G-Protein-Coupled Receptors.
Article in ACS central science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed, 8 citations in OpenAlex.
- Chemogenetics of cell surface receptors: beyond genetic and pharmacological approaches.RSC chemical biology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Investigating individual G-protein-coupled receptors (GPCRs) involved in various signaling cascades can unlock a myriad of invaluable physiological findings. One of the promising strategies for addressing the activity of each subtype of receptor is to design chemical turn-on switches on the target receptors. However, valid methods to selectively control class A GPCRs, the largest receptor family encoded in the human genome, remain limited. Here, we describe a novel approach to chemogenetically manipulate activity of engineered class A GPCRs carrying a His
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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.