ArticleScience (New York, N.Y.)2011
Chemical and genetic engineering of selective ion channel-ligand interactions.
Article in Science (New York, N.Y.), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers.
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.
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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.
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Who cites it
164 citing papers in PubMed, 306 citations in OpenAlex.
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104 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Ionic flux mediates essential physiological and behavioral functions in defined cell populations. Cell type-specific activators of diverse ionic conductances are needed for probing these effects. We combined chemistry and protein engineering to enable the systematic creation of a toolbox of ligand-gated ion channels (LGICs) with orthogonal pharmacologic selectivity and divergent functional properties. The LGICs and their small-molecule effectors were able to activate a range of ionic conductances in genetically specified cell types. LGICs constructed for neuronal perturbation could be used to selectively manipulate neuron activity in mammalian brains in vivo. The diversity of ion channel tools accessible from this approach will be useful for examining the relationship between neuronal activity and animal behavior, as well as for cell biological and physiological applications requiring chemical control of ion conductance.
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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.