The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
The 93-kDa glycine receptor-associated protein binds to tubulin.
Open accessAbstract
A peripheral membrane protein with a relative molecular mass of 93,000 Da is associated with cytoplasmic domains of the inhibitory glycine receptor of mammalian spinal cord. Here, evidence is given that this 93-kDa protein binds to polymerized tubulin. First, tubulin cofractionated with the 93-kDa protein upon affinity purification of the glycine receptor. Second, tubulin bound to the isolated 93-kDa protein in an overlay procedure. Third, in assays containing the purified glycine receptor, the 93-kDa protein as well as the glycine receptor alpha and beta subunits coassembled with tubulin and microtubules. The interaction of the 93-kDa protein with tubulin displayed high affinity (KD approximately 2.5 nM) and significant cooperativity (Hill coefficient approximately 2.1) and approached a stoichiometry of approximately 1:4 under saturating conditions. These data suggest that the 93-kDa protein anchors the glycine receptor at postsynaptic sites via binding to subsynaptic tubulin.
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Cites
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Cited by
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Metadata
- Authors
- Kirsch, J., Langosch, D., Prior, P., Littauer, U. Z., Schmitt, B., & Betz, H.
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 1991-11
- Volume
- 266
- Issue
- 33
- Pages
- 22242-22245
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W1526360825
- Cited by
- 273
- References
- 32
- FWCI
- 3.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Kirsch, J., Langosch, D., Prior, P., Littauer, U. Z., Schmitt, B., & Betz, H. (1991). The 93-kDa glycine receptor-associated protein binds to tubulin. Journal of Biological Chemistry. https://doi.org/10.1016/s0021-9258(18)54560-9
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.