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Structure of the TRPV1 ion channel determined by electron cryo-microscopy
Open accessAbstract
Transient receptor potential (TRP) channels are sensors for a wide range of cellular and environmental signals, but elucidating how these channels respond to physical and chemical stimuli has been hampered by a lack of detailed structural information. Here we exploit advances in electron cryo-microscopy to determine the structure of a mammalian TRP channel, TRPV1, at 3.4 Å resolution, breaking the side-chain resolution barrier for membrane proteins without crystallization. Like voltage-gated channels, TRPV1 exhibits four-fold symmetry around a central ion pathway formed by transmembrane segments 5–6 (S5–S6) and the intervening pore loop, which is flanked by S1–S4 voltage-sensor-like domains. TRPV1 has a wide extracellular ‘mouth’ with a short selectivity filter. The conserved ‘TRP domain’ interacts with the S4–S5 linker, consistent with its contribution to allosteric modulation. Subunit organization is facilitated by interactions among cytoplasmic domains, including amino-terminal ankyrin repeats. These observations provide a structural blueprint for understanding unique aspects of TRP channel function.
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Scheres, S. H. W. (2012) · Journal of Structural Biology · doi:10.1016/j.jsb.2012.09.006 · Cited by 5,446
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Suchyna, T. M. (2017) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2017.07.011 · Cited by 111
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Canduela, M.-J., Mendizabal-Zubiaga, J., Puente, N., Reguero, L., Elezgarai, I., Ramos-Uriarte, A., Gerrikagoitia, I., & Grandes, P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119401 · Cited by 13
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Metadata
- Authors
- Liao, M., Cao, E., Julius, D., & Cheng, Y.
- Venue
- Nature
- Published
- 2013-12-04
- Volume
- 504
- Issue
- 7478
- Pages
- 107-112
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2164659462
- Cited by
- 1,686
- References
- 2
- FWCI
- 91.33
- Type
- journal article
- Language
- en
- Open access
- bronze
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