Structural basis for ion selectivity in TMEM175 K+ channels
Abstract
The TMEM175 family constitutes recently discovered K+ channels that are important for autophagosome turnover and lysosomal pH regulation and are associated with the early onset of Parkinson Disease. TMEM175 channels lack a P-loop selectivity filter, a hallmark of all known K+ channels, raising the question how selectivity is achieved. Here, we report the X-ray structure of a closed bacterial TMEM175 channel in complex with a nanobody fusion-protein disclosing bound K+ ions. Our analysis revealed that a highly conserved layer of threonine residues in the pore conveys a basal K+ selectivity. An additional layer comprising two serines in human TMEM175 increases selectivity further and renders this channel sensitive to 4-aminopyridine and Zn2+. Our findings suggest that large hydrophobic side chains occlude the pore, forming a physical gate, and that channel opening by iris-like motions simultaneously relocates the gate and exposes the otherwise concealed selectivity filter to the pore lumen.
Data availability
Atomic coordinates have been deposited at the Protein Data Bank with thefollowing unique identifiers: 6HD8, 6HD9, 6HDA, 6HDB, 6HDC, 6SWR.
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Crystal structure of the potassium channel MtTMEM175 with rubidiumProtein Data Bank, 6HD9.
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Crystal structure of the potassium channel MtTMEM175 with cesiumProtein Data Bank, 6HDA.
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Crystal structure of the potassium channel MtTMEM175 with zincProtein Data Bank, 6HDB.
Article and author information
Author details
Funding
H2020 European Research Council (Advanced Grant 495 (AdG) n. 695078 noMAGIC)
- Anna Moroni
- Gerhard Thiel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Brunner et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Structural Biology and Molecular Biophysics
Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.
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