Structural insights into light-gating of potassium-selective channelrhodopsin
Bibliographic record
Abstract
Structural information on channelrhodopsins’ mechanism of light-gated ion conductance is scarce, limiting its engineering as optogenetic tools. Here, we use single-particle cryo-electron microscopy of peptidisc-incorporated protein samples to determine the structures of the slow-cycling mutant C110A of kalium channelrhodopsin 1 from Hyphochytrium catenoides (HcKCR1) in the dark and upon laser flash excitation. Upon photoisomerization of the retinal chromophore, the retinylidene Schiff base NH-bond reorients from the extracellular to the cytoplasmic side. This switch triggers a series of side chain reorientations and merges intramolecular cavities into a transmembrane K+ conduction pathway. Molecular dynamics simulations confirm K+ flux through the illuminated state but not through the resting state. The overall displacement between the closed and the open structure is small, involving mainly side chain rearrangements. Asp105 and Asp116 play a key role in K+ conductance. Structure-guided mutagenesis and patch-clamp analysis reveal the roles of the pathway-forming residues in channel gating and selectivity. Channelrhodopsins’ mechanism of light-gated ion conductance could be engineered for use in optogenetic tools. Here, structures of the slow-cycling mutant of HcKCR1, including an open state structure, provide insight into channel gating and selectivity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".