SYMPOSIUM REVIEW: Allosteric interactions and the modular nature of the voltage- and Ca<sup>2+</sup>-activated (BK) channel
Bibliographic record
Abstract
The high conductance voltage- and Ca(2+)-activated K(+) channel is one of the most broadly expressed channels in mammals. This channel is named BK for 'big K' because of its single-channel conductance that can be as large as 250 pS in 100 mm symmetrical K(+). BK channels increase their activity by membrane depolarization or an increase in cytosolic Ca(2+). One of the key features that defines the behaviour of BK channels is that neither Ca(2+) nor voltage is strictly necessary for channel activation. This and several other observations led to the idea that both Ca(2+) and voltage increase the open probability by an allosteric mechanism. In this type of mechanism, the processes of voltage sensor displacement, Ca(2+) binding and pore opening are independent equilibria that interact allosterically with each other. These allosteric interactions in BK channels reside in the structural characteristics of the BK channel in the sense that voltage and Ca(2+) sensors and the pore need to be contained in different structures or 'modules'. Through electrophysiological, mutagenesis, biochemical and fluorescence studies these modules have been identified and, more important, some of the interactions between them have been unveiled. In this review, we have covered the main advances achieved during the last few years in the elucidation of the structure of the BK channel and how this is related with its function as an allosteric protein.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".