Mechanism of chloride permeation in the cystic fibrosis transmembrane conductance regulator chloride channel
Bibliographic record
Abstract
The cystic fibrosis transmembrane conductance regulator (CFTR) functions as a Cl- channel important in transepithelial salt and water transport. While there is a paucity of direct structural information on CFTR, much has been learned about the molecular determinants of the CFTR Cl- channel pore region and the mechanism of Cl- permeation through the pore from indirect structure-function studies. The first and sixth transmembrane regions of the CFTR protein play major roles in forming the channel pore and determining its functional properties by interacting with permeating Cl- ions. Positively charged amino acid side-chains are involved in attracting negatively charged Cl- ions into the pore region, where they interact briefly with a number of discrete sites on the pore walls. The pore appears able to accommodate more than one Cl- ion at a time, and Cl- ions bound inside the pore are probably sensitive to one another's presence. Repulsive interactions between Cl- ions bound concurrently within the pore may be important in ensuring rapid movement of Cl- ions through the pore. Chloride ion binding sites also interact with larger anions that can occlude the pore and block Cl- permeation, thus inhibiting CFTR function. Other ions besides Cl- are capable of passing through the pore, and specific amino acid residues that may be important in allowing the channel to discriminate between different anions have been identified. This brief review summarizes these mechanistic insights and tries to incorporate them into a simple cartoon model depicting the interactions between the channel and Cl- ions that are important for ion translocation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".