Connexin 46 and connexin 50 gap junction channel open stability and unitary conductance are shaped by structural and dynamic features of their N-terminal domains
Bibliographic record
Abstract
Abstract The connexins form intercellular communication channels, known as gap junctions (GJs), that facilitate diverse physiological roles in vertebrate species, ranging from electrical coupling and long-range chemical signaling, to coordinating development and nutrient exchange. GJs formed by different connexins are expressed throughout the body and harbor unique channel properties that have not been fully defined mechanistically. Recent structural studies have implicated the amino-terminal (NT) domain as contributing to isoform-specific functional differences that exist between the lens connexins, Cx50 and Cx46. To better understand the structural and functional differences in the two closely related, yet functionally distinct GJs, we constructed models corresponding to CryoEM-based structures of the wildtype Cx50 and Cx46 GJs, NT domain swapped chimeras (Cx46-50NT and Cx50-46NT), and point variants at the 9 th residue (Cx46-R9N and Cx50-N9R) for comparative MD simulation and electrophysiology studies. All of these constructs formed functional GJ channels, except Cx46-50NT, which correlated with increased dynamical behavior (instability) of the NT domain observed by MD simulation. Single channel conductance (γ j ) also correlated well with free-energy landscapes predicted by MD, where γ j of Cx46-R9N was increased from Cx46 and the γ j s of Cx50-46NT and Cx50-N9R was decreased from Cx50, but to a surprisingly greater degree. Additionally, we observed significant effects on transjunctional voltage-dependent gating (V j -gating) and open-state dwell times induced by the designed NT domain variants. Together, these studies indicate that the NT domains of Cx46 and Cx50 play an important role in defining channel properties related to open-state stability and single channel conductance.
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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) | 0.001 | 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".