Role of Dimers in the cAMP-Dependent Activation of Hyperpolarization-Activated Cyclic-Nucleotide-Modulated (HCN) Ion Channels
Bibliographic record
Abstract
Hyperpolarization-activated cyclic-nucleotide-modulated (HCN) ion channels control rhythmicity in neurons and cardiomyocytes. Cyclic AMP (cAMP) modulates HCN activity through the cAMP-induced formation of a tetrameric gating ring spanning the intracellular region (IR) of HCN. Although evidence from confocal patch-clamp fluorometry indicates that the cAMP-dependent gating of HCN occurs through a dimer of dimers, the structural and dynamical basis of cAMP allostery in HCN dimers has so far remained elusive. Thus, here we examine how dimers influence IR structural dynamics, and the role that such structural dynamics play in HCN allostery. To this end, we performed molecular dynamics (MD) simulations of HCN4 IR dimers in their fully apo, fully holo, and partially cAMP-bound states, resulting in a total simulated time of 1.2 μs. Comparative analyses of these MD trajectories, as well as previous monomer and tetramer simulations utilized as benchmarks for comparison, reveal that dimers markedly sensitize the HCN IR to cAMP-modulated allostery. Our results indicate that dimerization fine-tunes the IR dynamics to enhance, relative to both monomers and tetramers, the allosteric intra- and interprotomer coupling between the cAMP-binding domain and tetramerization domain components of the IR. The resulting allosteric model provides a viable rationalization of electrophysiological data on the role of IR dimers in HCN activation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".