Molecular Investigation of Chicken Acid-Sensing Ion Channel 1 β11-12 Linker Isomerization and Channel Kinetics
Bibliographic record
Abstract
Structures of the trimeric acid-sensing ion channel have been solved in the resting, toxin-bound open and desensitized states. Within the extracellular domain, there is little difference between the toxin-bound open state and the desensitized state. The main exception is that a loop connecting the 11th and 12th β-strand, just two amino acid residues long, undergoes a significant and functionally critical re-orientation or flipping between the open and desensitized conformations. Here we investigate how specific interactions within the surrounding area influence linker stability in the "flipped" desensitized state using all-atom molecular dynamics simulations. An inherent challenge is bringing the relatively slow channel desensitization and recovery processes (in the milliseconds to seconds) within the time window of all-atom simulations (hundreds of nanoseconds). To accelerate channel behavior, we first identified the channel mutations at either the Leu414 or Asn415 position with the fastest recovery kinetics followed by molecular dynamics simulations of these mutants in a deprotonated state, accelerating recovery. By mutating one residue in the loop and examining the evolution of interactions in the neighbor, we identified a novel electrostatic interaction and validated prior important interactions. Subsequent functional analysis corroborates these findings, shedding light on the molecular factors controlling proton-mediated transitions between functional states of the channel. Together, these data suggest that the flipped loop in the desensitized state is stabilized by interactions from surrounding regions keeping both L414 and N415 in place. Interestingly, very few mutations in the loop allow for equivalent channel kinetics and desensitized state stability. The high degree of sequence conservation in this region therefore indicates that the stability of the ASIC desensitized state is under strong selective pressure and underlines the physiological importance of desensitization.
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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".