Thermodynamic Coupling between Folding Correctors and the First of Dimerized Nucleotide Binding Domains in CFTR
Bibliographic record
Abstract
The most common cystic fibrosis mutation is the F508del mutation in the human cystic fibrosis transmembrane conductance regulator (hCFTR), which causes misfolding of the first of two nucleotide binding domains (NBD1/2), preventing Mg/ATP-dependent NBD dimerization for normal function. Although folding correctors elexacaftor/VX-445 and lumacaftor/VX-809 have been combined to correct the NBD1 misfolding, the exact correction pathway is still unknown. In this study, the constrained tertiary noncovalent interaction networks or the thermoring structures of dimerized NBD1 in hCFTR/E1371Q with or without F508del were analyzed to identify the weakest noncovalent bridge as the final post-translational tertiary folding of dimerized NBD1 in response to folding correctors. These computational analyses suggested that hCFTR primarily used cooperative folding between α- and β-subdomains in dimerized NBD1 as the last step upon binding of the potentiator ivacaftor/VX-770. However, the binding of folding correctors allosterically protected the α-subdomain from misfolding until subsequent core formation. This thermodynamic protective mechanism, unlike the chaperone-based one in cotranslational NBD1 folding, may restore posttranslational NBD1 folding for tight Mg/ATP-mediated NBD dimerization in the F508del mutation and also potentially apply to treating other cystic fibrosis patients with rare mutations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".