Correctors Promote Maturation of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR)-processing Mutants by Binding to the Protein
Bibliographic record
Abstract
The most common cause of cystic fibrosis (CF) is defective folding of a cystic fibrosis transmembrane conductance regulator (CFTR) mutant lacking Phe(508) (DeltaF508). The DeltaF508 protein appears to be trapped in a prefolded state with incomplete packing of the transmembrane (TM) segments, a defect that can be repaired by expression in the presence of correctors such as corr-4a, VRT-325, and VRT-532. To determine whether the mechanism of correctors involves direct interactions with CFTR, our approach was to test whether correctors blocked disulfide cross-linking between cysteines introduced into the two halves of a Cys-less CFTR. Although replacement of the 18 endogenous cysteines of CFTR with Ser or Ala yields a Cys-less mutant that does not mature at 37 degrees C, we found that maturation could be restored if Val(510) was changed to Ala, Cys, Ser, Thr, Gly, Ala, or Asp. The V510D mutation also promoted maturation of DeltaF508 CFTR. The Cys-less/V510A mutant was used for subsequent cross-linking analysis as it yielded relatively high levels of mature protein that was functional in iodide efflux assays. We tested for cross-linking between cysteines introduced into TM6 and TM7 of Cys-less CFTR/V510A because cross-linking between TM6 and TM7 of P-glycoprotein, the sister protein of CFTR, was inhibited with the corrector VRT-325. Cys-less CFTR/V510A mutant containing cysteines at I340C(TM6) and S877C(TM7) could be cross-linked with a homobifunctional cross-linker. Correctors and the CFTR channel blocker benzbromarone, but not P-glycoprotein substrates, inhibited cross-linking of mutant I340C(TM6)/S877C(TM7). These results suggest that corrector molecules such as corr-4a interact directly with CFTR.
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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 | 0.001 |
| 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".