Allosteric folding correction of F508del and rare CFTR mutants by elexacaftor-tezacaftor-ivacaftor (Trikafta) combination
Bibliographic record
Abstract
Based on its clinical benefits, Trikafta - the combination of folding correctors VX-661 (tezacaftor), VX-445 (elexacaftor), and the gating potentiator VX-770 (ivacaftor) - was FDA approved for treatment of patients with cystic fibrosis (CF) carrying deletion of phenylalanine at position 508 (F508del) of the CF transmembrane conductance regulator (CFTR) on at least 1 allele. Neither the mechanism of action of VX-445 nor the susceptibility of rare CF folding mutants to Trikafta are known. Here, we show that, in human bronchial epithelial cells, VX-445 synergistically restores F508del-CFTR processing in combination with type I or II correctors that target the nucleotide binding domain 1 (NBD1) membrane spanning domains (MSDs) interface and NBD2, respectively, consistent with a type III corrector mechanism. This inference was supported by the VX-445 binding to and unfolding suppression of the isolated F508del-NBD1 of CFTR. The VX-661 plus VX-445 treatment restored F508del-CFTR chloride channel function in the presence of VX-770 to approximately 62% of WT CFTR in homozygous nasal epithelia. Substantial rescue of rare misprocessing mutations (S13F, R31C, G85E, E92K, V520F, M1101K, and N1303K), confined to MSD1, MSD2, NBD1, and NBD2 of CFTR, was also observed in airway epithelia, suggesting an allosteric correction mechanism and the possible application of Trikafta for patients with rare misfolding mutants of 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 | 0.000 |
| 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".