CFTR transmembrane segments are impaired in their conformational adaptability by a pathogenic loop mutation and dynamically stabilized by Lumacaftor
Bibliographic record
Abstract
The cystic fibrosis transmembrane conductance regulator (CFTR) is an ion channel protein that is defective in individuals with cystic fibrosis (CF). To advance the rational design of CF therapies, it is important to elucidate how mutational defects in CFTR lead to its impairment and how pharmacological compounds interact with and alter CFTR. Here, using a helical-hairpin construct derived from CFTR's transmembrane (TM) helices 3 and 4 (TM3/4) and their intervening loop, we investigated the structural effects of a patient-derived CF-phenotypic mutation, E217G, located in the loop region of CFTR's membrane-spanning domain. Employing a single-molecule FRET assay to probe the folding status of reconstituted hairpins in lipid bilayers, we found that the E217G hairpin exhibits an altered adaptive packing behavior stemming from an additional G XXX G helix–helix interaction motif created in the mutant hairpin. This observation suggested that the misfolding and functional defects caused by the E217G mutation arise from an impaired conformational adaptability of TM helical segments in CFTR. The addition of the small-molecule corrector Lumacaftor exerts a helix stabilization effect not only on the E217G mutant hairpin, but also on WT TM3/4 and other mutations in the hairpin. This finding suggests a general mode of action for Lumacaftor through which this corrector efficiently improves maturation of various CFTR mutants.
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 | 0.000 | 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".