Stabilization of a nucleotide-binding domain of the cystic fibrosis transmembrane conductance regulator yields insight into disease-causing mutations
Bibliographic record
Abstract
Characterization of the second nucleotide-binding domain (NBD2) of the cystic fibrosis transmembrane conductance regulator (CFTR) has lagged behind research into the NBD1 domain, in part because NBD1 contains the F508del mutation, which is the dominant cause of cystic fibrosis. Research on NBD2 has also been hampered by the overall instability of the domain and the difficulty of producing reagents. Nonetheless, multiple disease-causing mutations reside in NBD2, and the domain is critical for CFTR function, because channel gating involves NBD1/NBD2 dimerization, and NBD2 contains the catalytically active ATPase site in CFTR. Recognizing the paucity of structural and biophysical data on NBD2, here we have defined a bioinformatics-based method for manually identifying stabilizing substitutions in NBD2, and we used an iterative process of screening single substitutions against thermal melting points to both produce minimally mutated stable constructs and individually characterize mutations. We present a range of stable constructs with minimal mutations to help inform further research on NBD2. We have used this stabilized background to study the effects of NBD2 mutations identified in cystic fibrosis (CF) patients, demonstrating that mutants such as N1303K and G1349D are characterized by lower stability, as shown previously for some NBD1 mutations, suggesting a potential role for NBD2 instability in the pathology of CF.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".