Nanomechanics combined with HDX reveal allosteric drug binding sites of CFTR NBD1
Bibliographic record
Abstract
Abstract Cystic fibrosis is most frequently caused by the deletion of F508 (ΔF508) in CFTR’s nucleotide binding domain 1 (NBD1), compromising CFTR folding, stability and domain assembly. The limitation of developing a successful therapy is due to the lack of molecules that synergistically facilitate folding by targeting distinct structural defects of ΔF508-CFTR. To improve drug efficacy by targeting the ΔF508-NBD1 folding and stability, and to study potential ΔF508-NBD1 allosteric corrector binding sites at the atomic level, we combined molecular dynamics (MD) simulations, atomic force spectroscopy (AFM) and hydrogen-deuterium exchange (HDX) experiments. These methods allowed us to describe unfolding intermediates and forces acting during NBD1 mechanical unfolding and to elucidate the stabilization mechanism of ΔF508-NBD1 by 5-bromoindole-3-acetic acid (BIA). An NBD1 region, including the α-subdomain, was identified as a potentially important participant of the first folding steps, characterized by non-native interactions of F508, thus destabilized in the deletion mutant. The instability was counteracted by the low-potency corrector BIA, increasing the mechanical resistance of the ΔF508-NBD1 α-subdomain, which was confirmed as a binding site by computational modeling and HDX experiments. Our results underline the complementarity of computational and experimental methods and provide a possible strategy to improve folding correctors.
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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) | 0.002 | 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".