Development and characterization of synthetic antibodies binding to the cystic fibrosis conductance regulator
Bibliographic record
Abstract
Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel in the apical surface of epithelial cells in the airway and gastrointestinal tract, and mutation of CFTR is the underlying cause of cystic fibrosis. However, the precise molecular details of the structure and function of CFTR in native and disease states remains elusive and cystic fibrosis researchers are hindered by a lack of high specificity, high affinity binding reagents for use in structural and biological studies. Here, we describe a panel of synthetic antigen-binding fragments (Fabs) isolated from a phage-displayed library that are specific for intracellular domains of CFTR that include the nucleotide-binding domains (NBD1 and NBD2), the R-region, and the regulatory insertion loop of NBD1. Binding assays performed under conditions that promote the native fold of the protein demonstrated that all Fabs recognized full-length CFTR. However, only the NBD1-specific Fab recognized denatured CFTR by western blot, suggesting a conformational epitope requirement for the other Fabs. Surface plasmon resonance experiments showed that the R-region Fab binds with high affinity to both the phosphorylated and unphosphorylated R-region. In addition, NMR analysis of bound versus unbound R-region revealed a distinct conformational effect upon Fab binding. We further defined residues involved with antibody recognition using an overlapping peptide array. In summary, we describe methodology complementary to previous hybridoma-based efforts to develop antibody reagents to CFTR, and introduce a synthetic antibody panel to aid structural and biological studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".