Selective and Potent Peptide Binders of RNF43 for Wnt Signaling Inhibition
Bibliographic record
Abstract
The Wnt/β-catenin pathway is critical in human tumor progression. Cell-surface transmembrane E3 ubiquitin ligase ring finger 43 negatively regulates Wnt signaling through ubiquitination of Wnt coreceptor Frizzled. Aberrant Wnt signaling through inactivating mutations of RNF43 has been identified in various forms of cancers, highlighting its significance in tumor biology. However, the precise mechanism underlying the function of RNF43 remains elusive, largely due to the absence of selective molecular tools allowing for detection or manipulation of endogenous RNF43. Here we present a series of disulfide-constrained peptides, including GUR-1.6.12.2, which exhibit high affinity and specificity against RNF43. GUR-1.6.12.2 can be used as a valuable research tool to delineate RNF43 activity in various contexts. We showcased its application in immunofluorescence, where RNF43 was detected in intestinal crypts using biotinylated GUR-1.6.12.2. We then combined experimental and computational structural approaches to propose a model of GUR-1.6.12.2 and its binding to RNF43. Importantly, we generated a functional RNF43-DCP by producing a hexavalent GUR-1.6.12.2 molecule, which exhibited inhibitory activity against Wnt signaling in cells by competing with R-spondin, a RNF43 ligand that potentiates signaling. The RNF43 binders presented here offer new opportunities for the research and development of anticancer therapies targeting Wnt signaling with improved selectivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".