Disruption of β-Catenin/B-Cell Lymphoma 9 Protein–Protein Interaction Using Heterogeneous Peptidomimetic Foldamers
Bibliographic record
Abstract
Aberrant activation of the Wnt/β-catenin-signaling pathway is closely linked to the development and progression of colorectal cancer (CRC) and other malignancies. Targeting and inhibiting this pathway has proved to be a promising approach for the development of antitumor drugs. In this study, we designed and synthesized a series of helical 1:1 α/sulfonyl-γ-AApeptide inhibitors aiming to disrupt the interaction between β-catenin and BCL9. Circular dichroism spectroscopy and modeling studies suggest that these 1:1 α/sulfonyl-γ-AApeptides adopt a right-handed helical conformation and effectively mimic the crucial side chains of BCL9, with the most potent compound exhibiting nanomolar affinity for β-catenin. Notably, these peptidomimetics possess excellent permeability, allowing them to penetrate CRC cancer cells, downregulate Wnt target genes, disrupt the cellular β-catenin/BCL9 protein-protein interaction (PPI), and significantly reduce the proliferation of Wnt-hyperactive cell lines. Furthermore, these hybrid peptidomimetics demonstrate enhanced serum stability, which augments their potential as therapeutic agents for future applications. In addition, this study paves a new way to modulate a myriad of PPIs.
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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) | 0.001 | 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".