Design and synthesis of a bifunctional inhibitor to prevent infection by Vibrio cholerae
Bibliographic record
Abstract
Vibrio cholerae is the causative agent of cholera, a gastrointestinal infection which kills more than 100 000 people each year and infects over 1.3 million others. This bacterium attaches to its hosts using a long fibrillar adhesin called FrhA, which contains two ligand-binding domains: a carbohydrate-binding module (CBM) which binds fucosylated glycans, and a protein-binding domain (PBD) with high nanomolar affinity for the sequence Tyr-Thr-Asp at the C-terminal end. Using these known ligands to block the function of FrhA presents an attractive strategy for preventing host colonization by V. cholerae. Guided by an AlphFold3 model of FrhA, we designed a bifunctional inhibitor containing both fucose and the Tyr-Thr-Asp motif tethered by a flexible, water-soluble PEG-peptide linker. The sugar and peptide ligands were individually pre-functionalized with alkyne and azido groups, respectively, prior to synthesis of the inhibitor by a copper-catalyzed alkyne azide cycloaddition (“click”) reaction. With a linker size commensurate to the distance between ligand-binding domains, this inhibitor should simultaneously block both sites, offering a much higher affinity than the free peptide or carbohydrate ligands alone. In addition, the inclusion of the Tyr-Thr-Asp sequence within the bifunctional ligand increases its specificity for Vibrio cholerae over beneficial bacteria in the gut microbiome that may also attach to fucosylated glycans. Further studies will quantify the relative binding affinity of this inhibitor for FrhA compared to the two free ligands. Moreover, with its relative ease of design and simple, high yield “click” synthesis, this bifunctional inhibitor approach could be adapted to specifically inhibit the adhesins of other bacterial pathogens. Supported by GlycoNet and CIHR.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".