The Influence of Ligand Valency on Aggregation Mechanisms for Inhibiting Bacterial Toxins
Bibliographic record
Abstract
Divalent and tetravalent analogues of ganglioside GM1 are potent inhibitors of cholera toxin and Escherichia coli heat-labile toxin. However, they show little increase in inherent affinity when compared to the corresponding monovalent carbohydrate ligand. Analytical ultracentrifugation and dynamic light scattering have been used to demonstrate that the multivalent inhibitors induce protein aggregation and the formation of space-filling networks. This aggregation process appears to arise when using ligands that do not match the valency of the protein receptor. While it is generally accepted that multivalency is an effective strategy for increasing the activity of inhibitors, here we show that the valency of the inhibitor also has a dramatic effect on the kinetics of aggregation and the stability of intermediate protein complexes. Structural studies employing atomic force microscopy have revealed that a divalent inhibitor induces head-to-head dimerization of the protein toxin en route to higher aggregates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".