Design of Monodisperse and Well‐Defined Polypeptide‐Based Polyvalent Inhibitors of Anthrax Toxin
Bibliographic record
Abstract
The design of polyvalent molecules, presenting multiple copies of a specific ligand, represents a promising strategy to inhibit pathogens and toxins. The ability to control independently the valency and the spacing between ligands would be valuable for elucidating structure-activity relationships and for designing potent polyvalent molecules. To that end, we designed monodisperse polypeptide-based polyvalent inhibitors of anthrax toxin in which multiple copies of an inhibitory toxin-binding peptide were separated by flexible peptide linkers. By tuning the valency and linker length, we designed polyvalent inhibitors that were over four orders of magnitude more potent than the corresponding monovalent ligands. This strategy for the rational design of monodisperse polyvalent molecules may not only be broadly applicable for the inhibition of toxins and pathogens, but also for controlling the nanoscale organization of cellular receptors to regulate signaling and the fate of stem cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".