Molecular basis for inhibition of adhesin-mediated bacterial-host interactions through a novel peptide-binding domain
Bibliographic record
Abstract
Abstract Modulation of protein-protein interactions (PPIs) with small-molecules is a promising conceptual approach in drug discovery. In the area of bacterial colonization, PPIs contribute to adhesin-mediated biofilm formation that cause most infections. However, the molecular basis underlying these adhesin-ligand interactions is largely unknown. The 1.5-MDa adhesion protein, MpIBP, uses a peptide-binding domain ( Mp PBD) to help its Antarctic bacterium form symbiotic biofilms on sea ice with microalgae such as diatoms. X-ray crystallography revealed Mp PBD uses Camdependent interactions to self-associate with a crystal symmetry mate via the C-terminal threonine-proline-aspartate sequence. Structure-guided optimization derived penta-peptide ligands that bound Mp PBD 1,000-fold more tightly, with affinities in the nano-molar range. These ligands act as potent antagonists to block Mp PBD from binding to the diatom cells. Since adhesins of some human pathogens contain peptide-binding module homologs of Mp PBD, this same conceptual approach could help develop ligand-based PPI modulators to disrupt harmful bacteria-host interactions.
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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) | 0.002 | 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".