Identification of peptide inhibitors of<i>Pseudomonas aeruginosa</i>exotoxin A function using a yeast two-hybrid approach
Bibliographic record
Abstract
The yeast two-hybrid system was used to identify peptide inhibitors of exotoxin A of Pseudomonas aeruginosa with the goal of using these to design peptide-based drugs against the toxin. A random peptide library consisting of 10(7) peptides ranging in length from 16 to 63 residues was screened for peptides that interact with the C-domain of exotoxin A. From the 10(7) transformants screened, three unique peptides of 63, 61 and 25 amino acids in length were found to specifically interact with the enzyme domain. The genes encoding these peptides were cloned and expressed as fusion proteins with the maltose-binding protein. In vitro inhibition measurements indicated that two of the peptides were modest inhibitors of toxin enzyme activity. These peptides now provide the basis for the development of more potent inhibitors, which will serve as lead inhibitors for evolution of potent peptide-based therapeutics.
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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) | 0.001 | 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".