Sequence edition of single domains modulates the final immune and antimicrobial potential of a new generation of multidomain recombinant proteins
Bibliographic record
Abstract
Abstract Combining several innate immune peptides into a single recombinant antimicrobial and immunomodulatory polypeptide has been recently demonstrated. However, the versatility of the multidomain design, the role that each domain plays and how the sequence edition of the different domains affects their final protein activity is unknown. Parental multidomain antimicrobial and immunomodulatory protein JAMF1 and several protein variants (JAMF1.2, JAMF2 and AM2) have been designed and recombinantly produced to explore how the tuning of domain sequences affects their immunomodulatory potential in epithelial cells and their antimicrobial capacity against Gram-positive and Gram-negative bacteria. The replacement of the sequence of defensin HD5 and phospholipase sPLA2 by shorter active fragments of both peptides improves the final immunomodulatory (IL-8 secretion) and antimicrobial function of the multidomain protein against antimicrobial-resistant Klebsiella pneumoniae and Enterococcus spp. Further, the presence of Jun and Fos leucine zippers in multidomain proteins is crucial in preventing toxic effects on producer cells. The generation of antimicrobial proteins based on multidomain polypeptides allows specific immunomodulatory and antimicrobial functions, which can be easily edited by modifying of each domain sequence.
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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) | 0.001 | 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".