Peptide inhibitors of the essential cell division protein FtsA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The revolutionary era of antibiotics has been overwhelmed by the evolutionary capacity of microorganisms such as Pseudomonas aeruginosa to develop resistance to all classes of antibiotics. In the perspective of identifying new antimicrobials using novel strategies, we targeted the essential and highly conserved FtsA protein from the bacterial cell division machinery of P.aeruginosa. In a series of experiments we cloned, overproduced and purified the FtsA and FtsZ proteins. Expression of FtsA into Escherichia coli cells led to its accumulation in inclusion bodies. We developed a protocol permitting the purification and refolding of enzymatically active FtsA hydrolysing ATP. The purified enzyme was used to screen for peptide inhibitors of ATPase activity using phage display. Selective biopanning assays were done and phages were eluted using ATP, a non-hydrolysable ATP analogue and the protein FtsZ known to interact with FtsA in the divisome during the process of bacterial cell division. We identified two consensus peptide sequences interacting with FtsA and a competitive ELISA was used to identify peptides having high affinity for the target protein. Five of the six peptides synthesized showed specific inhibition of ATPase activity of FtsA with IC50 values between 0.7 and 35 mM. Discovery of peptides inhibiting the essential cell division machinery in bacteria is the first step for the future development of antimicrobial agents via peptidomimetism.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it