Armeniaspirols inhibit the AAA+ proteases ClpXP and ClpYQ leading to cell division arrest in Gram-positive bacteria
Bibliographic record
Abstract
ABSTRACT Multi-drug resistant bacteria present an urgent threat to modern medicine, creating a desperate need for the discovery of antibiotics with new modes of action. Natural products whose unique highly diverse structures have been shaped by evolution to possess biologically relevant activity are an ideal discovery ground for new antibiotics with new mechanisms of action. In this study we elucidate the mechanism of action of the Gram-positive antibiotic armeniaspirol, a compound for which resistant bacteria could not be selected for. We show that armeniaspirol inhibits the ATP-dependent proteases ClpXP and ClpYQ in biochemical assays and in the Gram-positive bacteria Bacillus subtilis. We then show that this activity dysregulates key proteins involved in the divisome and elongasome including FtsZ, DivIVA, and MreB all of which are known to inhibit cell division when upregulated. Inhibition of ClpXP and ClpYQ leading to dysregulation of the divisome and elongasome represents a new mechanism of action and armeniaspirol is the first known natural product inhibitor of the coveted anti-virulence target ClpP. Thus armeniaspirol is the lead compound for a promising new class of antibiotics with a unique pharmacology and a novel mechanism for combating antimicrobial resistance, making it a highly promising candidate for further development.
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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".