Bacterial proteases, untapped antimicrobial drug targets
Bibliographic record
Abstract
Bacterial proteases are an extensive collection of enzymes that have vital roles in cell viability, stress response and pathogenicity. Although their perturbation clearly offers the potential for antimicrobial drug development, both as traditional antibiotics and anti-virulence drugs, they are not yet the target of any clinically used therapeutics. Here we describe the potential for and recent progress in the development of compounds targeting bacterial proteases with a focus on AAA+ family proteolytic complexes and signal peptidases (SPs). Caseinolytic protease (ClpP) belongs to the AAA+ family of proteases, a group of multimeric barrel-shaped complexes whose activity is tightly regulated by associated AAA+ ATPases. The opportunity for chemical perturbation of these complexes is demonstrated by compounds targeting ClpP for inhibition, activation or perturbation of its associated ATPase. Meanwhile, SPs are also a proven antibiotic target. Responsible for the cleavage of targeting peptides during protein secretion, both type I and type II SPs have been successfully targeted by chemical inhibitors. As the threat of pan-antibiotic resistance continues to grow, these and other bacterial proteases offer an arsenal of novel antibiotic targets ripe for 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".