A screen for kinase inhibitors identifies antimicrobial imidazopyridine aminofurazans as specific inhibitors of the Listeria monocytogenes PASTA kinase PrkA
Bibliographic record
Abstract
Bacterial signaling systems such as protein kinases and quorum sensing have become increasingly attractive targets for the development of novel antimicrobial agents in a time of rising antibiotic resistance. The family of bacterial Penicillin-binding-protein And Serine/Threonine kinase-Associated (PASTA) kinases is of particular interest due to the role of these kinases in regulating resistance to β-lactam antibiotics. As such, small-molecule kinase inhibitors that target PASTA kinases may prove beneficial as treatments adjunctive to β-lactam therapy. Despite this interest, only limited progress has been made in identifying functional inhibitors of the PASTA kinases that have both activity against the intact microbe and high kinase specificity. Here, we report the results of a small-molecule screen that identified GSK690693, an imidazopyridine aminofurazan-type kinase inhibitor that increases the sensitivity of the intracellular pathogen Listeria monocytogenes to various β-lactams by inhibiting the PASTA kinase PrkA. GSK690693 potently inhibited PrkA kinase activity biochemically and exhibited significant selectivity for PrkA relative to the Staphylococcus aureus PASTA kinase Stk1. Furthermore, other imidazopyridine aminofurazans could effectively inhibit PrkA and potentiate β-lactam antibiotic activity to varying degrees. The presence of the 2-methyl-3-butyn-2-ol (alkynol) moiety was important for both biochemical and antimicrobial activity. Finally, mutagenesis studies demonstrated residues in the back pocket of the active site are important for GSK690693 selectivity. These data suggest that targeted screens can successfully identify PASTA kinase inhibitors with both biochemical and antimicrobial specificity. Moreover, the imidazopyridine aminofurazans represent a family of PASTA kinase inhibitors that have the potential to be optimized for selective PASTA kinase inhibition.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".