Bibliographic record
Abstract
Antibiotic kinases, which include aminoglycoside and macrolide phosphotransferases (APHs and MPHs), pose a serious threat to currently used antimicrobial therapies. These enzymes show structural and functional homology with Ser/Thr/Tyr kinases, which is suggestive of a common ancestor. Surprisingly, recent in vitro studies using purified antibiotic kinase enzymes have revealed that a number are able to utilize GTP as the antibiotic phospho donor, either preferentially or exclusively compared to ATP, the canonical phosphate donor in most biochemical reactions. To further explore this phenomenon, we examined three enzymes, APH(3')-IIIa, APH(2'')-Ib, and MPH(2')-I, using a competitive assay that mimics in vivo nucleotide triphosphate (NTP) concentrations and usage by each enzyme. Downstream analysis of reaction products by high-performance liquid chromatography enabled the determination of partitioning of phosphate flux from NTP donors to antibiotics. Using this ratio along with support from kinetic analysis and inhibitor studies, we find that under physiologic concentrations of NTPs, APH(3')-IIIa exclusively uses ATP, MPH(2')-I exclusively uses GTP, and APH(2'')-Ib is able to use both species with a preference for GTP. These differences reveal likely different pathways in antibiotic resistance enzyme evolution and can be exploited in selective inhibitor design to counteract resistance.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".