Polyphosphate Kinase 2 (PPK2) Enzymes: Structure, Function, and Roles in Bacterial Physiology and Virulence
Bibliographic record
Abstract
Inorganic polyphosphate (polyP) has been implicated in an astonishing array of biological functions, ranging from phosphorus storage to molecular chaperone activity to bacterial virulence. In bacteria, polyP is synthesized by polyphosphate kinase (PPK) enzymes, which are broadly subdivided into two families: PPK1 and PPK2. While both enzyme families are capable of catalyzing polyP synthesis, PPK1s preferentially synthesize polyP from nucleoside triphosphates, and PPK2s preferentially consume polyP to phosphorylate nucleoside mono- or diphosphates. Importantly, many pathogenic bacteria such as Pseudomonas aeruginosa and Acinetobacter baumannii encode at least one of each PPK1 and PPK2, suggesting these enzymes may be attractive targets for antibacterial drugs. Although the majority of bacterial polyP studies to date have focused on PPK1s, PPK2 enzymes have also begun to emerge as important regulators of bacterial physiology and downstream virulence. In this review, we specifically examine the contributions of PPK2s to bacterial polyP homeostasis. Beginning with a survey of the structures and functions of biochemically characterized PPK2s, we summarize the roles of PPK2s in the bacterial cell, with a particular emphasis on virulence phenotypes. Furthermore, we outline recent progress on developing drugs that inhibit PPK2 enzymes and discuss this strategy as a novel means of combatting bacterial infections.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".