Effects of phosphorylation on the NLRP3 inflammasome
Bibliographic record
Abstract
The pyrin domain containing Nod-like receptors (NLRPs) are a family of pattern recognition receptors known to regulate an array of immune signaling pathways. Emergent studies demonstrate the potential for regulatory control of inflammasome assembly by phosphorylation, notably NLRP3. Over a dozen phosphorylation sites have been identified for NLRP3 with many more suggested by phosphoproteomic studies of the NLRP family. Well characterized NLRP3 phosphorylation events include Ser198 by c-Jun terminal kinase (JNK), Ser295 by protein kinase D (PKD) and/or protein kinase A (PKA), and Tyr861 by an unknown kinase but is dephosphorylated by protein tyrosine phosphatase non-receptor 22 (PTPN22). Since the PKA- and PKD-dependent phosphorylation of NLRP3 at Ser295 is best characterized, we provide detailed review of this aspect of NLRP3 regulation. Phosphorylation of Ser295 can attenuate ATPase activity as compared to its dephosphorylated counterpart, and this event is likely unique to NLRP3. In silico modeling of NLRP3 is useful in predicting how Ser295 phosphorylation might impact upon the structural topology of the ATP-binding domain to influence catalytic activity. It is important to gain as complete understanding as possible of the complex phosphorylation-mediated mechanisms of regulation for NLRP3 in part because of its involvement in many pathological processes.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".