The Nod-Like Receptor (NLR) Family: A Tale of Similarities and Differences
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Bibliographic record
Abstract
Innate immunity represents an important system with a variety of vital processes at the core of many diseases. In recent years, the central role of the Nod-like receptor (NLR) protein family became increasingly appreciated in innate immune responses. NLRs are classified as part of the signal transduction ATPases with numerous domains (STAND) clade within the AAA+ ATPase family. They typically feature an N-terminal effector domain, a central nucleotide-binding domain (NACHT) and a C-terminal ligand-binding region that is composed of several leucine-rich repeats (LRRs). NLRs are believed to initiate or regulate host defense pathways through formation of signaling platforms that subsequently trigger the activation of inflammatory caspases and NF-kB. Despite their fundamental role in orchestrating key pathways in innate immunity, their mode of action in molecular terms remains largely unknown. Here we present the first comprehensive sequence and structure modeling analysis of NLR proteins, revealing that NLRs possess a domain architecture similar to the apoptotic initiator protein Apaf-1. Apaf-1 performs its cellular function by the formation of a heptameric platform, dubbed apoptosome, ultimately triggering the controlled demise of the affected cell. The mechanism of apoptosome formation by Apaf-1 potentially offers insight into the activation mechanisms of NLR proteins. Multiple sequence alignment analysis and homology modeling revealed Apaf-1-like structural features in most members of the NLR family, suggesting a similar biochemical behaviour in catalytic activity and oligomerization. Evolutionary tree comparisons substantiate the conservation of characteristic functional regions within the NLR family and are in good agreement with domain distributions found in distinct NLRs. Importantly, the analysis of LRR domains reveals surprisingly low conservation levels among putative ligand-binding motifs. The same is true for the effector domains exhibiting distinct interfaces ensuring specific interactions with downstream target proteins. All together these factors suggest specific biological functions for individual NLRs.
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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 | 0.000 |
| 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 it