Structural basis for NKG2A/CD94 recognition of HLA-E
Bibliographic record
Abstract
The NKG2x/CD94 (x = A, C, E) natural killer-cell receptors perform an important role in immunosurveillance by binding to HLA-E complexes that exclusively present peptides derived from MHC class I leader sequences, thereby monitoring MHC class I expression. We have determined the crystal structure of the NKG2A/CD94/HLA-E complex at 4.4-A resolution, revealing two critical aspects of this interaction. First, the C-terminal region of the peptide, which displays the most variability among class I leader sequences, interacts entirely with CD94, the invariant component of these receptors. Second, residues 167-170 of NKG2A/C account for the approximately 6-fold-higher affinity of the inhibitory NKG2A/CD94 receptor compared to its activating NKG2C/CD94 counterpart. These residues do not contact HLA-E or peptide directly but instead form part of the heterodimer interface with CD94. An evolutionary analysis across primates reveals that whereas CD94 is evolving under purifying selection, both NKG2A and NKG2C are evolving under positive selection. Specifically, residues at the CD94 interface have evolved under positive selection, suggesting that the evolution of these genes is driven by an interaction with pathogen-derived ligands. Consistent with this possibility, we show that NKG2C/CD94, but not NKG2A/CD94, weakly but specifically binds to the CMV MHC-homologue UL18. Thus, the evolution of the NKG2x/CD94 family of receptors has likely been shaped both by the need to bind the invariant HLA-E ligand and the need to avoid subversion by pathogen-derived decoys.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".