Critical Residues at the Ly49 Natural Killer Receptor’s Homodimer Interface Determine Functional Recognition of m157, a Mouse Cytomegalovirus MHC Class I-Like Protein
Bibliographic record
Abstract
NK cell function is regulated by Ly49 receptors in mice and killer cell Ig-like receptors in humans. Although inhibitory Ly49 and killer cell Ig-like receptors predominantly ligate classical MHC class I molecules, recent studies suggest that their activating counterparts recognize infection. The quintessential example is resistance to the mouse CMV in C57BL/6 mice, which depends on the functional recognition of m157, a mouse CMV-encoded MHC class I-like molecule, by Ly49H, an activating NK cell receptor. We have taken advantage of the natural variation in closely related members of the Ly49C-like receptors and the availability of Ly49 crystal structures to understand the molecular determinants of the Ly49H-m157 interaction and to identify amino acid residues discriminating between m157 binding and nonbinding receptors. Using a site-directed mutagenesis approach, we have targeted residues conserved in receptors binding to m157 (Ly49H and Ly49I(129)) but different from receptors lacking m157 recognition (Ly49C, Ly49I(B6), and Ly49U). Wild-type and mutant receptors were transfected into reporter cells, and physical binding as well as functional activation by m157 was studied. Our findings suggested that the Ly49 MHC class I contact "site 2," I226, may not be involved in m157 binding. In contrast, residue Y146 and G151, mapping at the receptor homodimer interface, are likely critical for functional recognition of the m157 glycoprotein. Our combined functional and three-dimensional modeling approach suggested that the architecture of the Ly49H dimer is crucial to accessing m157, but not MHC class I. These results link Ly49 homodimerization variability to the direct recognition of pathogen products.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".