Identification of Native and Posttranslationally Modified HLA‐B*57:01‐Restricted HIV Envelope Derived Epitopes Using Immunoproteomics
Bibliographic record
Abstract
The recognition of pathogen-derived peptides by T lymphocytes is the cornerstone of adaptive immunity, whereby intracellular antigens are degraded in the cytosol and short peptides assemble with class I human leukocyte antigen (HLA) molecules in the ER. These peptide-HLA complexes egress to the cell surface and are scrutinized by cytotoxic CD8+ T-cells leading to the eradication of the infected cell. Here, naturally presented HLA-B*57:01 bound peptides derived from the envelope protein of the human immunodeficiency virus (HIVenv) are identified. HIVenv peptides are present at a very small percentage of the overall HLA-B*57:01 peptidome (<0.1%) and both native and posttranslationally modified forms of two distinct HIV peptides are identified. Notably, a peptide bearing a natively encoded C-terminal tryptophan residue is also present in a modified form containing a kynurenine residue. Kynurenine is a major product of tryptophan catabolism and is abundant during inflammation and infection. Binding of these peptides at a molecular level and their immunogenicity in preliminary functional studies are examined. Modest immune responses are observed to the modified HIVenv peptide, highlighting a potential role for kynurenine-modified peptides in the immune response to HIV and other viral 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) | 0.000 | 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) | 0.001 | 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 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".