Peptidome Diversities of human leukocyte antigen (HLA-B) allotypes
Bibliographic record
Abstract
Abstract The HLA class I genes encode proteins that present short peptide antigen to CD8 T cells, thereby alerting the immune system to the presence of intracellular pathogens and cancers. The HLA class I genes are highly polymorphic, and the polymorphisms influence their peptide-binding specificities. Each HLA variant binds to a diverse array of peptides, the peptidome. Much remains to be understood about HLA class I peptidome diversity variations and their influencing factors. Here we validate the use of Shannon entropy (SE) plots to quantify and compare the diversities of HLA class I peptidomes derived from multiple independently-derived mass spectrometric (MS) data sets. The intrinsic peptide-binding preferences of HLA class I molecules and/or their intracellular assembly characteristics could influence their peptidome diversities. In particular, tapasin is an assembly factor that edits and optimizes the peptide repertoire of many HLA class I molecules, but is non-essential for several other HLA class I molecules. It has been suggested that a tapasin-independent assembly pathway could result in a broader, more diverse peptide repertoire. However, MS-based comparisons indicate that, under cellular conditions of tapasin sufficiency, the peptidome of HLA-B*4405 (a prototypic tapasin-independent allotype) is not more diverse than that of HLA-B*4402 (a prototypic tapasin-dependent allotype). Rather, the intrinsic peptide-binding specificity of HLA-B4402 results in greater length and C-terminal sequence diversity of its peptidome. Together, these studies indicate that structural constraints imposed by MHC class I peptide binding grooves are key determinants of their peptidome diversities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".