Synthetic Peptides with Inadvertent Chemical Modifications Can Activate Potentially Autoreactive T Cells
Bibliographic record
Abstract
Abstract The human CD8+ T cell clone 6C5 has previously been shown to recognize the tert-butyl-modified Bax161–170 peptide LLSY(3-tBu)FGTPT presented by HLA-A*02:01. This nonnatural epitope was likely created as a by-product of fluorenylmethoxycarbonyl protecting group peptide synthesis and bound poorly to HLA-A*02:01. In this study, we used a systematic approach to identify and characterize natural ligands for the 6C5 TCR. Functional analyses revealed that 6C5 T cells only recognized the LLSYFGTPT peptide when tBu was added to the tyrosine residue and did not recognize the LLSYFGTPT peptide modified with larger (di-tBu) or smaller chemical groups (Me). Combinatorial peptide library screening further showed that 6C5 T cells recognized a series of self-derived peptides with dissimilar amino acid sequences to LLSY(3-tBu)FGTPT. Structural studies of LLSY(3-tBu)FGTPT and two other activating nonamers (IIGWMWIPV and LLGWVFAQV) in complex with HLA-A*02:01 demonstrated similar overall peptide conformations and highlighted the importance of the position (P) 4 residue for T cell recognition, particularly the capacity of the bulky amino acid tryptophan to substitute for the tBu-modified tyrosine residue in conjunction with other changes at P5 and P6. Collectively, these results indicated that chemical modifications directly altered the immunogenicity of a synthetic peptide via molecular mimicry, leading to the inadvertent activation of a T cell clone with unexpected and potentially autoreactive specificities.
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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".