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Record W2950763275 · doi:10.1101/213264

The C-terminal extension landscape of naturally presented HLA-I ligands

2017· preprint· en· W2950763275 on OpenAlexfundno aff
Philippe Guillaume, S. Picaud, Petra Baumgaertner, Nicole Montandon, Julien Schmidt, Daniel E. Speiser, George Coukos, Michal Bassani‐Sternberg, Panagis Fillipakopoulos, David Gfeller

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicvaccines and immunoinformatics approaches
Canadian institutionsnot available
FundersOntario Ministry of Economic Development and InnovationEuropean Federation of Pharmaceutical Industries and AssociationsNovartis PharmaWellcome TrustMinistero dello Sviluppo EconomicoFundação de Amparo à Pesquisa do Estado de São PauloDiamond Light SourceGenome CanadaPfizer
KeywordsEpitopeHuman leukocyte antigenComputational biologyBiologyAlleleExtension (predicate logic)HLA-AGeneticsChemistryAntigenComputer scienceGene

Abstract

fetched live from OpenAlex

Abstract HLA-I molecules play a central role in antigen presentation. They typically bind 9- to 12-mer peptides and their canonical binding mode involves anchor residues at the second and last positions of their ligands. To investigate potential non-canonical binding modes we collected in-depth and accurate HLA peptidomics datasets covering 54 HLA-I alleles and developed novel algorithms to analyze these data. Our results reveal frequent (442 unique peptides) and statistically significant C-terminal extensions for at least eight alleles, including the common HLA-A03:01, HLA-A31:01 and HLA-A68:01. High resolution crystal structure of HLA-A68:01 with such a ligand uncovers structural changes taking place to accommodate C-terminal extensions and helps unraveling sequence and structural properties predictive of the presence of these extensions. Scanning viral proteomes with the new C-terminal extension motifs identifies many putative epitopes and we demonstrate direct recognition by human CD8+ T cells of a C-terminally extended epitope from cytomegalovirus.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.228
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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