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Record W4399129199 · doi:10.1101/2024.05.24.595718

Systematic analysis of CDR contacts and sequence constraints between T cell receptor <i>αβ</i> chains

2024· preprint· en· W4399129199 on OpenAlexaff
Martina Milighetti, Yuta Nagano, James Henderson, Uri Hershberg, Andreas Mayer, Anne‐Florence Bitbol, Benny Chain

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsInstitute of Infection and Immunity
FundersRoyal Free CharityNational Institute of Allergy and Infectious DiseasesIsrael Science FoundationCancer Research UK
KeywordsPairingT-cell receptorComputational biologyChemistryCell biologyComputer scienceBiologyPhysicsGeneticsT cellCondensed matter physicsImmune system

Abstract

fetched live from OpenAlex

Abstract The six complementarity determining regions (CDRs) of the T cell receptor (TCR) form multiple contacts with cognate peptide and major histocompatibility complex, thus determining antigen specificity. However, the contacts between the CDRs themselves are less understood. We perform a systematic study of all available TCR structures, and identify consistent patterns of intra- and inter-chain CDR contacts. We further show that the sequences of paired TCR α and TCR β are not independent within sets of antigen-specific TCRs, for most epitopes. We quantify this sequence restriction using a mutual information framework. Co-evolution models can achieve some de novo prediction of TCR α /TCR β pairing, without using a training set of known pairs. The conserved pattern of CDR amino acid contacts, and the mutual sequence constraints between antigen-specific sets of T cell receptor α and β chains could play an important role in shaping the antigen-specific T cell repertoire.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2024
Admission routes1
Has abstractyes

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Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicAdvanced Proteomics Techniques and ApplicationsFrench-language works237,207