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Record W2512802152 · doi:10.1093/protein/gzw043

Isolation of TGF-β-neutralizing single-domain antibodies of predetermined epitope specificity using next-generation DNA sequencing

2016· article· en· W2512802152 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProtein Engineering Design and Selection · 2016
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of GuelphWilfrid Laurier UniversityUniversity of OttawaNational Research Council Canada
Fundersnot available
KeywordsEpitopePanning (audio)Phage displayAntibodyMolecular biologyEpitope mappingBiologyComputational biologySingle-domain antibodyEctodomainReceptorGenetics

Abstract

fetched live from OpenAlex

The epitope specificity of therapeutic antibodies is often critical to their efficacy and mode of action. Here, we report the isolation of single-domain antibodies (sdAbs) against a pre-specified epitope of TGF-β3: namely, the site of interaction between the cytokine and its cell-surface type II receptor. By panning a phage-displayed immune llama VhH library against TGF-β3 using competitive elution with soluble dimeric type II receptor ectodomain in tandem with next-generation DNA sequencing, we identified several sdAbs that competed with the receptor for TGF-β3 binding and neutralized TGF-β3 in in vitro cellular assays. In contrast, all other sdAbs identified using conventional panning approaches (i.e., without regard to epitope specificity) did not target the site of receptor:cytokine interaction. We expect this strategy to be generally applicable for identifying epitope-specific sdAbs when binding reagents directed against the epitope of interest are available. The sdAbs identified here are of potential interest as cancer immunotherapeutics.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.267
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.110
GPT teacher head0.277
Teacher spread0.167 · 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