The serum protein transthyretin as a platform for dimerization and tetramerization of antibodies and Fab fragments to enable target clustering
Bibliographic record
Abstract
Transthyretin (TTR) is an abundant homotetrameric serum protein and was selected here for engineering higher-valency molecules because of its compact size, simple structure, and natural propensity to tetramerize. To demonstrate this utility, we fused TTR to the C terminus of conatumumab, an antibody that targets tumor necrosis factor-related apoptosis-inducing ligand receptor 2, as heavy chains to form antibody dimers and Fab heavy chains to form Fab tetramers. Moreover, we used constant heavy domain 3 heterodimerization substitutions to create TTR-mediated conatumumab tetramers. The conatumumab-TTR fusions displayed substantially enhanced potency in cell-based assays, as well as in murine tumor xenograft models. We conclude that antibody-TTR fusions may provide a powerful platform for multimerizing antibody and Fab fragments to enhance the capabilities of human therapeutics that benefit from target clustering and higher-order antigen-binding valency.
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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 | 0.001 |
| 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".