Rapid Access to Potent Bispecific T Cell Engagers Using Biogenic Tyrosine Click Chemistry
Bibliographic record
Abstract
Bispecific antibodies as T cell engagers designed to display binding capabilities to both tumor-associated antigens and antigens on T cells are considered promising agents in the fight against cancer. Even though chemical strategies to develop such constructs have emerged, a method that readily converts a therapeutically applied antibody into a bispecific construct by a fully non-genetic process is not yet available. Herein, we report the application of a biogenic, tyrosine-based click reaction utilizing chemoenzymatic modifications of native IgG1 antibodies to generate a synthetic bispecific antibody construct that exhibits tumor-killing capability at picomolar concentrations. Control experiments revealed that a covalent linkage of the different components is required for the observed biological activities. In view of the highly potent nature of the constructs and the modular approach that relies on convenient synthetic methods utilizing therapeutically approved biomolecules, our method expedites the production of potent bispecific antibody constructs with tunable cell killing efficacy with significant impact on therapeutic properties.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".