Real-time Monitoring of the Interactions of Transforming Growth Factor-β (TGF-β) Isoforms with Latency-associated Protein and the Ectodomains of the TGF-β Type II and III Receptors Reveals Different Kinetic Models and Stoichiometries of Binding
Bibliographic record
Abstract
Mature transforming growth factor-beta (TGF-beta) is proteolytically derived from the C terminus of a precursor protein. Latency-associated protein (LAP), the N-terminal remnant of the TGF-beta precursor, is able to bind and neutralize TGF-beta. Mature TGF-beta exerts its activity by binding and complexing members of two subfamilies of receptors, the type I and II receptors. In addition to these signaling receptors, TGF-beta can also interact with an accessory receptor termed the type III receptor. Using a surface plasmon resonance-based biosensor (BIAcore), we determined the mechanisms of interaction of four binding proteins (LAP, the type II and III receptor ectodomains (EDs), and a type II receptor ED/Fc chimera) with three TGF-beta isoforms, and we quantified their related kinetic parameters. Using global fitting based on a numerical integration data analysis method, we demonstrated that LAP and the type II receptor/Fc chimera interacted with the TGF-beta isoforms with a 1:1 stoichiometry. In contrast, the type II ED interactions with TGF-beta were best fit by a kinetic model assuming the presence of two independent binding sites on the ligand molecule. We also showed that the type III ED bound two TGF-beta molecules. Further experiments revealed that LAP was able to block the interactions of TGF-beta with the two EDs, but that the two EDs did not compete or cooperate with each other. Together, these results strongly support the existence of a cell-surface complex consisting of one type III receptor, two TGF-beta molecules, and four type II receptors, prior to the recruitment of the type I receptor for signal transduction. Additionally, our results indicate that the apparent dissociation rate constants are more predictive of the neutralizing potency of these TGF-beta-binding proteins (LAP, the type II and III receptor EDs, and the type II receptor/Fc chimera) than the apparent equilibrium constants.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".