Long-range cooperative binding effects in a T cell receptor variable domain
Bibliographic record
Abstract
Although cellular processes depend on protein-protein interactions, our understanding of molecular recognition between proteins remains far from comprehensive. Protein-protein interfaces are structural and energetic mosaics in which a subset of interfacial residues, called hot spots, contributes disproportionately to the affinity of the complex. These hot-spot residues can be further clustered into hot regions. It has been proposed that binding energetics between residues within a hot region are cooperative, whereas those between hot regions are strictly additive. If this idea held true for all protein-protein interactions, then energetically significant long-range conformational effects would be unlikely to occur. In the present study, we show cooperative binding energetics between distinct hot regions that are separated by >20 A. Using combinatorial mutagenesis and surface plasmon resonance binding analysis to dissect additivity and cooperativity in a complex formed between a variable domain of a T cell receptor and a bacterial superantigen, we find that combinations of mutations from each of two hot regions exhibited significant cooperative energetics. Their connecting sequence is composed primarily of a single beta-strand of the T cell receptor variable Ig domain, which has been observed to undergo a strand-switching event and does not form an integral part of the stabilizing core of this Ig domain. We propose that these cooperative effects are propagated through a dynamic structural network. Cooperativity between hot regions has significant implications for the prediction and inhibition of protein-protein interactions.
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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 | 0.001 | 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 | 0.001 |
| 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".