Optical Control of Protein–Protein Interactions via Blue Light-Induced Domain Swapping
Bibliographic record
Abstract
The design of new optogenetic tools for controlling protein function would be facilitated by the development of protein scaffolds that undergo large, well-defined structural changes upon exposure to light. Domain swapping, a process in which a structural element of a monomeric protein is replaced by the same element of another copy of the same protein, leads to a well-defined change in protein structure. We observe domain swapping in a variant of the blue light photoreceptor photoactive yellow protein in which a surface loop is replaced by a well-characterized protein-protein interaction motif, the E-helix. In the domain-swapped dimer, the E-helix sequence specifically binds a partner K-helix sequence, whereas in the monomeric form of the protein, the E-helix sequence is unable to fold into a binding-competent conformation and no interaction with the K-helix is seen. Blue light irradiation decreases the extent of domain swapping (from Kd = 10 μM to Kd = 300 μM) and dramatically enhances the rate, from weeks to <1 min. Blue light-induced domain swapping thus provides a novel mechanism for controlling of protein-protein interactions in which light alters both the stability and the kinetic accessibility of binding-competent states.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".