Improving a Designed Photocontrolled DNA-Binding Protein
Bibliographic record
Abstract
Photocontrolled transcription factors could be powerful tools for probing the roles of transcriptional processes in a variety of settings. Previously, we designed a photocontrolled DNA-binding protein based on a fusion between the bZIP region of GCN4 and photoactive yellow protein from Halorhodospira halophila [Morgan, S. A., et al. (2010) J. Mol. Biol. 399, 94-112]. Here we report a structure-based attempt to improve the degree of photoswitching observed with this chimeric protein. Using computational design tools PoPMuSiC 2.0, Rosetta, Eris, and bCIPA, we identified a series of single- and multiple-point mutations that were expected to stabilize the folded dark state of the protein and thereby enhance the degree of photoswitching. While a number of these mutations, particularly those that introduced a hydrophobic residue at position 143, did significantly enhance dark-state protein stability as judged by urea denaturation studies, dark-state stability did not correlate directly with the degree of photoswitching. Instead, the influence of mutations on the degree of photoswitching was found to be related to their effects on the degree to which DNA binding slowed the pB to pG transition in the PYP photocycle. One mutant, K143F, caused an ∼10-fold slowing of the photocycle and also showed the largest difference in the apparent K(d) for DNA binding, 3.5-fold lower, upon irradiation. This change in the apparent K(d) causes a 12-fold enhancement in the fraction bound DNA upon irradiation due to the cooperativity of DNA binding by this family of proteins. The results highlight the strengths and weaknesses of current approaches to a practical problem in protein design and suggest strategies for further improvement of designed photocontrolled transcription factors.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".