Circularly permuted monomeric red fluorescent proteins with new termini in the β‐sheet
Bibliographic record
Abstract
Circularly permuted fluorescent proteins (FPs) have a growing number of uses in live cell fluorescence biosensing applications. Most notably, they enable the construction of single fluorescent protein-based biosensors for Ca(2+) and other analytes of interest. Circularly permuted FPs are also of great utility in the optimization of fluorescence resonance energy transfer (FRET)-based biosensors by providing a means for varying the critical dipole-dipole orientation. We have previously reported on our efforts to create circularly permuted variants of a monomeric red FP (RFP) known as mCherry. In our previous work, we had identified six distinct locations within mCherry that tolerated the insertion of a short peptide sequence. Creation of circularly permuted variants with new termini at the locations corresponding to the sites of insertion led to the discovery of three permuted variants that retained no more than 18% of the brightness of mCherry. We now report the extensive directed evolution of the variant with new termini at position 193 of the protein sequence for improved fluorescent brightness. The resulting variant, known as cp193g7, has 61% of the intrinsic brightness of mCherry and was found to be highly tolerant of circular permutation at other locations within the sequence. We have exploited this property to engineer an expanded series of circularly permuted variants with new termini located along the length of the 10th beta-strand of mCherry. These new variants may ultimately prove useful for the creation of single FP-based Ca(2+) biosensors.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".