Recovery of Red Fluorescent Protein Chromophore Maturation Deficiency through Rational Design
Bibliographic record
Abstract
Red fluorescent proteins (RFPs) derived from organisms in the class Anthozoa have found widespread application as imaging tools in biological research. For most imaging experiments, RFPs that mature quickly to the red chromophore and produce little or no green chromophore are most useful. In this study, we used rational design to convert a yellow fluorescent mPlum mutant to a red-emitting RFP without reverting any of the mutations causing the maturation deficiency and without altering the red chromophore's covalent structure. We also created an optimized mPlum mutant (mPlum-E16P) that matures almost exclusively to the red chromophore. Analysis of the structure/function relationships in these proteins revealed two structural characteristics that are important for efficient red chromophore maturation in DsRed-derived RFPs. The first is the presence of a lysine residue at position 70 that is able to interact directly with the chromophore. The second is an absence of non-bonding interactions limiting the conformational flexibility at the peptide backbone that is oxidized during red chromophore formation. Satisfying or improving these structural features in other maturation-deficient RFPs may result in RFPs with faster and more complete maturation to the red chromophore.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".