Fluorogenic protein labelling: a review of photophysical quench mechanisms and principles of fluorogen design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fluorescent labelling of specific proteins in complex biological systems remains an important challenge in chemical biology. One promising approach comprises the use of small molecules designed to react specifically with a targeted protein of interest and to increase in fluorescent intensity following this reaction. This kind of fluorogenic reaction generally derives from fluorescence quenching in the unreacted probe that is abrogated over the course of the reaction. Herein, we review the mechanistic principles of three major photophysical quenching mechanisms involving Förster resonance energy transfer (FRET), through-bond energy transfer (TBET), and photoinduced electron transfer (PeT). We then present design principles for novel fluorogenic probes based on an understanding of these quench mechanisms, with emphasis on the emerging utility of density functional theory (DFT) calculations in the design process.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it