Molecular dynamics study of chemically engineered green fluorescent protein mutants: Comparison of intramolecular fluorescence resonance energy transfer rate
Bibliographic record
Abstract
Because of its unusual spectroscopic properties, green fluorescent protein (GFP) has become a useful tool in molecular genetics, biochemistry and cell biology. Here, we computationally characterize the behavior of two GFP constructs, designed as bioprobes for enzymatic triggering using intramolecular fluorescence resonance energy transfer (FRET). These constructs differ in the location of an intramolecular FRET partner, an attached chemical chromophore (either near an N-terminal or C-terminal site). We apply the temperature replica exchange molecular dynamics method to the two flexible constructs in conjunction with a generalized Born implicit solvent model. The calculated rate of FRET was derived from the interchromophore distance, R, and orientational factor, kappa(2). In agreement with experiment, the construct with the C-terminally attached dye was predicted to have higher energy transfer rate than observed for the N-terminal construct. The molecular basis for this observation is discussed. In addition, we find that the orientational factor, kappa(2), deviates from the commonly assumed value, the implications of which are also considered.
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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 | 0.001 |
| 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) | 0.000 | 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".