Advantages of Pyrene Excimer Formation (PEF) over Fluorescence Resonance Energy Transfer (FRET) for Probing the Conformation of Macromolecules in Solution
Bibliographic record
Abstract
Pyrene excimer formation (PEF) was applied to study the homopolypeptides poly( d, l -glutamic acid) (PDLGA) and poly( l -glutamic acid) (PLGA), collectively referred to as the PGA samples, in N, N -dimethylformamide (DMF) and dimethyl sulfoxide (DMSO). The polypeptides were labeled with 1-pyrenebutylamine (PyC4N) or 1-pyreneoctylamine (PyC8N) and were described as PyCX( x )N-PGA where X equals 4 or 8, respectively, and x represents the mole percentage of pyrene-labeled glutamic acid (Glu). The fluorescence results obtained with these polypeptides were compared with the results obtained earlier with the same polypeptides randomly labeled with 1-pyrenemethylamine (PyC1N). Analysis of the fluorescence decays of the PyCX( x )N-PGA samples with the fluorescence blob model (FBM) yielded the average number (⟨ N blob exp ⟩) of Glu units per blob, where a blob is the volume probed by an excited pyrenyl label. The ⟨ N blob exp ⟩ values obtained for the PyCX( x )N-PGA samples in DMF and DMSO were compared with the N blob MMO values determined via molecular mechanics optimizations (MMO) conducted for PLGA constructs adopting four different conformations and labeled with either PyC1N, PyC4N, or PyC8N. The good agreement obtained between the ⟨ N blob exp ⟩ and N blob MMO values for PDLGA in DMF and DMSO and PLGA in DMF, whose conformation was known to be a random coil and an α–helix, respectively, validated the PEF-based methodology. It was then applied to determine the unknown conformation of PLGA in DMSO. The excellent match found between ⟨ N blob exp ⟩ obtained for PLGA in DMSO and N blob MMO obtained for a PLGA 3 10 helix led to its unambiguous assignment as the conformation of PLGA in DMSO. Since PyC8N probed a volume whose 7.7 nm diameter was almost double that of PyC1N, these experiments significantly extended the range of distances over which PEF can be applied to characterize macromolecular conformations, making PEF competitive with the distance range accessible by fluorescence resonance energy transfer (FRET).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".