Long Range Polymer Chain Dynamics Studied by Fluorescence Quenching
Bibliographic record
Abstract
Over the years, fluorescence quenching experiments have provided a robust analytical means to retrieve information about the internal dynamics of macromolecules in general and the long range polymer chain dynamics (LRPCD) of linear chains in particular. This report reviews the results obtained to date with the two main fluorescence experiments based on collisional quenching that have been used over the years to describe LRPCD. These experiments involve the labeling of a chain with dyes and quenchers either at the ends of a monodisperse chain for fluorescence quenching end-to-end cyclization (fqEEC) experiments or randomly along a polydisperse chain for fluorescence decay analysis with the fluorescence blob model (FBM). The advantages and disadvantages of these two types of experiments are discussed as well as their range of applications and applicability to the field of protein folding. In particular, this Perspective illustrates how fqEEc experiments are being applied to probe loop formation in polypeptides and how FBM analysis of randomly labeled polypeptides could help determine the size of foldons which are expected to solve Levinthal’s long-standing paradox.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".