The Kinetics of Helix Unfolding of an Azobenzene Cross-Linked Peptide Probed by Nanosecond Time-Resolved Optical Rotatory Dispersion
Bibliographic record
Abstract
The unfolding dynamics of a 16 amino acid peptide (Ac-EACAREAAAREAACRQ-NH(2), FK-11-X) was followed using nanosecond time-resolved optical rotatory dispersion (ORD). The peptide was coupled to an azobenzene linker that undergoes subnanosecond photoisomerization and reisomerizes on a time scale of minutes. When the linker is in the trans form, the peptide favors a more helical structure (66% helix/34% disordered) and when in the cis configuration the helical content is reduced. Unfolding of FK-11-X was rapidly triggered by a 7-ns laser pulse at 355 nm, forming cis azobenzene-linked peptides that maintained the secondary structure (helical or disordered) of their trans azobenzene counterparts. The incompatibility of the instantaneous cis photoproduct with helical secondary structure drives the subsequent peptide unfolding to a new conformational equilibrium between cis helix and cis disordered structures. The kinetic results show a approximately 40% decrease in the time-dependent ORD signal at 230 nm that is best fit to a single-exponential decay with a time constant of 55 +/- 6 ns. Folding and unfolding rates for cis FK-11-X are estimated to be approximately 3.0 x 10(6) s(-)(1) (1/330 ns) and approximately 1.5 x 10(7) s(-)(1) (1/66 ns), respectively.
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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 | 0.000 |
| 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) | 0.001 | 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".