Raman Vibrational Signatures of Excited States of Echinenone in the Orange Carotenoid Protein (OCP) and Implications for its Photoactivation Mechanism
Bibliographic record
Abstract
In this study, the vibrational characteristics of optically excited echinenone in various solvents and the Orange Carotenoid Protein (OCP) in red and orange states are systematically investigated through steady-state and time-resolved spectroscopy techniques. Time-resolved experiments, employing both Transient Absorption (TA) and Femtosecond Stimulated Raman Spectroscopy (FSRS), reveal different states in the OCP photoactivation process. The time-resolved studies indicate vibrational signatures of exited states positioned above the S1 state during the initial 140 fs of carotenoid evolution in OCP, an absence of a vibrational signature for the relaxed S1 state of echinenone in OCP, and more robust signatures of a highly excited ground state (GS) in OCP. Differences in S1 state vibration population signatures between OCP and solvents are attributed to distinct conformations of echinenone in OCP and hydrogen bonds at the keto group forming a short-lived intramolecular charge transfer (ICT) state. The vibrational dynamics of the hot GS in OCP show a more pronounced red shift of ground state C=C vibration compared to echinenone in solvents, thus suggesting an unusually hot form of GS. The study proposes a hypothesis for the photoactivation mechanism of OCP, emphasizing the high level of excitation in longitudinal stretching modes as a driving force. In conclusion, the comparison of vibrational signatures reveals unique dynamics of energy dissipation in OCP, providing insights into the photoactivation mechanism and highlighting the impact of the protein environment on carotenoid behavior. The study underscores the importance of vibrational analysis in understanding the intricate processes involved in early phase OCP photoactivation.
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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".