Structural Characterization of Short-Lived Protein Unfolding Intermediates by Laser-Induced Oxidative Labeling and Mass Spectrometry
Bibliographic record
Abstract
The structural characterization of short-lived intermediates provides insights into the mechanisms of protein folding and unfolding. Using holo-myoglobin as a model system, this work reports the application of oxidative pulse labeling for experiments of this kind. Protein unfolding is triggered by a pH jump from 6.5 to 3.2 in 150 mM NaCl. Subsequent (.-)OH exposure at various time points using laser photolysis of H2O2 leads to covalent modifications of solvent-exposed side chains within approximately 1 mus (Hambly, D. M.; Gross, M. L. J. Am. Soc. Mass Spectrom. 2005, 16, 2057-2063). Most of these modifications appear as 16 Da adducts in the mass spectrum of the intact protein. The overall extent of labeling increases with time, reflecting the exposure of reactive side chains that had previously been buried. Unfolding and disruption of heme-protein interactions go to completion within approximately 10 s. Spatially resolved information is obtained by monitoring the signal intensities of unmodified tryptic peptides. After 50 ms, many regions have lost most of their protection, whereas structure is retained in the B, E, F, and G helices. The BEF core remains partially folded, even after 500 ms, at which point helix G is fully unprotected. The observation of an "early" (BEFG) and a "late" (BEF) intermediate is in accord with optical stopped-flow measurements. Formation of these transient species is attributed to the persistence of heme-protein interactions during the early stages of the reaction. Overall, this work demonstrates the feasibility of laser-induced oxidative labeling as a tool for characterizing the structure of short-lived protein conformers. The combination of this approach with ultrarapid mixing or photochemical triggering should allow folding experiments in the submillisecond range.
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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) | 0.000 | 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".