Submillisecond Protein Folding Events Monitored by Rapid Mixing and Mass Spectrometry-Based Oxidative Labeling
Bibliographic record
Abstract
Kinetic measurements can provide insights into protein folding mechanisms. However, the initial (submillisecond) stages of folding still represent a formidable analytical challenge. A number of ultrarapid triggering techniques have been available for some time, but coupling of these techniques with detection methods that are capable of providing detailed structural information has proven to be difficult. The current work addresses this issue by combining submillisecond mixing with laser-induced oxidative labeling. Apomyoglobin (aMb) serves as a model system for our measurements. Exposure of the protein to a brief pulse of hydroxyl radical (·OH) at different time points during folding introduces covalent modifications at solvent accessible side chains. The extent of labeling is monitored using mass spectrometry-based peptide mapping, providing spatially resolved measurements of changes in solvent accessibility. The submillisecond mixer used here improves the time resolution by a factor of 50 compared to earlier ·OH labeling experiments from our laboratory. Data obtained in this way indicate that early aMb folding events are driven by both local and sequence-remote docking of hydrophobic side chains. Assembly of a partially formed A(E)G(H) scaffold after 0.2 ms is followed by stepwise consolidation that ultimately yields the native state. Major conformational changes go to completion within 0.1 s. The technique introduced here is capable of providing in-depth structural information on very short time scales that have thus far been dominated by low resolution (global) spectroscopic probes. By employing submillisecond mixing in conjunction with slower mixing techniques, it is possible to observe complete folding pathways, from fractions of a millisecond all the way to minutes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.012 | 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 teacher head, 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".