Mass spectrometry combined with oxidative labeling for exploring protein structure and folding
Bibliographic record
Abstract
This review discusses various mass spectrometry (MS)-based approaches for exploring structural aspects of proteins in solution. Electrospray ionization (ESI)-MS, in particular, has found fascinating applications in this area. For example, when used in conjunction with solution-phase hydrogen/deuterium exchange (HDX), ESI-MS is a highly sensitive tool for probing conformational dynamics. The main focus of this article is a technique that is complementary to HDX, that is, the covalent labeling of proteins by hydroxyl radicals. The reactivity of individual amino acid side chains with *OH is strongly affected by their degree of solvent exposure. Thus, analysis of the oxidative labeling pattern by peptide mapping and tandem mass spectrometry provides detailed structural information. A convenient method for *OH production is the photolysis of H(2)O(2) by a pulsed UV laser, resulting in oxidative labeling on the microsecond time scale. Selected examples demonstrate the use of this technique for structural studies on membrane proteins, and the combination with rapid mixing devices for characterizing the properties of short-lived protein (un)folding intermediates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".