Mapping pH-Induced Protein Structural Changes Under Equilibrium Conditions by Pulsed Oxidative Labeling and Mass Spectrometry
Bibliographic record
Abstract
Mass spectrometry (MS)-based protein conformational studies are a rapidly growing field. The characterization of partially disordered conformers is of particular interest because these species are not amenable to classical high-resolution techniques. Such equilibrium intermediates can often be populated by exposure to mildly acidic pH. Hydroxyl radical (·OH) introduces oxidative modifications at solvent-accessible side chains, while buried sites are protected. ·OH can be generated by laser photolysis of H(2)O(2) (fast photochemical oxidation of proteins-FPOP). The resulting labeling pattern can be analyzed by MS. The characterization of partially disordered intermediates usually involves comparative measurements under different solvent conditions. It can be challenging to separate structurally induced labeling changes from pH-mediated "secondary" effects. The issue of secondary effects in FPOP has received little prior attention. We demonstrate that with a proper choice of conditions (e.g., in the absence of pH-dependent ·OH scavengers) such undesired phenomena can be almost completely eliminated. Using apomyoglobin as a model system, we map the structure of an intermediate that is formed at pH 4. This species retains a highly protected helix G that is surrounded by partially protected helices A, B, and H. Our results demonstrate the utility of FPOP for the structural characterization of equilibrium intermediates. The near absence of an intrinsic pH dependence represents an advantage compared to hydrogen/deuterium exchange MS.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".