Protein structure and dynamics studied by mass spectrometry: H/D exchange, hydroxyl radical labeling, and related approaches
Bibliographic record
Abstract
Mass spectrometry (MS) plays a central role in studies on protein structure and dynamics. This review highlights some of the recent developments in this area, with focus on applications involving the use of electrospray ionization (ESI) MS. Although this technique involves the transformation of analytes into highly nonphysiological species (desolvated gas-phase ions in the vacuum), ESI-MS can provide detailed insights into the solution-phase behavior of proteins. Notably, the ionization process itself occurs in a structurally sensitive manner. An increased degree of solution-phase unfolding is correlated with a higher level of protonation. Also, ESI allows the transfer of intact noncovalent complexes into the gas phase, thereby yielding information on binding partners, stoichiometries, and even affinities. A particular focus of this article is the use of hydrogen/deuterium exchange (HDX) methods and hydroxyl radical (.OH) labeling for monitoring dynamic and structural aspect of solution-phase proteins. Conceptual similarities and differences between the two methods are discussed. We describe a simple method for the computational simulation of protein HDX patterns, a tool that can be helpful for the interpretation of isotope exchange data recorded under mixed EX1/EX2 conditions. Important aspects of .OH labeling include a striking dependence on protein concentration, and the tendency of commonly used solvent additives to act as highly effective radical scavengers. If not properly controlled, both of these factors may lead to experimental artifacts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".