Conformer-Specific Hydrogen Exchange Analysis of Aβ(1–42) Oligomers by Top-Down Electron Capture Dissociation Mass Spectrometry
Bibliographic record
Abstract
Protein structural studies are particularly challenging under conditions in which several conformational species (e.g., monomers and aggregated forms) coexist in solution. Most spectroscopic techniques provide population-averaged data. Hence, it is usually not possible to obtain detailed structural information on individual protein species in heterogeneous samples. The current work employs an experimental strategy that addresses this issue. Solution-phase hydrogen exchange (HX) is used in combination with tandem mass spectrometry. Electrosprayed intact ions exhibiting specific HX mass shifts are selected in the gas phase, followed by electron capture dissociation. The resulting fragment ion deuteration pattern provides amide hydrogen bonding information in a conformer-specific and spatially resolved fashion. The feasibility of this approach is demonstrated by applying it to neurotoxic Aβ(1-42) oligomers that coexist with disordered monomers in solution. The findings of this study point to similarities between oligomers and mature amyloid fibrils with regard to the Aβ(1-42) backbone organization. Specifically, fibrils and oligomers appear to share a β-loop-β secondary structure motif. The spatial resolution obtained with the "top-down" approach used here exceeds that of earlier proteolysis-based HX data on Aβ.
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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".