Measuring Dynamics in Weakly Structured Regions of Proteins Using Microfluidics-Enabled Subsecond H/D Exchange Mass Spectrometry
Bibliographic record
Abstract
This work introduces an integrated microfluidic device for measuring rapid H/D exchange (HDX) in proteins. By monitoring backbone amide HDX on the millisecond to low second time scale, we are able to characterize conformational dynamics in weakly structured regions, such as loops and molten globule-like domains that are inaccessible in conventional HDX experiments. The device accommodates the entire MS-based HDX workflow on a single chip with residence times sufficiently small (ca. 8 s) that back-exchange is negligible (≤5%), even without cooling. Components include an adjustable position capillary mixer providing a variable-time labeling pulse, a static mixer for HDX quenching, a proteolytic microreactor for rapid protein digestion, and on-chip electrospray ionization (ESI). In the present work, we characterize device performance using three model systems, each illustrating a different application of 'time-resolved' HDX. Ubiquitin is used to illustrate a crude, high throughput structural analysis based on a single subsecond HDX time-point. In experiments using cytochrome c, we distinguish dynamic behavior in loops, establishing a link between flexibility and interactions with the heme prosthetic group. Finally, we localize an unusually high 'burst-phase' of HDX in the large tetrameric enzyme DAHP synthase to a 'molten globule-like' region surrounding the active site.
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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".