<scp>HX‐MS</scp>2 for high performance conformational analysis of complex protein states
Bibliographic record
Abstract
Water-mediated hydrogen exchange (HX) processes involving the protein main chain are sensitive to structural dynamics and molecular interactions. Measuring deuterium uptake in amide bonds provides information on conformational states, structural transitions and binding events. Increasingly, deuterium levels are measured by mass spectrometry (MS) from proteolytically generated peptide fragments of large molecular systems. However, this bottom-up method has limited spectral capacity and requires a burdensome manual validation exercise, both of which restrict analysis of protein systems to generally less than 150 kDa. In this study, we present a bottom-up HX-MS(2) method that improves peptide identification rates, localizes high-quality HX data and simplifies validation. The method combines a new peptide scoring algorithm (WUF, weighted unique fragment) with data-independent acquisition of peptide fragmentation data. Scoring incorporates the validation process and emphasizes identification accuracy. The HX-MS(2) method is illustrated using data from a conformational analysis of microtubules treated with dimeric kinesin MCAK. When compared to a conventional Mascot-driven HX-MS method, HX-MS(2) produces two-fold higher α/β-tubulin sequence depth at a peptide utilization rate of 74%. A Mascot approach delivers a utilization rate of 44%. The WUF score can be constrained by false utilization rate (FUR) calculations to return utilization values exceeding 90% without serious data loss, indicating that automated validation should be possible. The HX-MS(2) data confirm that N-terminal MCAK domains anchor kinesin force generation in kinesin-mediated depolymerization, while the C-terminal tails regulate MCAK-tubulin interactions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".