Nepenthesin from Monkey Cups for Hydrogen/Deuterium Exchange Mass Spectrometry
Bibliographic record
Abstract
Studies of protein dynamics, structure and interactions using hydrogen/deuterium exchange mass spectrometry (HDX-MS) have sharply increased over the past 5-10 years. The predominant technology requires fast digestion at pH 2-3 to retain deuterium label. Pepsin is used almost exclusively, but it provides relatively low efficiency under the constraints of the experiment, and a selectivity profile that renders poor coverage of intrinsically disordered regions. In this study we present nepenthesin-containing secretions of the pitcher plant Nepenthes, commonly called monkey cups, for use in HDX-MS. We show that nepenthesin is at least 1400-fold more efficient than pepsin under HDX-competent conditions, with a selectivity profile that mimics pepsin in part, but also includes efficient cleavage C-terminal to "forbidden" residues K, R, H, and P. High efficiency permits a solution-based analysis with no detectable autolysis, avoiding the complication of immobilized enzyme reactors. Relaxed selectivity promotes high coverage of disordered regions and the ability to "tune" the mass map for regions of interest. Nepenthesin-enriched secretions were applied to an analysis of protein complexes in the nonhomologous end-joining DNA repair pathway. The analysis of XRCC4 binding to the BRCT domains of Ligase IV points to secondary interactions between the disordered C-terminal tail of XRCC4 and remote regions of the BRCT domains, which could only be identified with a nepenthesin-based workflow. HDX data suggest that stalk-binding to XRCC4 primes a BRCT conformation in these remote regions to support tail interaction, an event which may be phosphoregulated. We conclude that nepenthesin is an effective alternative to pepsin for all HDX-MS applications, and especially for the analysis of structural transitions among intrinsically disordered proteins and their binding partners.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".