Subzero Temperature Chromatography and Top-Down Mass Spectrometry for Protein Higher-Order Structure Characterization: Method Validation and Application to Therapeutic Antibodies
Bibliographic record
Abstract
Characterization of the higher-order structure and structural dynamics of proteins is crucial for in-depth understanding of their functions. Amide hydrogen/deuterium exchange (HDX), monitored by mass spectrometry (MS), is now a popular technique for measuring protein higher-order structural changes. Although the proteolysis-based HDX-MS approach is most commonly used, the "top-down" approach, which fragments intact proteins directly using electron-based dissociation, is becoming an important alternative and has several advantages. However, the commonly used top-down strategies are direct-infusion based and thus can only be used with volatile buffers. This has meant that the "top-down" approach could not be used for studying proteins under physiological conditions-the very conditions which are often very important for preserving a protein's native structure and function. More complex proteins such as those with disulfide bonds present another challenge. Therefore, there is significant interest in developing novel top-down HDX methods that are applicable to all types of protein samples. In this paper, we show how top-down electron capture dissociation and subzero temperature HPLC can be combined and used for this purpose. This method keeps the back-exchange level as low as 2% and has no limitations in terms of protein type and sample solution conditions. Close to single-residue level protein structural information can be generated. The new method is validated through comparison with NMR data using calmodulin as a model protein. Its capability of determining structural changes in therapeutic antibodies (Herceptin) is also demonstrated.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".