2003 Fred Beamish Award Lecture Exploring the dynamics of biological systems by mass spectrometry
Bibliographic record
Abstract
This review describes the use of electrospray ionization mass spectrometry (ESI-MS) in conjunction with on-line rapid mixing techniques. This combination, termed "time-resolved" ESI-MS, provides a powerful approach for studying solution-phase reactions on timescales as short as a few milliseconds. Of particular interest is the application of this technique for monitoring protein folding reactions. Time-resolved ESI-MS can provide detailed information on structural changes of the polypeptide chain, while at the same time probing the occurrence of noncovalent ligandprotein interactions. Especially when used in combination with hydrogendeuterium pulse labeling, these measurements yield valuable structural information on short-lived folding intermediates. Similar approaches can be used to monitor the dynamics of proteins under equilibrium conditions. Another important application of time-resolved ESI-MS are mechanistic studies on enzyme-catalyzed processes. These reactions can be monitored under presteady-state conditions, without requiring artificial chromophoric substrates or radioactive labeling. We also discuss the use of ESI-MS for monitoring noncovalent ligandprotein interactions by diffusion measurements. In contrast to conventional MS-based techniques, this approach does not rely on the preservation of noncovalent interactions in the gas phase. It appears that diffusion measurements by ESI-MS could become an interesting alternative to existing methods for the high throughput screening of compound libraries in the context of drug discovery.Key words: reaction intermediate, rapid mixing, kinetics, protein conformation, protein function.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.078 | 0.031 |
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".