Signal Response of Coexisting Protein Conformers in Electrospray Mass Spectrometry
Bibliographic record
Abstract
Electrospray ionization mass spectrometry (ESI-MS) is a commonly used tool for characterizing conformational changes of proteins in solution. Different conformations can be distinguished on the basis of their ESI charge state distributions. ESI-MS studies carried out under semidenaturing conditions result in bi- or multimodal distributions that reflect the presence of coexisting conformers. This study explores whether the concentration ratios of these species in solution are reflected in the measured ion intensities. Experiments on two model proteins, lysozyme and myoglobin, reveal that non-native polypeptide chains tend to result in a much stronger signal response than natively folded species. The measured ion intensity ratios can differ from the actual concentration ratios by as much as 2 orders of magnitude. It is proposed that the higher ionization efficiency of unfolded proteins is due to their partially hydrophobic character, which results in a larger surface activity and facilitates protein transfer into ion-producing progeny droplets. Conversely, natively folded proteins have a lower affinity for the air/liquid interface, such that ionization of these conformers is suppressed. The extent of ion suppression is strongly dependent on the experimental conditions such as flow rate and protein concentration, which determine if ESI occurs in a charge deficient or a charge surplus regime. These aspects should be taken into account for the design of ESI-MS-based protein folding experiments and for studies that use ion intensity ratios for the determination of protein-ligand binding affinities.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".