Cation-Induced Stabilization of Protein Complexes in the Gas Phase: Mechanistic Insights From Hemoglobin Dissociation Studies
Bibliographic record
Abstract
Collision-induced dissociation (CID) of electrosprayed protein complexes usually involves asymmetric charge partitioning, where a single unfolded chain gets ejected that carries a disproportionately large fraction of charge. Using hemoglobin (Hb) tetramers as model system, we confirm earlier reports that bound metal ions can stabilize protein complexes under CID conditions. We examine the mechanism underlying this effect. Nonvolatile salts cause extensive adduct formation. Significant stabilization was observed for Mg(2+) and Ca(2+), whereas K(+), Rb(+), and Cs(+) had no effect. Precursor ion selection was used to examine Hb subpopulations with well-defined metal binding levels. K(+), Rb(+), and Cs(+)-adducted tetramers eject monomers that carry roughly one-quarter of the metal ions that were bound to the precursor. This demonstrates that charge migration during CID is exclusively due to proton transfer, not metal ion transfer. Also, replacement of highly mobile charge carriers (protons) with less mobile species (metal ions) does not exert a stabilizing influence under the conditions used here. Interestingly, Hb carrying stabilizing ions (Mg(2+) and Ca(2+)) generates monomeric CID products that are metal depleted. This effect is attributed to a combination of two factors: (1) Me(2+) binding stabilizes Hb via formation of chelation bridges (e.g., R-COO(-) Me(2+) (-)OOC-R); the more Me(2+) a subunit contains the more stable it is. (2) More than ~90% of the tetramers contain at least one subunit with a below-average number of Me(2+). The prevalence of monomeric CID products with depleted Me(2+) levels is caused by the tendency of these low metal-containing subunits to undergo preferential unfolding/ejection.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".