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Record W1973902002 · doi:10.1007/s13361-013-0814-7

Cation-Induced Stabilization of Protein Complexes in the Gas Phase: Mechanistic Insights From Hemoglobin Dissociation Studies

2014· article· en· W1973902002 on OpenAlexafffund
JiangJiang Liu, Lars Konermann

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2014
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsChemistryDissociation (chemistry)HemoglobinGas phaseBiophysicsComputational chemistryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.310
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2014
Admission routes2
Has abstractyes

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