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Record W2013302888 · doi:10.1007/s13361-014-0831-1

Controlling Dissociation Channels of Gas-Phase Protein Complexes Using Charge Manipulation

2014· article· en· W2013302888 on OpenAlexafffund
Sarah K. Fegan, Mark Thachuk

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of British Columbia
FundersWestern Canada Research Grid
KeywordsChemistryProtonationDissociation (chemistry)MonomerChemical physicsCharge (physics)Partial chargeStatic electricityElectrostaticsGas phaseMolecular dynamicsComputational chemistryCrystallographyMoleculeIonPhysical chemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Coarse-grained simulations with charge hopping were performed for a positively charged tetrameric transthyretin (TTR) protein complex with a total charge of +20. Charges were allowed to move among basic amino acid sites as well as N-termini. Charge distributions and radii of gyration were calculated for complexes simulated at two temperatures, 300 and 600 K, under different scenarios. One scenario treated the complex in its normal state allowing charge to move to any basic site. Another scenario blocked protonation of all the N-termini except one. A final scenario used the complex in its normal state but added a basic-site containing tether (charge tag) near the N-terminus of one chain. The differences in monomer unfolding and charging were monitored in all three scenarios and compared. The simulation results show the importance of the N-terminus in leading the unfolding of the monomer units; a process that follows a zipper-like mechanism. Overall, experimentally modifying the complex by adding a tether or blocking the protonation of N-termini may give the potential for controlling the unraveling and subsequent dissociation of protein complexes.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.280
Teacher spread0.268 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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Same venueJournal of the American Society for Mass SpectrometrySame topicProtein Structure and DynamicsFrench-language works237,207