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Record W2136974802 · doi:10.1021/jp035675d

Model Calculations Relevant to Disulfide Bond Cleavage via Electron Capture Influenced by Positively Charged Groups

2003· article· en· W2136974802 on OpenAlexaff
Agnieszka Sawicka, Piotr Skurski, Robert R. Hudgins, Jack Simons

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2003
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsYork University
FundersNational Science Foundation
KeywordsExothermic reactionEndothermic processElectronChemistryDissociation (chemistry)CoulombCleavage (geology)Fragmentation (computing)IonBond cleavageDisulfide bondAb initioChemical physicsComputational chemistryMaterials scienceAdsorptionPhysical chemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Ab initio electronic structure calculations are used to explore the effect of nonneighboring positively charged groups on the ability of low-energy (<1 eV) electrons to directly attach to S−S σ bonds in disulfides to effect bond cleavage. It is shown that, although direct vertical attachment to the σ* orbital of an S−S σ bond is endothermic, the stabilizing Coulomb potential produced in the region of the S−S bond by one or more distant positive groups can render the S−S σ* anion state electronically stable. This stabilization, in turn, can make near vertical electron attachment exothermic. The focus of these model studies is to elucidate a proposed mechanism for bond rupture that may, in addition to other mechanisms, be operative in electron capture dissociation (ECD) experiments. The importance of these findings lies in the fact that a more complete understanding of how ECD takes place will allow workers to better interpret ECD fragmentation patterns observed in mass spectrometric studies of proteins and polypeptides.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations111
Published2003
Admission routes1
Has abstractyes

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