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Record W1967804496 · doi:10.1016/s1044-0305(00)00162-8

Formation of [M − <i>n</i>H + <i>m</i>Na]<sup>(m−n)+</sup> and [M − <i>n</i>H + <i>m</i>K]<sup>(m−n)+</sup> ions in electrospray mass spectrometry of peptides and proteins

2000· article· he· W1967804496 on OpenAlexaff
Christopher F. Rodriquez, Xu Guo, Tamer Shoeib, Alan C. Hopkinson, K. W. Michael Siu

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2000
Typearticle
Languagehe
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsChemistryFormamideIonDensity functional theoryMoleculeEndothermic processAcetic acidAlkali metalCrystallographyMedicinal chemistryProton affinityInorganic chemistryPhysical chemistryProtonationComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The [M - nH + mNa](m-n)+ and [M - nH + mK](m-n)+ ions are common in the electrospray mass spectra of proteins and peptides. The feasibility of forming these ions in the gas phase via collision activation and/or ion-molecule reaction is investigated. Sodium and potassium affinities of the N-methylacetamide anion, the acetate anion, and the 1-propanamide anion have been calculated using density functional theory at the B3LYP/6-311+ +G(d,p) level of theory. These anions were chosen as models for the functional groups on a protein or peptide. These affinity values are then used to calculate reaction enthalpies of alkali hydroxides, chlorides, and hydrates with N-methylacetamide, acetic acid, the acetate anion, and 1-propanamine, model reactions that may lead to formation of the [M - nH + mNa](m-n) and [M - nH + mK](m-n)+ ions. It is found that a number of these reactions are exothermic or slightly endothermic (deltaH(o) < + 20 kcal/mol) and are accessible after collision activation in the lens region. The potential energy hypersurfaces of model reactions between NaOH and formamide as well as NaCl and formamide show relatively flat surfaces devoid of significant barriers.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.089
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.005
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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 teacher head, not a consensus.

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

Citations28
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Society for Mass SpectrometrySame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207