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Record W2179382838 · doi:10.1007/s13361-015-1298-4

Proton Mobility in b<sub>2</sub> Ion Formation and Fragmentation Reactions of Histidine-Containing Peptides

2015· article· en· W2179382838 on OpenAlexaff
Carissa Nelson, Maha T. Abutokaikah, Alex G. Harrison, Benjamin J. Bythell

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2015
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Toronto
FundersUniversity of Missouri
KeywordsChemistryIsomerizationFragmentation (computing)ProtonationIonAmideHistidineComputational chemistryPeptide bondMass spectrumDensity functional theoryBond cleavageStereochemistryPeptideOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

A detailed energy-resolved study of the fragmentation reactions of protonated histidine-containing peptides and their b2 ions has been undertaken. Density functional theory calculations were utilized to predict how the fragmentation reactions occur so that we might discern why the mass spectra demonstrated particular energy dependencies. We compare our results to the current literature and to synthetic b2 ion standards. We show that the position of the His residue does affect the identity of the subsequent b2 ion (diketopiperazine versus oxazolone versus lactam) and that energy-resolved CID can distinguish these isomeric products based on their fragmentation energetics. The histidine side chain facilitates every major transformation except trans-cis isomerization of the first amide bond, a necessary prerequisite to diketopiperazine b2 ion formation. Despite this lack of catalyzation, trans-cis isomerization is predicted to be facile. Concomitantly, the subsequent amide bond cleavage reaction is rate-limiting.

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 score0.004

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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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