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Record W1993248159 · doi:10.1139/v09-034

The affinity of HGGG, GHGG, GGHG, and GGGH peptides for copper(II) and the structures of their complexes — An ab initio study

2009· article· en· W1993248159 on OpenAlexaffvenue
Stephen D. Barry, Gail A. Rickard, M. Jake Pushie, Arvi Rauk

Bibliographic record

VenueCanadian Journal of Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistrySolvationDeprotonationAb initioAqueous solutionComputational chemistryImplicit solvationPotentiometric titrationAmidePeptideCrystallographyIonic bondingCopperHistidineIonStereochemistryPhysical chemistryAmino acidOrganic chemistry

Abstract

fetched live from OpenAlex

The structures and relative free energies in aqueous solution of the Cu(II) complexes of the “histidine walk” peptides, AcHGGGNH2, AcGHGGNH2, AcGGHGNH2, and AcGGGHNH2, were determined as a function of pH. Numerous structures of each species were found by gaseous- and solution-phase geometry optimization at the B3LYP/6–31G(d) level, and the effect of solvation estimated by the IEFPCM continuum solvation model. Free energies of solvation of the ionic species are large and favour structures with an extended peptide chain. In all Cu(II)–peptide complexes, deprotonation of two amide groups occurs readily at or below pH 7. In each system, the most abundant species at pH 7 is a neutral 1:1 complex with N3O1 coordination pattern. Binding in the forward direction toward the C terminus is preferred. The results are compared to recent experimental spectroscopic and potentiometric studies on related systems. Alternative explanations are offered for some of the experimental observations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Citations10
Published2009
Admission routes2
Has abstractyes

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