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Record W2007384564 · doi:10.1021/jp050843i

Computational Studies of Cu(II)/Met and Cu(I)/Met Binding Motifs Relevant for the Chemistry of Alzheimer's Disease

2005· article· en· W2007384564 on OpenAlexafffund
Rodolfo Gómez‐Balderas, Duilio F. Raffa, Gail A. Rickard, Patrick Brunelle, Arvi Rauk

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2005
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiseaseChemistryComputational biologyMedicineBiologyPathology

Abstract

fetched live from OpenAlex

A systematic study of the binding motifs of Cu(II) and Cu(I) to a methionine model peptide, namely, N-formylmethioninamide 1, has been carried out by quantum chemical computations. Geometries of the coordination modes obtained at the B3LYP/6-31G(d) level of theory are discussed in the context of copper coordination by the peptide backbone and the S atom of a methionine residue in peptides with special emphasis on Met35 of the amyloid-beta peptide (Abeta) of Alzheimer's disease. The relative binding free energies in the gas phase, DeltaG(g), are calculated at the B3LYP/6-311+G(2df,2p)//B3LYP/6-31G(d) level of theory, and the solvation affects are included by means of the COSMO model to obtain the relative binding energies in solution, DeltaG(aq). A free energy of binding, DeltaG(aq) = -19.4 kJ mol(-1), relative to aqueous Cu(II) and the free peptide is found for the most stable Cu(II)/Met complex, 12. The most stable Cu(I)/Met complex, 23, is bound by -15.6 kJ mol(-1) relative to the separated species. The reduction potential relative to the standard hydrogen electrode is estimated to be E degrees (12/23) = 0.41 V. On the basis of these results, the participation of Met35 as a low affinity binding site of Cu(II) in Abeta, and its role in the redox chemistry underlying Alzheimer's disease is discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.297
Teacher spread0.269 · 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.

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

Citations23
Published2005
Admission routes2
Has abstractyes

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