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Record W2891773955 · doi:10.1021/acs.jpcb.8b05053

Effects of Intense Electric Fields on the Double Proton Transfer in the Watson–Crick Guanine–Cytosine Base Pair

2018· article· en· W2891773955 on OpenAlexafffund
Alya A. Arabi, Chérif F. Matta

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsMount Saint Vincent UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaKillam TrustsCanada Foundation for InnovationMount Saint Vincent University
KeywordsMolecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic AcidGuanineCytosineBase pairWatsonBase (topology)PhysicsElectric fieldProtonChemistryDNANucleotideQuantum mechanicsMathematicsComputer scienceBiochemistry

Abstract

fetched live from OpenAlex

The double proton transfer reaction in the guanine–cytosine (GC) base pair is studied, using density functional theory, to understand the chances of mutations under the effect of uniform electric fields in the order of 108 to 109 V m–1. On the basis of potential energy surfaces, reaction Gibbs energies, equilibrium constants, imaginary frequencies, forward and reverse barrier heights, tunneling-corrected rate constants, half-lives of the forward and reverse reactions, percent tautomerization, and Boltzmann distributions, it was found that fields ≥+3.60 × 109 V m–1 facilitate the mutation in the GC base pair and reduce the rectification of point mutations. Fields applied along the double proton transfer in the −x (defined in the C to G direction) direction favor the canonical over the rare tautomers. Tunneling-corrected rate constants of the forward reaction increase exponentially with stronger fields in the −x direction and follow a Gaussian curve for the reverse reaction.

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 score0.001
Threshold uncertainty score0.309

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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

Citations46
Published2018
Admission routes2
Has abstractyes

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