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Record W1993156452 · doi:10.1021/bi061104a

Iron as a Bound Secondary Electron Donor in Modified Bacterial Reaction Centers

2006· article· en· W1993156452 on OpenAlexaff
László Kálmán, Russell LoBrutto, J. C. Williams, James P. Allen

Bibliographic record

VenueBiochemistry · 2006
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsConcordia University
Fundersnot available
KeywordsChemistryFerrousReaction rate constantManganeseBacteriochlorophyllElectron paramagnetic resonanceMetalDimerBicarbonateDissociation (chemistry)Dissociation constantPhotochemistryInorganic chemistryKineticsPhysical chemistryBiochemistryNuclear magnetic resonanceOrganic chemistry

Abstract

fetched live from OpenAlex

The binding and oxidation of ferrous iron were studied in wild-type reaction centers and in mutants that have been modified to be both highly oxidizing and able to bind manganese [Thielges et al. (2005) Biochemistry 44, 7389-7394]. After illumination of wild-type reaction centers, steady-state optical spectroscopy showed that the oxidized bacteriochlorophyll dimer, P+, could oxidize iron but only as a second-order reaction at iron concentrations above 100 microM. In the modified reaction centers, P+ was reduced by iron in the presence of sodium bicarbonate with dissociation constants of approximately 1 microM for two mutants with different metal-binding sites. Transient optical spectroscopy showed that P+ was rapidly reduced with first-order rates of 170 and 275 s-1 for the two mutants. The dependence of the amplitude of this rate on the iron concentration yielded a dissociation constant of approximately 1 microM for both mutants, in agreement with the steady-state determination. The oxidation of bound iron by P+ was confirmed by the observation of a light-induced EPR signal centered at g values of 2.2 and 4.3 and attributed to high-spin Fe3+. Bicarbonate was required at pH 7 for low dissociation constants for both iron and manganese binding. The similarity between iron and manganese binding in these mutants provides insight into general properties of metal-binding sites in proteins.

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 score0.040
Threshold uncertainty score0.835

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 science0.0000.000
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 head0.004
GPT teacher head0.212
Teacher spread0.208 · 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

Citations10
Published2006
Admission routes1
Has abstractyes

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