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Record W4241552290 · doi:10.26434/chemrxiv.14614152

Cluster Models of FeMoco with Sulfide and Carbyne Ligands: Effect of Interstitial Atom in Nitrogenase Active Site

2021· preprint· en· W4241552290 on OpenAlexfundno aff
Linh Le, Gwendolyn A. Bailey, Anna Scott, Theodor Agapie

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsnot available
FundersResnick Sustainability Institute for Science, Energy and Sustainability, California Institute of TechnologyNatural Sciences and Engineering Research Council of CanadaCalifornia Institute of TechnologyNational Institutes of HealthNational Science Foundation
KeywordsCarbyneNitrogenaseChemistryLigand (biochemistry)SulfideCrystallographyStereochemistryBridging ligandAmmoniaNitrogenCrystal structureNitrogen fixationCarbeneOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Nitrogen-fixing organisms perform dinitrogen reduction to ammonia at an iron-M (M = Mo, Fe, or V) cofactor (FeMco) of nitrogenase. FeMoco displays eight metal centers bridged by sulfides and a carbide having the MoFe7S8C cluster composition. The role of the carbide ligand, a unique motif in protein active sites, remains poorly understood. Toward addressing its function, we isolated synthetic models of subsite MFe3S3C displaying sulfides and a carbyne ligand. We developed synthetic protocols for structurally related clusters, [Tp*MFe3S3X]n-, where M = Mo or W, the bridging ligand X = CR, N, NR, S, and Tp* = tris(3,5-dimethyl-1-pyrazolyl)hydroborate, to study the effects of the identity of the heterometal and the bridging X group on structure and electrochemistry. While the nature of M results in minor changes, the μ3-bridging ligand X has a large impact on reduction potentials, with differences higher than 1 V, even for the same formal charge, the most reducing clusters being supported by the carbyne ligand.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.217
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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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