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Record W2159700780 · doi:10.1074/jbc.m112.431270

The Mammalian Proteins MMS19, MIP18, and ANT2 Are Involved in Cytoplasmic Iron-Sulfur Cluster Protein Assembly

2012· article· en· W2159700780 on OpenAlexaff
Niek van Wietmarschen, Annie Moradian, Gregg B. Morin, Peter M. Lansdorp, Evert-Jan Uringa

Bibliographic record

VenueJournal of Biological Chemistry · 2012
Typearticle
Languageen
FieldEnergy
TopicMetalloenzymes and iron-sulfur proteins
Canadian institutionsBC Cancer AgencyUniversity of British ColumbiaCanada's Michael Smith Genome Sciences Centre
Fundersnot available
KeywordsCytosolProtein subunitTranslocaseCytoplasmIron–sulfur clusterBiochemistryCofactorChemistryBiologyCell biologyBiophysicsGeneEnzymeChromosomal translocation

Abstract

fetched live from OpenAlex

Iron-sulfur (Fe-S) clusters are essential cofactors of proteins with a wide range of biological functions. A dedicated cytosolic Fe-S cluster assembly (CIA) system is required to assemble Fe-S clusters into cytosolic and nuclear proteins. Here, we show that the mammalian nucleotide excision repair protein homolog MMS19 can simultaneously bind probable cytosolic iron-sulfur protein assembly protein CIAO1 and Fe-S proteins, confirming that MMS19 is a central protein of the CIA machinery that brings Fe-S cluster donor proteins and the receiving apoproteins into proximity. In addition, we show that mitotic spindle-associated MMXD complex subunit MIP18 also interacts with both CIAO1 and Fe-S proteins. Specifically, it binds the Fe-S cluster coordinating regions in Fe-S proteins. Furthermore, we show that ADP/ATP translocase 2 (ANT2) interacts with Fe-S apoproteins and MMS19 in the CIA complex but not with the individual proteins. Together, these results elucidate the composition and interactions within the late CIA complex.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.237
Teacher spread0.213 · 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 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

Citations50
Published2012
Admission routes1
Has abstractyes

Explore more

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