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Record W2044775677 · doi:10.1073/pnas.1117783109

Two copies of the SecY channel and acidic lipids are necessary to activate the SecA translocation ATPase

2012· article· en· W2044775677 on OpenAlexafffund
Kush Dalal, Catherine Chan, Stephen G. Sligar, Franck Duong

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversity of British Columbia
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsChromosomal translocationDimerTransport proteinATPaseTranslocaseCell biologyCytoplasmChemistryVesicleBiophysicsBiochemistryMembrane transport proteinBiologyMembrane proteinMembraneEnzymeGene

Abstract

fetched live from OpenAlex

The SecA ATPase associates with the SecY complex to push preproteins across the bacterial membrane. Because a single SecY is sufficient to create the conducting channel, the function of SecY oligomerization remains unclear. Here, we have analyzed the translocation reaction using nanodiscs. We show that one SecY copy is sufficient to bind SecA and the preprotein, but only the SecY dimer together with acidic lipids supports the activation of the SecA translocation ATPase. In discs, the dimer is predominantly arranged in a back-to-back manner and remains active even if a constituent SecY copy is defective for SecA binding. In membrane vesicles and in intact cells, the coproduction of two inactive SecYs, one for channel gating and the other for SecA binding, recreates a functional translocation unit. These results indisputably argue that the SecY dimer is crucial for the activation of SecA, which is necessary for preprotein transport.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.278
Teacher spread0.254 · 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

Citations49
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicBacterial Genetics and BiotechnologyFrench-language works237,207