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Record W2884701921 · doi:10.1038/s41598-018-29693-z

Engineered Protein Model of the ATP synthase H+- Channel Shows No Salt Bridge at the Rotor-Stator Interface

2018· article· en· W2884701921 on OpenAlexafffund
Hannah Pierson, Mandeep Kaler, Christopher O’Grady, Eva-Maria E. Uhlemann, Oleg Y. Dmitriev

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthUniversity of Wisconsin-Madison
KeywordsATP synthaseRotor (electric)StatorInterface (matter)Salt bridgeBridge (graph theory)Channel (broadcasting)Computer scienceSalt (chemistry)ChemistryCell biologyBiophysicsBioinformaticsBiologyBiochemistryEngineeringEnzymeElectrical engineeringComputer networkAnatomyGene

Abstract

fetched live from OpenAlex

ATP synthase is powered by the flow of protons through the molecular turbine composed of two α-helical integral membrane proteins, subunit a, which makes a stator, and a cylindrical rotor assembly made of multiple copies of subunit c. Transient protonation of a universally conserved carboxylate on subunit c (D61 in E. coli) gated by the electrostatic interaction with arginine on subunit a (R210 in E. coli) is believed to be a crucial step in proton transfer across the membrane. We used a fusion protein consisting of subunit a and the adjacent helices of subunit c to test by NMR spectroscopy if cD61 and aR210 are involved in an electrostatic interaction with each other, and found no evidence of such interaction. We have also determined that R140 does not form a salt bridge with either D44 or D124 as was suggested previously by mutation analysis. Our results demonstrate the potential of using arginines as NMR reporter groups for structural and functional studies of challenging membrane 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)0.001
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 score0.031
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.022
GPT teacher head0.283
Teacher spread0.260 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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