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Record W2035369171 · doi:10.1002/qua.20319

Computer simulations of voltage‐gated potassium channel KvAP

2004· article· en· W2035369171 on OpenAlexaff
D. Peter Tieleman, Kindal M. Robertson, Justin L. MacCallum, Luca Monticelli

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGatingPaddleChemistryPotassium channelVoltageCrystal structureChemical physicsMembrane potentialVoltage-gated potassium channelCrystallographyOctaneGranularityPotassiumCrystal (programming language)BiophysicsMaterials sciencePhysicsComputer scienceBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The recent crystal structures of the voltage‐gated potassium channel KvAP and its isolated voltage‐sensing “paddle” (composed of segments S1 to S4) (Jiang et al., Nature 2003, 423, 33–41) challenged existing models of voltage gating and encouraged a large number of experimental and theoretical studies to answer a number of questions about the structure of the physiologically relevant states of voltage‐gated potassium channels and their gating mechanism. We describe equilibrium simulations of the KvAP crystal structure. The crystal structure of the full channel undergoes a large conformational change, localized to the S1–S4 domains, as the S1–S4 domains move into the membrane. We also present a model of the closed state, in agreement with the position of the paddle in the paddle model of voltage gating. Finally, we estimate the energetic cost of transferring a single arginine sidechain from water into an octane slab with the approximate hydrophobic thickness of a membrane. © 2004 Wiley Periodicals, Inc. Int J Quantum Chem, 2004

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)0.003
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.268
Teacher spread0.253 · 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

Citations14
Published2004
Admission routes1
Has abstractyes

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