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Record W1504727591 · doi:10.1002/9780470515716.ch5

Engineering Charge Selectivity in Alamethicin Channels

2007· article· en· W1504727591 on OpenAlexaff
G. Andrew Woolley, A. V. Starostin, Radu Butan, D. Andrew James, Holger Wenschuh, Mark S.P. Sansom

Bibliographic record

VenueNovartis Foundation symposium · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAlamethicinSelectivityChemistryPeptideIon channelMembraneDivalentIonMembrane potentialBiophysicsBiochemistryOrganic chemistryLipid bilayerBiology

Abstract

fetched live from OpenAlex

The peptide alamethicin provides a system for engineering ion channel charge selectivity. To define alamethicin charge selectivity experimentally, we measured single-channel current-voltage relationships in KCl gradients using covalently linked peptide dimers. Two factors were found to contribute to the charge selectivity of these channels: (i) the ionic strength of the surrounding solutions; and (ii) the distribution of fixed charge on the peptide. Native alamethicin channels exhibited either cation selectivity or anion selectivity depending on which end of the channel was at the low salt side of the membrane. When the glutamine residue at position 18 in the sequence was replaced with a lysine residue, an anion-selective channel was obtained regardless of which end of the channel was at the low salt side of the membrane.

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 score0.025
Threshold uncertainty score0.554

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.265
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 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

Citations1
Published2007
Admission routes1
Has abstractyes

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