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Record W3114295265 · doi:10.1021/acsomega.0c05254

Systematic Design and Validation of Ion Channel Stabilization of Amphipathic α-Helical Peptides Incorporating Tryptophan Residues

2020· article· en· W3114295265 on OpenAlexaff
Keita Shigedomi, Satoshi Osada, Masoud Jelokhani‐Niaraki, Hiroaki Kodama

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsWilfrid Laurier University
FundersMinistry of Education, Culture, Sports, Science and Technology
KeywordsChemistryTryptophanAmphiphilePeptideCircular dichroismIon channelBiophysicsTransmembrane proteinHelix (gastropod)Transmembrane domainLiposomeMembraneStereochemistryBiochemistryAmino acidOrganic chemistryReceptor

Abstract

fetched live from OpenAlex

Aromatic interactions such as π-π interaction and cation-π interaction are present in membrane proteins and play important roles in both structure and function. To systematically investigate the effect of aromatic residues on the structural stability and ion permeability of peptide-formed ion channels, we designed several peptides with one or two tryptophan (Trp) residues incorporated at different positions in amphipathic α-helical peptides. Circular dichroism (CD) studies revealed the preferable position of Trp residues for self-association in these designed peptides. Systematically designed di-substituted peptides with two Trps at each helix termini demonstrated intermolecular Trp-Trp interactions caused by aggregation. In the presence of liposomes, Trp on the hydrophilic face of the peptide enhanced interaction with the lipid membrane to increase the amphipathic α-helical contents. Appropriate incorporation and positioning of Trp enabled peptides to form more stable channels and had notable effects with Trp di-substituted peptides. The ion channel forming capability of a series of these peptides showed that the cation-π interactions between Trp and Lys residues in adjacent transmembrane helices contribute to remarkable stabilization of the channel structure.

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)0.000
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 score0.011
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.029
GPT teacher head0.235
Teacher spread0.205 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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