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Record W2046961604 · doi:10.1021/bi049414l

Antimicrobial 14-Helical β-Peptides:  Potent Bilayer Disrupting Agents

2004· article· en· W2046961604 on OpenAlexaff
Raquel F. Epand, L. Raguse, Samuel H. Gellman, Richard M. Epand

Bibliographic record

VenueBiochemistry · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsMcMaster UniversityHealth Sciences Centre
FundersNational Institute of General Medical Sciences
KeywordsMagaininAntimicrobial peptidesPeptideChemistryLiposomeMembraneLipid bilayerAmphiphileBilayerBiochemistryStereochemistryBiophysicsBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The interactions of two amphiphilic and cationic, nine-residue beta-peptides with liposomal membranes were studied. These beta-peptides are shown to form 14-helices in the presence of bilayers. Membrane binding and membrane permeabilization occur preferentially in the presence of anionic lipids. The beta-peptides have the ability to cause tranbilayer diffusion of phospholipids, form pores, and promote lipid mixing between liposomes. These beta-peptides have previously been shown to display antimicrobial activity comparable to that of a longer beta-peptide, beta-17, which adopts a different type of helical conformation (12-helix), and to the 23 amino acid (Ala(8,13,18))-magainin-II-amide, which adopts an alpha-helical conformation. In addition, these 14-helical beta-peptides show relatively low hemolytic activity. The biological potency and microbial specificity of the 14-helical beta-peptides, despite their relatively short length, suggests that 14-helices can be particularly disruptive to microbial membranes.

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 score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.243
Teacher spread0.229 · 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

Citations101
Published2004
Admission routes1
Has abstractyes

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