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Record W2107391428 · doi:10.3762/bjoc.8.130

Design of a novel tryptophan-rich membrane-active antimicrobial peptide from the membrane-proximal region of the HIV glycoprotein, gp41

2012· article· en· W2107391428 on OpenAlexafffund
Leonard T. Nguyen, David Schibli, Hans J. Vogel

Bibliographic record

VenueBeilstein Journal of Organic Chemistry · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsOntario GenomicsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesUniversity of Calgary
KeywordsPeptideChemistryAntimicrobialAntimicrobial peptidesGp41MembraneBiochemistryGlycoproteinTryptophanResidue (chemistry)BiophysicsAmino acidBiologyImmunologyEpitopeOrganic chemistry

Abstract

fetched live from OpenAlex

A number of physicochemical characteristics have been described which contribute to the biological activity of antimicrobial peptides. This information was used to design a novel antimicrobial peptide sequence by using an intrinsically inactive membrane-associated peptide derived from the HIV glycoprotein, gp41, as a starting scaffold. This peptide corresponds to the tryptophan-rich membrane-proximal region of gp41, which is known to interact at the interfacial region of the viral membrane and adopts a helical structure in the presence of lipids. Three synthetic peptides were designed to increase the net positive charge and amphipathicity of this 19-residue peptide. Ultimately, the peptide with the greatest degree of amphipathicity and largest positive charge proved to be the most potent antimicrobial, and this peptide could be further modified to improve the antimicrobial activity. However, the other two peptides were relatively ineffective antimicrobials and instead proved to be extremely hemolytic. This work demonstrates a novel approach for the design of unexplored antimicrobial peptide sequences but it also reveals that the biological and cytotoxic activities of these polypeptides depend on a number of interrelated factors.

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 score0.003
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.211
Teacher spread0.193 · 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

Citations26
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueBeilstein Journal of Organic ChemistrySame topicAntimicrobial Peptides and ActivitiesFrench-language works237,207