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Record W2981566651 · doi:10.3390/biom9110646

Design of N-Terminal Derivatives from a Novel Dermaseptin Exhibiting Broad-Spectrum Antimicrobial Activity against Isolates from Cystic Fibrosis Patients

2019· article· en· W2981566651 on OpenAlexfundno aff
Ying Yuan, Hui Wang, Xinping Xi, Chengbang Ma, Yue Liu, Mei Zhou, Qiang Du, James F. Burrows, Minjie Wei, Tianbao Chen, Lei Wang

Bibliographic record

VenueBiomolecules · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsnot available
FundersQueen's UniversityNational Natural Science Foundation of ChinaQueen's University Belfast
KeywordsAntimicrobialPeptideAntimicrobial peptidesChemistryDerivative (finance)BiofilmPotencyCystic fibrosisBacteriaMicrobiologyStereochemistryCombinatorial chemistryBiochemistryBiologyIn vitro

Abstract

fetched live from OpenAlex

, and further investigate the properties of this peptide, and a number of rationally designed truncated derivatives. The truncated 19-mer derived from the N-terminus exhibited similar antimicrobial potency when compared to the parent peptide, but the haemolytic effect of this truncated peptide was significantly decreased. Based on previous studies, the charge and hydrophobicity of truncated derivatives can affect the bioactivity of these peptides and thus we designed a 10-mer derivative with an optimised positive charge and a cyclohexylalanine (Cha) at the C-terminus for enhancing the hydrophobicity, DMPC-10A, which retained the antimicrobial activity of the parent peptide. To further investigate the influence of Cha at the C-terminus on activity, it was substituted by alanine (Ala) to generate another derivative, DMPC-10, but this was found to be much less potent. In addition, DM-PC, DMPC-19 and DMPC-10A not only rapidly killed planktonic bacteria isolated from cystic fibrosis (CF) patient, but also effectively eradicated their biofilm matrices.

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 categoriesMeta-epidemiology (narrow)
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 score0.018
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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.

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

Citations13
Published2019
Admission routes1
Has abstractyes

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