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Record W2019275100 · doi:10.2174/1386207053764558

Design of Host Defence Peptides for Antimicrobial and Immunity Enhancing Activities

2005· review· en· W2019275100 on OpenAlexafffund
Joseph B. McPhee, Monisha G. Scott, Robert E. W. Hancock

Bibliographic record

VenueCombinatorial Chemistry & High Throughput Screening · 2005
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of British Columbia
FundersGenome PrairieCanada Research ChairsGenome British ColumbiaCystic Fibrosis Foundation
KeywordsAntimicrobial peptidesAntimicrobialInnate immune systemBiologyHost (biology)OrganismFunction (biology)Immune systemImmunityComputational biologyMicrobiologyEcologyImmunologyEvolutionary biologyGenetics

Abstract

fetched live from OpenAlex

Host defense peptides are a vital component of the innate immune systems of humans, other mammals, amphibians, and arthropods. The related cationic antimicrobial peptides are also produced by many species of bacteria and function as part of the antimicrobial arsenal to help the producing organism reduce competition for resources from sensitive species. The antimicrobial activities of many of these peptides have been extensively characterized and the structural requirements for these activities are also becoming increasingly clear. In addition to their known antimicrobial role, many host defense peptides are also involved in a plethora of immune functions in the host. In this review, we examine the role of structure in determining antimicrobial activity of certain prototypical cationic peptides and ways that bacteria have evolved to usurp these activities. We also review recent literature on what structural components are related to these immunomodulatory effects. It must be stressed however that these studies, and the area of peptide research, are still in their infancy. Keywords: cationic antimicrobial peptide, intracellular targets, bacterial membrane, polyphemusin, lipopolysaccharide (lps), phosphatidylglycerol (pg), electrophorese, hydrophobic moment, gramicidin s (gs), gram-negative bacteria

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.436
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.036
GPT teacher head0.286
Teacher spread0.249 · 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
GenreReview

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

Citations76
Published2005
Admission routes2
Has abstractyes

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