Evidence map›Paper›PMID 22194847›Full record

ArticlePloS one2011

Prediction of antibacterial activity from physicochemical properties of antimicrobial peptides.

Manuel N Melo, Rafael Ferre, Lídia Feliu, Eduard Bardají, Marta Planas, Miguel A R B Castanho

Abstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Manuel N MeloInstitute of Molecular Medicine, University of Lisbon, Lisbon, Portugal. m.n.melo@rug.nl
Rafael Ferre
Lídia Feliu
Eduard Bardají
Marta Planas
Miguel A R B Castanho

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations.

Indexed as

Anti-Bacterial AgentsAntimicrobial Cationic PeptidesCell MembraneGram-Negative BacteriaMicrobial Sensitivity TestsModels, BiologicalOligopeptidesAnti-Bacterial AgentsAntimicrobial Cationic Peptideslysyl-lysyl-leucyl-phenylalanyl-lysyl-lysyl-isoleucyl-leucyl-lysyl-tyrosyl-leucinamideOligopeptidesomiganan pentahydrochloride

Identifiers

PMID22194847
PMCPMC3237455

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.