Evidence map›Paper›PMID 20946928›Full record

ReviewPeptides2011

Computational studies of protegrin antimicrobial peptides: a review.

Dan S Bolintineanu, Yiannis N Kaznessis

Abstract readReview
In one paragraph

Review in Peptides, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
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

32 citing papers in PubMed, 78 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Concerted Rolling and Penetration of Peptides during Membrane Binding.Journal of chemical theory and computation · 2022
    Article
  9. Frontiers in plant science · 2021
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Computational studies of peptide-induced membrane pore formation.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
    Review
  16. Computational prediction of the optimal oligomeric state for membrane-inserted β-barrels of protegrin-1 and related mutants.Journal of peptide science : an official publication of the European Peptide Society · 2017
    Article
  17. Article
  18. Article
  19. Review
  20. Article
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

2 authors at 1 institution in 1 country.

Dan S BolintineanuDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Ave SE, Minneapolis, MN 55455, USA.
Yiannis N Kaznessis
University of Minnesota · US

Funding

Computational Modeling /Design of Antimicrobial PeptidesR01GM070989 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI KAZNESSIS, YIANNIS · 2005 to 2009
$1.1M
NIGMS NIH HHS GM 070989NIGMS NIH HHS R01 GM070989
6 · The paper itself

Abstract

Antimicrobial peptides (AMPs) are small, naturally occurring peptides that exhibit strong antibacterial properties generally believed to be a result of selective bacterial membrane disruption. As a result, there has been significant interest in the development of therapeutic antibiotics based on AMPs; however, the poor understanding of the fundamental mechanism of action of these peptides has largely hampered such efforts. We present a summary of computational and theoretical investigations of protegrin, a particularly potent peptide that is both an excellent model for the mechanism of action of AMPs and a promising therapeutic candidate. Experimental investigations have shed light on many of the key steps in the action of protegrin: protegrin monomers are known to dimerize in various lipid environments; protegrin peptides interact strongly with lipid bilayer membranes, particularly anionic lipids; protegrins have been shown to form pores in lipid bilayers, which results in uncontrolled ion transport and may be a key factor in bacterial death. In this work, we present a comprehensive review of the computational and theoretical studies that have complemented and extended the information obtained from experimental work with protegrins, as well as a brief survey of the experimental biophysical studies that are most pertinent to such computational work. We show that a consistent, mechanistic description of the bactericidal mechanism of action of protegrins is emerging, and briefly outline areas where the current understanding is deficient. We hope that the research reviewed herein offers compelling evidence of the benefits of computational investigations of protegrins and other AMPs, as well as providing a useful guide to future work in this area.

Indexed as

Anti-Infective AgentsAntimicrobial Cationic PeptidesLipid BilayersMolecular Dynamics SimulationProtein ConformationAnti-Infective AgentsAntimicrobial Cationic PeptidesLipid Bilayers

Identifiers

PMID20946928
PMCPMC3013618
OpenAlexW2016768959

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.