Evidence map›Paper›PMID 23108593›Full record

ReviewAmino acids2013

Cationic membrane peptides: atomic-level insight of structure-activity relationships from solid-state NMR.

Yongchao Su, Shenhui Li, Mei Hong

Abstract readReview
In one paragraph

Review in Amino acids, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Solid-State NMR of Virus Membrane Proteins.Accounts of chemical research · 2025
    Article
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  6. Review
  7. Article
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  14. Article
  15. Cm-p5: an antifungal hydrophilic peptide derived from the coastal mollusk Cenchritis muricatus (Gastropoda: Littorinidae).FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2015
    Article
  16. Article
  17. Article
  18. Article
  19. 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

3 authors.

Yongchao SuDepartment of Chemistry, Iowa State University, Ames, IA 50011, USA. ycsu@mit.edu
Shenhui Li
Mei Hong

Funding

Structures and lipid interactions of curvature-inducing membrane peptides by NMRR01GM066976 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HONG, MEI · 2003 to 2021
$4.8M
NIGMS NIH HHS GM066976NIGMS NIH HHS R01 GM066976
6 · The paper itself

Abstract

Many membrane-active peptides, such as cationic cell-penetrating peptides (CPPs) and antimicrobial peptides (AMPs), conduct their biological functions by interacting with the cell membrane. The interactions of charged residues with lipids and water facilitate membrane insertion, translocation or disruption of these highly hydrophobic species. In this review, we will summarize high-resolution structural and dynamic findings towards the understanding of the structure-activity relationship of lipid membrane-bound CPPs and AMPs, as examples of the current development of solid-state NMR (SSNMR) techniques for studying membrane peptides. We will present the most recent atomic-resolution structure of the guanidinium-phosphate complex, as constrained from experimentally measured site-specific distances. These SSNMR results will be valuable specifically for understanding the intracellular translocation pathway of CPPs and antimicrobial mechanism of AMPs, and more generally broaden our insight into how cationic macromolecules interact with and cross the lipid membrane.

Indexed as

AnimalsAntimicrobial Cationic PeptidesCell MembraneCell-Penetrating PeptidesHumansMagnetic Resonance SpectroscopyStructure-Activity RelationshipAntimicrobial Cationic PeptidesCell-Penetrating Peptides

Identifiers

PMID23108593
PMCPMC3570695

What OpenQuestion holds

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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.