Evidence map›Paper›PMID 40164567›Full record

ArticleAngewandte Chemie (International ed. in English)2025

Hydrophobicity-Controlled Self-Assembly of Supramolecular Peptide Nanotubes in Water.

Min Zeng, William Parsons, Yixuan Chen, David K Chalmers, Sébastien Perrier

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Min Zeng *Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.
William Parsons *Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia.
Yixuan ChenDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.
David K ChalmersMonash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia.
Sébastien PerrierDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.

Funding

Royal Society NIF∖R1∖212165
6 · The paper itself

Abstract

Polymer-conjugated peptides are attractive building blocks for the construction of new nanomaterials. However, the ability to control the self-assembly of these materials remains a major limitation to their wider utilization. Herein, we report a facile strategy to fine-tune the assembly of water-soluble hydrophilic polymer-conjugated cyclic peptides by incorporating a defined, short hydrocarbon linker between the polymer and peptide. This addition creates a well-defined hydrophobic "inner shell" that suppresses water from disrupting the organized peptide hydrogen bond network. Our approach is demonstrated using a series of cyclic peptide-linker-PDMA conjugates that were evaluated by asymmetric flow field flow fractionation, small angle neutron scattering and transmission electron microscopy. Molecular dynamics simulations were also used to show how the polymer and the peptide stacks interact and illustrate the impact of this hydrophobic inner shell approach. This strategy provides a modular approach to fine control the nanotube self-assembling behavior. We expect that this technique will improve the versatility of peptide nanotubes for the engineering of advanced nanomaterials.

Indexed as

NanotubesNanotubes, PeptidePeptidesPeptides, CyclicWaterHydrophobic and Hydrophilic InteractionsMolecular Dynamics SimulationNanotubes, PeptidePeptidesPeptides, CyclicWaterCyclic peptideMolecular dynamics simulationNanotubeSelf‐assemblySupramolecular

Identifiers

PMID40164567
PMCPMC12105707

What OpenQuestion holds

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LicenceCC BY
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.