Evidence map›Paper›PMID 25438167›Full record

ArticleNanoscale2015

Receptor-mediated membrane adhesion of lipid-polymer hybrid (LPH) nanoparticles studied by dissipative particle dynamics simulations.

Zhenlong Li, Alemayehu A Gorfe

Abstract read
In one paragraph

Article in Nanoscale, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. 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.

Zhenlong LiDepartment of Integrative Biology and Pharmacology, The University of Texas Health Science Center at Houston, 6431 Fannin St., Houston, Texas 77030, USA. zhenlong.li@uth.tmc.edu alemayehu.a.gorfe@uth.tmc.edu.
Alemayehu A Gorfe

Funding

Nanoclusters of Lipid-anchored Proteins in Membranes: How and where they appearR01GM100078 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI GORFE, ALEMAYEHU A. · 2012 to 2016
$1.4M
NIGMS NIH HHS R01 GM100078
6 · The paper itself

Abstract

Lipid-polymer hybrid (LPH) nanoparticles represent a novel class of targeted drug delivery platforms that combine the advantages of liposomes and biodegradable polymeric nanoparticles. However, the molecular details of the interaction between LPHs and their target cell membranes remain poorly understood. We have investigated the receptor-mediated membrane adhesion process of a ligand-tethered LPH nanoparticle using extensive dissipative particle dynamics (DPD) simulations. We found that the spontaneous adhesion process follows a first-order kinetics characterized by two distinct stages: a rapid nanoparticle-membrane engagement, followed by a slow growth in the number of ligand-receptor pairs coupled with structural re-organization of both the nanoparticle and the membrane. The number of ligand-receptor pairs increases with the dynamic segregation of ligands and receptors toward the adhesion zone causing an out-of-plane deformation of the membrane. Moreover, the fluidity of the lipid shell allows for strong nanoparticle-membrane interactions to occur even when the ligand density is low. The LPH-membrane avidity is enhanced by the increased stability of each receptor-ligand pair due to the geometric confinement and the cooperative effect arising from multiple binding events. Thus, our results reveal the unique advantages of LPH nanoparticles as active cell-targeting nanocarriers and provide some general principles governing nanoparticle-cell interactions that may aid future design of LPHs with improved affinity and specificity for a given target of interest.

Indexed as

Cell MembraneLigandsLipid BilayersLipidsNanoparticlesPolymersLigandsLipid BilayersLipidsPolymers

Identifiers

PMID25438167
PMCPMC5048752

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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.