Evidence map›Paper›PMID 25855953›Full record

ArticleJournal of functional biomaterials2015

Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

Adriana A T Martin, Michael Tomasini, Vladyslav Kholodovych, Li Gu, Sven Daniel Sommerfeld, Kathryn E Uhrich, N Sanjeeva Murthy, William J Welsh, Prabhas V Moghe

Abstract read
In one paragraph

Article in Journal of functional biomaterials, 2015. 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. Review
  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

9 authors.

Adriana A T MartinDepartment of Pharmacology, Rutgers University, Piscataway, 675 Hoes Lane, Piscataway, NJ 08854, USA. adrianamartin7@gmail.com.
Michael TomasiniDepartment of Chemical and Biochemical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. toma0052@gmail.com.
Vladyslav KholodovychDepartment of Pharmacology, Rutgers University, Piscataway, 675 Hoes Lane, Piscataway, NJ 08854, USA. kholodvl@ca.rutgers.edu.
Li GuDepartment of Chemistry and Chemical Biology, Rutgers University, 610 Taylor Road, Piscataway, NJ 08854, USA. lig@mit.edu.
Sven Daniel SommerfeldNew Jersey Center for Biomaterials, 145 Bevier Road, Piscataway, NJ 08854, USA. Sommerfeld@dls.rutgers.edu.
Kathryn E UhrichDepartment of Chemistry and Chemical Biology, Rutgers University, 610 Taylor Road, Piscataway, NJ 08854, USA. keuhrich@rutgers.edu.
N Sanjeeva MurthyNew Jersey Center for Biomaterials, 145 Bevier Road, Piscataway, NJ 08854, USA. Murthy@dls.rutgers.edu.
William J WelshDepartment of Pharmacology, Rutgers University, Piscataway, 675 Hoes Lane, Piscataway, NJ 08854, USA. welshwj@rwjms.rutgers.edu.
Prabhas V MogheDepartment of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA. Moghe@rutgers.edu.

Funding

Translational Research Support CoreP30ES005022 · NIEHS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI PANOS G. GEORGOPOULOS · 1988 to 2026
$47.4M
RESBIO - the Technology Resource for Polymeric BiomaterialsP41EB001046 · NIBIB · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI KOHN, JOACHIM B. · 2003 to 2017
$17.0M
UMDNJ-RUTGERS UNIVERSITY PIPELINE PROGRAMR25GM055145 · NIGMS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI HAIMOVICH, BEATRICE, LANGER, JEROME ALAN · 1996 to 2020
$8.7M
UMDNJ TRAINING GRANT IN BIOTECHNOLOGYT32GM008339 · NIGMS · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI YARMUSH, MARTIN L · 1989 to 2019
$6.1M
Synthetic Counter-ligands for Inhibition of AtherosclerosisR01HL107913 · NHLBI · RUTGERS, THE STATE UNIV OF N.J. · PI MOGHE, PRABHAS V, UHRICH, KATHRYN ELIZABETH · 2011 to 2014
$2.3M
Nanoscale Receptor Blockers for Inhibition of AtherosclerosisR21HL093753 · NHLBI · RUTGERS, THE STATE UNIV OF N.J. · PI MOGHE, PRABHAS V · 2009 to 2010
$671k
NHLBI NIH HHS R01 HL107913NHLBI NIH HHS R21 HL093753NIBIB NIH HHS P41 EB001046NIEHS NIH HHS P30 ES005022NIGMS NIH HHS R25 GM055145NIGMS NIH HHS T32 GM008339
6 · The paper itself

Abstract

The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

Identifiers

PMID25855953
PMCPMC4493506

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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.