Evidence map›Paper›PMID 28853474›Full record

ReviewOrganic & biomolecular chemistry2017

Molecular simulations of peptide amphiphiles.

Anjela Manandhar, Myungshim Kang, Kaushik Chakraborty, Phu K Tang, Sharon M Loverde

Abstract readReview
In one paragraph

Review in Organic & biomolecular chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
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  9. Review
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  14. Molecular Dynamics Simulations of Supramolecular Anticancer Nanotubes.Journal of chemical information and modeling · 2018
    Article
  15. Article
  16. Review
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.

Anjela ManandharDepartment of Chemistry, College of Staten Island, City University of New York, Staten Island, NY 10314, USA. Sharon.Loverde@csi.cuny.edu.
Myungshim Kang
Kaushik Chakraborty
Phu K Tang
Sharon M Loverde

Funding

Molecular Modeling of Peptide-Drug AmphiphilesR15EB020343 · NIBIB · COLLEGE OF STATEN ISLAND · PI LOVERDE, SHARON MARIE · 2016 to 2016
$477k
NIBIB NIH HHS R15 EB020343
6 · The paper itself

Abstract

This review describes recent progress in the area of molecular simulations of peptide assemblies, including peptide-amphiphiles and drug-amphiphiles. The ability to predict the structure and stability of peptide self-assemblies from the molecular level up is vital to the field of nanobiotechnology. Computational methods such as molecular dynamics offer the opportunity to characterize intermolecular forces between peptide-amphiphiles that are critical to the self-assembly process. Furthermore, these computational methods provide the ability to computationally probe the structure of these supramolecular assemblies at the molecular level, which is a challenge experimentally. Herein, we briefly highlight progress in the areas of all-atomistic and coarse-grained simulation studies investigating the self-assembly process of short peptides and peptide amphiphiles. We also discuss recent all-atomistic and coarse-grained simulations of the self-assembly of a drug-amphiphile into elongated filaments. Next, we discuss how these computational methods can provide further insight into the pathway of cylindrical nanofiber formation and predict their biocompatibility by studying the interaction of these peptide-amphiphile nanostructures with model cell membranes.

Indexed as

Computer SimulationModels, ChemicalModels, MolecularPeptidesPeptides

Identifiers

PMID28853474
PMCPMC5744600

What OpenQuestion holds

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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.