Evidence map›Paper›PMID 25341001›Full record

ArticleFaraday discussions2014

Methodologies for the analysis of instantaneous lipid diffusion in MD simulations of large membrane systems.

Matthieu Chavent, Tyler Reddy, Joseph Goose, Anna Caroline E Dahl, John E Stone, Bruno Jobard, Mark S P Sansom

Abstract read
In one paragraph

Article in Faraday discussions, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Dynamics and Activation of Membrane-Bound B Cell Receptor Assembly.bioRxiv : the preprint server for biology · 2024
    Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Design - a new way to look at old molecules.Journal of integrative bioinformatics · 2022
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

7 authors.

Matthieu ChaventDepartment of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, United Kingdom. matthieu.chavent@bioch.ox.ac.uk.
Tyler ReddyDepartment of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, United Kingdom. matthieu.chavent@bioch.ox.ac.uk.
Joseph GooseDepartment of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, United Kingdom. matthieu.chavent@bioch.ox.ac.uk.
Anna Caroline E DahlDepartment of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, United Kingdom. matthieu.chavent@bioch.ox.ac.uk.
John E StoneBeckman Institute University of Illinois, 405 N. Mathews Avenue Urbana, IL 61801, USA.
Bruno JobardLIUPPA laboratory, University of Pau, 1, av. de l'Université, 64013 Pau Cedex, FRANCE.
Mark S P SansomDepartment of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, United Kingdom. matthieu.chavent@bioch.ox.ac.uk.

Funding

WHOLE CELL SIMULATIONP41GM104601 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2012 to 2021
$19.0M
Biotechnology and Biological Sciences Research Council B19456Biotechnology and Biological Sciences Research Council BB/H000267/1Biotechnology and Biological Sciences Research Council BB/I019855/1Biotechnology and Biological Sciences Research Council BB/L002558/1Biotechnology and Biological Sciences Research Council BB/L01386X/1Biotechnology and Biological Sciences Research Council BBS/B/16011Biotechnology and Biological Sciences Research Council BEP17032CIHRNIGMS NIH HHS 9P41GM104601NIGMS NIH HHS P41 GM104601Wellcome Trust
6 · The paper itself

Abstract

Interactions between lipids and membrane proteins play a key role in determining the nanoscale dynamic and structural properties of biological membranes. Molecular dynamics (MD) simulations provide a valuable tool for studying membrane models, complementing experimental approaches. It is now possible to simulate large membrane systems, such as simplified models of bacterial and viral envelope membranes. Consequently, there is a pressing need to develop tools to visualize and quantify the dynamics of these immense systems, which typically comprise millions of particles. To tackle this issue, we have developed visual and quantitative analyses of molecular positions and their velocity field using path line, vector field and streamline techniques. This allows us to highlight large, transient flow-like movements of lipids and to better understand crowding within the lipid bilayer. The current study focuses on visualization and analysis of lipid dynamics. However, the methods are flexible and can be readily applied to e.g. proteins and nanoparticles within large complex membranes. The protocols developed here are readily accessible both as a plugin for the molecular visualization program VMD and as a module for the MDAnalysis library.

Indexed as

Molecular Dynamics SimulationDiffusionMembrane LipidsMembrane ProteinsMembrane LipidsMembrane Proteins

Identifiers

PMID25341001
PMCPMC4208077

What OpenQuestion holds

Textmetadata
LicenceTDM
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.