Evidence map›Paper›PMID 30859819›Full record

ArticleChemical reviews2019

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance.

Giray Enkavi, Matti Javanainen, Waldemar Kulig, Tomasz Róg, Ilpo Vattulainen

Abstract read
In one paragraph

Article in Chemical reviews, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers.

0numbers the graph read from it
0cells of the map it votes in
122citing 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

122 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Sketching microprotein portraits.Protein science : a publication of the Protein Society · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. bioRxiv : the preprint server for biology · 2025
    Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Marine Natural Products as Novel Treatments for Parasitic Diseases.Handbook of experimental pharmacology · 2025
    Review
  17. Review
  18. Article
  19. Toward understanding lipid reorganization in RNA lipid nanoparticles in acidic environments.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  20. Article

62 more citing papers are in PubMed but not listed here.

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.

Giray EnkaviDepartment of Physics , University of Helsinki , P.O. Box 64, FI-00014 Helsinki , Finland.ORCID 0000-0001-5033-8649
Matti JavanainenDepartment of Physics , University of Helsinki , P.O. Box 64, FI-00014 Helsinki , Finland.ORCID 0000-0003-4858-364X
Waldemar KuligDepartment of Physics , University of Helsinki , P.O. Box 64, FI-00014 Helsinki , Finland.ORCID 0000-0001-7568-0029
Tomasz RógDepartment of Physics , University of Helsinki , P.O. Box 64, FI-00014 Helsinki , Finland.ORCID 0000-0001-6765-7013
Ilpo VattulainenDepartment of Physics , University of Helsinki , P.O. Box 64, FI-00014 Helsinki , Finland.ORCID 0000-0001-7408-3214

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

Indexed as

Models, BiologicalAnimalsCarboxylic AcidsComputer SimulationHumansLipidomicsMembrane LipidsMembranesPhospholipidsCarboxylic AcidsMembrane LipidsPhospholipids

Identifiers

PMID30859819
PMCPMC6727218

What Socratic holds

Textmetadata
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 Socratic graph.