Evidence map›Paper›PMID 21943424›Full record

ArticleBiophysical journal2011

Relation between molecular shape and the morphology of self-assembling aggregates: a simulation study.

Robert Vácha, Daan Frenkel

Abstract read
In one paragraph

Article in Biophysical journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Review
  2. Article
  3. Prediction and Evaluation of Protein Aggregation with Computational Methods.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  4. Article
  5. Review
  6. Review
  7. Self-replication of AProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  8. Article
  9. Computational Models for the Study of Protein Aggregation.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Beyond icosahedral symmetry in packings of proteins in spherical shells.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  19. Article
  20. Challenges in structural approaches to cell modeling.Journal of molecular biology · 2016
    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

2 authors.

Robert VáchaDepartment of Chemistry, University of Cambridge, Cambridge, United Kingdom. rv260@cam.ac.uk
Daan Frenkel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteins can aggregate in a wide variety of structures, both compact and extended. We present simulations of a coarse-grained anisotropic model that reproduce many of the experimentally observed aggregate structures. Conversely, all structures predicted by our model have experimental counterparts (ribbons, multistranded fibrils, and vesicles). The model we use is that of a rodlike particle with an attractive (hydrophobic) stripe on its side. Our Monte Carlo simulations show that aggregate morphologies crucially depend on two parameters. The first one is the width of the attractive stripe and the second one is a presence or absence of attractive interactions at the particle ends. These results provide us with a generic insight into the relation between the shape of protein-protein interaction potential and the morphology of protein aggregates.

Indexed as

Models, MolecularProtein MultimerizationAnisotropyHydrophobic and Hydrophilic InteractionsMonte Carlo MethodProteinsProtein Structure, SecondaryVolatilizationProteins

Identifiers

PMID21943424
PMCPMC3177051

What OpenQuestion 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 OpenQuestion graph.