Evidence map›Paper›PMID 24454816›Full record

ArticlePloS one2014

A simple lattice model that captures protein folding, aggregation and amyloid formation.

Sanne Abeln, Michele Vendruscolo, Christopher M Dobson, Daan Frenkel

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
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

20 citing papers in PubMed, 74 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Mapping the configurational landscape and aggregation phase behavior of the tau protein fragment PHF6.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  7. Review
  8. Article
  9. Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  10. Computational Models for the Study of Protein Aggregation.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Review
  19. Article
  20. Knotted proteins: A tangled tale of Structural Biology.Computational and structural biotechnology journal · 2015
    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

4 authors at 1 institution in 1 country.

Sanne AbelnIBIVU - Deptartment of Computer Science, VU University, Amsterdam, The Netherlands.
Michele VendruscoloDeptartment of Chemistry, University of Cambridge, Cambridge, United Kingdom.
Christopher M DobsonDeptartment of Chemistry, University of Cambridge, Cambridge, United Kingdom.
Daan FrenkelDeptartment of Chemistry, University of Cambridge, Cambridge, United Kingdom.
University of Cambridge · GB

Funding

Biotechnology and Biological Sciences Research Council BB/H003843/1Wellcome Trust
6 · The paper itself

Abstract

The ability of many proteins to convert from their functional soluble state to amyloid fibrils can be attributed to inter-molecular beta strand formation. Such amyloid formation is associated with neurodegenerative disorders like Alzheimer's and Parkinson's. Molecular modelling can play a key role in providing insight into the factors that make proteins prone to fibril formation. However, fully atomistic models are computationally too expensive to capture the length and time scales associated with fibril formation. As the ability to form fibrils is the rule rather than the exception, much insight can be gained from the study of coarse-grained models that capture the key generic features associated with amyloid formation. Here we present a simple lattice model that can capture both protein folding and beta strand formation. Unlike standard lattice models, this model explicitly incorporates the formation of hydrogen bonds and the directionality of side chains. The simplicity of our model makes it computationally feasible to investigate the interplay between folding, amorphous aggregation and fibril formation, and maintains the capability of classic lattice models to simulate protein folding with high specificity. In our model, the folded proteins contain structures that resemble naturally occurring beta-sheets, with alternating polar and hydrophobic amino acids. Moreover, fibrils with intermolecular cross-beta strand conformations can be formed spontaneously out of multiple short hydrophobic peptide sequences. Both the formation of hydrogen bonds in folded structures and in fibrils is strongly dependent on the amino acid sequence, indicating that hydrogen-bonding interactions alone are not strong enough to initiate the formation of beta sheets. This result agrees with experimental observations that beta sheet and amyloid formation is strongly sequence dependent, with hydrophobic sequences being more prone to form such structures. Our model should open the way to a systematic study of the interplay between the factors that lead to amyloid formation.

Indexed as

Models, BiologicalProtein FoldingAmino Acid SequenceAmyloidMolecular Sequence DataAmyloid

Identifiers

PMID24454816
PMCPMC3893179
OpenAlexW2110845600

What OpenQuestion holds

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LicenceCC BY
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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.