4.6 Article

Connecting Macroscopic Observables and Microscopic Assembly Events in Amyloid Formation Using Coarse Grained Simulations

期刊

PLOS COMPUTATIONAL BIOLOGY
卷 8, 期 10, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1002692

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资金

  1. University of Cambridge, Churchill College, Cambridge
  2. European Regional Development Fund [CZ.1.05/1.1.00/02.0068]
  3. Wellcome Trust
  4. BBSRC
  5. ERC [227758]
  6. Royal Society of London [2007/R3]
  7. EPSRC [EP/I001352/1]
  8. EPSRC [EP/I001352/1] Funding Source: UKRI
  9. MRC [MC_G1000734] Funding Source: UKRI
  10. Engineering and Physical Sciences Research Council [EP/I001352/1] Funding Source: researchfish
  11. Medical Research Council [MC_G1000734] Funding Source: researchfish

向作者/读者索取更多资源

The pre-fibrillar stages of amyloid formation have been implicated in cellular toxicity, but have proved to be challenging to study directly in experiments and simulations. Rational strategies to suppress the formation of toxic amyloid oligomers require a better understanding of the mechanisms by which they are generated. We report Dynamical Monte Carlo simulations that allow us to study the early stages of amyloid formation. We use a generic, coarse-grained model of an amyloidogenic peptide that has two internal states: the first one representing the soluble random coil structure and the second one the beta-sheet conformation. We find that this system exhibits a propensity towards fibrillar self-assembly following the formation of a critical nucleus. Our calculations establish connections between the early nucleation events and the kinetic information available in the later stages of the aggregation process that are commonly probed in experiments. We analyze the kinetic behaviour in our simulations within the framework of the theory of classical nucleated polymerisation, and are able to connect the structural events at the early stages in amyloid growth with the resulting macroscopic observables such as the effective nucleus size. Furthermore, the free-energy landscapes that emerge from these simulations allow us to identify pertinent properties of the monomeric state that could be targeted to suppress oligomer formation.

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