Connecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulations

• Published in: PLoS computational biology Vol. 8; no. 10; p. e1002692
• Main Authors: Bieler, Noah S, Knowles, Tuomas P J, Frenkel, Daan, Vácha, Robert
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.10.2012; Public Library of Science (PLoS)
• Subjects: Aggregates; Agreements; Amyloid - chemistry; Amyloid - metabolism; Amyloid beta-Peptides - chemistry; Amyloid beta-Peptides - metabolism; Biology; Chemistry; Computational biology; Experiments; Glycoproteins; Humans; Kinetics; Molecular Dynamics Simulation; Molecular weight; Monte Carlo Method; Neurodegeneration; Peptides; Physiological aspects; Proteins; Reproducibility of Results; Studies; Theory; Thermodynamics; United Kingdom; Switzerland; Czech Republic; Thermodynamics; Reproducibility of Results; Humans; Amyloid beta-Peptides; Amyloid; Kinetics; Monte Carlo Method; Molecular Dynamics Simulation
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1002692

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 [Formula: see text]-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.