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. 2009 Aug;5(8):e1000458.
doi: 10.1371/journal.pcbi.1000458. Epub 2009 Aug 14.

A condensation-ordering mechanism in nanoparticle-catalyzed peptide aggregation

Affiliations

A condensation-ordering mechanism in nanoparticle-catalyzed peptide aggregation

Stefan Auer et al. PLoS Comput Biol. 2009 Aug.

Abstract

Nanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self-assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered as their size increases.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Illustration of the “condensation-ordering” mechanism of peptide self-assembly in the presence of a hydrophobic nanoparticle.
(A) Initially, at formula image microseconds, the peptides are in their monomeric state. (B) At intermediate times, formula image milliseconds, small oligomeric assemblies form on the nanoparticle surface. (C) At later times, formula image milliseconds, these oligomers re-order into fibrillar structures as their size increases. Peptides that do not form intermolecular hydrogen bonds are shown in blue, while peptides that form intermolecular hydrogen bonds are assigned a random colour, which is the same for peptides that belong to the same formula image. Two peptides are defined as belonging to the same cluster if their centres of mass distance is less than 5 Å. Two peptides are taken to participate within a formula image if they form more than four inter-chain hydrogen bonds with each other. The spherical nanoparticle is displayed in orange in the centre of the simulation box; the diameter of the peptides is slightly reduced for illustration purposes. Panels (B) and (C) show enlarged views of the nanoparticle-peptide system. The simulation was performed at formula image, formula image, formula image, and formula image.
Figure 2
Figure 2. Structural analysis of the nanoparticle-induced self-assembly mechanism.
(A) Average size of the largest cluster formula image observed during a simulation in presence of a hard sphere nanoparticle: formula image, formula image (green line), and several hydrophobic nanoparticles that differ in diameter and hydrophobicity: formula image, formula image (blue line), formula image, formula image (red line), and formula image, formula image (black line). The results are averaged over ten independent simulation runs and the error bars correspond to the standard deviation of the mean. (B) Number of clusters formula image of size formula image as a function of time: formula image microseconds (left), formula image milliseconds (middle), formula image milliseconds (right), for the MD trajectory and parameters described in Fig. 1. Black lines correspond to all clusters formed in the system; red lines correspond to the number of clusters formed on the nanoparticle surface. (C) Structural order parameter formula image as a function of the cluster size formula image averaged over ten independent simulations. The line colours are as described in (A). (D) Normalized density profile formula image, where formula image is the bulk density of the system, as a function of the distance from the centre of mass of the nanoparticle at the beginning of the simulation, formula image microseconds (left panel), intermediate times, formula image milliseconds (middle panel), and at the end formula image milliseconds (right panel). The different line colours are as described in (A) and correspond to the different seed sizes and peptide seed interaction energies. The results are averaged over ten independent simulations and the error bars correspond to the standard deviation of the mean.
Figure 3
Figure 3. Illustration of the condensation-ordering mechanism for different hydrophobicity of the nanoparticle, nanoparticle diameter.
(A) formula image, formula image at formula image microseconds(left), formula image milliseconds (middle), formula image milliseconds (right). (B) formula image, formula image at formula image microseconds (left), formula image milliseconds (middle), formula image milliseconds (right). The concentration and temperature are formula image, formula image respectively, and the colour code is as described in Fig 1.
Figure 4
Figure 4. Normalised histograms of distances between atoms involved in backbone-backbone hydrogen bonds.
The analysis is based on 500 high resolution PDB structures and used to define hydrogen bonds in the protein model employed in our simulation. (A) Histogram of distances formula image and formula image between formula image atoms formula image and formula image used to define a formula image helical hydrogen bond assigned to atoms formula image with formula image. (B) Histogram of distances formula image between formula image atoms formula image that form a parallel, anti-parallel, or helical hydrogen bond. For the formula image helical hydrogen bond formula image. (C) Illustration of the alternation of distances for consecutive formula image atoms that form anti-parallel hydrogen bonds. (D) as in (C). (E) The distance formula image is used to define hydrogen bonds between atoms formula image in parallel and anti parallel formula image. (F) Distances used to define cooperative hydrogen bonds between two consecutive atoms formula image and formula image that form parallel formula image or formula image and formula image that form anti parallel formula image.

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