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      Impact of nanoparticles on amyloid peptide and protein aggregation: a review with a focus on gold nanoparticles

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          Abstract

          The accelerating and inhibiting effects of nanoparticles on amyloid peptide aggregation are discussed for varying nanoparticle and peptide properties in the context of recent studies.

          Abstract

          Society is increasingly exposed to nanoparticles as they are ubiquitous in nature and introduced as man-made air pollutants and as functional ingredients in cosmetic products as well as in nanomedicine. Nanoparticles differ in size, shape and material properties. In addition to their intended function, the side effects on biochemical processes in organisms remain unclear. Nanoparticles can significantly influence the nucleation and aggregation process of peptides. The development of several neurodegenerative diseases, such as Alzheimer's disease, is related to the aggregation of peptides into amyloid fibrils. However, there is no comprehensive or universal mechanism to predict or explain apparent acceleration or inhibition of these aggregation processes. In this work, selected studies and possible mechanisms for amyloid peptide nucleation and aggregation, in the presence of nanoparticles, are highlighted. These studies are discussed in the context of recent data from our group on the role of gold nanoparticles in amyloid peptide aggregation using experimental methods and large-scale molecular dynamics simulations. A complex interplay of the surface properties of the nanoparticles, the properties of the peptides, as well as the resulting forces between both the nanoparticles and the peptides, appear to determine whether amyloid peptide aggregation is influenced, catalysed or inhibited by the presence of nanoparticles.

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          VMD: Visual molecular dynamics

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            Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems

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              GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.

              Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.
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                Author and article information

                Journal
                NANOHL
                Nanoscale
                Nanoscale
                Royal Society of Chemistry (RSC)
                2040-3364
                2040-3372
                November 22 2018
                2018
                : 10
                : 45
                : 20894-20913
                Affiliations
                [1 ]Leibniz Institute of Surface Engineering (IOM)
                [2 ]04318 Leipzig
                [3 ]Germany
                [4 ]Wilhelm-Ostwald-Institute for Physical and Theoretical Chemistry
                [5 ]Leipzig University
                [6 ]School of Chemistry
                [7 ]Monash University
                [8 ]Clayton
                [9 ]Australia
                [10 ]Institute for Theoretical Physics
                [11 ]Georg-August-Universität Göttingen
                Article
                10.1039/C8NR04506B
                © 2018

                http://rsc.li/journals-terms-of-use

                Product
                Self URI (article page): http://xlink.rsc.org/?DOI=C8NR04506B

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