Amyloid Fibril Solubility

Rizzi, L. G.; Auer, Stefan

doi:10.1021/acs.jpcb.5b09210

Cited by 14 publications

(22 citation statements)

References 58 publications

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“…According, Eq. 7 has recently been used to study the honeycomb-peptide lattice model of fibril formation [ 41 ]. In this model, peptides are represented by hexagons in a two-dimensional triangular lattice which can bind to each other along a straight line to form a β -sheet.…”

Section: Resultsmentioning

confidence: 99%

“…5 are results from Fig. 6b of reference [ 41 ] where i represents the thickness of the fibril, i.e., the number of β -sheet layers in the fibril. Results in reference [ 41 ] were obtained from Monte Carlo simulations.…”

Section: Resultsmentioning

confidence: 99%

“…Despite its small value, we show that Δ C p can be measured in our model. We also study Δ C p for the honeycomb lattice model of amyloid fibrils which has recently been developed to study fibril solubility [ 41 ]. We find that changes in the thickness of the fibril in the honeycomb lattice accounts for an increase in the magnitude of Δ C p .…”

Section: Introductionmentioning

confidence: 99%

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Thermodynamic properties of amyloid fibrils in equilibrium

Urbič

Najem

Dias

2017

Biophysical Chemistry

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In this manuscript we use a two-dimensional coarse-grained model to study how amyloid fibrils grow towards an equilibrium state where they coexist with proteins dissolved in a solution. Free-energies to dissociate proteins from fibrils are estimated from the residual concentration of dissolved proteins. Consistent with experiments, the concentration of proteins in solution affects the growth rate of fibrils but not their equilibrium state. Also, studies of the temperature dependence of the equilibrium state can be used to estimate thermodynamic quantities, e.g., heat capacity and entropy.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Thermodynamic properties of amyloid fibrils in equilibrium

Urbič

Najem

Dias

2017

Biophysical Chemistry

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“…On the background is a fibre network configuration extracted from our simulations. Fibres are formed from the self-assemble of anisotropically interacting peptide monomers [24,25]. f = + f 0 on upper boundary nodes, and f = − f 0 on lower boundary nodes, where all f 0 on each surface sum to give the required stress.…”

mentioning

confidence: 99%

“…The interactions between peptide monomers are characterized by their anisotropy ratio ξ = ψ/ψ h > 1, where ψ and ψ h are the strengths of strong directional hydrogen bonds and weak isotropic hydrophobicity-mediated bonds [24], respectively. The anisotropy in the interactions between peptide monomers enables their assembly into crosslinked networks that exhibit a universal time-dependent behaviour in their microstructural geometry (i.e.…”

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confidence: 99%

Importance of non-affine viscoelastic response in disordered fibre networks

2016

Self Cite

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Disordered fibre networks are ubiquitous in nature and have a wide range of industrial applications as novel biomaterials. Predicting their viscoelastic response is straightforward for affine deformations that are uniform over all length scales, but when affinity fails, as has been observed experimentally, modelling becomes challenging. Here we introduce a numerical methodology to predict the steadystate viscoelastic spectra and degree of affinity for disordered fibre networks driven at arbitrary frequencies. Applying this method to a peptide gel model reveals a monotonic increase of the shear modulus as the soft, non-affine normal modes are successively suppressed as the driving frequency increases. In addition to being dominated by fibril bending, these low frequency network modes are also shown to be delocalised. The presented methodology provides insights into the importance of non-affinity in the viscoelastic response of peptide gels, and is easily extendible to all types of fibre networks. [5]. Nature employs protein fibre networks in the multi-functional cellular cytoskeleton [6,7]. The mechanical stiffness of fibre networks is often central to their function, and although static properties come under most scrutiny, they often exist in dynamic environments subject to temporally-varying mechanical loads, including the cytoskeleton of motile cells [7], and scaffolds for tendon and ligament regeneration, where habitual loading propagating through the network influences the viability of embedded stem cells [8][9][10]. Understanding the dynamical network response is essential to design novel materials with properties suited for such situations.A key modelling challenge is to determine the degree to which the deformation is affine [11], i.e. uniform over all relevant length scales; see Fig. 1. If affinity holds, extrapolating the macroscopic response from a putative microstructure is straightforward, and a range of thermal and athermal affine models for fibre networks have been developed [12,13]. When affinity fails, however, as experimentally observed over broad parameter ranges [14][15][16][17], it is necessary to determine the microscopic deformation field, which typically requires numerical solution for explicit network realisations. This has thus far been limited to the elastic plateau amenable to energy minimization algorithms [18][19][20][21], or computationally-intensive particle methods that only access short times [22,23]. Without a more general understanding of fibre networks dynamics, we lack the capability to predict potentially large changes in viscoelastic properties over experimentally relevant time scales.Here we present a methodology which allows the numerical calculation of the viscoelastic spectra for any type of disordered fibre network driven at arbitrary oscillation frequencies. The method is based on normal modes which ensures linear response, and since no thermal effects or crosslink dynamics are included by construction, all measured variation in affinity and viscoelasticity can be as...

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Microrheology of Biological Specimens

Rizzi

Tassieri

2018

Encyclopedia of Analytical Chemistry

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A great number of important biological phenomena that occur in living organisms demand energy transduction processes that critically depend on the viscoelastic properties of their constituent building blocks, such as cytoplasm, microtubules, and motor proteins. Accordingly, several techniques have been developed to characterize biological systems with complex mechanical properties at micron‐ and nano‐length scales; these are now part of an established field of study known as Microrheology. In this article, we provide an overview of the theoretical principles underpinning the most popular experimental techniques used in such fields, including video particle tracking, dynamic light scattering, diffusing wave spectroscopy, optical and magnetic tweezers, and atomic force microscopy. We report examples of both active and passive microrheology techniques and discuss their applications in the study of biological specimens, where the use of small volumes in controlled environments and the intrinsic heterogeneities of the samples can be critical conditions to both perform and interpret the experiments.

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Amyloid Fibril Solubility

Cited by 14 publications

References 58 publications

Thermodynamic properties of amyloid fibrils in equilibrium

Thermodynamic properties of amyloid fibrils in equilibrium

Importance of non-affine viscoelastic response in disordered fibre networks

Microrheology of Biological Specimens

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