Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Effect of Chain Polydispersity on the Elasticity of Disordered Polymer Networks.

ABSTRACT: Due to their unique structural and mechanical properties, randomly cross-linked polymer networks play an important role in many different fields, ranging from cellular biology to industrial processes. In order to elucidate how these properties are controlled by the physical details of the network (e.g., chain-length and end-to-end distributions), we generate disordered phantom networks with different cross-linker concentrations C and initial densities ρ_init and evaluate their elastic properties. We find that the shear modulus computed at the same strand concentration for networks with the same C, which determines the number of chains and the chain-length distribution, depends strongly on the preparation protocol of the network, here controlled by ρ_init. We rationalize this dependence by employing a generic stress-strain relation for polymer networks that does not rely on the specific form of the polymer end-to-end distance distribution. We find that the shear modulus of the networks is a nonmonotonic function of the density of elastically active strands, and that this behavior has a purely entropic origin. Our results show that if short chains are abundant, as it is always the case for randomly cross-linked polymer networks, the knowledge of the exact chain conformation distribution is essential for correctly predicting the elastic properties. Finally, we apply our theoretical approach to literature experimental data, qualitatively confirming our interpretations.

SUBMITTER: Sorichetti V

PROVIDER: S-EPMC8154883 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

How sequence determines elasticity of disordered proteins.

Project description:How nature tunes sequences of disordered protein to yield the desired coiling properties is not yet well understood. To shed light on the relationship between protein sequence and elasticity, we here investigate four different natural disordered proteins with elastomeric function, namely: FG repeats in the nucleoporins; resilin in the wing tendon of dragonfly; PPAK in the muscle protein titin; and spider silk. We obtain force-extension curves for these proteins from extensive explicit solvent molecular dynamics simulations, which we compare to purely entropic coiling by modeling the four proteins as entropic chains. Although proline and glycine content are in general indicators for the entropic elasticity as expected, divergence from simple additivity is observed. Namely, coiling propensities correlate with polyproline II content more strongly than with proline content, and given a preponderance of glycines for sufficient backbone flexibility, nonlocal interactions such as electrostatic forces can result in strongly enhanced coiling, which results for the case of resilin in a distinct hump in the force-extension curve. Our results, which are directly testable by force spectroscopy experiments, shed light on how evolution has designed unfolded elastomeric proteins for different functions.

| S-EPMC3000487 | biostudies-literature

Determining elasticity from single polymer dynamics.

Project description:The ability to determine polymer elasticity and force-extension relations from polymer dynamics in flow has been challenging, mainly due to difficulties in relating equilibrium properties such as free energy to far-from-equilibrium processes. In this work, we determine polymer elasticity from the dynamic properties of polymer chains in fluid flow using recent advances in statistical mechanics. In this way, we obtain the force-extension relation for DNA from single molecule measurements of polymer dynamics in flow without the need for optical tweezers or bead tethers. We further employ simulations to demonstrate the practicality and applicability of this approach to the dynamics of complex fluids. We investigate the effects of flow type on this analysis method, and we develop scaling laws to relate the work relation to bulk polymer viscometric functions. Taken together, our results show that nonequilibrium work relations can play a key role in the analysis of soft material dynamics.

| S-EPMC3966029 | biostudies-literature

Boson peak, elasticity, and glass transition temperature in polymer glasses: Effects of the rigidity of chain bending.

Project description:The excess low-frequency vibrational spectrum, called boson peak, and non-affine elastic response are the most important particularities of glasses. Herein, the vibrational and mechanical properties of polymeric glasses are examined by using coarse-grained molecular dynamics simulations, with particular attention to the effects of the bending rigidity of the polymer chains. As the rigidity increases, the system undergoes a glass transition at a higher temperature (under a constant pressure), which decreases the density of the glass phase. The elastic moduli, which are controlled by the decrease of the density and the increase of the rigidity, show a non-monotonic dependence on the rigidity of the polymer chain that arises from the non-affine component. Moreover, a clear boson peak is observed in the vibrational density of states, which depends on the macroscopic shear modulus G. In particular, the boson peak frequency ?BP is proportional to [Formula: see text]. These results provide a positive correlation between the boson peak, shear elasticity, and the glass transition temperature.

| S-EPMC6925306 | biostudies-literature

Disentangling polydispersity in the PCNA-p15PAF complex, a disordered, transient and multivalent macromolecular assembly.

Project description:The intrinsically disordered p15PAF regulates DNA replication and repair when interacting with the Proliferating Cell Nuclear Antigen (PCNA) sliding clamp. As many interactions between disordered proteins and globular partners involved in signaling and regulation, the complex between p15PAF and trimeric PCNA is of low affinity, forming a transient complex that is difficult to characterize at a structural level due to its inherent polydispersity. We have determined the structure, conformational fluctuations, and relative population of the five species that coexist in solution by combining small-angle X-ray scattering (SAXS) with molecular modelling. By using explicit ensemble descriptions for the individual species, built using integrative approaches and molecular dynamics (MD) simulations, we collectively interpreted multiple SAXS profiles as population-weighted thermodynamic mixtures. The analysis demonstrates that the N-terminus of p15PAF penetrates the PCNA ring and emerges on the back face. This observation substantiates the role of p15PAF as a drag regulating PCNA processivity during DNA repair. Our study reveals the power of ensemble-based approaches to decode structural, dynamic, and thermodynamic information from SAXS data. This strategy paves the way for deciphering the structural bases of flexible, transient and multivalent macromolecular assemblies involved in pivotal biological processes.

| S-EPMC5388412 | biostudies-literature

Learning hidden elasticity with deep neural networks.

Project description:Elastography is an imaging technique to reconstruct elasticity distributions of heterogeneous objects. Since cancerous tissues are stiffer than healthy ones, for decades, elastography has been applied to medical imaging for noninvasive cancer diagnosis. Although the conventional strain-based elastography has been deployed on ultrasound diagnostic-imaging devices, the results are prone to inaccuracies. Model-based elastography, which reconstructs elasticity distributions by solving an inverse problem in elasticity, may provide more accurate results but is often unreliable in practice due to the ill-posed nature of the inverse problem. We introduce ElastNet, a de novo elastography method combining the theory of elasticity with a deep-learning approach. With prior knowledge from the laws of physics, ElastNet can escape the performance ceiling imposed by labeled data. ElastNet uses backpropagation to learn the hidden elasticity of objects, resulting in rapid and accurate predictions. We show that ElastNet is robust when dealing with noisy or missing measurements. Moreover, it can learn probable elasticity distributions for areas even without measurements and generate elasticity images of arbitrary resolution. When both strain and elasticity distributions are given, the hidden physics in elasticity-the conditions for equilibrium-can be learned by ElastNet.

| S-EPMC8346903 | biostudies-literature

Cytoskeleton-inspired artificial protein design to enhance polymer network elasticity.

Project description:Reducing topological network defects to enhance elasticity in polymeric materials remains a grand challenge. Efforts to control network topology, primarily focused on crosslinking junctions, continue to underperform compared to theoretical estimations from idealized networks using affine and phantom network theories. Here, artificial protein technology was adapted for the design of polymer-network hydrogels with precisely defined coil-like and rod-like strands to observe the impact of strand rigidity on the mechanical properties of polymeric materials. Cytoskeleton-inspired polymer-network hydrogels incorporated with rod-like protein strands nearly tripled the gel shear elastic modulus and relaxation time compared to coil-like protein strands, indicating an enhanced effective crosslinking density. Furthermore, asymmetric rod-coil protein designs in network strands with an optimal rod:coil ratio improved the hydrogel relaxation time, enhancing the stability of physical macromolecular associations by modulating crosslinker mobility. The careful design of strand rigidity presents a new direction to reduce topological defects for optimizing polymeric materials.

| S-EPMC7323958 | biostudies-literature

Auxetic metamaterials from disordered networks.

Project description:Recent theoretical work suggests that systematic pruning of disordered networks consisting of nodes connected by springs can lead to materials that exhibit a host of unusual mechanical properties. In particular, global properties such as Poisson's ratio or local responses related to deformation can be precisely altered. Tunable mechanical responses would be useful in areas ranging from impact mitigation to robotics and, more generally, for creation of metamaterials with engineered properties. However, experimental attempts to create auxetic materials based on pruning-based theoretical ideas have not been successful. Here we introduce a more realistic model of the networks, which incorporates angle-bending forces and the appropriate experimental boundary conditions. A sequential pruning strategy of select bonds in this model is then devised and implemented that enables engineering of specific mechanical behaviors upon deformation, both in the linear and in the nonlinear regimes. In particular, it is shown that Poisson's ratio can be tuned to arbitrary values. The model and concepts discussed here are validated by preparing physical realizations of the networks designed in this manner, which are produced by laser cutting 2D sheets and are found to behave as predicted. Furthermore, by relying on optimization algorithms, we exploit the networks' susceptibility to tuning to design networks that possess a distribution of stiffer and more compliant bonds and whose auxetic behavior is even greater than that of homogeneous networks. Taken together, the findings reported here serve to establish that pruned networks represent a promising platform for the creation of unique mechanical metamaterials.

| S-EPMC5816187 | biostudies-literature

Shape memory polymer network with thermally distinct elasticity and plasticity.

Project description:Stimuli-responsive materials with sophisticated yet controllable shape-changing behaviors are highly desirable for real-world device applications. Among various shape-changing materials, the elastic nature of shape memory polymers allows fixation of temporary shapes that can recover on demand, whereas polymers with exchangeable bonds can undergo permanent shape change via plasticity. We integrate the elasticity and plasticity into a single polymer network. Rational molecular design allows these two opposite behaviors to be realized at different temperature ranges without any overlap. By exploring the cumulative nature of the plasticity, we demonstrate easy manipulation of highly complex shapes that is otherwise extremely challenging. The dynamic shape-changing behavior paves a new way for fabricating geometrically complex multifunctional devices.

| S-EPMC4730863 | biostudies-other

Impact of branching on the elasticity of actin networks.

Project description:Actin filaments play a fundamental role in cell mechanics: assembled into networks by a large number of partners, they ensure cell integrity, deformability, and migration. Here we focus on the mechanics of the dense branched network found at the leading edge of a crawling cell. We develop a new technique based on the dipolar attraction between magnetic colloids to measure mechanical properties of branched actin gels assembled around the colloids. This technique allows us to probe a large number of gels and, through the study of different networks, to access fundamental relationships between their microscopic structure and their mechanical properties. We show that the architecture does regulate the elasticity of the network: increasing both capping and branching concentrations strongly stiffens the networks. These effects occur at protein concentrations that can be regulated by the cell. In addition, the dependence of the elastic modulus on the filaments' flexibility and on increasing internal stress has been studied. Our overall results point toward an elastic regime dominated by enthalpic rather than entropic deformations. This result strongly differs from the elasticity of diluted cross-linked actin networks and can be explained by the dense dendritic structure of lamellipodium-like networks.

| S-EPMC3387051 | biostudies-literature

Elasticity of podosome actin networks produces nanonewton protrusive forces.

Project description:Actin filaments assemble into force-generating systems involved in diverse cellular functions, including cell motility, adhesion, contractility and division. It remains unclear how networks of actin filaments, which individually generate piconewton forces, can produce forces reaching tens of nanonewtons. Here we use in situ cryo-electron tomography to unveil how the nanoscale architecture of macrophage podosomes enables basal membrane protrusion. We show that the sum of the actin polymerization forces at the membrane is not sufficient to explain podosome protrusive forces. Quantitative analysis of podosome organization demonstrates that the core is composed of a dense network of bent actin filaments storing elastic energy. Theoretical modelling of the network as a spring-loaded elastic material reveals that it exerts forces of a few tens of nanonewtons, in a range similar to that evaluated experimentally. Thus, taking into account not only the interface with the membrane but also the bulk of the network, is crucial to understand force generation by actin machineries. Our integrative approach sheds light on the elastic behavior of dense actin networks and opens new avenues to understand force production inside cells.

| S-EPMC9253342 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data