scholarly journals Multiscale model of integrin adhesion assembly

2019 ◽  
Author(s):  
Tamara C Bidone ◽  
Austin V Skeeters ◽  
Patrick W Oakes ◽  
Gregory A Voth
Keyword(s):  
Ligand Binding ◽  
Physical Properties ◽  
Bound States ◽  
Dynamic Properties ◽  
Leading Edge ◽  
Multiscale Model ◽  
Coarse Grained ◽  
Pairwise Interactions ◽  
Bond Kinetics ◽  
Adhesion Stability

The ability of adherent cells to form adhesions is critical to several phases of their physiology. The assembly of adhesions is mediated by several types of integrins. These integrins differ in physical properties, including rate of diffusion on the plasma membrane, rapidity of changing conformation from bent to extended, affinity for extracellular matrix ligands, and lifetimes of their ligand-bound states. However, the way in which nanoscale physical properties of integrins ensure proper adhesion assembly remains elusive. We observe experimentally that both beta-1 and beta-3 integrins localize in nascent adhesions at the cell leading edge. In order to understand how different nanoscale parameters of beta-1 and beta-3 integrins mediate proper adhesion assembly, we therefore develop a coarse-grained computational model. Results from the model demonstrate that morphology and distribution of nascent adhesions depend on ligand binding affinity and strength of pairwise interactions. Organization of nascent adhesions depends on the relative amounts of integrins with different bond kinetics. Moreover, the model shows that the architecture of an actin filament network does not perturb the total amount of integrin clustering and ligand binding; however, only bundled actin architectures favor adhesion stability and ultimately maturation. Together, our results support the view that cells can finely tune the expression of different integrin types to determine both structural and dynamic properties of adhesions.

scholarly journals Magnetic Janssen effect

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
L. Thorens ◽  
K. J. Måløy ◽  
M. Bourgoin ◽  
S. Santucci
Keyword(s):  
Magnetic Field ◽  
Dynamic Properties ◽  
Radial Force ◽  
Fine Tuning ◽  
Apparent Mass ◽  
Confined Geometries ◽  
Pairwise Interactions ◽  
Janssen Effect ◽  
Lateral Walls ◽  
Granular Column

AbstractA pile of grains, even when at rest in a silo, can display fascinating properties. One of the most celebrated is the Janssen effect, named after the pioneering engineer who explained the pressure saturation at the bottom of a container filled with corn. This surprising behavior arises because of frictional interactions between the grains through a disordered network of contacts, and the vessel lateral walls, which partially support the weight of the column, decreasing its apparent mass. Here, we demonstrate control over frictional interactions using ferromagnetic grains and an external magnetic field. We show that the anisotropic pairwise interactions between magnetized grains result in a radial force along the walls, whose amplitude and direction is fully determined by the applied magnetic field. Such magnetic Janssen effect allows for the fine tuning of the granular column apparent mass. Our findings pave the way towards the design of functional jammed materials in confined geometries, via a further control of both their static and dynamic properties.

Conformational dynamics and thermodynamics of protein–ligand binding studied by NMR relaxation

2012 ◽  
Vol 40 (2) ◽  
pp. 419-423 ◽  
Author(s):  
Mikael Akke
Keyword(s):  
Ligand Binding ◽  
Bound States ◽  
Conformational Dynamics ◽  
Nmr Relaxation ◽  
Titration Calorimetry ◽  
Conformational Entropy ◽  
Chain Order ◽  
Ligand Interactions ◽  
Galectin 3 ◽  
Relaxation Experiments

Protein conformational dynamics can be critical for ligand binding in two ways that relate to kinetics and thermodynamics respectively. First, conformational transitions between different substates can control access to the binding site (kinetics). Secondly, differences between free and ligand-bound states in their conformational fluctuations contribute to the entropy of ligand binding (thermodynamics). In the present paper, I focus on the second topic, summarizing our recent results on the role of conformational entropy in ligand binding to Gal3C (the carbohydrate-recognition domain of galectin-3). NMR relaxation experiments provide a unique probe of conformational entropy by characterizing bond-vector fluctuations at atomic resolution. By monitoring differences between the free and ligand-bound states in their backbone and side chain order parameters, we have estimated the contributions from conformational entropy to the free energy of binding. Overall, the conformational entropy of Gal3C increases upon ligand binding, thereby contributing favourably to the binding affinity. Comparisons with the results from isothermal titration calorimetry indicate that the conformational entropy is comparable in magnitude to the enthalpy of binding. Furthermore, there are significant differences in the dynamic response to binding of different ligands, despite the fact that the protein structure is virtually identical in the different protein–ligand complexes. Thus both affinity and specificity of ligand binding to Gal3C appear to depend in part on subtle differences in the conformational fluctuations that reflect the complex interplay between structure, dynamics and ligand interactions.

Physical properties of particles obeying generalized statistics

1955 ◽  
Vol 51 (1) ◽  
pp. 131-140 ◽  
Author(s):  
I. E. McCarthy
Keyword(s):  
Scattering Amplitudes ◽  
Physical Properties ◽  
Bound States ◽  
Statistical Thermodynamics ◽  
Vacuum Fluctuations ◽  
Thermodynamical Equilibrium ◽  
Spin Fields ◽  
Integral Spin ◽  
Number Of Particles

ABSTRACTThe Feynman probability amplitudes for interactions between spin ½ fields and fields of integral spin quantized according to the generalized method of Green are investigated. It is shown that the scattering amplitudes are independent of the method of quantization though the amplitudes of the vacuum fluctuations are not. The question of distinguishing particles satisfying the generalized statistics, if they exist in nature, from Fermi or Bose particles is considered. It is shown that the statistical thermodynamics of the particles depends on the statistics, but as this requires a large number of particles in thermodynamical equilibrium, it offers no means of distinction for particles with short lifetimes. In practice, an examination of particles in bound states would identify particles obeying generalized statistics.

Gaussian Network Model Revisited: Effects of Mutation and Ligand Binding on Protein Behavior

2021 ◽  
Author(s):  
Burak Erman
Keyword(s):  
Ligand Binding ◽  
Network Model ◽  
Adjacency Matrix ◽  
In Silico ◽  
Coarse Grained ◽  
Published Data ◽  
Specific Information ◽  
Gaussian Network Model ◽  
Gaussian Network ◽  
Alpha Carbon

The coarse-grained Gaussian Network model, GNM, considers only the alpha carbons of the folded protein. Therefore it is not directly applicable to the study of mutation or ligand binding problems where atomic detail is required. This shortcoming is improved by including the local effect of heavy atoms in the neighborhood of each alpha carbon into the Kirchoff Adjacency Matrix. The presence of other atoms in the coordination shell of each alpha carbon diminishes the magnitude of fluctuations of that alpha carbon. But more importantly, it changes the graph-like connectivity structure, i.e., the Kirchoff Adjacency Matrix of the whole system which introduces amino acid specific and position specific information into the classical coarse-grained GNM which was originally modelled in analogy with phantom network theory of rubber elasticity. With this modification, it is now possible to make predictions on the effects of mutation and ligand binding on residue fluctuations and their pair-correlations. We refer to the new model as all-atom GNM. Using examples from published data we show that the all-atom GNM applied to in silico mutated proteins and to their laboratory mutated structures gives similar results. Thus, loss and gain of correlations, which may be related to loss and gain of function, may be studied by using simple in silico mutations only.

A new spectral coarse-graining algorithm based on K-means clustering in complex networks

2019 ◽  
Vol 33 (01) ◽  
pp. 1850421 ◽  
Author(s):  
Lang Zeng ◽  
Zhen Jia ◽  
Yingying Wang
Keyword(s):  
Complex Networks ◽  
Large Scale ◽  
Dynamic Properties ◽  
Coarse Graining ◽  
Kuramoto Model ◽  
Coarse Grained ◽  
Original Network ◽  
Topological Information ◽  
Real World Applications ◽  
Large Scale Networks

Coarse-graining of complex networks is one of the important algorithms to study large-scale networks, which is committed to reducing the size of networks while preserving some topological information or dynamic properties of the original networks. Spectral coarse-graining (SCG) is one of the typical coarse-graining algorithms, which can keep the synchronization ability of the original network well. However, the calculation of SCG is large, which limits its real-world applications. And it is difficult to accurately control the scale of the coarse-grained network. In this paper, a new SCG algorithm based on K-means clustering (KCSCG) is proposed, which cannot only reduce the amount of calculation, but also accurately control the size of coarse-grained network. At the same time, KCSCG algorithm has better effect in keeping the network synchronization ability than SCG algorithm. A large number of numerical simulations and Kuramoto-model example on several typical networks verify the feasibility and effectiveness of the proposed algorithm.

scholarly journals Low-amplitude dynamic tests of fine gravel in a resonant column

2019 ◽  
Vol 97 ◽  
pp. 04024
Author(s):  
Zaven Ter-Martirosyan ◽  
Evgeny Sobolev ◽  
George Anzhelo
Keyword(s):  
Mechanical Properties ◽  
Dynamic Properties ◽  
Sample Volume ◽  
Coarse Grained ◽  
Software Systems ◽  
Resonant Column ◽  
Dynamic Effects ◽  
Laboratory Equipment ◽  
Aggregate Fractions ◽  
Sample Assembly

Construction of industrial and civil buildings, taking into account the dynamic effects on the foundations, requires special experiments on the mechanical properties of soils. This article presents the results of studying the dynamic properties of coarse gravelly soils using the resonant column method. These studies are relevant, since the determination of the dynamic properties of coarse-grained soils under laboratory conditions is associated with a restriction on the size of the fractions in the sample volume. This circumstance leads to the fact that at the moment most of the laboratory tests of the dynamic properties of coarse-grained soils are performed on smaller aggregate fractions, which, in general, significantly reduces the resulting mechanical properties of soils. It does not reflect the real operation of the foundation of buildings during dynamic effects. This paper presents a description of the available laboratory equipment, the sequence of preparation of samples of coarse grained crushed stone soil and sample assembly in the working chamber of the installation. The article contains the main graphs characterizing the change in shear modulus and damping coefficient depending on shear deformations. It is noted that the results obtained are particularly relevant for modeling the dynamic effects of natural and man-made character on the foundations of industrial and civil buildings, the bases of which are composed of coarse-grained soils. Dynamic parameters considered in this paper, can and must be used in numerical calculations by finite element method with the use of modern groundwater models in geotechnical software systems.

scholarly journals Coarse-Grained Models of RNA Nanotubes for Large Time Scale Studies in Biomedical Applications

Biomedicines ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 195 ◽  
Author(s):  
Shyam Badu ◽  
Sanjay Prabhakar ◽  
Roderick Melnik
Keyword(s):  
Physical Properties ◽  
Time Scale ◽  
Biomedical Applications ◽  
Md Simulation ◽  
Large Time ◽  
Coarse Grained ◽  
Dihedral Angles ◽  
Computation Cost ◽  
In Series ◽  
Large Time Scale

In order to describe the physical properties of large time scale biological systems, coarse-grained models play an increasingly important role. In this paper we develop Coarse-Grained (CG) models for RNA nanotubes and then, by using Molecular Dynamics (MD) simulation, we study their physical properties. Our exemplifications include RNA nanotubes of 40 nm long, equivalent to 10 RNA nanorings connected in series. The developed methodology is based on a coarse-grained representation of RNA nanotubes, where each coarse bead represents a group of atoms. By decreasing computation cost, this allows us to make computations feasible for realistic structures of interest. In particular, for the developed coarse-grained models with three bead approximations, we calculate the histograms for the bond angles and the dihedral angles. From the dihedral angle histograms, we analyze the characteristics of the links used to build the nanotubes. Furthermore, we also calculate the bead distances along the chains of RNA strands in the nanoclusters. The variations in these features with the size of the nanotube are discussed in detail. Finally, we present the results on the calculation of the root mean square deviations for a developed RNA nanotube to demonstrate the equilibration of the systems for drug delivery and other biomedical applications such as medical imaging and tissue engineering.

scholarly journals Energy renormalization for coarse-graining polymers having different segmental structures

2019 ◽  
Vol 5 (4) ◽  
pp. eaav4683 ◽  
Author(s):  
Wenjie Xia ◽  
Nitin K. Hansoge ◽  
Wen-Sheng Xu ◽  
Frederick R. Phelan ◽  
Sinan Keten ◽  
...  
Keyword(s):  
Dynamic Properties ◽  
Interaction Strength ◽  
Configurational Entropy ◽  
Coarse Graining ◽  
Soft Materials ◽  
Polymer Materials ◽  
Coarse Grained ◽  
Art Form ◽  
Polymer Models ◽  
Energy Renormalization

Multiscale coarse-grained (CG) modeling of soft materials, such as polymers, is currently an art form because CG models normally have significantly altered dynamics and thermodynamic properties compared to their atomistic counterparts. We address this problem by exploiting concepts derived from the generalized entropy theory (GET), emphasizing the central role of configurational entropy sc in the dynamics of complex fluids. Our energy renormalization (ER) method involves varying the cohesive interaction strength in the CG models in such a way that dynamic properties related to sc are preserved. We test this ER method by applying it to coarse-graining polymer melts (i.e., polybutadiene, polystyrene, and polycarbonate), representing polymer materials having a relatively low, intermediate, and high degree of glass “fragility”. We find that the ER method allows the dynamics of the atomistic polymer models to be faithfully described to a good approximation by CG models over a wide temperature range.

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