Dynamic strength of molecular adhesion bonds

Evans, Evan; Ritchie, Ken

doi:10.1016/s0006-3495(97)78802-7

Cited by 2,344 publications

(2,856 citation statements)

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“…For simulation C (N), the summation of the matching probability, P n sim %n rand P match ðn rand Þ, was 0.00043 (24), 0.0043 (20), 0.087 (21), (0.15 (20), and 0.37 (21)), indicating that the matches of the peak positions between the experiments and simulation C were not regarded as accidental coincidence, while the concordance rates were less satisfactory for simulation N. This indicates that our simulation condition may be closer to the experimental conditions of Sapra et al (24) and Kessler and Gaub (20) than to those of Voïtch-ovsky et al (21). Note that the peak positions were not recorded in the interval [0,60] in the extraction from the N-terminus by Kessler and Gaub (20), and we could not obtain any match in this portion.…”

Section: Comparison With the Experimental F-d Curvesmentioning

confidence: 77%

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Forced Unfolding Mechanism of Bacteriorhodopsin as Revealed by Coarse-Grained Molecular Dynamics

Yamada

Yamato

Mitaku

2016

Biophysical Journal

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Developments in atomic force microscopy have opened up a new path toward single-molecular phenomena; in particular, during the process of pulling a membrane protein out of a lipid bilayer. However, the characteristic features of the force-distance (F-D) curve of a bacteriorhodopsin in purple membrane, for instance, have not yet been fully elucidated in terms of physicochemical principles. To address the issue, we performed a computer simulation of bacteriorhodopsin with, to our knowledge, a novel coarse-grained (C-G) model. Peptide planes are represented as rigid spheres, while the surrounding environment consisting of water solvents and lipid bilayers is represented as an implicit continuum. Force-field parameters were determined on the basis of auxiliary simulations and experimental values of transfer free energy of each amino acid from water to membrane. According to Popot's two-stage model, we separated molecular interactions involving membrane proteins into two parts: I) affinity of each amino acid to the membrane and intrahelical hydrogen bonding between main chain peptide bonds; and II) interhelix interactions. Then, only part I was incorporated into the C-G model because we assumed that the part plays a dominant role in the forced unfolding process. As a result, the C-G simulation has successfully reproduced the key features, including peak positions, of the experimental F-D curves in the literature, indicating that the peak positions are essentially determined by the residue-lipid and intrahelix interactions. Furthermore, we investigated the relationships between the energy barrier formation on the forced unfolding pathways and the force peaks of the F-D curves.

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Section: Comparison With the Experimental F-d Curvesmentioning

confidence: 77%

“…Note that it is possible to estimate the widths and heights of the energy barriers by using the loading-rate dependence of the magnitude of peak forces (59)(60)(61). Focusing especially on the peaks at 90.2 aa and 158.0 aa, we characterize the energy barriers in detail (Supporting Material).…”

Section: Height and Width Of Energy Barriermentioning

confidence: 99%

Forced Unfolding Mechanism of Bacteriorhodopsin as Revealed by Coarse-Grained Molecular Dynamics

Yamada

Yamato

Mitaku

2016

Biophysical Journal

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“…The CC junctions dissociate in a force-dependent manner (13,20,26,27) according to a relationship that accounts for different bond rupture rates in two force regimes, similar to Evans and Ritchie's equations (22,28):…”

Section: Dynamics Of Cell-cell Junctionsmentioning

confidence: 99%

Scattering of Cell Clusters in Confinement

Pathak

2016

Biophysical Journal

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Epithelial-to-mesenchymal transition (EMT) enables scattering of cell clusters and disseminates motile cells to distant locations in vivo during embryonic development and cancer metastasis. Both stiffness and topography of the extracellular matrix (ECM) have been shown to influence EMT. In this work, we examine how the integrity of epithelial cell clusters is regulated by subcellular forces, protrusions, and adhesions for varying ECM inputs, such as stiffness, topography, and dimensionality. Our model simulates multicell networks of defined sizes and shapes in ECMs of varied stiffness and geometry. The integrity of cell clusters is dictated by cell-cell junctions, which depend on subcellular forces and adhesion dynamics within each cell of the cluster. Our simulations demonstrate an enhanced dissociation of cell-cell junctions in stiffer and more confined three-dimensional (3D) environments, consistent with experimental findings. In narrow channels, the cell edges parallel to the axis of channels lose their cell-cell junctions more readily than those oriented in the perpendicular direction. The inhibition of protrusive activity and cell polarity disables confinement-dependent cell scattering. Here, cell adhesion and spreading along channel walls is found to be essential for scattering. The model also predicts that two-dimensional (2D) confinement of clusters restricts cell spreading and simultaneously blunts the confinement-sensitive cell scattering. This new, to our knowledge, multiscale model integrates molecular adhesion dynamics, subcellular forces, cellular deformation, and macroscale mechanical properties of the ECM to predict the state of cell clusters of defined shapes and sizes. The predictions made by our model not only match experimental findings from a number of experimental setups, but also provide a new conceptual framework for understanding mechanosensitive cell scattering and EMT.

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“…Adhesion in most biological situations is thermally activated with an activation barrier present for the formation/dissociation of bonds. This results in a rate dependent bond strength/energy (Evans and Ritchie, 1997). Here we do not model these details but rather specify a simple phenomenological relation between the bond stress and bond stretch (we do not need to consider the compression of the bond for the purposes of this discussion) that captures the key element of the rate dependence of the bond strength.…”

Section: 2mentioning

confidence: 99%