Simplified computational model for generating biological networks

Bailey, Matthew; Morley, David Ormrod; Wilson, Mark

doi:10.1039/d0ra06205g

Cited by 5 publications

(14 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2.1, missing edges are not the only form of defect that is likely to occur in a polymer network. Previous work by Bailey et al has shown that bond switching algorithms can generate networks that are similar to real biological networks 17 . To test the hypothesis that a small defect could prevent a tear (simulated by the edge removal defect) from propagating further, we combined single bond switching defects with edge removal defects studied in Sec.…”

Section: Combined Defectsmentioning

confidence: 98%

See 1 more Smart Citation

Simulation of Defects, Flexibility and Rupture in Biopolymer Networks

Bailey

Wilson

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Networks of biopolymers occur often in nature, and are vulnerable to damage over time. In this work, a coarse grained model of collagen IV molecules is applied in a 2D hexagonal network and the mechanisms by which these networks can rupture are explored. The networks are stretched linearly in order to study their structural limits and mechanism of rupture over timescale of up to 100 microseconds. Metrics are developed to track the damage networks suffer over time, and qualitatively analyse ruptures that occur. Further simulations repeatedly stretch the networks sinusoidally to mimic the in vivo strains. Defects of increasing levels of complexity are introduced into an ordered network, and their effect on the rupturing behaviour of the biopolymer networks studied. The effect of introducing holes of varying size in the network, as well as strips of finite width to mimic surgical damage are studied. These demonstrate the importance of the flexibility of the networks to preventing damage.

show abstract

Section: Combined Defectsmentioning

confidence: 98%

“…The second way to introduce a defect is using an extended Wooten-Winer-Weaire bond switching algorithm as extended by Ormrod Morley and Wilson and shown to be useful to generate high-quality continuous random networks by Bailey et al [16][17][18] . The bond switching step is shown schematically in Fig.…”

Section: Defect Introductionmentioning

confidence: 99%

Simulation of Defects, Flexibility and Rupture in Biopolymer Networks

Bailey

Wilson

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…A key feature of the polymer model is that it can take enthalpic effects into account naturally. The importance of enthalpy to biological networks can be demonstrated by comparing with polygon networks which are dominated purely by entropy, such as those studied using bond switching methods [12]. A simple, numerical model is the maximum entropy distribution.…”

Section: Comparison To the Ideal (Maximum Entropy) Networkmentioning

confidence: 99%

“…These metrics must capture the key differences that biopolymer networks exhibit compared with inorganic networks, describe the effects of enthalpy and entropy, and provide simple proxies for complex physical phenomena. These metrics build on those previously applied to characterise 2D networks [12].…”

Section: Comparison To Previous Network Studiesmentioning

confidence: 99%

“…Previous work has used animal models, such as mice, cows, and monkeys, to understand the ageing of human lens capsules; or coarse-grained finite-element models to treat the whole lens as an engineering problem [8,9,1]. Previous computational models have been based on graph theory; these include Erdös-Rényi random graphs, Mikado networks and bond-switching of ordered graphs [10,11,12]. These graph approaches are parameterised and based on experimental data and small-scale simulations, but provide an incomplete link between detailed molecule simulations and the wider network behaviour.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Self Assembly of Model Polymers into Biological Random Networks

Bailey

Wilson²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

<div>The properties of biological networks, such as those found in the ocular lens capsule, are difficult to study without simplified models.</div><div>Model polymers are developed, inspired by "worm-like'' curve models, that are shown to spontaneously self assemble</div><div>to form networks similar to those observed experimentally in biological systems.</div><div>These highly simplified coarse-grained models allow the self assembly process to be studied on near-realistic time-scales.</div><div>Metrics are developed (using a polygon-based framework)</div><div>which are useful for describing simulated networks and can also be applied to images of real networks.</div><div>These metrics are used to show the range of control that the computational polymer model has over the networks, including the polygon structure and short range order.</div><div>The structure of the simulated networks are compared to previous simulation work and microscope images of real networks. </div><div>The network structure is shown to be a function of the interaction strengths, cooling rates and external pressure. </div><div>In addition, "pre-tangled'' network structures are introduced and shown to significantly influence the subsequent network structure.</div><div>The network structures obtained fit into a region of the network landscape effectively inaccessible to random</div><div>(entropically-driven) networks but which are occupied by experimentally-derived configurations.</div>

show abstract