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Self assembly of model polymers into biological random networks

The properties of biological networks, such as those found in the ocular lens capsule, are difficult to study without simplified models. Model polymers are developed, inspired by “worm-like” curve models, that are shown to spontaneously self assemble to form networks similar to those observed experi...

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Detalles Bibliográficos
Autores principales: Bailey, Matthew H.J., Wilson, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918283/
https://www.ncbi.nlm.nih.gov/pubmed/33717422
http://dx.doi.org/10.1016/j.csbj.2021.02.001
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author Bailey, Matthew H.J.
Wilson, Mark
author_facet Bailey, Matthew H.J.
Wilson, Mark
author_sort Bailey, Matthew H.J.
collection PubMed
description The properties of biological networks, such as those found in the ocular lens capsule, are difficult to study without simplified models. Model polymers are developed, inspired by “worm-like” curve models, that are shown to spontaneously self assemble to form networks similar to those observed experimentally in biological systems. These highly simplified coarse-grained models allow the self assembly process to be studied on near-realistic time-scales. Metrics are developed (using a polygon-based framework) which are useful for describing simulated networks and can also be applied to images of real networks. 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. The structure of the simulated networks are compared to previous simulation work and microscope images of real networks. The network structure is shown to be a function of the interaction strengths, cooling rates and external pressure. In addition, “pre-tangled” network structures are introduced and shown to significantly influence the subsequent network structure. The network structures obtained fit into a region of the network landscape effectively inaccessible to random (entropically-driven) networks but which are occupied by experimentally-derived configurations.
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spelling pubmed-79182832021-03-12 Self assembly of model polymers into biological random networks Bailey, Matthew H.J. Wilson, Mark Comput Struct Biotechnol J Research Article The properties of biological networks, such as those found in the ocular lens capsule, are difficult to study without simplified models. Model polymers are developed, inspired by “worm-like” curve models, that are shown to spontaneously self assemble to form networks similar to those observed experimentally in biological systems. These highly simplified coarse-grained models allow the self assembly process to be studied on near-realistic time-scales. Metrics are developed (using a polygon-based framework) which are useful for describing simulated networks and can also be applied to images of real networks. 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. The structure of the simulated networks are compared to previous simulation work and microscope images of real networks. The network structure is shown to be a function of the interaction strengths, cooling rates and external pressure. In addition, “pre-tangled” network structures are introduced and shown to significantly influence the subsequent network structure. The network structures obtained fit into a region of the network landscape effectively inaccessible to random (entropically-driven) networks but which are occupied by experimentally-derived configurations. Research Network of Computational and Structural Biotechnology 2021-02-12 /pmc/articles/PMC7918283/ /pubmed/33717422 http://dx.doi.org/10.1016/j.csbj.2021.02.001 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Bailey, Matthew H.J.
Wilson, Mark
Self assembly of model polymers into biological random networks
title Self assembly of model polymers into biological random networks
title_full Self assembly of model polymers into biological random networks
title_fullStr Self assembly of model polymers into biological random networks
title_full_unstemmed Self assembly of model polymers into biological random networks
title_short Self assembly of model polymers into biological random networks
title_sort self assembly of model polymers into biological random networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918283/
https://www.ncbi.nlm.nih.gov/pubmed/33717422
http://dx.doi.org/10.1016/j.csbj.2021.02.001
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