An Analytic Toolbox for Simulated Filament Networks
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An Analytic Toolbox for Simulated Filament Networks Ronald J. Pandolfi1, Lauren Edwards1 and Linda S. Hirst1 1
Dept. of Physics, School of Natural Sciences, University of California, Merced, California 95343, USA ABSTRACT Semi-flexible polymer networks generate a diverse family of structures. The network generating behaviors of specific semi-flexible biological filaments are well known (i.e. F-actin, microtubules, DNA etc.), however recent developments in tunable synthetic filaments extend the range of accessible structures. A similarly tunable model was developed using the molecular dynamics platform NAMD to provide a guide for generating synthetic filament networks. Structural characteristics of simulated networks may be quantitatively examined using connectivity analysis, radial pair distribution functions and scaling analysis. These methods provide a basis to calculate morphological properties, including mesh size, packing order, network connectivity, avg. cluster size, filaments per bundle, and space-filling dimensionality. An analytic toolset for describing the structure of filament networks is thus provided by detailing these methods.
INTRODUCTION Semi-flexible polymer filaments are important to biological systems. For example, the cellular cytoskeleton is formed from F-actin, microtubule, and intermediate filaments crosslinked to form a network [1–3]. Recent experimental work has achieved the synthesis of semiflexible polymers that can model the properties of these biological materials, but also have tunable properties [4]. This opens a new path for generating tunable hydrogels, applications for which have been discussed for drug delivery [5–7], tissue engineering [8], and mesoscale templating [2]. Such applications will benefit from the unique structure and rheology of these light yet rigid gels [9]. A diverse family of network-based materials can be generated from semi-flexible polymers, with structures distinct from those generated by flexible Gaussian polymers. In particular semiflexible filaments have been demonstrated to generate branching networks of bundles – a structure unique to such systems [2,3,4]. Computational models for semi-flexible biological filaments (i.e. F-actin [10,11]) have been recently reported and agree well with experimental results. While the basic solution behavior of biological filaments is fairly well known, a broader understanding of their self-assembly properties is needed to provide a generalized model that supports development of tunable synthetic polymers. Particularly in the formation of out-ofequilibrium structures such as the network of bundles. Our group’s recent work has provided such a model describing semi-flexible polymer network formation [12] with generalized parameters allowing a range of structures to be generated (see Figure 1). In this paper we
describe a set of analytical techniques to quantitatively characterize the filamentous structures generated by coarse grained molecular dynamics simulation. These techniques provide a basis for the analysis of fila
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