From Self‐Assembly to Evolutionary Structures

Papadopoulou, Athina; Laucks, Jared; Tibbits, Skylar

doi:10.1002/ad.2192

Cited by 11 publications

(9 citation statements)

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“…Programmable materials is a branch of technology to generate complex objects by self-assembly of their suitably programmed constituents [20]. Recent ideas and advances point in the direction of evolutionary materials that are capable of self-repair and adaptation to changing environmental conditions [21]. A pertinent example are urban water-supply systems where pipes self-adapt the flow capacity in response to local demand fluctuations in a city with evolving population density [20].…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Cyclic Structure Induced by Load Fluctuations in Adaptive Transportation Networks

Martens¹,

Klemm

2019

Progress in Industrial Mathematics at ECMI 2018

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Transport networks are crucial to the functioning of natural systems and technological infrastructures. For flow networks in many scenarios, such as rivers or blood vessels, acyclic networks (i.e., trees) are optimal structures when assuming time-independent in-and outflow. Dropping this assumption, fluctuations of net flow at source and/or sink nodes may render the pure tree solutions unstable even under a simple local adaptation rule for conductances. Here, we consider tree-like networks under the influence of spatially heterogeneous distribution of fluctuations, where the root of the tree is supplied by a constant source and the leaves at the bottom are equipped with sinks with fluctuating loads. We find that the network divides into two regions characterized by tree-like motifs and stable cycles. The cycles emerge through transcritical bifurcations at a critical amplitude of fluctuation. For a simple network structure, depending on parameters defining the local adaptation, cycles first appear close to the leaves (or root) and then appear closer towards the root (or the leaves). The interaction between topology and dynamics gives rise to complex feedback mechanisms with many open questions in the theory of network dynamics. A general understanding of the dynamics in adaptive transport networks is essential in the study of mammalian vasculature, and adaptive transport networks may find technological applications in self-organizing piping systems.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Cyclic Structure Induced by Load Fluctuations in Adaptive Transportation Networks

Martens¹,

Klemm

2019

Progress in Industrial Mathematics at ECMI 2018

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“…To demonstrate this property, we studied their behavior upon the agitation of many pieces together in a container. 25 While this property nicely illustrates the modularity of protein structure-that a single structural unit can be linked together to form a larger, regular secondary structure-it does not accurately mimic the protein folding process in biology. To facilitate the self-assembly design, we created a special class of Skeletide models with weaker magnets and observed their collective behavior by letting them interact via random collision in a circulating water tank (Fig.…”

Section: Spontaneous Assembly Of Secondary Structuresmentioning

confidence: 99%

Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure

Asachi

Nguyen

Dang

et al. 2020

3D Printing and Additive Manufacturing

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Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure-the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intramain chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

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“…MIT's self-assembly lab has developed an alternative approach to programming matter through a series of practice-based investigations (Tibbits, 2016). Instead, material units are pre-programmed by designing the geometries and the material interfaces of individual material units, which still enables computational processes such as self-error correction (Papadopoulou et al, 2017). It also enables increased material resolution and an increasingly scaleable process due to material unit cost and ease of fabrication.…”

Section: Introductionmentioning

confidence: 99%