DNA Origami. Группа авторов
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designed by the same group). In the paper, the folding of six different structures is demonstrated: a “ball” (a subdivided icosahedron), a nicked torus, a helix, a rod, a stickman, a bottle, and a polygonal version of the Stanford bunny. A feature of wireframe polygonal DNA origami highlighted in the paper is the higher resistance to unfolding in low‐salt buffers that are more similar to physiological solutions. Classically, tightly packed DNA origami structures need high concentrations of cations to remain stable, because of the repulsion between the helices. Although alternative approaches have now been proposed to solve this problem [22–24], the possibility of having higher stability without relying on additional modifications is an interesting approach to develop more robust nanostructures for biomedical applications.
In a following paper, we expanded the capabilities of the software packages to 2D meshes [56] by modifying the routing process. We showed the application to the three regular tessellations (hexagon tiling, square tiling, triangular tiling) on a rectangular mesh and four other, less regular structures. The rigidity of the structures appears to be highly dependent on the tessellation used, with the triangular tessellation being the most rigid. According to the authors, these wireframe 2D sheets allow, with the same scaffold usage, to cover an area 70% larger relative to classic DNA origami, and they can be folded in low‐salt buffers.
Compared to the more classical DNA origami designs, these one‐layer, hollow structures are more structurally flexible, making their use less feasible in applications where high rigidity is a desired property. This is addressed in two recent works [57, 58], where both an experimental and a computational approach (through the oxDNA simulation package [18–20]) were used to evaluate and control the flexibility of wireframe DNA nanorods. In the first work, they found out that different factors can be modified to reach the optimal stiffness of a rod nanostructure, with the edge length and the salt concentration apparently the most important. In the second one, an unsupervised software is used to evaluate the stiffness of DNA nanostructures simulated using oxDNA. The software then autonomously modifies the structures by changing the position of internal supports or by adding or removing base pairs. This cycle of modification and simulation is used to create a completely in silico evolution of more rigid DNA structures.
An alternative approach to the design of wireframe DNA origami is the one introduced by Veneziano et al. in 2016 [47] (Figure 2.4b and c). This paper introduced the fully automatic design procedure DAEDALUS (DNA Origami Sequence Design Algorithm for User‐defined Structures) to create arbitrary wireframe DNA origami nanostructures. The authors decided to represent geometries as node‐edge networks, based on the double crossover (DX) motif: each edge thus consists of two duplexes joined by antiparallel double crossovers. The scaffold routing is based on the spanning tree, determined on the Schlegel diagram of a polygon, on which the scaffold crossovers are assigned. Once the scaffold routing is established, the staple strands are assigned using pre‐defined rules, different for vertices and edges. The last step of the process is the modelling of each nucleotide, used to predict the 3D structure of the nanostructures. This design process is used in the work to create 45 different polygonal structures, of which 7 are experimentally characterized using agarose gel electrophoresis, AFM, and cryo‐EM. To realize these structures, Veneziano et al. introduced an asymmetric PCR to produce custom scaffolds of variable length, ranging from 450 nt to over 10 000. The authors also show that these wireframe structures have enhanced stability in physiological buffers.
Figure 2.4 Entire DNA origami design. (a) (I) BSCOR and vHelix design pipeline. (II) Examples of 3D vHelix structures.
Source: Benson et al. [55] / With permission of Springer Nature (III) Examples of 2D vHelix structures.
Source: Benson et al. [56] / With permission of John Wiley & Sons
(b) (I) Daedalus routing workflow.
Source: Veneziano et al. [47] / With permission of AAAS. (II) Perdix routing workflow [59].
(c) Comparison between two octahedrons designed with vHelix (left) and Daedalus (right).
In a following work [59], the same research group introduced an automated procedure to fold any free‐form 2D DNA origami, called PERDIX (Programmed Eulerian Routing for DNA Design using X‐overs). In this paper, the authors change the approach to the scaffold routing, in contrast with previous works [47, 55, 56], using a dual graph approach for the scaffold routing, defined from the starting geometry. Once the scaffold routing is established, the staple strands are determined; the staple strands in the vertices are connected using poly‐T loops to achieve the desired angles. In the end, the structure is converted into an atomic model for visualization and analysis. The versatility and robustness of the method have been shown with the creation of several structures, with arbitrary edge lengths, vertex degree, and vertex angles, imaged by AFM.
In a contemporary work, the group applies the same scaffold routing to 3D objects to render them using 6HB as edges, thus highly enhancing their mechanical stability and resistance against nucleases [60]. The new algorithm, called TALOS (Three‐dimensional, Algorithmically‐generated Library of DNA Origami Shapes), is used to create a library of 240 3D nanostructures. The authors also introduced two different vertices style: a “flat vertex” (FV), with a single‐scaffold crossover between the edges, and a “mitered vertex” (MV), where every duplex in the honeycomb lattice is extended to the neighbor edge in the vertex, creating a three‐way vertex. This further enhances the mechanical stability of these new 3D nanostructures, with variable edge lengths and vertex angles. Like for PERDIX, the length of the edges is arbitrary because the edges do not need to be an integral number of double‐helical turns of B‐form DNA.
Yet another algorithm, called METIS (Mechanically Enhanced and Three‐layered orIgami Structure), has been introduced for the design of 2D wireframe structures with honeycomb edges [61]. This is possible combining the algorithms described above: while PERDIX generated 2D wireframe objects with single‐layer DX edges, METIS generates honeycomb‐based structures stacking three layers and connecting them using the three‐way connection introduced with TALOS. The structures designed using METIS were characterized by AFM, TEM, and molecular dynamics simulations.
All these software packages have been recently united in a single graphical interface called ATHENA [62]. This allows the design of all variety of 2D and 3D nanostructures described in the works before, with DX or 6HB edges; the final structures are then available in PDB format and in JSON format, compatible with caDNAno, for following editing of the nanostructure.
2.5 DNA Origami Wireframe as Tools for Molecular Force Application
2.5.1 Introduction
In this section, we will investigate the possibility of using wireframe DNA origami as force‐producing molecular machines in biological contests.
Mechanosensitive cellular receptors allow cells to sense the mechanical properties of their environment, especially those arising from the interaction between cells and the extracellular matrix [63]. In these receptors, chemical (receptor‐ligand interactions) and mechanical activations are combined to activate downstream signal processes [64]. One well‐studied example of mechanosensitive cellular receptors is the Notch receptor, for which it has proven that the binding of the ligand is not sufficient for the activation of the receptor and a mechanical force is also necessary [65]. Recent studies found that the force necessary for the activation of the Notch receptor seems to be higher than 4 pN and lower than 12 pN [65, 66].
The mechanical properties of single‐stranded and double‐stranded DNA (ssDNA and dsDNA) are considerably different [67]. While dsDNA can be considered