Configurational Design of Mechanical Perturbation for Fine Control of Twisted DNA Origami Structures

Prediction of DNA origami shape using graph neural network

Unlike proteins, which have a wealth of validated structural data, experimentally or computationally validated DNA origami datasets are limited. Here we present a graph neural network that can predict the three-dimensional conformation of DNA origami assemblies both rapidly and accurately. We develop a hybrid data-driven and physics-informed approach for model training, designed to minimize not only the data-driven loss but also the physics-informed loss. By employing an ensemble strategy, the model can successfully infer the shape of monomeric DNA origami structures almost in real time. Further refinement of the model in an unsupervised manner enables the analysis of supramolecular assemblies consisting of tens to hundreds of DNA blocks. The proposed model enables an automated inverse design of DNA origami structures for given target shapes. Our approach facilitates the real-time virtual prototyping of DNA origami, broadening its design space.

Controlling Chiroptical Responses via Chemo-Mechanical Deformation of DNA Origami Structures

DNA origami-based templates have been widely used to fabricate chiral plasmonic metamaterials due to their precise control of the placement of nanoparticles (NPs) in a desired configuration. However, achieving various chiroptical responses inevitably requires a change in the structure of DNA origami-based templates or binding sites on them, leading to the use of significantly different sets of DNA strands. Here, we propose an approach to controlling various chiroptical responses with a single DNA origami design using its chemo-mechanical deformation induced by DNA intercalators. The chiroptical response could be finely tuned by altering the concentration of intercalators only. The silver (Ag) enhancement was used to amplify the chiroptical signal by enlarging NPs and to maintain it by stiffening the template DNA structure. Furthermore, the sensitivity in the chiroptical signal change to the concentration of intercalators could be modulated by the type of intercalator, the mixture of two intercalators, and the stiffness of DNA origami structures. This approach would be useful in a variety of optical applications that require programmed spatial modification of chiroptical responses.

Mechanics of dynamic and deformable DNA nanostructures

In DNA nanotechnology, DNA molecules are designed, engineered, and assembled into arbitrary-shaped architectures with predesigned functions. Static DNA assemblies often have delicate designs with structural rigidity to overcome thermal fluctuations. Dynamic structures reconfigure in response to external cues, which have been explored to create functional nanodevices for environmental sensing and other applications. However, the precise control of reconfiguration dynamics has been a challenge due partly to flexible single-stranded DNA connections between moving parts. Deformable structures are special dynamic constructs with deformation on double-stranded parts and single-stranded hinges during transformation. These structures often have better control in programmed deformation. However, related deformability and mechanics including transformation mechanisms are not well understood or documented. In this review, we summarize the development of dynamic and deformable DNA nanostructures from a mechanical perspective. We present deformation mechanisms such as single-stranded DNA hinges with lock-and-release pairs, jack edges, helicity modulation, and external loading. Theoretical and computational models are discussed for understanding their associated deformations and mechanics. We elucidate the pros and cons of each model and recommend design processes based on the models. The design guidelines should be useful for those who have limited knowledge in mechanics as well as expert DNA designers.

Tuning curved DNA origami structures through mechanical design and chemical adducts

The bending and twisting of DNA origami structures are important features for controlling the physical properties of DNA nanodevices. It has not been fully explored yet how to finely tune the bending and twisting of curved DNA structures. Traditional tuning of the curved DNA structures was limited to controlling the in-plane-bending angle through varying the numbers of base pairs of deletions and insertions. Here, we developed two tuning strategies of curved DNA origami structures fromin silicoandin vitroaspects.In silico, the out-of-plane bending and twisting angles of curved structures were introduced, and were tuned through varying the patterns of base pair deletions and insertions.In vitro, a chemical adduct (ethidium bromide) was applied to dynamically tune a curved spiral. The 3D structural conformations, like chirality, of the curved DNA structures were finely tuned through these two strategies. The simulation and TEM results demonstrated that the patterns of base pair insertions and deletions and chemical adducts could effectively tune the bending and twisting of curved DNA origami structures. These strategies expand the programmable accuracy of curved DNA origami structures and have potential in building efficient dynamic functional nanodevices.

Predicting the Free-Form Shape of Structured DNA Assemblies from Their Lattice-Based Design Blueprint

Structured DNA assemblies have been designed primarily on a three-dimensional lattice because it is easy to arrange and cross-link the helices there. However, when we design free-form structures including wireframes and topologically closed circular objects on a lattice, artificially stretched bonds connecting bases are inevitably and arbitrarily formed. They often lead to nonconvergence or convergence to a wrong configuration in computational analysis to predict the equilibrium shape of the structure when started from its lattice-based configuration, which hinders the design process of free-form structures. Here, we present a computational procedure enabling the shape prediction of free-form structures from their lattice-based design blueprint without any convergence issue. It automatically partitions the structure into substructures and relocates them into a new configuration. When the analysis for calculating the equilibrium shape begins from this configuration, no convergence issue occurs because substructures and stretched bonds connecting them do not overlap and intertwine each other during analysis. Using the proposed approach, we could obtain the free-form shape of a comprehensive set of wireframe and circular structures accurately and quickly. We further demonstrated that it also facilitated a design of wireframe structures with nonstraight edges.

Accelerating AFM Characterization via Deep-Learning-Based Image Super-Resolution

Atomic force microscopy (AFM) is one of the most popular imaging and characterizing methods applicable to a wide range of nanoscale material systems. However, high-resolution imaging using AFM generally suffers from a low scanning yield due to its method of raster scanning. Here, a systematic method of data acquisition and preparation combined with a deep-learning-based image super-resolution, enabling rapid AFM characterization with accuracy, is proposed. Its application to measuring the geometrical and mechanical properties of structured DNA assemblies reveals that around a tenfold reduction in AFM imaging time can be achieved without significant loss of accuracy. Through a transfer learning strategy, it can be efficiently customized for a specific target sample on demand.

Characterizing and Harnessing the Mechanical Properties of Short Single-Stranded DNA in Structured Assemblies

Precise engineering of DNA structures is of growing interest to solve challenging problems in biomolecular applications and beyond. The introduction of single-stranded DNA (ssDNA) into the DNA structure can play a pivotal role in providing high controllability of critical structural features. Herein, we present a computational model of ssDNA with structural applications to harness its characteristics. The nonlinear properties of nucleotide gaps are systematically characterized to construct a structural model of the ssDNA across length scales with the incorporation of a finite element framework. The proposed method shows the programmability of structural bending, twisting, and persistence length by implementing the ssDNA in various DNA structures with experimental validation. Our results have significant implications for DNA nanotechnology in expanding the boundary of design and analysis of structural shape and stiffness.

Modulating the chemo-mechanical response of structured DNA assemblies through binding molecules

Recent advances in DNA nanotechnology led the fabrication and utilization of various DNA assemblies, but the development of a method to control their global shapes and mechanical flexibilities with high efficiency and repeatability is one of the remaining challenges for the realization of the molecular machines with on-demand functionalities. DNA-binding molecules with intercalation and groove binding modes are known to induce the perturbation on the geometrical and mechanical characteristics of DNA at the strand level, which might be effective in structured DNA assemblies as well. Here, we demonstrate that the chemo-mechanical response of DNA strands with binding ligands can change the global shape and stiffness of DNA origami nanostructures, thereby enabling the systematic modulation of them by selecting a proper ligand and its concentration. Multiple DNA-binding drugs and fluorophores were applied to straight and curved DNA origami bundles, which demonstrated a fast, recoverable, and controllable alteration of the bending persistence length and the radius of curvature of DNA nanostructures. This chemo-mechanical modulation of DNA nanostructures would provide a powerful tool for reconfigurable and dynamic actuation of DNA machineries.

Design Approaches and Computational Tools for DNA Nanostructures

Designing a structure in nanoscale with desired shape and properties has been enabled by structural DNA nanotechnology. Design strategies in this research field have evolved to interpret various aspects of increasingly more complex nanoscale assembly and to realize molecular-level functionality by exploring static to dynamic characteristics of the target structure. Computational tools have naturally been of significant interest as they are essential to achieve a fine control over both shape and physicochemical properties of the structure. Here, we review the basic design principles of structural DNA nanotechnology together with its computational analysis and design tools.

Programming ultrasensitive threshold response through chemomechanical instability

The ultrasensitive threshold response is ubiquitous in biochemical systems. In contrast, achieving ultrasensitivity in synthetic molecular structures in a controllable way is challenging. Here, we propose a chemomechanical approach inspired by Michell's instability to realize it. A sudden reconfiguration of topologically constrained rings results when the torsional stress inside reaches a critical value. We use DNA origami to construct molecular rings and then DNA intercalators to induce torsional stress. Michell's instability is achieved successfully when the critical concentration of intercalators is applied. Both the critical point and sensitivity of this ultrasensitive threshold reconfiguration can be controlled by rationally designing the cross-sectional shape and mechanical properties of DNA rings.

Computing the Elastic Mechanical Properties of Rodlike DNA Nanostructures

To study the elastic properties of rodlike DNA nanostructures, we perform long simulations of these structures using the oxDNA coarse-grained model. By analyzing the fluctuations in these trajectories, we obtain estimates of the bend and twist persistence lengths and the underlying bend and twist elastic moduli and couplings between them. Only on length scales beyond those associated with the spacings between the interhelix crossovers do the bending fluctuations behave like those of a wormlike chain. The obtained bending persistence lengths are much larger than that for double-stranded DNA and increase nonlinearly with the number of helices, whereas the twist moduli increase approximately linearly. To within the numerical error in our data, the twist-bend coupling constants are of order zero. That the bending persistence lengths that we obtain are generally somewhat higher than in experiment probably reflects both that the simulated origamis have no assembly defects and that the oxDNA extensional modulus for double-stranded DNA is too large.