Computational Approaches to Nucleic Acid Origami

DNA hairpin dimer-mediated dual-catalysis circuit for efficient and amplifiable electrochemical biosensing

Exploring a variable catalytic hairpin assembly to amplify specific input might be intriguing for electrochemically detecting short-stranded DNA segment related to U. virens (iDNA). Herein, we proposed the first concept of hairpin dimer-mediated Dual-Catalysis Circuit (hdDCC) for creating rapid and efficient electrochemical biosensor. For proof-of-concept, we designed two functional hairpins (H1 and H2) both ended by a sulfhydryl (-SH) group. H1 was recognizable to iDNA, and H2 was modified with electroactive ferrocene (Fc) for signal readout. Under certain condition, two -SH groups were oxidized to form a disulfide bond (S-S), thus linking two mono-hairpins into their own dimers (dH1 or dH2). Upon presenting iDNA, the hdDCC was operated progressively via two consecutive cross-hybridization and displacement events among iDNA, dH1, dH2 and another helping hairpin. During this process, iDNA and dH1 as two cooperative catalysts were repeatedly displaced to accelerate the transduction and amplification, guiding the immobilization of Fc tags in the modified electrode surface for outputting significant current signal. Due to the structural confinement, two reactive units of hdDCC were closely oriented in shorter spatial distance to increase their local concentration, enabling rapider reaction kinetics and more efficient yield. By introducing hairpin dimers for dual-catalysis recycles, this strategy would provide a new paradigm to extend more extensive applications of typical catalytic hairpin assemblies, particularly in the disease prevention of agricultural crops.

Biomolecular Actuators for Soft Robots

Biomolecules present promising stimuli-responsive mechanisms to revolutionize soft actuators. Proteins, peptides, and nucleic acids foster specific intermolecular interactions, and their boundless sequence design spaces encode precise actuation capabilities. Drawing inspiration from nature, biomolecular actuators harness existing stimuli-responsive properties to meet the needs of diverse applications. This review features biomolecular actuators that respond to a wide variety of stimuli to drive both user-directed and autonomous actuation. We discuss how advances in biomaterial fabrication accelerate prototyping of precise, custom actuators, and we identify biomolecules with untapped actuation potential. Finally, we highlight opportunities for multifunctional and reconfigurable biomolecules to improve the versatility and sustainability of next-generation soft actuators.

Models and simulations of structural DNA nanotechnology reveal fundamental principles of self-assembly

DNA is not only a centrally important molecule in biology: the specificity of bonding that allows it to be the primary information storage medium for life has also allowed it to become one of the most promising materials for designing intricate, self-assembling structures at the nanoscale. While the applications of these structures are both broad and highly promising, the self-assembly process itself has attracted interest not only for the practical applications of designing structures with more efficient assembly pathways, but also due to a desire to understand the principles underlying self-assembling systems more generally, of which DNA-based systems provide intriguing and unique examples. Here, we review the fundamental physical principles that underpin the self-assembly process in the field of DNA nanotechnology, with a specific focus on simulation and modelling and what we can learn from them. In particular, we compare and contrast DNA origami and bricks and briefly outline other approaches, with an overview of concepts such as cooperativity, nucleation and hysteresis; we also explain how nucleation barriers can be controlled and why they can be helpful in ensuring error-free assembly. While high-resolution models may be needed to obtain accurate system-specific properties, often very simple coarse-grained models are sufficient to extract the fundamentals of the underlying physics and can enable us to gain deep insight. By combining experimental and simulation approaches to understand the details of the self-assembly process, we can optimise its yields and fidelity, which may in turn facilitate its use in practical applications.

DinoKnot: Duplex Interaction of Nucleic Acids With PseudoKnots

Interaction of nucleic acid molecules is essential for their functional roles in the cell and their applications in biotechnology. While simple duplex interactions have been studied before, the problem of efficiently predicting the minimum free energy structure of more complex interactions with possibly pseudoknotted structures remains a challenge. In this work, we introduce a novel and efficient algorithm for prediction of Duplex Interaction of Nucleic acids with pseudoKnots, DinoKnot follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (both homo- and hetero-dimers). DinoKnot utilizes the structure of molecules before interaction as a guide to find their duplex structure allowing for possible base pair competitions. To showcase DinoKnots's capabilities we evaluated its predicted structures against (1) experimental results for SARS-CoV-2 genome and nine primer-probe sets, (2) a clinically verified example of a mutation affecting detection, and (3) a known nucleic acid interaction involving a pseudoknot. In addition, we compared our results against our closest competition, RNAcofold, further highlighting DinoKnot's strengths. We believe DinoKnot can be utilized for various applications including screening new variants for potential detection issues and supporting existing applications involving DNA/RNA interactions, adding structural considerations to the interaction to elicit functional information.

Toward a Molecular Mechanism of Complementary RNA Duplexes Denaturation

RNA duplexes are relatively rare but play very important biological roles. As an end-product of template-based RNA replication, they also have key implications for hypothetical primitive forms of life. Unless they are specifically separated by enzymes, these duplexes denature upon a temperature increase. However, mechanistic and kinetic aspects of RNA (and DNA) duplex thermal denaturation remain unclear at the microscopic level. We propose an in silico strategy that probes the thermal denaturation of RNA duplexes and allows for an extensive conformational space exploration along a wide temperature range with atomistic precision. We show that this approach first accounts for the strong sequence and length dependence of the duplexes melting temperature, reproducing the trends seen in the experiments and predicted by nearest-neighbor models. The simulations are then instrumental at providing a molecular picture of the temperature-induced strand separation. The textbook canonical "all-or-nothing" two-state model, very much inspired by the protein folding mechanism, can be nuanced. We demonstrate that a temperature increase leads to significantly distorted but stable structures with extensive base-fraying at the extremities, and that the fully formed duplexes typically do not form around melting. The duplex separation therefore appears as much more gradual than commonly thought.

Computer Aided Development of Nucleic Acid Applications in Nanotechnologies

Utilization of nucleic acids (NAs) in nanotechnologies and nanotechnology-related applications is a growing field with broad application potential, ranging from biosensing up to targeted cell delivery. Computer simulations are useful techniques that can aid design and speed up development in this field. This review focuses on computer simulations of hybrid nanomaterials composed of NAs and other components. Current state-of-the-art molecular dynamics simulations, empirical force fields (FFs), and coarse-grained approaches for the description of deoxyribonucleic acid and ribonucleic acid are critically discussed. Challenges in combining biomacromolecular and nanomaterial FFs are emphasized. Recent applications of simulations for modeling NAs and their interactions with nano- and biomaterials are overviewed in the fields of sensing applications, targeted delivery, and NA templated materials. Future perspectives of development are also highlighted.

Application of Nucleic Acid Frameworks in the Construction of Nanostructures and Cascade Biocatalysts: Recent Progress and Perspective

Nucleic acids underlie the storage and retrieval of genetic information literally in all living organisms, and also provide us excellent materials for making artificial nanostructures and scaffolds for constructing multi-enzyme systems with outstanding performance in catalyzing various cascade reactions, due to their highly diverse and yet controllable structures, which are well determined by their sequences. The introduction of unnatural moieties into nucleic acids dramatically increased the diversity of sequences, structures, and properties of the nucleic acids, which undoubtedly expanded the toolbox for making nanomaterials and scaffolds of multi-enzyme systems. In this article, we first introduce the molecular structures and properties of nucleic acids and their unnatural derivatives. Then we summarized representative artificial nanomaterials made of nucleic acids, as well as their properties, functions, and application. We next review recent progress on constructing multi-enzyme systems with nucleic acid structures as scaffolds for cascade biocatalyst. Finally, we discuss the future direction of applying nucleic acid frameworks in the construction of nanomaterials and multi-enzyme molecular machines, with the potential contribution that unnatural nucleic acids may make to this field highlighted.

Advances in the DNA Nanotechnology for the Cancer Biomarkers Analysis: Attributes and Applications

The most commonly used clinical methods are enzyme-linked immunosorbent assay (ELISA) and quantitative PCR (qPCR) in which ELISA was applied for the detection of protein biomarkers and qPCR was especially applied for nucleic acid biomarker analysis. Although these constructed methods have been applied in wide range, they also showed some inherent shortcomings such as low sensitivity, large sample volume and complex operations. At present, many methods have been successfully constructed on the basis of DNA nanotechnology with the merits of high accuracy, rapid and simple operation for cancer biomarkers assay. In this review, we summarized the bioassay strategies based on DNA nanotechnology from the perspective of the analytical attributes for the first time and discussed and the feasibility of the reported strategies for clinical application in the future.

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.

RNA origami design tools enable cotranscriptional folding of kilobase-sized nanoscaffolds

RNA origami is a framework for the modular design of nanoscaffolds that can be folded from a single strand of RNA, and used to organize molecular components with nanoscale precision. Design of genetically expressible RNA origami, which must cotranscriptionally fold, requires modeling and design tools that simultaneously consider thermodynamics, folding pathway, sequence constraints, and pseudoknot optimization. Here, we describe RNA Origami Automated Design software (ROAD), which builds origami models from a library of structural modules, identifies potential folding barriers, and designs optimized sequences. Using ROAD, we extend the scale and functional diversity of RNA scaffolds, creating 32 designs of up to 2360 nucleotides, five that scaffold two proteins, and seven that scaffold two small molecules at precise distances. Micrographic and chromatographic comparison of optimized and nonoptimized structures validates that our principles for strand routing and sequence design substantially improve yield. By providing efficient design of RNA origami, ROAD may simplify construction of custom RNA scaffolds for nanomedicine and synthetic biology.

In Vitro Identification of the Hamiltonian Cycle Using a Circular Structure Assisted DNA Computer

Adleman's illustration of molecular computing using DNA paved the way toward an entirely new direction of computing (Adleman, L. M. Science 1994, 266, 1021). The exponential time complex combinatorial problem on a traditional computer turns out to be a separation problem involving a polynomial number of steps in DNA computing experiments. Despite being a promising concept, the implementations of existing DNA computing procedures were restricted only to the smaller size formulations. In this work, we demonstrate a structure assisted DNA computing procedure on a bigger size Hamiltonian cycle problem involving 18 vertices. The developed model involves the formation and digestion of circular structure DNA, iteratively over multiple stages to eliminate the incorrect solutions to the given combinatorial problem. A high accuracy is obtained compared to other structure assisted models, which enable one to solve the bigger size problems.

A dendritically amplified fluorescent signal probe on SiO2 microspheres for the ultrasensitive detection of mercury ions

In this work, a new kind of dendritically amplified fluorescent signal probe on SiO₂ microspheres was controllably fabricated by the terminal deoxynucleotidyl transferase (TdT)-catalyzed incorporation of nucleotides combined with bio-barcode (BBC) amplification for the ultrasensitive detection of Hg²⁺. A thymine T-Hg²⁺-T hairpin structure was first formed and further initiated the strand displacement amplification (SDA) reaction, generating a mimic target (MT). MT hybridized with a capture probe 1 (C1) on SiO₂ microspheres, and the 3'-hydroxyl (OH) termini of MT initiated TdT-based DNA extension, producing abundant poly-guanine sequences (G1). Then, G1 hybridized with a capture probe 2 (C2) with abundant cytosine (C) species to assemble multiple C2/reporter probe-AuNPs onto the SiO₂ microspheres. The reporter DNA further initiated TdT-based extension with a poly-T sequence (T1) to link large numbers of signal probes, which generated a very high fluorescence signal for the ultrasensitive detection of target Hg²⁺. This TdT-based signal amplification method coupled with SDA exhibits extraordinary sensitivity for Hg²⁺ assay with a limit down to 1.0 aM. The proposed highly sensitive fluorescence strategy holds great potential for detecting targets in environmental and biological fields.

Adjusting Linking Strands to Form Size-Controllable DNA Origami Rings

DNA origami is a powerful tool in nanotechnology that can be used to construct arbitrary structures for several nanoengineering applications. Generally, the more complex and sophisticated the construction, the greater is the number of origamis and connection strands that will be needed. Therefore, developing an effective and low-cost method for multiform DNA architecture is important in nanoengineering. Here, we adopted an oblique linking strategy to connect cross-shaped DNA origami with a controlled curing angle. The size of the DNA rings ranged from four blocks of approximately 200 nm to eleven blocks of c.a. 600 nm. We observed that the minimum size of the DNA ring structure was limited by the width of a single block. The largest rings were negatively affected by thermodynamic randomness, and thus, DNA rings consisting of more than eleven blocks were not observed. This strategy facilitates the generation of various DNA origami rings, whose size can be controlled by adjusting the length of the connection strands.

Coarse-grained modelling of the structural properties of DNA origami

We use the oxDNA coarse-grained model to provide a detailed characterization of the fundamental structural properties of DNA origami, focussing on archetypal 2D and 3D origami. The model reproduces well the characteristic pattern of helix bending in a 2D origami, showing that it stems from the intrinsic tendency of anti-parallel four-way junctions to splay apart, a tendency that is enhanced both by less screened electrostatic interactions and by increased thermal motion. We also compare to the structure of a 3D origami whose structure has been determined by cryo-electron microscopy. The oxDNA average structure has a root-mean-square deviation from the experimental structure of 8.4 Å, which is of the order of the experimental resolution. These results illustrate that the oxDNA model is capable of providing detailed and accurate insights into the structure of DNA origami, and has the potential to be used to routinely pre-screen putative origami designs and to investigate the molecular mechanisms that regulate the properties of DNA origami.

Placing and shaping liposomes with reconfigurable DNA nanocages

The diverse structure and regulated deformation of lipid bilayer membranes are among a cell's most fascinating features. Artificial membrane-bound vesicles, known as liposomes, are versatile tools for modelling biological membranes and delivering foreign objects to cells. To fully mimic the complexity of cell membranes and optimize the efficiency of delivery vesicles, controlling liposome shape (both statically and dynamically) is of utmost importance. Here we report the assembly, arrangement and remodelling of liposomes with designer geometry: all of which are exquisitely controlled by a set of modular, reconfigurable DNA nanocages. Tubular and toroid shapes, among others, are transcribed from DNA cages to liposomes with high fidelity, giving rise to membrane curvatures present in cells yet previously difficult to construct in vitro. Moreover, the conformational changes of DNA cages drive membrane fusion and bending with predictable outcomes, opening up opportunities for the systematic study of membrane mechanics.

An enzyme-free molecular catalytic device: dynamically self-assembled DNA dendrimers for in situ imaging of microRNAs in live cells

DNA has become a promising material to construct high-order structures and molecular devices owing to its sequence programmability. Herein, a DNA machine based on branched catalytic hairpin assembly (bCHA) is introduced for dynamic self-assembly of DNA dendrimers. For this system, a Y-shaped hairpin trimer tethered with three kinds of hairpins (H1, H2 and H3) is constructed. The introduction of an initiator (I) triggers a cascade of CHA reactions among hairpin trimers, leading to the formation of DNA dendrimers. Through labeling fluorophore/quencher pairs in the hairpin trimers, this catalytic DNA machine is applied as a versatile amplification platform to analyze nucleic acids using microRNA-155 (miR-155) as a model analyte. Benefiting from the "diffusion effect", the proposed bCHA achieves a greatly improved sensitivity in comparison with traditional CHA. This catalytic amplifier exhibits high sensitivity toward miR-155 detection with a dynamic range from 2.5 nM to 500 nM and demonstrates excellent selectivity to distinguish the single-base mismatched sequence from the perfectly complementary one, which is further applied to detect low-abundance miR-155 spiked in complex matrices with minimal interference. This method is further applied for in situ imaging of miR-155 in different live cells. The bCHA reaction can be specifically triggered by intracellular miR-155, achieving monitoring of the dynamic miRNA expression and distribution. Overall, our proposed enzyme-free dynamic DNA self-assembly strategy provides a versatile approach for the development of DNA nanotechnology in biosensing and bioimaging, and monitoring the cellular miRNA-related biological events.

Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation.

RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model

Motivation

RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method.

Results

The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

Hybridization chain reaction: a versatile molecular tool for biosensing, bioimaging, and biomedicine

This review provides a comprehensive overview of the fundamental principles, analysis techniques, and application fields of hybridization chain reaction and its development status.