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Molecular engineering seeks to create functional entities for modular use in the bottom-up design of nanoassemblies that can perform complex tasks. Such systems require fuel-consuming nanomotors that can actively drive downstream passive followers. Most artificial molecular motors are driven by Brownian motion, in which, with few exceptions, the generated forces are non-directed and insufficient for efficient transfer to passive second-level components. Consequently, efficient chemical-fuel-driven nanoscale driver–follower systems have not yet been realized. Here we present a DNA nanomachine (70 nm × 70 nm × 12 nm) driven by the chemical energy of DNA-templated RNA-transcription-consuming nucleoside triphosphates as fuel to generate a rhythmic pulsating motion of two rigid DNA-origami arms. Furthermore, we demonstrate actuation control and the simple coupling of the active nanomachine with a passive follower, to which it then transmits its motion, forming a true driver–follower pair.

 

Ribonucleic acid (RNA) is a fundamental biological molecule that is essential to all living organisms, performing a versatile array of cellular tasks. The function of many RNA molecules is strongly related to the structure it adopts. As a result, great effort is being dedicated to the design of efficient algorithms that solve the “folding problem”—given a sequence of nucleotides, return a probable list of base pairs, referred to as the secondary structure prediction. Early algorithms largely rely on finding the structure with minimum free energy. However, the predictions rely on effective simplified free energy models that may not correctly identify the correct structure as the one with the lowest free energy. In light of this, new, data-driven approaches that not only consider free energy, but also use machine learning techniques to learn motifs are also investigated and recently been shown to outperform free energy–based algorithms on several experimental data sets. In this work, we introduce the new ExpertRNA algorithm that provides a modular framework that can easily incorporate an arbitrary number of rewards (free energy or nonparametric/data driven) and secondary structure prediction algorithms. We argue that this capability of ExpertRNA has the potential to balance out different strengths and weaknesses of state-of-the-art folding tools. We test ExpertRNA on several RNA sequence-structure data sets, and we compare the performance of ExpertRNA against a state-of-the-art folding algorithm. We find that ExpertRNA produces, on average, more accurate predictions of nonpseudoknotted secondary structures than the structure prediction algorithm used, thus validating the promise of the approach. Summary of Contribution: ExpertRNA is a new algorithm inspired by a biological problem. It is applied to solve the problem of secondary structure prediction for RNA molecules given an input sequence. The computational contribution is given by the design of a multibranch, multiexpert rollout algorithm that enables the use of several state-of-the-art approaches as base heuristics and allowing several experts to evaluate partial candidate solutions generated, thus avoiding assuming the reward being optimized by an RNA molecule when folding. Our implementation allows for the effective use of parallel computational resources as well as to control the size of the rollout tree as the algorithm progresses. The problem of RNA secondary structure prediction is of primary importance within the biology field because the molecule structure is strongly related to its functionality. Whereas the contribution of the paper is in the algorithm, the importance of the application makes ExpertRNA a showcase of the relevance of computationally efficient algorithms in supporting scientific discovery. 

The domains of DNA and RNA nanotechnology are steadily gaining in popularity while proving their value with various successful results, including biosensing robots and drug delivery cages. Nowadays, the nanotechnology design pipeline usually relies on computer-based design (CAD) approaches to design and simulate the desired structure before the wet lab assembly. To aid with these tasks, various software tools exist and are often used in conjunction. However, their interoperability is hindered by a lack of a common file format that is fully descriptive of the many design paradigms. Therefore, in this paper, we propose a Unified Nanotechnology Format (UNF) designed specifically for the biomimetic nanotechnology field. UNF allows storage of both design and simulation data in a single file, including free-form and lattice-based DNA structures. By defining a logical and versatile format, we hope it will become a widely accepted and used file format for the nucleic acid nanotechnology community, facilitating the future work of researchers and software developers. Together with the format description and publicly available documentation, we provide a set of converters from existing file formats to simplify the transition. Finally, we present several use cases visualizing example structures stored in UNF, showcasing the various types of data UNF can handle. 

The emerging field of hybrid DNA–protein nanotechnology brings with it the potential for many novel materials which combine the addressability of DNA nanotechnology with the versatility of protein interactions. However, the design and computational study of these hybrid structures is difficult due to the system sizes involved. To aid in the design and in silico analysis process, we introduce here a coarse-grained DNA/RNA–protein model that extends the oxDNA/oxRNA models of DNA/RNA with a coarse-grained model of proteins based on an anisotropic network model representation. Fully equipped with analysis scripts and visualization, our model aims to facilitate hybrid nanomaterial design towards eventual experimental realization, as well as enabling study of biological complexes. We further demonstrate its usage by simulating DNA–protein nanocage, DNA wrapped around histones, and a nascent RNA in polymerase. 

Abstract OxDNA and oxRNA are popular coarse-grained models used by the DNA/RNA nanotechnology community to prototype, analyze and rationalize designed DNA and RNA nanostructures. Here, we present oxDNA.org, a graphical web interface for running, visualizing and analyzing oxDNA and oxRNA molecular dynamics simulations on a GPU-enabled high performance computing server. OxDNA.org automatically generates simulation files, including a multi-step relaxation protocol for structures exported in non-physical states from DNA/RNA design tools. Once the simulation is complete, oxDNA.org provides an interactive visualization and analysis interface using the browser-based visualizer oxView to facilitate the understanding of simulation results for a user’s specific structure. This online tool significantly lowers the entry barrier of integrating simulations in the nanostructure design pipeline for users who are not experts in the technical aspects of molecular simulation. The webserver is freely available at oxdna.org. 

Abstract This work seeks to remedy two deficiencies in the current nucleic acid nanotechnology software environment: the lack of both a fast and user-friendly visualization tool and a standard for structural analyses of simulated systems. We introduce here oxView, a web browser-based visualizer that can load structures with over 1 million nucleotides, create videos from simulation trajectories, and allow users to perform basic edits to DNA and RNA designs. We additionally introduce open-source software tools for extracting common structural parameters to characterize large DNA/RNA nanostructures simulated using the coarse-grained modeling tool, oxDNA, which has grown in popularity in recent years and is frequently used to prototype new nucleic acid nanostructural designs, model biophysics of DNA/RNA processes, and rationalize experimental results. The newly introduced software tools facilitate the computational characterization of DNA/RNA designs by providing multiple analysis scripts, including mean structures and structure flexibility characterization, hydrogen bond fraying, and interduplex angles. The output of these tools can be loaded into oxView, allowing users to interact with the simulated structure in a 3D graphical environment and modify the structures to achieve the required properties. We demonstrate these newly developed tools by applying them to design and analysis of a range of DNA/RNA nanostructures. 

We introduce a new online database of nucleic acid nanostructures for the field of DNA and RNA nanotechnology. The database implements an upload interface, searching and database browsing. Each deposited nanostructures includes an image of the nanostructure, design file, an optional 3D view, and additional metadata such as experimental data, protocol or literature reference. The database accepts nanostructures in any preferred format used by the uploader for the nanostructure design. We further provide a set of conversion tools that encourage design file conversion into common formats (oxDNA and PDB) that can be used for setting up simulations, interactive editing or 3D visualization. The aim of the repository is to provide to the DNA/RNA nanotechnology community a resource for sharing their designs for further reuse in other systems and also to function as an archive of the designs that have been achieved in the field so far. Nanobase.org is available at https://nanobase.org/.