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1. MENDEL: an automated design tool for DNA nanotechnology

   Guerrero, Jorge; Zadegan, Reza (September 2020, DNA26: 26th International Conference on DNA Computing and Molecular Programming)

   null (Ed.)

   Designing complex DNA nanostructures is a complicated process that requires efficient software to calculate and populate structural details. Most of the published software require manual manipulation and careful inspection of the models that increase the time cost and user error and decrease the flexibility of designing process. We created a python library that we coined MENDEL as a flexible and robust solution for automatic design of complex DNA nanostructures. MENDEL receives a set of sequential commands and creates the structures by following logical steps. Each step instructs the growth of the DNA nanostructure either by adding new nucleotides or repeating sections of arbitrary size and shape. User is able to monitor the design progress by executing the commands in Blender software’s scripting mode. Figure 1 shows an example of using MENDEL library to design a triple-layered origami that represents the word “MENDEL.” MENDEL generates the geometry preview, which helps to understand the design details. Moreover, for convenience, the exported file is compatible with caDNAno. Figure 2 shows the exported model when opened in caDNAno, and Figure 3 shows the modeling results obtained from CanDo for different number of layers. Future work include improving nucleotide twist and rise calculations, supporting honeycomb designs, detecting overlaps, inserting and skipping nucleotides, and generating molecular file formats such as Protein Data Bank (PDB). 

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2. A Python library for structural DNA nanotechnology

   Guerrero, Jorge Eduardo; Zadegan, Reza (April 2021, FNANO (Foundations of Nanoscience))

   null (Ed.)

   Structural DNA nanotechnology is a powerful technique for bottom-up self-assembly of nanoscale structures. Potential applications are vast and only limited by the researchers' imagination. For large and complex structures, the manual or semi-automatic designing process is time-consuming and requires a detailed inspection of the model, leading to user error. We introduce MENDEL, a software library that allows the automatic, extensive, and parametric DNA nanostructures design in this work. MENDEL contains a set of commands that automate the designing process, allow the abstraction of turning sites, compute staples, and parametrize scaling and repetitive features; thus, reducing user error, design complications, and time-to-complete. Running MENDEL through Blender renders a 3D representation of the model. Also, for community convenience, MENDEL generates caDNAno/CanDo compatible files. MENDEL is available as open-source software at https://github.com/SBMI-LAB/MENDEL. 

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3. Elucidating the Mechanical Energy for Cyclization of a DNA Origami Tile

   https://doi.org/10.3390/app11052357  

   Li, Ruixin; Chen, Haorong; Lee, Hyeongwoon; Choi, Jong Hyun (March 2021, Applied Sciences)

   null (Ed.)

   DNA origami has emerged as a versatile method to synthesize nanostructures with high precision. This bottom-up self-assembly approach can produce not only complex static architectures, but also dynamic reconfigurable structures with tunable properties. While DNA origami has been explored increasingly for diverse applications, such as biomedical and biophysical tools, related mechanics are also under active investigation. Here we studied the structural properties of DNA origami and investigated the energy needed to deform the DNA structures. We used a single-layer rectangular DNA origami tile as a model system and studied its cyclization process. This origami tile was designed with an inherent twist by placing crossovers every 16 base-pairs (bp), corresponding to a helical pitch of 10.67 bp/turn, which is slightly different from that of native B-form DNA (~10.5 bp/turn). We used molecular dynamics (MD) simulations based on a coarse-grained model on an open-source computational platform, oxDNA. We calculated the energies needed to overcome the initial curvature and induce mechanical deformation by applying linear spring forces. We found that the initial curvature may be overcome gradually during cyclization and a total of ~33.1 kcal/mol is required to complete the deformation. These results provide insights into the DNA origami mechanics and should be useful for diverse applications such as adaptive reconfiguration and energy absorption. 

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

   https://doi.org/10.1038/s41557-021-00679-1  

   Cody Geary, Guido Grossi (May 2021, Nature chemistry)

   null (Ed.)

   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. The design of genetically expressible RNA origami, which must fold cotranscriptionally, requires modelling and design tools that simultaneously consider thermodynamics, the 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 2,360 nucleotides, five that scaffold two proteins, and seven that scaffold two small molecules at precise distances. Micrographic and chromatographic comparisons of optimized and non-optimized structures validate that our principles for strand routing and sequence design substantially improve yield. By providing efficient design of RNA origami, ROAD may simplify the construction of custom RNA scaffolds for nanomedicine and synthetic biology. 

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5. Computational generation of an annotated gigalibrary of synthesizable, composite peptidic macrocycles

   https://doi.org/10.1073/pnas.2007304117  

   Saha, Ishika; Dang, Eric_K; Svatunek, Dennis; Houk, Kendall_N; Harran, Patrick_G (September 2020, Proceedings of the National Academy of Sciences)

   Significance We describe computations to anticipate products of multistep reaction sequences. The work is based on experimental methods developed earlier to amalgamate synthetic scaffolding reagents with small linear peptides. Hybrid products retain molecular recognition elements in the peptide, but display that functionality as part of amphipathic macrocycles having defined conformations and improved pharmacological properties. The hypothetical scope of the chemistry is large and far outpaces the experimental format. To explore the structure space more extensively, we devised algorithms to predict outcomes of more than 2 billion processing sequences. Software was also developed to generate accurate three-dimensional structures for each product. The resultant virtual library is a resource that can be deployed broadly in search of novel ligands for protein receptors. 

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