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Abstract DNA origami information storage is a promising alternative to silicon-based data storage, offering a molecular cryptography technique concealing information within DNA origami. Routing, sliding, and interlacing staple strands lead to a large 700-bit key size. Practical DNA data storage requires high information density, robust security, and accurate and rapid information retrieval. Consequently, advanced readout techniques and large encryption key sizes are essential. Here, we report an enhanced DNA origami cryptography protocol in 2D and 3D DNA origami, increasing the encryption key size. We employ all-DNA-based steganography with fast readout through high-speed DNA-PAINT super-resolution imaging. By combining DNA-PAINT data with unsupervised clustering, we achieve an accuracy of up to 89%, despite the flexibility in the 3D DNA origami shown by oxDNA simulation. Furthermore, we propose criteria that ensure complete information retrieval for the DNA origami cryptography. Our findings show that DNA-based cryptography is a secure and versatile solution for storing information. 

Constraining proximity-based drugs, such as proteolysis targeting chimeras (PROTACs), into their bioactive conformation can significantly impact their selectivity and potency. However, traditional methods for achieving this often involve complex and time-consuming synthetic procedures. Here, we introduced an alternative approach by demonstrating DNA-templated spatially controlled PROTACs (DTACs), which leverage the programmability of nucleic acid-based self-assembly for efficient synthesis and offer precise control over inhibitors’ spacing and orientation. The resulting constructs revealed distance- and orientation-dependent selectivity and degradation potency for the Cyclin D1–CDK4/6 protein complex in cancer cells. Notably, the optimal construct DTAC-V1 demonstrated unprecedented synchronous degradation of the entire Cyclin D1–CDK4/6 complex, leading to robust G1-phase cell cycle arrest and effective inhibition of cancer cell proliferation. Furthermore, in a xenograft mouse model, DTAC-V1 exhibited potent therapeutic efficacy by effectively degrading Cyclin D1–CDK4/6 and suppressing tumor growth, underscoring its potential as an anticancer agent. Overall, our findings demonstrate the feasibility of DTAC as a rapid, scalable, and modular platform for the spatial control of functional inhibitors for optimal effectiveness, making it a promising method for proximity-based therapeutics. 

GPUs are used in many settings to accelerate large-scale scientific computation, including simulation, computational biology, and molecular dynamics. However, optimizing codes to run efficiently on GPUs requires developers to have both detailed understanding of the application logic and significant knowledge of parallel programming and GPU architectures. This paper shows that an automated GPU program optimization tool, GEVO, can leverage evolutionary computation to find code edits that reduce the runtime of three important applications, multiple sequence alignment, agent-based simulation and molecular dynamics codes, by 28.9%, 29%, and 17.8% respectively. The paper presents an in-depth analysis of the discovered optimizations, revealing that (1) several of the most important optimizations involve significant epistasis, (2) the primary sources of improvement are application-specific, and (3) many of the optimizations generalize across GPU architectures. In general, the discovered optimizations are not straightforward even for a GPU human expert, showcasing the potential of automated program optimization tools to both reduce the optimization burden for human domain experts and provide new insights for GPU experts. 

The folding of RNA and DNA strands plays crucial roles in biological systems and bionanotechnology. However, studying these processes with high-resolution numerical models is beyond current computational capabilities due to the timescales and system sizes involved. In this article, we present a new coarse-grained model for investigating the folding dynamics of nucleic acids. Our model represents three nucleotides with a patchy particle and is parameterized using well-established nearest-neighbor models. Thanks to the reduction of degrees of freedom and to a bond-swapping mechanism, our model allows for simulations at timescales and length scales that are currently inaccessible to more detailed models. To validate the performance of our model, we conducted extensive simulations of various systems: We examined the thermodynamics of DNA hairpins, capturing their stability and structural transitions, the folding of an MMTV pseudoknot, which is a complex RNA structure involved in viral replication, and also explored the folding of an RNA tile containing a k-type pseudoknot. Finally, we evaluated the performance of the new model in reproducing the melting temperatures of oligomers and the dependence on the toehold length of the displacement rate in toehold-mediated displacement processes, a key reaction used in molecular computing. All in all, the successful reproduction of experimental data and favorable comparisons with existing coarse-grained models validate the effectiveness of the new model. 

Understanding the mechanisms by which single-stranded RNA viruses regulate capsid assembly around their RNA genomes has become increasingly important for the development of both antiviral treatments and drug delivery systems. In this study, we investigate the effects of RNA-induced allostery in a single-stranded RNA virus—Levivirus bacteriophage MS2 assembly—using the computational methods of the Dynamic Flexibility Index and the Dynamic Coupling Index. We demonstrate that not only does asymmetric binding of RNA to a symmetric MS2 coat protein dimer increase the flexibility of the distant FG-loop, inducing a conformational change to an asymmetric dimer, but also RNA binding reorganizes long-distance communications, making all the other positions extremely sensitive to the fluctuation of the ordered FG-loop. Additionally, we find that a point mutation in the FG-loop, W82R, leads to the loss of this asymmetry in communications, likely being a leading cause for assembly-deficient dimers. Lastly, this dominant communication that enhances its dynamic coupling with all the distal positions is not only a property of the dimer but is also exhibited by all the observed capsid intermediates. This strong dynamic coupling allows for unidirectional signal transduction that drives the formation of the experimentally observed capsid intermediates and fully assembled capsid. 

We present a tutorial on setting-up the oxDNA coarse-grained model for simulations of DNA and RNA nanotechnology. The model is a popular tool used both by theorists and experimentalists to simulate nucleic acid systems both in biology and nanotechnology settings. The tutorial is aimed at new users asking "Where should I start if I want to use oxDNA". We assume no prior background in using the model. This tutorial shows basic examples that can get a novice user started with the model, and points the prospective user towards additional reading and online resources depending on which aspect of the model they are interested in pursuing.