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Tikhomirov, G.

Publications and source records attributed to Tikhomirov, G..

2 recordsLinked to original sources

Uncovering Design and Assembly Rules for mRNA-DNA Origami

mRNA-DNA hybrid origami offers a powerful route to combine the structural programmability of DNA origami with the biological functionality of messenger RNA, but generalizable design and assembly rules for these hybrids remain poorly defined. Here we systematically investigate the design principles and synthesis conditions that govern high-yield formation of mRNA-DNA hybrid nanostructures. Using mature mRNAs encoding firefly luciferase, EGFP, and mCherry as scaffolds, we construct a series of five hybrid compact origamis with diverse sizes, shapes, crossover strategies, and packing densities. We identify key parameters that control folding fidelity, including asymmetric A-form crossovers, monovalent-cation concentrations, and moderate-temperature annealing protocols, which together mitigate RNA instability, reduce kinetic traps, and accommodate RNA-DNA helical geometry. Atomic force microscopy reveals monodisperse, well-folded structures consistent with design expectations across most architectures and confirms that optimized conditions produce nanoscale precision comparable to DNA origami. Our findings establish generalizable design rules and a standard synthesis protocol for mRNA-DNA hybrid origami, providing a framework for their use in gene delivery and other RNA-based nanotechnologies.

bioengineering↗

AI-based Prediction of Protein Corona Composition on DNA Nanostructures

DNA nanotechnology has emerged as a powerful approach to engineering biophysical tools, therapeutics, and diagnostics because it enables the construction of designer nanoscale structures with high programmability. Based on DNA base pairing rules, nanostructure size, shape, surface functionality, and structural reconfiguration can be programmed with a degree of spatial, temporal, and energetic precision that is difficult to achieve with other methods. However, the properties and structure of DNA constructs are greatly altered in vivo due to spontaneous protein adsorption from biofluids. These adsorbed proteins, referred to as the protein corona, remain challenging to control or predict, and subsequently, their functionality and fate in vivo are difficult to engineer. To address these challenges, we prepared a library of diverse DNA nanostructures and investigated the relationship between their design features and the composition of their protein corona. We identified protein characteristics important for their adsorption to DNA nanostructures and developed a machine-learning model that predicts which proteins will be enriched on a DNA nanostructure based on the DNA structures design features and protein properties. Our work will help to understand and program the function of DNA nanostructures in vivo for biophysical and biomedical applications.

bioengineering↗