ArticleJournal of molecular biology2026
Self-Assembling RNA Nanostructures are Highly Sensitive to Environmental Conditions.
Article in Journal of molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
Recent developments in RNA nanotechnology have led to an increase in the design of specific, higher-order RNA structures, which will ultimately be used in drug delivery and immunomodulation applications. As researchers create RNA nanostructures with the intention of making them a standard tool in molecular biologists' toolkits, further investigation is required into the robustness of RNA designs. Primarily, in what different molecular contexts are the designed and intended nanostructures stable? In this work, we show that RNA nanostructure self-assembly is highly sensitive to environmental conditions by using second-order right-angle light scattering. While a test RNA hexagonal grid nanostructure forms correctly through 120° kissing loops under ideal conditions, small variations in salt conditions and annealing times cause the nanostructure to form less structured variants. Tertiary contacts for self-assembly require magnesium and break over a broad range of low temperatures, melting at 43 °C. In contrast, this was found to be considerably lower than the secondary structure melting, which occurred at 75 °C. This work highlights the importance of quantitatively and thermodynamically characterizing self-assembling nanostructures as they are increasingly deployed for engineering and therapeutic applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.