Stabilizing DNA origami nanostructures for clinical translation through chemical and computational engineering

This is the authors' abstract. We don't add key points for this paper.

However, despite their tremendous therapeutic potential for sensing and delivery, DNA origamis cannot be used for the development of therapeutic agents due to three interrelated physiological barriers: degradation through nucleases, structural collapse under low ionic strength conditions, and instability in biological fluid temperatures. The recent developments in the field include chemical modification, cross-linking, and computational designs, which individually increase stability several times. Yet, even using phosphorothioate backbone, ultraviolet (UV) cross-linking, and machine learning techniques separately allows achieving only an order of magnitude improvement. In the current paper, we comprehensively analyzed the combination effect on the stability provided by protective coating, covalent modification, and artificial intelligence (AI)-assisted sequence optimization for generating DNA origami with an increase of stability by thousands of times and presented a dedicated mathematical model proving a synergic effect in applying the strategies orthogonal to each other. Moreover, we considered the critical problem of scaling DNA origamis up from laboratory grams of production to industrial kilos, analyzing costs of staples' synthesis, GMP purification process, and complex regulatory requirements from Food and Drug Administration (FDA), European Medicines Agency (EMA), Pharmaceuticals and Medical Devices Agency (PMDA) regarding medical product classification. Finally, we discussed the key importance of large datasets generation in DNA origami research for successful use of machine learning.