Generative design-enabled exploration of wireframe DNA origami nanostructures
Recent advances in computer-aided design tools have helped rapidly advance the development of wireframe DNA origami nanostructures. Specifically, automated tools now exist that can convert an input polyhedral mesh into a DNA origami nanostructure, greatly reducing the design difficulty for wireframe DNA origami nanostructures. However, one limitation of these automated tools is that they require a designer to fully conceptualize their intended nanostructure, which may be limited by their own preconceptions. Here, a generative design framework is introduced capable of generating many wireframe DNA origami nanostructures without the need for a predefined mesh. User-defined objectives that guide the generative process are input as either single- or multi-objective optimization problems. A graph grammar is used to both contextualize physical properties of the DNA nanostructure and control the types of generated design features. This framework allows a designer to explore upon and ideate among many generated nanostructures that comply with their own unique constraints. A web-based graphical user interface is provided, allowing users to compare various generated solutions side by side in an interactive environment. Overall, this work illustrates how a constrained generative design framework can be implemented as an assistive tool in exploring design-feature trade-offs of wireframe DNA nanostructures, resulting in novel wireframe nanostructures.
Authors
- Jonathan Cagan (ORCID: https://orcid.org/0000-0002-3935-9219)
- R. E. Taylor (ORCID: https://orcid.org/0000-0001-5299-8296)
- Anthony J Vetturini (ORCID: https://orcid.org/0009-0005-3822-5138)
Institutions
- Carnegie Mellon University (US)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-12-31
- DOI
- https://doi.org/10.1093/nar/gkae1268
- Citations
- 3
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- National Science Foundation
- National Defense Science and Engineering Graduate
- Division of Civil, Mechanical and Manufacturing Innovation
- Air Force Office of Scientific Research