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DNA as a Genetic Template

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Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...

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Updated: Jun 15, 2026

Designing a Bio-responsive Robot from DNA Origami

Designing a Bio-responsive Robot from DNA Origami

Published on: July 8, 2013

Generative design-enabled exploration of wireframe DNA origami nanostructures.

Anthony J Vetturini¹, Jonathan Cagan¹, Rebecca E Taylor^1,2,3

¹Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Nucleic Acids Research

|December 31, 2024

Summary

This summary is machine-generated.

This study introduces a generative design framework for creating novel wireframe DNA origami nanostructures without predefined designs. The tool aids designers in exploring diverse nanostructures based on user-defined objectives and constraints.

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Last Updated: Jun 15, 2026

Designing a Bio-responsive Robot from DNA Origami

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Published on: September 27, 2019

Area of Science:

Biotechnology
Nanotechnology
Computational Biology

Background:

Wireframe DNA origami nanostructures are advancing rapidly due to computer-aided design (CAD) tools.
Current automated CAD tools require designers to pre-conceptualize nanostructures, limiting innovation.
Existing methods for designing DNA origami nanostructures can be constrained by designer preconceptions.

Purpose of the Study:

To introduce a generative design framework for wireframe DNA origami nanostructures.
To enable the generation of diverse nanostructures without requiring a predefined input mesh.
To assist designers in exploring design-feature trade-offs and ideating novel nanostructures.

Main Methods:

A generative design framework utilizing graph grammar for contextualizing physical properties and controlling design features.
Implementation of single- or multi-objective optimization problems to guide the generative process.
Development of a web-based graphical user interface for comparing generated nanostructures.

Main Results:

The framework successfully generates numerous wireframe DNA origami nanostructures without a predefined mesh.
User-defined objectives and constraints effectively guide the design generation process.
The interactive web interface facilitates side-by-side comparison of diverse nanostructure solutions.

Conclusions:

The constrained generative design framework serves as an assistive tool for exploring design-feature trade-offs in wireframe DNA origami.
This approach facilitates the discovery of novel wireframe DNA origami nanostructures.
The method overcomes limitations of existing tools by enabling exploration beyond designer preconceptions.