Artificial molecular communication network based on DNA nanostructures recognition

Junke Wang, Mo Xie, Lilin Ouyang, Jinggang Li, Lianhui Wang, Chunhai Fan and Jie Chao ()
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Junke Wang: Nanjing University of Posts and Telecommunications
Mo Xie: Nanjing University of Posts and Telecommunications
Lilin Ouyang: Nanjing University of Posts and Telecommunications
Jinggang Li: Nanjing University of Posts and Telecommunications
Lianhui Wang: Nanjing University of Posts and Telecommunications
Chunhai Fan: Shanghai Jiao Tong University
Jie Chao: Nanjing University of Posts and Telecommunications

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract Artificial simulated communication networks inspired by molecular communication in organisms use biological and chemical molecules as information carriers to realize information transmission. However, the design of programmable, multiplexed and general simulation models remains challenging. Here, we develop a DNA nanostructure recognition-based artificial molecular communication network (DR-AMCN), in which rectangular DNA origami nanostructures serve as nodes and their recognition as edges. After the implementation of DR-AMCN with various communication mechanisms including serial, parallel, orthogonal, and multiplexing, it is applied to construct various communication network topologies with bus, ring, star, tree, and hybrid structures. By the establishment of a node partition algorithm for path traversal based on DR-AMCN, the computational complexity of the seven-node Hamiltonian path problem is reduced with the final solution directly obtained through the rate-zonal centrifugation method, and scalability of this approach is also demonstrated. The developed DR-AMCN enhances our understanding of signal transduction mechanisms, dynamic processes, and regulatory networks in organisms, contributing to the solution of informatics and computational problems, as well as having potential in computer science, biomedical engineering, information technology and other related fields.

Date: 2025
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DOI: 10.1038/s41467-024-55527-w

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