Conformation-programmed DNA computing

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Authors: 謙忠 永嶺, Bozhao Li, Yuhua Feng, Jing Yang, Shi‐An Wang, S. LI, Cheng Zhang
Cited by: 3
References: 44

Abstract

Natural biological systems achieve precise cellular control through multidimensional signaling architectures that integrate sequence specificity, structural dynamics, and conformational switching. While synthetic DNA networks have been engineered primarily using sequence programmability, exclusive reliance on this dimension constrains signaling range and integrated regulation. Here, we report an allosteric DNA computing framework enabling the simultaneous integration of sequence programmability with conformational dynamics for integrated multilevel signal processing. By encoding conformational signals within polythymidine loops (0 to 40 nucleotides), this system executes loop-dependent logic operations with expanded signaling ranges. Moreover, catalytic allosteric hairpin assemblies achieve ~30-fold signal amplification with enhanced signal-to-noise ratios. Concurrently, allosteric DNA neural networks discriminate conformational signals based on loop lengths (7 to 15 nucleotides) at two-nucleotide resolution. Crucially, microRNA-responsive versions of this framework regulate gene expression, thereby bridging conformational signaling with genetic control regulations in vivo. Collectively, this work establishes a conformational signal-processing paradigm for adaptive DNA computing, paving the way for advanced synthetic biology and precision therapeutics.

Fields of Study & Subjects

DNA and Biological Computing Advanced biosensing and bioanalysis techniques DNA and Nucleic Acid Chemistry

Publication details

Journal / source
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Volume
12
Issue
8
Pages
eaec8383–eaec8383
Publication date
18 February 2026
Language
EN