Evidence map›Paper›PMID 41706864›Full record

ArticleScience advances2026

Conformation-programmed DNA computing.

Qian Ling, Bozhao Li, Yuhua Feng, Jing Yang, Shi'an Wang, Suping Li, Cheng Zhang

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Qian LingSchool of Computer Science, Peking University, Beijing 100871, China.ORCID 0009-0002-0810-0201
Bozhao LiCAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center of Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China.ORCID 0000-0001-6502-4722
Yuhua FengSchool of Computer Science, Peking University, Beijing 100871, China.
Jing YangSchool of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China.ORCID 0000-0001-5481-7962
Shi'an WangKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China.ORCID 0000-0001-8323-4344
Suping LiCAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center of Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China.ORCID 0000-0002-0294-8861
Cheng ZhangSchool of Computer Science, Peking University, Beijing 100871, China.ORCID 0000-0002-1131-6516

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Computers, MolecularDNANucleic Acid ConformationAllosteric RegulationMicroRNAsSynthetic BiologyDNAMicroRNAs

Identifiers

PMID41706864
PMCPMC12915622

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.