A Computationally Optimized Ribonucleic Acid Circularization Strategy without Byproducts

Circular mRNA (mRNA) exhibits promising potential in mRNA therapy due to its increased stability and extended duration of protein translation, which has sparked an urgent demand for efficient methods to prepare circular RNAs <i>in vitro</i>. Here, we present a versatile self-circularization strategy that employs simple motifs to synthesize circular RNAs, achieving robust efficiencies for sequences ranging from dozens to thousands of nucleotides. By leveraging an automated computational program, we optimized highly specific lock-key structures to maximize circularization efficiency, particularly for long RNA substrates. Furthermore, the shared sequence and functionality between linear precursor RNAs and circular products eliminate the need for additional purification steps to remove excess nucleic acid components, simplifying the production process. This approach also yields circular RNAs with superior stability and translation efficiency, enabling sustained protein expression <i>in vitro</i> and <i>in vivo</i>. Our computationally optimized, purification-free method holds immense promise for scalable circular RNA production and the development of advanced RNA therapeutics, significantly advancing mRNA therapy.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2025-08-28
DOI
https://doi.org/10.1021/jacs.5c09798
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.00

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article

A Computationally Optimized Ribonucleic Acid Circularization Strategy without Byproducts

Yuanyuan Wu, Yuanchen Dong, Baolei Tian, Liangzhi Luo et al.
Journal of the American Chemical Society
RNA and protein synthesis mechanisms
article

A Computationally Optimized Ribonucleic Acid Circularization Strategy without Byproducts

Yuanyuan Wu, Yuanchen Dong, Baolei Tian, Liangzhi Luo, Yufan Pan, Yuan Zhuang, Chenyou Zhu, R. Chen, Yujie Li, Liang Zhang, Dongsheng Liu, Rui Xu, Yifan Jiang, Ziyang Hao, Li Zhang
article en

Abstract

Circular mRNA (mRNA) exhibits promising potential in mRNA therapy due to its increased stability and extended duration of protein translation, which has sparked an urgent demand for efficient methods to prepare circular RNAs <i>in vitro</i>. Here, we present a versatile self-circularization strategy that employs simple motifs to synthesize circular RNAs, achieving robust efficiencies for sequences ranging from dozens to thousands of nucleotides. By leveraging an automated computational program, we optimized highly specific lock-key structures to maximize circularization efficiency, particularly for long RNA substrates. Furthermore, the shared sequence and functionality between linear precursor RNAs and circular products eliminate the need for additional purification steps to remove excess nucleic acid components, simplifying the production process. This approach also yields circular RNAs with superior stability and translation efficiency, enabling sustained protein expression <i>in vitro</i> and <i>in vivo</i>. Our computationally optimized, purification-free method holds immense promise for scalable circular RNA production and the development of advanced RNA therapeutics, significantly advancing mRNA therapy.

Journal of the American Chemical SocietyVol. 147(36)
National Academy of Medicine (US), Zhejiang Sci-Tech University (CN), Capital University (US), Hong Kong Polytechnic University (HK), Capital Medical University (CN), Chinese Academy of Sciences (CN), Ministry of Advanced Education (CA), HKUST Shenzhen Research Institute (CN), Beijing National Laboratory for Molecular Sciences (CN), Institute of Chemistry (CN), Innovative Research (United States) (US), Beijing Haidian Hospital (CN), University of Chinese Academy of Sciences (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Beijing Municipal Science and Technology Commission, Beijing Municipal Natural Science Foundation, National Key Research and Development Program of China
Openalex Percentile: Top 80%
RNA and protein synthesis mechanisms
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