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 in vitro. 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 in vitro and in vivo. 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.