Aug 2026· Angewandte Chemie· pp.
e4782087
· 0 citations· 31 references
Medicine
TL;DR
circDesign is presented, an algorithm that explicitly incorporates IRES structural deviation into circRNA sequence design while jointly optimizing codon adaptation and thermodynamic stability and establishes IRES structural preservation as a mechanistic design principle for circRNA engineering and position circDesign as a rational framework for therapeutic circRNA development.
Abstract
Synthetic circular mRNA (hereafter referred to as circRNA) reduces susceptibility to exonuclease-mediated degradation by its covalently closed circular structure, enabling prolonged protein expression for therapeutic applications. In this circular format, protein expression from engineered circRNAs is achieved mainly through cap-independent translation initiation, commonly mediated by internal ribosome entry site (IRES) elements whose activity is influenced by RNA structure. Consequently, the coding sequence (CDS) and other elements should be designed with consideration of inter-region base pairing that can shift IRES folding, a constraint not explicitly addressed by existing linear mRNA CDS optimization algorithms. Here, we present circDesign, an algorithm that explicitly incorporates IRES structural deviation into circRNA sequence design while jointly optimizing codon adaptation and thermodynamic stability. In a rabies virus glycoprotein (RABV-G) vaccine model, circDesign-generated circRNAs showed improved stability, translation efficiency, and vaccine immunogenicity compared with benchmark sequences optimized using conventional linear mRNA CDS design strategies, with CR3 achieving a 3.5-fold increase in neutralizing antibody titers. Polysome profiling and targeted IRES-disruption experiments support IRES structural integrity as a critical determinant of circRNA translation performance. Together, these results establish IRES structural preservation as a mechanistic design principle for circRNA engineering and position circDesign as a rational framework for therapeutic circRNA development.
A new chemically regulated circRNA translation system based on small ligand-induced stabilization of RNA-binding proteins (RBPs), engineered by incorporating RNA motifs into an internal ribosomal entry site and fusing RBPs with small ligand-stabilized conditional proteins is developed.
This review argues that circular topology should be viewed as an active pharmacologic variable, not merely a stability enhancement, and dissect recent advances in cap-independent translation initiation, including IRES elements and m6A-driven mechanisms, rolling-circle translation for multi-epitope vaccine design, and p...
Amr A. El-Sehrawy, H. Al-Ameer, J. Rizaev et al.· Biotechnology and Bioenginee...· 0 citations
The split intron-exon (SIE) system is introduced, which separates ribozymes from substrates to facilitate the efficient production of modified circular RNAs, optimizing production process.
Lei Wang, Qiaoli Zhai, Chunbo Dong et al.· Nature Communications· 0 citations
These findings identify nucleotide class composition as a previously unrecognized parameter governing IVT-mRNA function and establish hybrid ribonucleotide-deoxyribonucleotide backbone engineering as a versatile strategy to expand the chemical space for next-generation mRNA therapeutics.
Xiaoyan Ding, Riu Liao, G. Bampi et al.· bioRxiv· 0 citations
The versatility of the assay is demonstrated and a 4-fold reduction in 5' cap concentration for in vitro transcription results in equivalent translation in cellulo, illustrating how split luminescent tagging can be easily integrated into the mRNA therapeutic workflow, enabling monitoring of real-time mRNA-driven protei...
C. Batho, Camilla Ascanelli, Megan L. Maple et al.· Journal of Visualized Experi...· 0 citations
An underappreciated constraint in saRNA therapeutics is defined and saRNA-specific payload design frameworks that incorporate alphavirus associated compositional biases during transgene sequence optimization are motivated.
N. V. Bathula, Shekinah K V Soriano, Cynthia Huang et al.· Molecular Therapy· 1 citation
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.