Engineering the MmeFz2-ωRNA system for efficient genome editing through an integrated computational-experimental framework

Eukaryotic Fanzor proteins are compact, programmable RNA-guided nucleases with substantial potential for genome editing, although their efficiency in mammalian cells remains suboptimal. Here, we present a combinatorial engineering strategy to optimize a representative Fanzor system, MmeFz2–ωRNA. AlphaFold3-powered rational redesign produced a minimized ωRNA scaffold that is 30% smaller while maintaining up to 82.2% efficiency. Synergistic structure-guided and AI-augmented protein engineering generated two variants, enMmeFz2 and evoMmeFz2, which exhibited an average ~32-fold increase in activity across 38 genomic loci. Moreover, fusion of the non-specific DNA-binding domain HMG-D further enhanced editing performance (enMmeFz2-HMG-D and evoMmeFz2-HMG-D). Notably, evoMmeFz2-HMG-D demonstrated robust in vivo genome editing activity, enabling dystrophin restoration in humanized male Duchenne muscular dystrophy mouse models via single adeno-associated virus (AAV) delivery. This study establishes Fanzor2 as a gene editing platform for genome engineering and therapeutic applications, and underscores the power of AI-guided engineering to accelerate genome editor development while reducing experimental burden. Eukaryotic Fanzor proteins are compact and advantageous for delivery, but their activity remains limited. Here, the authors engineer an improved Fanzor2 system (evoMmeFz2) using structure-guided and AI-assisted strategies to enable efficient exon skipping in a Duchenne muscular dystrophy model.