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

Abstract

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.