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Engineered Fanzor proteins show enhanced genome editing efficiency in mammalian cells. AI-guided optimization led to significant improvements, enabling therapeutic applications like Duchenne muscular dystrophy correction in mouse models.

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Area of Science:

  • Molecular Biology
  • Biotechnology
  • Genetics

Background:

  • Eukaryotic Fanzor proteins are RNA-guided nucleases with genome editing potential.
  • Current Fanzor systems exhibit suboptimal efficiency in mammalian cells, limiting their therapeutic applications.

Purpose of the Study:

  • To optimize the MmeFz2-ωRNA Fanzor system for enhanced genome editing in mammalian cells.
  • To develop improved Fanzor variants for potential therapeutic applications.

Main Methods:

  • Utilized AlphaFold3 for rational redesign of the ωRNA scaffold, resulting in a smaller and efficient structure.
  • Employed structure-guided and AI-augmented protein engineering to generate novel Fanzor variants (enMmeFz2, evoMmeFz2).
  • Fused Fanzor variants with the HMG-D DNA-binding domain to further enhance editing performance.

Main Results:

  • Minimized ωRNA scaffold maintained high efficiency (up to 82.2%) and was 30% smaller.
  • Engineered Fanzor variants (enMmeFz2, evoMmeFz2) showed an average 32-fold increase in activity across 38 genomic loci.
  • Fanzor-HMG-D fusions demonstrated enhanced editing, with evoMmeFz2-HMG-D successfully restoring dystrophin in a Duchenne muscular dystrophy mouse model via AAV delivery.

Conclusions:

  • Fanzor2 represents a promising gene editing platform for genome engineering and therapeutic development.
  • AI-guided engineering significantly accelerates the development of genome editors and reduces experimental workload.
  • Optimized Fanzor systems hold potential for treating genetic disorders like Duchenne muscular dystrophy.