Related Experiment Video
Updated: Jun 28, 2025

09:11
Genome Editing with CompoZr Custom Zinc Finger Nucleases ZFNs
Published on: June 14, 2012
25.4K
Engineering of Zinc Finger Nucleases Through Structural Modeling Improves Genome Editing Efficiency in Cells
Shota Katayama1, Masahiro Watanabe2, Yoshio Kato3
1Genome Editing Innovation Center, Hiroshima University, Higashi-Hiroshima, 739-0046, Japan.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|April 11, 2024
Summary
This study details efficient construction of Zinc Finger Nucleases (ZFNs) for genome editing. Engineering ZFNs with AlphaFold, Coot, and Rosetta improved editing efficiency by 5%.
Area of Science:
- Biomedical Research
- Molecular Biology
- Gene Editing Technologies
Background:
- Zinc finger nucleases (ZFNs) are crucial for genome editing, offering advantages in size over TALENs and CRISPR-Cas9.
- ZFNs' small size facilitates packaging into viral vectors like AAV for in vivo and clinical applications.
- Challenges exist in constructing functional ZFNs and enhancing their genome editing efficiency.
Purpose of the Study:
- To describe an efficient method for constructing functional ZFNs.
- To improve the genome editing efficiency of ZFNs.
- To demonstrate the utility of structural modeling tools in ZFN engineering.
Main Methods:
- Assembly of plasmids encoding six-finger ZFNs using public zinc-finger resources.
- Utilized AlphaFold, Coot, and Rosetta for engineering ZFNs.
- Tested ten ZFN constructs for functionality and editing efficiency.
Main Results:
- Successfully constructed two functional ZFNs out of ten tested.
- Engineering ZFNs with AlphaFold, Coot, or Rosetta enhanced genome editing efficiency by 5%.
- Structural modeling-based engineering proved effective for improving ZFN performance.
Conclusions:
- Efficient construction and engineering of ZFNs are achievable using structural modeling tools.
- The developed methods enhance ZFNs' potential for translational research and clinical applications.
- This work validates the use of AlphaFold, Coot, and Rosetta for optimizing genome editing tools.

