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A general theoretical framework to design base editors with reduced bystander effects
Qian Wang1,2, Jie Yang3, Zhicheng Zhong4
1Hefei National Laboratory for Physical Sciences at the Microscale and Department of Physics, University of Science and Technology of China, Hefei, 230026, Anhui, China. wqq@ustc.edu.cn.
Nature Communications
|November 12, 2021
Summary
Base editors (BEs) precisely edit genes for therapy but can affect nearby DNA. This study develops a computational model to predict and minimize unwanted "bystander" edits, guiding the design of more accurate gene-editing tools.
Area of Science:
- Molecular Biology
- Bioinformatics
- Computational Biology
Background:
- Base editors (BEs) are crucial for gene therapy, but off-target edits reduce precision.
- Achieving high precision requires BEs to distinguish target bases from bystander bases within a narrow window.
Purpose of the Study:
- To develop a computational model for predicting and minimizing bystander editing in base editors.
- To establish design principles for creating more precise base editors.
Main Methods:
- A discrete-state stochastic approach was used to build an analytical model.
- All-atom molecular dynamic simulations were combined with the model.
- Experimental validation of designed base editor variants was performed.
Main Results:
- The model accurately reproduced experimental data for A3A-BE3 and its variants.
- General principles for reducing bystander effects were identified.
- Designed mutations in A3G-BEs experimentally reduced bystander editing.
Conclusions:
- The developed computational platform aids in the rational design of base editors with reduced bystander effects.
- This approach facilitates the development of safer and more effective gene therapies.
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