AI-driven strategies for Cas12 protein design and genome editing optimization

The rise of the CRISPR-CAS system has greatly promoted the development of gene editing technology. Cas12, with its unique molecular characteristics, has become an important editing tool following Cas9. In recent years, artificial intelligence (AI) has been widely applied in Cas12-related research, ranging from protein structure optimization, target design to editing efficiency prediction and off-target risk assessment. AI has demonstrated great potential in enhancing system performance and discovering new mutants. Most of these models were trained and benchmarked in human cell lines, E. coli , or yeast, whereas only a subset of engineering strategies has been validated directly in plants, including soybean hairy roots, rice, and Populus . This mini-review summarizes the latest research progress of AI in the field of Cas12 protein optimization and functional prediction, discusses the opportunities and challenges in its application in plants, and provides new ideas for future AI-driven plant gene editing.

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Publication Details

Journal
Frontiers in Plant Science
Published
2026-11-09
DOI
https://doi.org/10.3389/fpls.2026.1997664
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
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article

AI-driven strategies for Cas12 protein design and genome editing optimization

Fanli Meng, Chi Zhang, Yang Li
Frontiers in Plant Science
CRISPR and Genetic Engineering
article

AI-driven strategies for Cas12 protein design and genome editing optimization

Fanli Meng, Chi Zhang, Yang Li
article en

Abstract

The rise of the CRISPR-CAS system has greatly promoted the development of gene editing technology. Cas12, with its unique molecular characteristics, has become an important editing tool following Cas9. In recent years, artificial intelligence (AI) has been widely applied in Cas12-related research, ranging from protein structure optimization, target design to editing efficiency prediction and off-target risk assessment. AI has demonstrated great potential in enhancing system performance and discovering new mutants. Most of these models were trained and benchmarked in human cell lines, E. coli , or yeast, whereas only a subset of engineering strategies has been validated directly in plants, including soybean hairy roots, rice, and Populus . This mini-review summarizes the latest research progress of AI in the field of Cas12 protein optimization and functional prediction, discusses the opportunities and challenges in its application in plants, and provides new ideas for future AI-driven plant gene editing.

Frontiers in Plant ScienceVol. 17
Chinese Academy of Sciences (CN), Northeast Institute of Geography and Agroecology (CN), University College London (GB)
CRISPR and Genetic Engineering
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