数字农科院2.0

Discovery of deaminase functions by structure-based protein clustering

文献类型： 外文期刊

作者： Jiaying Huang;Qiupeng Lin;Hongyuan Fei;Zixin He;Hu Xu;Yunjia Li;Kunli Qu;Peng Han;Qiang Gao;Boshu Li;Guanwen Liu;Lixiao Zhang;Jiacheng Hu;Rui Zhang;Erwei Zuo;Yonglun Luo;Yidong Ran;Jin Long Qiu;Kevin Tianmeng Zhao;Caixia Gao

作者机构：

关键词： base editing;context preference;Ddd;deaminase;protein classification;Sdd;specificity;structural prediction

期刊名称： Cell

ISSN： 0092-8674

年卷期： 2023 年 186 卷 15 期

页码：

收录情况： SCIE（2023版）

摘要： The elucidation of protein function and its exploitation in bioengineering have greatly advanced the life sciences. Protein mining efforts generally rely on amino acid sequences rather than protein structures. We describe here the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected deaminase proteins to analyze and identified many previously unknown properties. We were surprised to find that most proteins in the DddA-like clade were not double-stranded DNA deaminases. We engineered the smallest single-strand-specific cytidine deaminase, enabling efficient cytosine base editor (CBE) to be packaged into a single adeno-associated virus (AAV). Importantly, we profiled a deaminase from this clade that edits robustly in soybean plants, which previously was inaccessible to CBEs. These discovered deaminases, based on AI-assisted structural predictions, greatly expand the utility of base editors for therapeutic and agricultural applications.

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