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机器学习驱动的抗CRISPR蛋白中关键结合偏好性的发现

Machine Learning-Driven Discovery of Essential Binding Preference in Anti-CRISPR Proteins.

作者信息

Ma QingLan, Zhang YuHang, Chen Lei, Bao YuShen, Guo Wei, Feng KaiYan, Huang Tao, Cai Yu-Dong

机构信息

School of Life Sciences, Shanghai University, Shanghai, China.

Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

出版信息

Proteomics Clin Appl. 2025 Jul;19(4):e70013. doi: 10.1002/prca.70013. Epub 2025 Jun 30.

DOI:10.1002/prca.70013
PMID:40588792
Abstract

PURPOSE

Anti-CRISPR (Acr) proteins can evade CRISPR-Cas immunity, yet their molecular determinants remain poorly understood. This study aimed to uncover key features driving Acr activity, thereby advancing both fundamental knowledge and the rational design of robust CRISPR-based tools.

EXPERIMENTAL DESIGN

We compiled a binary-encoded matrix of 761 InterPro-annotated domains and binding-site features for known Acr proteins. Seven feature ranking algorithms were applied to prioritize determinant features, and an incremental feature selection strategy, coupled with four distinct classifiers, was used to identify optimal subsets. Consensus key features were defined by intersecting the top subsets across all methods.

RESULTS

Key identified features include the DUF2829 domain, the Lambda repressor-like domain and Sulfolobus islandicus virus proteins, the Cro/C1-type helix-turn-helix domain, phage protein, and replication initiator A. These findings illuminate novel structural modules and regulatory motifs that underpin Acr inhibition.

CONCLUSIONS

This study provides critical theoretical support for deciphering Acr mechanisms and offers actionable insights for engineering next-generation CRISPR-Cas applications in clinical and biotechnological settings.

SUMMARY

The CRISPR system is a part of the antiviral immune defense initially discovered in bacteria and archaea. At present, the CRISPR system has become the cornerstone of genome editing technologies such as CRISPR-Cas9, widely used in clinical, agricultural, and biological research. Anti-CRISPR proteins are a group of proteins that inhibit the normal activity of CRISPR-Cas system in certain bacteria or archaea and avoid having the phages' genomes destroyed by the prokaryotic cells. The anti-CRISPR protein family has various components, but with similar functions to help exogenous DNA escape from the immune system. This study tried to uncover molecular mechanisms for anti-CRISPR proteins.

摘要

目的

抗CRISPR(Acr)蛋白可规避CRISPR-Cas免疫,但对其分子决定因素仍知之甚少。本研究旨在揭示驱动Acr活性的关键特征,从而增进基础知识并推动基于CRISPR的强大工具的合理设计。

实验设计

我们为已知的Acr蛋白编制了一个由761个InterPro注释结构域和结合位点特征组成的二进制编码矩阵。应用七种特征排名算法对决定因素特征进行优先级排序,并采用增量特征选择策略,结合四种不同的分类器,来识别最佳子集。通过交叉所有方法中的顶级子集来定义共识关键特征。

结果

确定的关键特征包括DUF2829结构域、λ阻遏物样结构域和冰岛硫化叶菌病毒蛋白、Cro/C1型螺旋-转角-螺旋结构域、噬菌体蛋白和复制起始因子A。这些发现揭示了支撑Acr抑制作用的新型结构模块和调控基序。

结论

本研究为解读Acr机制提供了关键的理论支持,并为在临床和生物技术环境中设计下一代CRISPR-Cas应用提供了可行的见解。

总结

CRISPR系统是最初在细菌和古细菌中发现的抗病毒免疫防御的一部分。目前,CRISPR系统已成为CRISPR-Cas9等基因组编辑技术的基石,广泛应用于临床、农业和生物学研究。抗CRISPR蛋白是一类能抑制某些细菌或古细菌中CRISPR-Cas系统正常活性的蛋白质,可避免噬菌体基因组被原核细胞破坏。抗CRISPR蛋白家族有多种成分,但功能相似,有助于外源DNA逃避免疫系统。本研究试图揭示抗CRISPR蛋白的分子机制。

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