Yao Zhihao, Li Wanglu, He Kaiyu, Wang Hongmei, Xu Yan, Wu Qun, Wang Liu, Nie Yao
The Key Laboratory of Industrial Biotechnology, Ministry of Education, State Key Laboratory of Food Science and Resources, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, 214122, China.
State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Agro-product Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China.
Adv Sci (Weinh). 2025 Jul;12(25):e2501269. doi: 10.1002/advs.202501269. Epub 2025 May 8.
The CRISPR-Cas12a system has gained significant attention as a rapid nucleic acid diagnostic tool due to its crRNA-guided trans-cleavage activity. Accurately predicting the activity of different targets is significant to facilitate the crRNA availability but remains challenging. In this study, a novel approach is presented that combines molecular dynamics simulations and neural network modeling to predict the trans-cleavage activity. Unlike conventional tools that rely solely on the base sequences, our method integrated sequence features and molecular interaction features of DNA in the CRISPR-Cas12a system, significantly improving prediction accuracy. Through feature importance analysis, key sequence features that influence Cas12a trans-cleavage activity are identified. Additionally, a crRNA-DNA library with over 23 456 feature sequences from representative viruses and bacteria is established, and validated the high predictive accuracy of the model (Pearson's r = 0.9328) by screening crRNAs from reference targets. This study offers new insights into the molecular interactions of Cas12a/crRNA-DNA and provides a reliable framework for optimizing crRNA design, facilitating the application of the CRISPR-Cas12a in rapid nucleic acid diagnostics.
CRISPR-Cas12a系统因其crRNA引导的反式切割活性,作为一种快速核酸诊断工具而备受关注。准确预测不同靶点的活性对于促进crRNA的可用性具有重要意义,但仍然具有挑战性。在本研究中,提出了一种结合分子动力学模拟和神经网络建模来预测反式切割活性的新方法。与仅依赖碱基序列的传统工具不同,我们的方法整合了CRISPR-Cas12a系统中DNA的序列特征和分子相互作用特征,显著提高了预测准确性。通过特征重要性分析,确定了影响Cas12a反式切割活性的关键序列特征。此外,建立了一个包含来自代表性病毒和细菌的超过23456个特征序列的crRNA-DNA文库,并通过从参考靶点筛选crRNA验证了模型的高预测准确性(皮尔逊相关系数r = 0.9328)。本研究为Cas12a/crRNA-DNA的分子相互作用提供了新的见解,并为优化crRNA设计提供了可靠的框架,促进了CRISPR-Cas12a在快速核酸诊断中的应用。