Tan Cheng, Zhang Yijie, Gao Zhangyang, Cao Hanqun, Li Siyuan, Ma Siqi, Blanchette Mathieu, Li Stan Z
Zhejiang University, Zhejiang, China.
AI Lab, Research Center for Industries of the Future, Westlake University, Zhejiang 310058, China.
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbae682.
The rational design of Ribonucleic acid (RNA) molecules is crucial for advancing therapeutic applications, synthetic biology, and understanding the fundamental principles of life. Traditional RNA design methods have predominantly focused on secondary structure-based sequence design, often neglecting the intricate and essential tertiary interactions. We introduce R3Design, a tertiary structure-based RNA sequence design method that shifts the paradigm to prioritize tertiary structure in the RNA sequence design. R3Design significantly enhances sequence design on native RNA backbones, achieving high sequence recovery and Macro-F1 score, and outperforming traditional secondary structure-based approaches by substantial margins. We demonstrate that R3Design can design RNA sequences that fold into the desired tertiary structures by validating these predictions using advanced structure prediction models. This method, which is available through standalone software, provides a comprehensive toolkit for designing, folding, and evaluating RNA at the tertiary level. Our findings demonstrate R3Design's superior capability in designing RNA sequences, which achieves around $44%$ in terms of both recovery score and Macro-F1 score in multiple datasets. This not only denotes the accuracy and fairness of the model but also underscores its potential to drive forward the development of innovative RNA-based therapeutics and to deepen our understanding of RNA biology.
核糖核酸(RNA)分子的合理设计对于推进治疗应用、合成生物学以及理解生命的基本原理至关重要。传统的RNA设计方法主要集中在基于二级结构的序列设计上,常常忽略了复杂且关键的三级相互作用。我们引入了R3Design,这是一种基于三级结构的RNA序列设计方法,它转变了范式,在RNA序列设计中优先考虑三级结构。R3Design显著增强了天然RNA骨架上的序列设计,实现了高序列回收率和宏F1分数,并且在很大程度上优于传统的基于二级结构的方法。我们通过使用先进的结构预测模型验证这些预测,证明R3Design可以设计出折叠成所需三级结构的RNA序列。这种通过独立软件提供的方法,为在三级水平上设计、折叠和评估RNA提供了一个全面的工具包。我们的研究结果表明R3Design在设计RNA序列方面具有卓越的能力,在多个数据集中,其回收率分数和宏F1分数均达到了约44%。这不仅表明了该模型的准确性和公正性,还突出了其推动创新的基于RNA的治疗方法发展以及加深我们对RNA生物学理解的潜力。