Xiao Huan, Zhang Yihao, Yang Xin, Yu Sifan, Chen Ziqi, Lu Aiping, Zhang Zongkang, Zhang Ge, Zhang Bao-Ting
School of Chinese Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China.
Law Sau Fai Institute for Advancing Translational Medicine in Bone & Joint Diseases, Hong Kong Baptist University, Hong Kong SAR 999077, China.
Mol Ther Nucleic Acids. 2024 Aug 15;35(3):102303. doi: 10.1016/j.omtn.2024.102303. eCollection 2024 Sep 10.
Mature microRNAs (miRNAs) are short, single-stranded RNAs that bind to target mRNAs and induce translational repression and gene silencing. Many miRNAs discovered in animals have been implicated in diseases and have recently been pursued as therapeutic targets. However, conventional pharmacological screening for candidate small-molecule drugs can be time-consuming and labor-intensive. Therefore, developing a computational program to assist mature miRNA-targeted drug discovery is desirable. Our previous work (https://doi.org/10.1002/advs.201903451) revealed that the unique functional loops formed during Argonaute-mediated miRNA-mRNA interactions have stable structural characteristics and may serve as potential targets for small-molecule drug discovery. Developing drugs specifically targeting disease-related mature miRNAs and their target mRNAs would avoid affecting unrelated ones. Here, we present SMTRI, a convolutional neural network-based approach for efficiently predicting small molecules that target RNA secondary structural motifs formed by interactions between miRNAs and their target mRNAs. Measured on three additional testing sets, SMTRI outperformed state-of-the-art algorithms by 12.9%-30.3% in AUC and 2.0%-18.4% in accuracy. Moreover, four case studies on the published experimentally validated RNA-targeted small molecules also revealed the reliability of SMTRI.
成熟的微小RNA（miRNA）是短的单链RNA，它们与靶mRNA结合并诱导翻译抑制和基因沉默。在动物中发现的许多miRNA都与疾病有关，并且最近已被作为治疗靶点进行研究。然而，传统的候选小分子药物药理筛选可能既耗时又费力。因此，开发一个计算程序来辅助成熟miRNA靶向药物的发现是很有必要的。我们之前的工作（https://doi.org/10.1002/advs.201903451）表明，在AGO蛋白介导的miRNA-mRNA相互作用过程中形成的独特功能环具有稳定的结构特征，可能作为小分子药物发现的潜在靶点。开发专门针对疾病相关成熟miRNA及其靶mRNA的药物将避免影响无关的miRNA和mRNA。在这里，我们提出了SMTRI，一种基于卷积神经网络的方法，用于有效预测靶向由miRNA与其靶mRNA相互作用形成的RNA二级结构基序的小分子。在另外三个测试集上进行测量时，SMTRI在AUC方面比现有算法高出12.9%-30.3%，在准确率方面高出2.0%-18.4%。此外，对已发表的经实验验证的RNA靶向小分子的四个案例研究也揭示了SMTRI的可靠性。
