Modeling of Biological Networks and Systems Therapeutics Laboratory, Department of Biomedical Engineering, University of California, 451 East Health Sciences Drive, Davis, CA, 95616, USA.
Sci Rep. 2017 Apr 26;7(1):1178. doi: 10.1038/s41598-017-01348-5.
Aptamers consist of short oligonucleotides that bind specific targets. They provide advantages over antibodies, including robustness, low cost, and reusability. Their chemical structure allows the insertion of reporter molecules and surface-binding agents in specific locations, which have been recently exploited for the development of aptamer-based biosensors and direct detection strategies. Mainstream use of these devices, however, still requires significant improvements in optimization for consistency and reproducibility. DNA aptamers are more stable than their RNA counterparts for biomedical applications but have the disadvantage of lacking the wide array of computational tools for RNA structural prediction. Here, we present the first approach to predict from sequence the three-dimensional structures of single stranded (ss) DNA required for aptamer applications, focusing explicitly on ssDNA hairpins. The approach consists of a pipeline that integrates sequentially building ssDNA secondary structure from sequence, constructing equivalent 3D ssRNA models, transforming the 3D ssRNA models into ssDNA 3D structures, and refining the resulting ssDNA 3D structures. Through this pipeline, our approach faithfully predicts the representative structures available in the Nucleic Acid Database and Protein Data Bank databases. Our results, thus, open up a much-needed avenue for integrating DNA in the computational analysis and design of aptamer-based biosensors.
适体是由短寡核苷酸组成的,能够与特定的靶标结合。它们提供了优于抗体的优势,包括稳健性、低成本和可重复使用性。它们的化学结构允许在特定位置插入报告分子和表面结合剂,这在最近的适体基生物传感器和直接检测策略的开发中得到了利用。然而,这些设备的主流应用仍需要在一致性和可重复性方面进行重大改进。对于生物医学应用,DNA 适体比 RNA 适体更稳定,但缺点是缺乏用于 RNA 结构预测的广泛计算工具。在这里,我们提出了一种从序列预测单链 (ss) DNA 三维结构的方法,该方法用于适体应用,特别关注 ssDNA 发夹。该方法包括一个流水线,该流水线顺序地从序列中构建 ssDNA 二级结构,构建等效的 3D ssRNA 模型,将 3D ssRNA 模型转换为 ssDNA 3D 结构,并细化所得的 ssDNA 3D 结构。通过这个流水线,我们的方法忠实地预测了核酸数据库和蛋白质数据库中可用的代表性结构。因此,我们的结果为将 DNA 整合到适体基生物传感器的计算分析和设计中开辟了一条急需的途径。