Optimization of aptamers in length and chemistry is crucial for industrial applications. Here, we developed aptamers against the SARS-CoV-2 spike protein and achieved optimization with a deep-learning-based algorithm, RaptGen. We conducted a primer-less SELEX against the receptor binding domain (RBD) of the spike with an RNA/DNA hybrid library, and the resulting sequences were subjected to RaptGen analysis. Based on the sequence profiling by RaptGen, a short truncation aptamer of 26 nucleotides was obtained and further optimized by a chemical modification of relevant nucleotides. The resulting aptamer is bound to RBD not only of SARS-CoV-2 wildtype but also of its variants, SARS-CoV-1, and Middle East respiratory syndrome coronavirus (MERS-CoV). We concluded that the RaptGen-assisted discovery is efficient for developing optimized aptamers.

中文翻译：

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RaptGen 辅助生成针对 SARS-CoV-2 刺突蛋白的 RNA/DNA 混合适体

适体长度和化学性质的优化对于工业应用至关重要。在这里，我们开发了针对 SARS-CoV-2 刺突蛋白的适体，并通过基于深度学习的算法 RaptGen 实现了优化。我们使用 RNA/DNA 混合文库对刺突的受体结合域 (RBD) 进行无引物 SELEX，并对所得序列进行 RaptGen 分析。基于RaptGen的序列分析，获得了26个核苷酸的短截断适配体，并通过相关核苷酸的化学修饰进一步优化。由此产生的适体不仅与 SARS-CoV-2 野生型的 RBD 结合，而且还与其变体 SARS-CoV-1 和中东呼吸综合征冠状病毒 (MERS-CoV) 的 RBD 结合。我们得出的结论是，RaptGen 辅助的发现对于开发优化的适体是有效的。