Bioinformatics Graduate Program, Metrópole Digital Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, 59078-400, Brazil.
Instituto do Cérebro, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, 59078-970, Brazil.
Sci Rep. 2021 Apr 23;11(1):8849. doi: 10.1038/s41598-021-88310-8.
Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we presented a database of SARS-CoV-2 targets for small interference RNA (siRNA) based approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. The siRNAs sequences are characterized and evaluated by more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess possible bindings to off-target sequences. This dataset is available as a set of four tables, available in a spreadsheet and CSV (Comma-Separated Values) formats, each one corresponding to sequences of 18, 19, 20, and 21 nucleotides length, aiming to meet the diversity of technology and expertise among laboratories around the world. A metadata table (Supplementary Table S1), which describes each feature, is also provided in the aforementioned formats. We hope that this database helps to speed up the development of new target antivirals for SARS-CoV-2, contributing to a possible strategy for a faster and effective response to the COVID-19 pandemic.
新型冠状病毒病 2019(COVID-19)迅速演变为全球性大流行,因此需要开发能够针对 SARS-CoV-2 RNA 基因组并阻断其基因活性的抗病毒药物。在这项工作中,我们提供了一个针对 SARS-CoV-2 的小干扰 RNA(siRNA)靶点数据库,旨在通过提供广泛的可能靶点和 siRNA 序列来加速设计过程。siRNA 序列的特征和评估由 170 多个特征组成,包括热力学信息、碱基上下文、靶点基因和序列与人类基因组的比对信息,以及多种 SARS-CoV-2 毒株,以评估可能与脱靶序列的结合情况。该数据集以四个表的形式提供,以电子表格和 CSV(逗号分隔值)格式提供,每个表对应 18、19、20 和 21 个核苷酸长度的序列,旨在满足全球实验室在技术和专业知识方面的多样性。还提供了一个描述每个特征的元数据表(补充表 S1),也以上述格式提供。我们希望这个数据库能够帮助加快针对 SARS-CoV-2 的新型靶向抗病毒药物的开发,为 COVID-19 大流行的快速有效应对提供一种可能的策略。