Informatics and Systems Department, Division of Engineering Research, National Research Centre, Egypt.
Bioinformatics. 2011 Dec 15;27(24):3364-70. doi: 10.1093/bioinformatics/btr555. Epub 2011 Oct 11.
There is an urgent need for new medications to combat influenza pandemics.
Using the genome analysis of the influenza A virus performed previously, we designed and performed a combinatorial exhaustive systematic methodology for optimal design of universal therapeutic small interfering RNA molecules (siRNAs) targeting all diverse influenza A viral strains. The rationale was to integrate the factors for highly efficient design in a pipeline of analysis performed on possible influenza-targeting siRNAs. This analysis selects specific siRNAs that has the ability to target highly conserved, accessible and biologically significant regions. This would require minimal dosage and side effects.
First, >6000 possible siRNAs were designed. Successive filtration followed where a novel method for siRNA scoring filtration layers was implemented. This method excluded siRNAs below the 90% experimental inhibition mapped scores using the intersection of 12 different scoring algorithms. Further filtration of siRNAs is done by eliminating those with off-targets in the human genome and those with undesirable properties and selecting siRNA targeting highly probable single-stranded regions. Finally, the optimal properties of the siRNA were ensured through selection of those targeting 100% conserved, biologically functional short motifs. Validation of a predicted active (sh114) and a predicted inactive (sh113) (that was filtered out in Stage 8) silencer of the NS1 gene showed significant inhibition of the NS1 gene for sh114, with negligible decrease for sh113 which failed target accessibility. This demonstrated the fertility of this methodology.
Supplementary data are available at Bioinformatics online.
迫切需要新的药物来对抗流感大流行。
利用之前对甲型流感病毒的基因组分析，我们设计并实施了一种组合式穷举系统方法，以优化针对所有不同甲型流感病毒株的通用治疗性小干扰 RNA 分子（siRNA）的设计。其基本原理是将高效设计的因素整合到针对可能的流感靶向 siRNA 进行的分析流水线中。这种分析选择具有靶向高度保守、可及和具有生物学意义的区域的能力的特定 siRNA。这将需要最小的剂量和副作用。
首先，设计了>6000 个可能的 siRNA。随后进行了连续过滤，其中实施了一种针对 siRNA 评分过滤层的新型方法。该方法使用 12 种不同评分算法的交集，排除了低于 90%实验抑制映射评分的 siRNA。通过消除人类基因组中的脱靶 siRNA 和具有不良特性的 siRNA，并选择靶向高度可能的单链区域的 siRNA，进一步过滤 siRNA。最后，通过选择靶向 100%保守、具有生物学功能的短基序的 siRNA，确保 siRNA 的最佳特性。验证了 NS1 基因的一个预测活性（sh114）和一个预测非活性（sh113）（在第 8 阶段被过滤掉）沉默子，结果表明 sh114 对 NS1 基因有显著抑制作用，而 sh113 几乎没有靶向可及性的下降，这证明了该方法的有效性。
补充数据可在“Bioinformatics”在线获取。
