Comparison of approaches for rational siRNA design leading to a new efficient and transparent method.
Comparison of approaches for rational siRNA design leading to a new efficient and transparent method.
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DOI：
10.1093/nar/gkm088
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发表时间：
2007
影响因子：
14.9
通讯作者：
Shabalina SA
中科院分区：
文献类型：
--
作者：
Matveeva O;Nechipurenko Y;Rossi L;Moore B;Saetrom P;Ogurtsov AY;Atkins JF;Shabalina SA
目前的文献描述了几种设计高效 siRNA 的方法，该 siRNA 具有 19 个完美匹配的碱基对和 2 个核苷酸突出端。我们使用四个独立数据库（总共 3336 个经过实验验证的 siRNA），比较了其中几种方法预测 siRNA 切割效率的效果。根据接受者操作特征 (ROC) 和相关性分析，最好的程序是 BioPredsi、ThermoComposition 和 DSIR。我们还研究了不同数据库中与 siRNA 功效显着且一致相关的各个参数。作为这项工作的结果，我们开发了一种新方法，该方法利用线性回归拟合，以局部双链体稳定性、核苷酸位置依赖性偏好和 siRNA 双链体的总 G/C 含量作为输入参数。新方法对高效和低效siRNA的区分能力与现有的最佳方法相当，但与BioPredsi相比，其参数与siRNA作用机制的相关性更明显。这样可以洞察潜在的物理特征和参数的相对重要性。预测 siRNA 效率的新方法比 ThermoComposition 更快，因为它不采用耗时的 RNA 二级结构计算，并且参数比 DSIR 少得多。它可以作为名为“siRNA scales”的网络工具使用。
Current literature describes several methods for the design of efficient siRNAs with 19 perfectly matched base pairs and 2 nt overhangs. Using four independent databases totaling 3336 experimentally verified siRNAs, we compared how well several of these methods predict siRNA cleavage efficiency. According to receiver operating characteristics (ROC) and correlation analyses, the best programs were BioPredsi, ThermoComposition and DSIR. We also studied individual parameters that significantly and consistently correlated with siRNA efficacy in different databases. As a result of this work we developed a new method which utilizes linear regression fitting with local duplex stability, nucleotide position-dependent preferences and total G/C content of siRNA duplexes as input parameters. The new method's discrimination ability of efficient and inefficient siRNAs is comparable with that of the best methods identified, but its parameters are more obviously related to the mechanisms of siRNA action in comparison with BioPredsi. This permits insight to the underlying physical features and relative importance of the parameters. The new method of predicting siRNA efficiency is faster than that of ThermoComposition because it does not employ time-consuming RNA secondary structure calculations and has much less parameters than DSIR. It is available as a web tool called ‘siRNA scales’.
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