Improved asymmetry prediction for short interfering RNAs

Abstract

In the development of RNA interference (RNAi) therapeutics, merely selecting short, interfering RNA (siRNA) sequences that are complementary to the messenger RNA (mRNA) target does not guarantee target silencing. Current algorithms for selecting siRNAs rely on many parameters, one of which is asymmetry, often predicted through calculation of the relative thermodynamic stability of the two ends of the siRNA. However, we have previously shown that highly-active siRNA sequences are likely to have particular nucleotides at each 5’-end, independent of their thermodynamic asymmetry. Here, we describe an algorithm for predicting highly active siRNA sequences based only on these two asymmetry parameters. The algorithm uses end sequence nucleotide preferences and predicted thermodynamic stabilities, each weighted based on training data from the literature, to rank the probability that an siRNA sequence will have high or low activity. The algorithm successfully predicts weakly- and highly-active sequences for enhanced green fluorescent protein (EGFP) and protein kinase R (PKR). Use of these two parameters in combination improves the prediction of siRNA activity over current approaches for predicting asymmetry. Going forward, we anticipate that this approach to siRNA asymmetry prediction will be incorporated into the next generation of siRNA selection algorithms.

Dicer-TRBP Complex Formation Ensures Accurate Mammalian MicroRNA Biogenesis

“…We observed no such correlation, and similarly detected no correlation between the thermodynamic asymmetry of miRNA duplexes with their strand selection score under any single experimental condition (Figure S3A). These observations underscore the difficulty of predicting miRNA strand selection behavior based on thermodynamic properties alone (Malefyt et al, 2014). …”

Terminal Duplex Stability and Nucleotide Identity Differentially Control siRNA Loading and Activity in RNA Interference

“…TN Rank and DDG 3nn influence siRNA functional asymmetry in cultured HeLa cells Our previous work described the importance of TN Rank (Table 1) and DDG 3nn (Fig. 1A) in predicting siRNA activity [18]. The set of siRNAs chosen to investigate TN Rank and DDG 3nn was selected to possess favorable, neutral, and unfavorable rankings of the two features, with favorable referring to a characteristic that would be associated with higher silencing of the siRNA against its target mRNA, in this case PKR (Fig.…”

“…The set of siRNAs chosen to investigate TN Rank and DDG 3nn was selected to possess favorable, neutral, and unfavorable rankings of the two features, with favorable referring to a characteristic that would be associated with higher silencing of the siRNA against its target mRNA, in this case PKR (Fig. 1B) [18]. In this study, we wished to determine if these parameters could also predict siRNA functional asymmetry, as the most highly active and specific siRNAs will have functional asymmetries highly biased in favor of the intended guide strand.…”

“…In our prior work, we classified siRNA asymmetries according to the 5¢ terminal nucleotide (TN) on each strand (TN Rank) ( Fig. 1A and Table 1) [17][18][19], showing this feature to be more predictive of siRNA activity than DDG.…”

Endocytosis Controls siRNA Efficiency: Implications for siRNA Delivery Vehicle Design and Cell-Specific Targeting

“…Nonetheless, we chose LF2K for these studies for two principal reasons. First, we have considerable prior experience using this vehicle [37][38][39]. Second, there is extensive prior literature on the use of this vehicle [40,41], allowing our results to be compared to the extant literature.…”