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siRNA Design: It's All in the Algorithm

ive control siRNA at the same total siRNA concentration.


What Makes this Algorithm So Successful?
One theory broadly circulated early on in the field was that low overall G/C content in siRNAs tended to correlate with increased silencing efficacy. While it is true that effective siRNAs tend to have G/C contents less than 50%, overall G/C content is not very predictive of siRNA efficacy. Instead, Cenix recognized the strong impact of differential end-stabilities, as conferred by the choice of residues at or near the ends of the target sequence, on silencing efficacy. It emerged that siRNAs containing higher G/C contents at certain residues near the 3' end of the antisense strand, and lower G/C content at certain residues near the 5' end of the antisense strand offered significantly higher success rates. This principle was therefore implemented as one of the key algorithm determinants for maximizing silencing efficacy.

Since then, a recent article published in the journal Cell has suggested a biological reason for the correlation between the nucleotide end-composition of the target site and siRNA efficacy. Schwarz et al. [7] used an in vitro assay system to demonstrate that the sense and antisense strands of an siRNA are not equally likely to be bound by the RNA Induced Silencing Complex (RISC). Each RISC in a cell uses only one strand of an siRNA as a guide for RNAi [4], thus the strand that is bound by RISC d
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