RNA interference (RNAi) is a revolutionary technique in gene silencing. While early studies predicted that this method would be highly specific, recent investigations employing microarray technologies have identified off-target gene silencing that is ostensibly driven by as few as 11 bases of complementarity between the sense and/or antisense strand of the small interfering RNA (siRNA) and the unintended target (Jackson et al, 2004, Zamore 2004). As off-target effects represent a potentially serious impediment to expansion of RNAi technologies, we have compared a collection of experimentally validated off-targets with a group of known untargeted genes using multiple sequence alignment algorithms and scoring techniques to determine whether these computational tools can accurately predict off-targeted genes. Our results show that when the frequencies of maximum alignment scores for off-targeted and untargeted genes were compared, the distributions were statistically indistinguishable. These findings indicate that maximum complementarity by itself is insufficient for predicting off-targeted genes, and that factors outside of siRNA-mRNA duplex formation may be key to off-target effects. For this reason, future efforts should focus on the expansion of existing complementarity-based algorithms to incorporate additional factors that accurately predict RNAi-induced off-target gene knockdown.