Thermodynamic instability of siRNA duplex is a prerequisite for dependable prediction of siRNA activities.

ABSTRACT: We developed a simple algorithm, i-Score (inhibitory-Score), to predict active siRNAs by applying a linear regression model to 2431 siRNAs. Our algorithm is exclusively comprised of nucleotide (nt) preferences at each position, and no other parameters are taken into account. Using a validation dataset comprised of 419 siRNAs, we found that the prediction accuracy of i-Score is as good as those of s-Biopredsi, ThermoComposition21 and DSIR, which employ a neural network model or more parameters in a linear regression model. Reynolds and Katoh also predict active siRNAs efficiently, but the numbers of siRNAs predicted to be active are less than one-eighth of that of i-Score. We additionally found that exclusion of thermostable siRNAs, whose whole stacking energy (DeltaG) is less than -34.6 kc

SUBMITTER: Ichihara M 

PROVIDER: S-EPMC2094068 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature