**2.2. Structural and thermodynamic consideration**

siRNA potency largely depends upon structural constraints of the target region. Heavily structured sites are less likely to be bound by siRNAs as these sites are not accessible by siRNAs. The relative binding energy of the 5' and 3' ends of the siRNA with the target site play a vital role in the choice of strand to be incorporated into RISC complex and thus is one of the most important parameter to be considered during siRNA design.

Computational Approaches for Designing Efficient and Specific siRNAs 265

complex. Also, too low GC content is not favourable because too low GC content can destabilize the siRNA duplex and reduce their affinity to target mRNA binding. Analysis of

effective siRNAs showed G/C content between 35% and 60% is most favorable.

**Position specific nucleotides**

Presence of A base at position 19 of the sense strand. Presence of U base at position 10 of the sense strand.

Presence of A base at position 3 of the sense strand.

A base other than G at position 13 of the sense strand.

A base other than G or C at position 19 of the sense strand.

Presence of A base at the 2nd nucleotide position of the sense strand. Presence of C base at the 4th nucleotide position of the sense strand. Absence of C base at the 6th nucleotide position of the sense strand. Absence of U base at the 7th nucleotide position of the sense strand. Presence of C base at the 9th nucleotide position of the sense strand.

Presence of A base at the 17th nucleotide position of the sense strand. Absence of C base at the 18th nucleotide position of the sense strand.

**Table 1.** Position specific nucleotide composition prefered in functional siRNAs

All the parameters discussed above are not equally important for selection of efficient siRNAs. By far, many research groups have conducted studies for evaluation of effective parameter sets for siRNA selection. Gong et al. studied 276 known siRNA selection parameters on a sufficiently large set of 3277 experimentally validated siRNAs targeting 1518 genes to identify common parameters that effectively distinguishes functional siRNAs from non functional ones [9]. They were able to identify 34 features associated with improved siRNA efficacy among which 27 features were associated with greater than 70% efficacy. They examined combination of siRNA features to find their cooperative effects on potent siRNA selection and used a disjunctive rule merging (DRM) algorithm to generate a bunch of non-redundant rules set to efficiently predict functional siRNAs and lower the false positive predictions. Table 2 list 17 features set associated with greater than 90%

No occurrences of four or more identical nucleotides in a row.

No occurrences of G/C stretch of length 7 or longer.

efficacy and used for optimal features combination.

**3. Choice of appropriate parameters** 
