<![CDATA[Small interfering RNA (siRNA) is a promising therapeutic against viral infection, includ-ing Influenza viruses. However, the Influenza viruses have massive variants with high mutation rates. Therefore, the siRNAs could be futile against newly emerging viruses. Thus, this study aimed to analyze siRNAs targeting the nucleoprotein gene of Influen-za viruses. Using bioinformatic analyses, the siRNAs were simulated against 5 sub-types of Influenza viruses, including H1N1, H3N2, H5N1, H7N9, and H9N2. Bioinfor-matic tools for the folding structure of messenger RNA were utilized to select effective siRNA. As a result, 32 siRNA sequences targeting the nucleoprotein gene were identi-fied. The precision medicine concept seems applied to the siRNA treatment for the In-fluenza virus since each siRNA is effective in its respective virus target. Based on the nucleotide mismatch parameter, most siRNA does not have coverage for the multiple infections of all five subtypes of Influenza viruses, except for NP1089 and NP1496. Later, the secondary and tertiary structure analysis of messenger RNA demonstrated that siRNA has different circumstances in its RNA target position. Therefore, siRNA mapping based on the RNA folding structure approach provides a tool for selecting more effective sequences against Influenza virus infection. Both siRNA NP1089 and NP1496 were predicted to have similar effectivity in knocking down Influenza virus in-fection. Moreover, the cocktail application of siRNA treatment may be effective as an alternative strategy in matching co-infection of multiple Influenza virus subtypes.]]>
