MOTIVATION: There is an urgent need for new medications to combat influenza pandemics. METHODS: Using the genome analysis of the influenza A virus performed previously, we designed and performed a combinatorial exhaustive systematic methodology for optimal design of universal therapeutic small interfering RNA molecules (siRNAs) targeting all diverse influenza A viral strains. The rationale was to integrate the factors for highly efficient design in a pipeline of analysis performed on possible influenza-targeting siRNAs. This analysis selects specific siRNAs that has the ability to target highly conserved, accessible and biologically significant regions. This would require minimal dosage and side effects. RESULTS AND DISCUSSION: First, >6000 possible siRNAs were designed. Successive filtration followed where a novel method for siRNA scoring filtration layers was implemented. This method excluded siRNAs below the 90% experimental inhibition mapped scores using the intersection of 12 different scoring algorithms. Further filtration of siRNAs is done by eliminating those with off-targets in the human genome and those with undesirable properties and selecting siRNA targeting highly probable single-stranded regions. Finally, the optimal properties of the siRNA were ensured through selection of those targeting 100% conserved, biologically functional short motifs. Validation of a predicted active (sh114) and a predicted inactive (sh113) (that was filtered out in Stage 8) silencer of the NS1 gene showed significant inhibition of the NS1 gene for sh114, with negligible decrease for sh113 which failed target accessibility. This demonstrated the fertility of this methodology. CONTACT: mahef@aucegypt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: There is an urgent need for new medications to combat influenza pandemics. METHODS: Using the genome analysis of the influenza A virus performed previously, we designed and performed a combinatorial exhaustive systematic methodology for optimal design of universal therapeutic small interfering RNA molecules (siRNAs) targeting all diverse influenza A viral strains. The rationale was to integrate the factors for highly efficient design in a pipeline of analysis performed on possible influenza-targeting siRNAs. This analysis selects specific siRNAs that has the ability to target highly conserved, accessible and biologically significant regions. This would require minimal dosage and side effects. RESULTS AND DISCUSSION: First, >6000 possible siRNAs were designed. Successive filtration followed where a novel method for siRNA scoring filtration layers was implemented. This method excluded siRNAs below the 90% experimental inhibition mapped scores using the intersection of 12 different scoring algorithms. Further filtration of siRNAs is done by eliminating those with off-targets in the human genome and those with undesirable properties and selecting siRNA targeting highly probable single-stranded regions. Finally, the optimal properties of the siRNA were ensured through selection of those targeting 100% conserved, biologically functional short motifs. Validation of a predicted active (sh114) and a predicted inactive (sh113) (that was filtered out in Stage 8) silencer of the NS1 gene showed significant inhibition of the NS1 gene for sh114, with negligible decrease for sh113 which failed target accessibility. This demonstrated the fertility of this methodology. CONTACT: mahef@aucegypt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Babak Basiri; Fang Xie; Bin Wu; Sara C Humphreys; Julie M Lade; Mai B Thayer; Pam Yamaguchi; Monica Florio; Brooke M Rock Journal: Mol Ther Nucleic Acids Date: 2020-07-10 Impact factor: 8.886