In Silico Design and Experimental Validation of siRNAs Targeting Conserved Regions of Multiple Hepatitis C Virus Genotypes.

RNA interference (RNAi) is a post-transcriptional gene silencing mechanism that mediates the sequence-specific degradation of targeted RNA and thus provides a tremendous opportunity for development of oligonucleotide-based drugs. Here, we report on the design and validation of small interfering RNAs (siRNAs) targeting highly conserved regions of the hepatitis C virus (HCV) genome. To aim for therapeutic applications by optimizing the RNAi efficacy and reducing potential side effects, we considered different factors such as target RNA variations, thermodynamics and accessibility of the siRNA and target RNA, and off-target effects. This aim was achieved using an in silico design and selection protocol complemented by an automated MysiRNA-Designer pipeline. The protocol included the design and filtration of siRNAs targeting highly conserved and accessible regions within the HCV internal ribosome entry site, and adjacent core sequences of the viral genome with high-ranking efficacy scores. Off-target analysis excluded siRNAs with potential binding to human mRNAs. Under this strict selection process, two siRNAs (HCV353 and HCV258) were selected based on their predicted high specificity and potency. These siRNAs were tested for antiviral efficacy in HCV genotype 1 and 2 replicon cell lines. Both in silico-designed siRNAs efficiently inhibited HCV RNA replication, even at low concentrations and for short exposure times (24h); they also exceeded the antiviral potencies of reference siRNAs targeting HCV. Furthermore, HCV353 and HCV258 siRNAs also inhibited replication of patient-derived HCV genotype 4 isolates in infected Huh-7 cells. Prolonged treatment of HCV replicon cells with HCV353 did not result in the appearance of escape mutant viruses. Taken together, these results reveal the accuracy and strength of our integrated siRNA design and selection protocols. These protocols could be used to design highly potent and specific RNAi-based therapeutic oligonucleotide interventions.

The design of optimal therapeutic small interfering RNA molecules targeting diverse strains of influenza A virus.

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.

Identification of novel conserved functional motifs across most Influenza A viral strains.

BACKGROUND: Influenza A virus poses a continuous threat to global public health. Design of novel universal drugs and vaccine requires a careful analysis of different strains of Influenza A viral genome from diverse hosts and subtypes. We performed a systematic in silico analysis of Influenza A viral segments of all available Influenza A viral strains and subtypes and grouped them based on host, subtype, and years isolated, and through multiple sequence alignments we extrapolated conserved regions, motifs, and accessible regions for functional mapping and annotation. RESULTS: Across all species and strains 87 highly conserved regions (conservation percentage > = 90%) and 19 functional motifs (conservation percentage = 100%) were found in PB2, PB1, PA, NP, M, and NS segments. The conservation percentage of these segments ranged between 94-98% in human strains (the most conserved), 85-93% in swine strains (the most variable), and 91-94% in avian strains. The most conserved segment was different in each host (PB1 for human strains, NS for avian strains, and M for swine strains). Target accessibility prediction yielded 324 accessible regions, with a single stranded probability > 0.5, of which 78 coincided with conserved regions. Some of the interesting annotations in these regions included sites for protein-protein interactions, the RNA binding groove, and the proton ion channel. CONCLUSIONS: The influenza virus has evolved to adapt to its host through variations in the GC content and conservation percentage of the conserved regions. Nineteen universal conserved functional motifs were discovered, of which some were accessible regions with interesting biological functions. These regions will serve as a foundation for universal drug targets as well as universal vaccine design.