Design of a workflow generating novel broad-spectrum siRNA therapeutics targeting critical conserved RNA elements in the viral genome in silico: a study in Dengue
JSHS · 2025
Overview
The likelihood of another COVID -19-level pandemic occurring within 100 years is currently predicted to be 17% and is expected to increase to 44% in the next six decades. Emerging pathogens pose significant threats to global health due to their potential to trigger catastrophic pandemics. Traditional drug development, requiring an average of 12-15 years and $879.3 million per pathogen, is insufficient to combat pathogenic outbreaks, as demonstrated by dengue: despite infecting ~400 million people yearly and being endemic to >100 countries, dengue still lacks universal treatments. If a computational biology workflow is applied to the dengue virus’s sequences and serotypes, then siRNA molecules targeting critical conserved regions of the viral genome can be designed and validated for effectiveness, safety, and broad -spectrum capability fully computationally. Generated siRNAs were filtered through stability, efficacy, conservancy, and specificity parameters. Molecular docking and dynamics analysis evaluated siRNA interactions with cellular machinery. Three siRNA molecules were identified as promising candidates for targeting all dengue serotypes, demonstrating optimal GC content (38.10-42.90%), binding free energies ( -29.4 to -31.6 kcal/mol), and predicted efficac y (84.95-92.98%). siRNAs exhibited excellent conservancy across dengue serotypes (90 -100%) with minimal off -target interactions (E -values 0.66 -2.6). High molecular docking scores ( -308.79 to -381.49) and confidence scores (>0.95) confirmed robust interactions with cellular machinery vital for genomic silencing. This workflow could advance the rapid and flexible development of broad -spectrum antivirals for further in vitro validation, potentially reducing development times by ~22% and costs by ~39%.
Competition history
- JSHS 2025
Resources
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