Key result
In silico analysis of over 400,000 influenza RNA sequences identified 185 significant regions of predicted ordered stability, but found limited evidence of sequence covariation.
Why the study?
Influenza virus remains a major threat to human health, and an RNA-centric perspective was needed to identify local structural motifs of likely significance to the infectious cycle for therapeutic targeting.
In silico analysis of influenza RNA reveals widespread ordered stability but limited sequence covariation, identifying potential novel structural motifs for therapeutic targeting.
Should not yet guide antiviral design; leaves open whether these motifs are functionally exploitable.
Influenza virus is a persistent threat to human health; indeed, the deadliest modern pandemic was in 1918 when an H1N1 virus killed an estimated 50 million people globally. The intent of this work is to better understand influenza from an RNA-centric perspective to provide local, structural motifs with likely significance to the influenza infectious cycle for therapeutic targeting. To accomplish this, we analyzed over four hundred thousand RNA sequences spanning three major clades: influenza A, B and C. We scanned influenza segments for local secondary structure, identified/modeled motifs of likely functionality, and coupled the results to an analysis of evolutionary conservation. We discovered 185 significant regions of predicted ordered stability, yet evidence of sequence covariation was limited to 7 motifs, where 3-found in influenza C-had higher than expected amounts of sequence covariation.
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Peterson et al. (2022) studied Influenza A, B, and C. In silico RNA secondary structure analysis (ScanFold) was evaluated on Regions of predicted ordered stability and sequence covariation. In silico analysis of over 400,000 influenza RNA sequences identified 185 significant regions of predicted ordered stability, but found limited evidence of sequence covariation.
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