Computational identification of novel therapeutic candidates for Streptococcus pyogenes and influenza A coinfections through transcriptomic-based drug repositioning.

backgroundInfluenza A virus (IAV) causes severe illness with a high mortality rate, and secondary bacterial infections can lead to severe pneumonia. Despite the availability of antibiotics and antivirals, treatment of concurrent IAV and invasive group A streptococcal infections remains challenging. As bioinformatic drug repurposing represents a cost- and time-effective manner for discovering novel treatments, this study aimed at the identification of novel therapeutic options for the S. pyogenes-IAV coinfection through this computational approach.

resultsFollowing in vitro infections of pharyngeal epithelial cell lines with either IAV or S. pyogenes serotypes M1 or M49, transcriptomic changes in host cells were analyzed by RNA-seq, obtaining patterns of differentially expressed genes for each infection. These genes were then queried against the LINCS L1000 small molecule database to find compounds capable of reversing infection-induced molecular phenotypes. In this manner, we identified through computational analyses the antitumoral and antibacterial compound mitoxantrone as well as three kinase inhibitors: AT7519 and flavopiridol, which act against cyclin-dependent kinases, and BI2536, an inhibitor of the Polo-like kinase 1 (PLK1), as the main candidates to treat these coinfections.

conclusionsUsing computational drug repurposing we identified four compounds that have the potential to act as suitable drugs in IAV-S. pyogenes coinfections. BI2536 and flavopiridol have been previously confirmed as active against IAV infections in vitro, while mitoxantrone is effective against S. pneumoniae. These results validate our approach, which offers a cost-effective alternative to large-scale drug screenings to find suitable candidate compounds.