Respiratory Syncytial Virus (RSV) hospitalises thousands of children each year, yet effective treatments remain unavailable. This research investigates a critical protein–protein interaction that enables RSV infection. By identifying and disrupting key molecular binding sites using AI, the work aims to support the development of targeted antiviral therapies for severe RSV.

This research develops a computational method for detecting hidden RNA viruses within existing RNA sequencing datasets. By identifying conserved viral protein signatures, the approach enables large-scale discovery of previously unknown viruses, improving understanding of viral diversity, disease mechanisms, and future opportunities for diagnostics, surveillance, and antiviral treatment development.