Project A01.2

Human herpesviruses include widespread pathogens such as Herpes Simplex Viruses (HSV-I, -II), Epstein-Barr Virus, and Human Cytomegalovirus [1]. Unlike many other viruses, herpesviruses can establish lifelong infections. While these latent infections are often self-contained in healthy individuals, viral reactivation can lead to severe, life-threatening complications within immunocompromised populations [1,2].

To develop the tools needed to treat these patients, we must first understand the molecular machinery underpinning viral infection. Our goal is to map specific protein-protein interactions (PPIs) into „interactomes,” giving us a glimpse into the proteins driving viral pathology [3,4]. By identifying the conserved binding interfaces within these PPIs, we can pinpoint specific vulnerabilities to target with new treatments.

Our research bridges the gap between computational prediction and experimental biology. We use AI-based structure-prediction tools, such as AlphaFold, to identify viral protein-binding interfaces in 3D with high fidelity [3-5]. With these targets identified, we then employ in silico tools to generate synthetic protein binders that bind to these interfaces, inhibiting viral function.

We are currently moving these designs from computer modelling to the bench. The synthetic inhibitors are expressed and validated using structural studies, along with a recently developed specialized cell-free binding assay. By combining AI prediction with rigorous experimental testing, we aim to build a reliable pipeline for developing the next generation of antiviral therapeutics.