FoldFlash: pushing the boundaries of protein structure prediction

Deepening our understanding of pathogens and their infection strategies is essential for effectively combating infectious diseases and safeguarding human health.

These intricate interactions often depend on protein-protein interactions (PPIs), which play a critical role in the ongoing genetic "arms race" between pathogens and their hosts.

Nevertheless, identifying these crucial PPIs remains a formidable challenge, often requiring time-consuming experiments. Here, we delve into the complexities of PPIs within pathogens and their significant interactions with hosts.

By capitalizing on advancements in computational structural biology, our aim is to develop a deep learning-based computational method capable of accurately predicting protein complexes.

This research project spans three years and will be co-supervised by Professor Susanne Häußler (Helmholtz Centre for Infection Research, Braunschweig, Germany) and Dr. Lionel Guy (Uppsala University, Sweden).

This proposed approach will significantly enhance our ability to identify PPIs within clinically relevant pathogens, as well as key proteins involved in host-pathogen interactions.

Our findings will provide essential guidance for developing precise treatments against antibiotic-resistant pathogens, including specialised inhibitors, innovative anti-infective agents, and vaccine development. These prospects offer hope in the ongoing battle against infectious diseases.