Comprehensive Atomic-Scale 3D Viral-Host Protein Interactomes Enable Dissection of Key Mechanisms and Evolutionary...

Area of Science:

• Structural biology
• Virology
• Computational biology

Background:

• Viral-human protein interactions are crucial for viral replication and immune response modulation.
• Structural insights into these interactions are vital for developing antiviral therapies and vaccines.
• A significant gap exists in structural information for experimentally determined host-viral interactions.

Purpose of the Study:

• To address the lack of structural data for viral-human interactions by predicting structures computationally.
• To create the most comprehensive atomic-scale 3D viral-host protein interactomes.
• To analyze evolutionary patterns and identify potential therapeutic targets.

Main Methods:

• Utilized AlphaFold for accurate protein structure prediction of host-pathogen interactions.
• Predicted structures for 11,666 binary protein interactions across 33 viral families.
• Integrated predicted interactomes with genetic variation data.

Main Results:

• Developed the largest 3D viral-host protein interactomes to date.
• Identified population-specific selection signatures on interaction interfaces.
• Observed that viral interaction interfaces are less conserved than host interfaces, indicating different evolutionary pressures.
• Discovered mutation rate-dependent differences in interface mimicry.
• Classified human papillomaviruses (HPVs) based on E6 protein binding patterns.
• Unveiled a mechanism of immune suppression by herpes simplex virus-1 UL37.

Conclusions:

• The comprehensive 3D interactomes provide a valuable resource for understanding viral-human interactions and disease progression.
• Enables exploration of how genetic variation influences viral interactions and disease.
• Facilitates identification of conserved and unique viral interaction patterns for therapeutic target discovery.