Multimodal SARS-CoV-2 interactome sketches the virus-host spatial organization

Area of Science:

• Virology
• Structural Biology
• Systems Biology

Background:

• Accurate spatial representation of protein-protein interaction networks (interactomes) is crucial for biological relevance.
• Understanding the spatial organization of viral-host interactions is key to deciphering infection mechanisms.

Purpose of the Study:

• To model the 3D organization of the SARS-CoV-2-human interactome using spatial information from Proximity-Dependent Biotin Identification (BioID).
• To validate the accuracy and predictive value of the 3D interactome map for direct protein interactions.
• To identify functionally important virus-host complexes and facilitate structure-directed drug discovery.

Main Methods:

• Leveraging spatial information from SARS-CoV-2 protein BioID interactomes.
• Calculating weighted distances to model the 3D organization within a cell-like volume.
• Profiling intra-virus and virus-host physical contacts.

Main Results:

• Developed a 3D map of the SARS-CoV-2-human interactome, highlighting viral occupancy and protein coordination.
• Demonstrated the accuracy and predictive power of the 3D map for direct physical interactions.
• Identified key virus-host complexes and generated robust structural models.

Conclusions:

• The 3D interactome map provides a realistic spatial representation, crucial for understanding viral infections.
• This approach aids in identifying therapeutic targets and developing structure-directed drugs.
• The methodology offers a promising tool for combating emerging infectious diseases.