Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing

Area of Science:

• Computational biology
• Pharmacology
• Neuroscience

Background:

• Drug repurposing is an efficient strategy for Alzheimer's disease (AD) drug discovery.
• Network-based methods leverage interaction data for identifying candidate drugs.
• Existing methods often overlook the varying importance of network paths of the same length.

Conclusions:

• MPI offers a more effective approach to AD drug repurposing by differentiating path importance.
• Learned node embeddings are crucial for capturing network structure and prioritizing therapeutic paths.
• Further investigation of etodolac, nicotine, and BBB-crossing ACE-INHs is warranted for potential AD repurposing strategies.