Drugst.One DREAM-Drug repurposing through expert annotation and modification

Area of Science:

• Network and systems medicine
• Computational biology
• Pharmacology

Background:

• Complex diseases often lack actionable understanding of causal biological mechanisms, leading to symptom-based treatments.
• Network and systems medicine utilize disease-associated genes, proteins, and protein-protein interactions (PPIs) to form disease modules.
• Current computational methods for disease module construction overlook pathway annotations, cellular compartments, and directed PPIs, necessitating contextual refinement.

Purpose of the Study:

• To present Drugst.One DREAM, a user-friendly toolbox for refining disease modules without requiring bioinformatics expertise.
• To enable biomedical experts to identify dysregulations, select appropriate drug classes, and eliminate promiscuous proteins in disease modules.
• To facilitate precision therapy by subdividing complex diseases into actionable causal mechanisms.

Main Methods:

• Drugst.One DREAM extends the existing Drugst.One web tool with network editing features.
• Users can refine PPI modules using pathway enrichment analysis and network clustering.
• Dedicated graph layouts visualize subcellular localization and causal relationships sourced from OmniPath.

Main Results:

• The tool was demonstrated by reproducing a known NOX5-containing module.
• An algorithmically inferred candidate module for Crohn's disease was refined, showcasing the tool's effectiveness.
• The study highlights the tool's utility for a broad user group in pharmacology and biomedical research.

Conclusions:

• The Drugst.One DREAM extension addresses a critical need in network medicine tools.
• It provides experts with an accessible option for refining disease modules.
• This advancement supports the development of more precise and effective therapeutic strategies for complex diseases.