SmartGraph

SmartGraph enables network pharmacology analysis by integrating bioactivity and biological pathway data into a Neo4j graph database to analyze drug-target and target-target interactions.

Key Features:

• Integration of High-Quality Data: Aggregates bioactivity data and biological pathway information comprising 420,526 unique compound-target interactions involving 271,098 compounds and 2,018 targets.
• Graph-database Backend (Neo4j): Stores and queries complex interaction networks using a Neo4j graph-database structure.
• Predictive Analytics (Bemis-Murcko scaffolds): Performs bioactivity predictions using Bemis-Murcko scaffolds derived from the compound corpus, utilizing 63,783 scaffolds.
• Visualization (D3): Produces graphical representations of network pharmacology data using D3 visualization techniques.
• Hypothesis Generation: Supports generation of hypotheses for mechanisms-of-action, drug repurposing, and off-target prediction based on integrated data and predictions.

Scientific Applications:

• Mechanism-of-Action Elucidation: Maps compound-target and target-target interactions to support interpretation of molecular mechanisms underlying drug effects.
• Drug Repurposing: Identifies candidate novel therapeutic uses for existing compounds through integrated interaction data and scaffold-based predictions.
• Off-Target Prediction: Predicts unintended compound-target interactions to inform safety and selectivity analyses.

Methodology:

Integration of bioactivity and pathway data into a Neo4j graph-database, bioactivity prediction using Bemis-Murcko scaffolds, and network visualization with D3.