ScaffoldGraph

ScaffoldGraph generates and analyzes molecular scaffold networks and trees to support exploration of chemical space and identification of active molecular series.

Key Features:

• Implementation: Implemented using RDKit and NetworkX for cheminformatics operations and graph analysis.
• Scaffold generation: Generates molecular scaffold networks and trees from input molecules.
• Large-scale processing: Processes large datasets of input molecules, including high-throughput screening data.
• Visualization: Provides visualization capabilities for scaffold graphs.
• Clustering: Performs clustering of scaffolds or scaffold-derived graph elements.
• Scaffold-diversity analysis: Conducts scaffold-diversity analysis across compound collections.
• Active-series identification: Identifies active molecular series within scaffold graphs.
• Python integration: Provided as a Python library to integrate with Python cheminformatics workflows.

Scientific Applications:

• Chemical diversity exploration: Facilitates exploration of chemical diversity across compound collections.
• High-throughput screening analysis: Enables analysis and organization of high-throughput screening datasets by scaffold relationships.
• Active series discovery: Supports identification and prioritization of active molecular series for drug discovery research.
• Chemical space navigation: Aids navigation and structural analysis of chemical space using scaffold networks and trees.

Methodology:

Uses RDKit and NetworkX to process input molecules and to construct and analyze scaffold networks and trees, including visualization, clustering, scaffold-diversity analysis, and active-series identification.