Molecular Anatomy

Molecular Anatomy maps compound datasets into a hierarchically interconnected network of molecular frameworks using nine distinct molecular representations and fragmentation rules to reveal chemically relevant moieties.

Key Features:

• Multi-Dimensional Scaffold Representation: Employs nine distinct molecular representations at varying abstraction levels integrated via fragmentation rules to construct a hierarchically interconnected network of molecular frameworks and identify chemical moieties.
• Flexible Scaffold Definition and Pruning Rules: Implements flexible scaffold definitions and multiple pruning rules to cluster active molecules across molecular classes and capture structure-activity relationship (SAR) information, including in libraries with numerous singletons.
• Network Visualization: Generates network visualizations that represent compound datasets as scaffold-space graphs to support navigation and interpretation of SAR patterns.

Scientific Applications:

• Compound Classification: Uses common core structures to classify bioactive compounds and correlate scaffolds with specific biological activities.
• Structure-Activity Relationship (SAR) Analysis: Clusters active molecules from diverse classes to extract detailed SAR information and identify key chemical moieties responsible for biological activity.
• Analysis of Large Compound Libraries: Analyzes libraries with many singletons to reveal scaffold relationships and SAR insights that may be missed by traditional methods.

Methodology:

Defines molecular frameworks through hierarchical connections, employs fragmentation and pruning rules, uses scaffold-based metrics to identify and cluster chemically relevant structures, and integrates results into network visualizations.