LigMerge

LigMerge generates novel ligands by identifying the maximum common substructure between two three-dimensional ligand models, superimposing those substructures, and recombining distinct fragments to produce candidate compounds with potential for improved binding affinity.

Key Features:

• Maximum common substructure identification: Detects the maximum common substructure between two three-dimensional ligand models to preserve critical binding elements.
• Superimposition and fragment mixing: Superimposes identified substructures and systematically mixes and matches distinct fragments attached to common atoms to create new compound configurations.
• Automated generation of novel ligands: Automatically produces multiple compound models related to known inhibitors by recombining chemical moieties at common attachment points.

Scientific Applications:

• Ligand optimization: Generates modified ligand structures aimed at improving binding affinity while retaining essential binding features.
• Lead diversification and scaffold exploration: Produces structurally distinct compounds for exploration of chemical space and novel scaffold generation.
• Target-specific inhibitor identification: Has been used to identify candidate inhibitors for peroxisome proliferator-activated receptor gamma (PPARγ), HIV reverse transcriptase, and dihydrofolate reductase (DHFR).

Methodology:

Identify the maximum (largest) common substructure between two ligands; superimpose these substructures to align them spatially; systematically combine distinct fragments from each ligand at common attachment points to generate new compound models; evaluate generated compounds using computer docking.