LigTMap

LigTMap predicts protein targets of small molecular compounds by combining ligand similarity search, molecular docking, and binding similarity analysis against 17 classes of therapeutic proteins from the PDBbind database.

Key Features:

• Automated workflow: Performs an end-to-end automated target prediction workflow.
• Comprehensive database utilization: Searches candidate targets drawn from 17 classes of therapeutic proteins curated from the PDBbind database.
• Integrative prediction methods: Integrates ligand similarity search with molecular docking and binding similarity analysis to identify putative targets and assess binding interactions.
• Validation performance: In a validation of 1,251 compounds, it predicted targets for over 70% of compounds within the top-10 list.
• Comparative success rates: On newly compiled compounds from recent literature, it achieved a top-10 success rate of 66% (SwissTargetPrediction 60%, SEA 64%) and a top-1 success rate of 45% (SwissTargetPrediction 51%, SEA 41%).
• Structural output: Provides ligand docking structures in PDB format for downstream structural analyses.

Scientific Applications:

• Target identification for drug discovery: Predicts likely protein targets for small molecules to support early-stage drug discovery.
• Structure-based drug design: Supplies docking poses and target predictions to inform structure-based optimization of compounds.
• Drug repurposing and target exploration: Facilitates identification of alternative protein targets for existing compounds using combined similarity and docking analyses.

Methodology:

Ligand similarity search is combined with molecular docking and binding similarity analysis against 17 therapeutic protein classes from the PDBbind database, and docking results are output in PDB format.