MoMA-LigPath

MoMA-LigPath simulates ligand unbinding pathways from protein active sites using robotics-inspired geometric algorithms to explore conformational space while accounting for partial molecular flexibility.

Key Features:

• Mechanistic Representation: Employs a mechanistic representation of the molecular system that incorporates partial flexibility to model realistic conformational changes.
• Robotics-Inspired Algorithm: Uses robotics-inspired algorithms to navigate protein–ligand conformational space and identify potential unbinding pathways.
• Geometric Approach: Relies on a purely geometric representation to efficiently simulate ligand exit paths from active sites to the protein surface within short computing times.

Scientific Applications:

• Approximate unbinding pathway prediction: Provides initial approximations of ligand unbinding pathways from PDB structures.
• Protein–ligand interaction analysis beyond the active site: Offers preliminary insights into interactions occurring outside the active site that influence molecular specificity and activity.
• Input for energy refinement and molecular modeling: Generates candidate pathways that can be further refined using advanced energy models and molecular modeling techniques.

Methodology:

Inputs a PDB file containing one or several ligands and applies a robotics-inspired, purely geometric algorithm with partial flexibility to explore potential exit paths from the active site to the protein surface.