ShaEP

ShaEP performs rigid-body superimposition and computes a similarity index for ligand-sized three-dimensional molecular structures to quantify 3D overlap for computational chemistry and drug discovery applications.

Key Features:

• Rigid-body superimposition: Aligns two 3D molecular structure models without internal deformation to evaluate spatial overlap.
• Similarity index calculation: Computes a quantitative similarity score that reflects how well two molecular structures overlap in three dimensions.
• Hybrid field and volumetric approach: Integrates field-based and volumetric methods to combine electrostatic/shape information with volume overlap calculations.
• Graph-based initial matching: Generates initial superimpositions using a matching algorithm on graphs representing electrostatic potential and local shape at points near molecular surfaces.
• Gaussian-based volume optimization: Optimizes overlays by maximizing volume overlap calculated through atom-centered Gaussian functions representing molecular volume.
• Scaffold hopping capability: Identifies chemically diverse structures with similar electrostatic and shape properties to enable scaffold hopping.
• Computational efficiency: Processes drug-sized molecules on a subsecond timescale, enabling large virtual-library screening and high-throughput preparatory analyses for 3D QSAR and virtual screening.

Scientific Applications:

• Computational chemistry: Quantitative comparison of 3D molecular shape and electrostatic similarity for structure-based analyses.
• Drug discovery: Identification and prioritization of ligand-sized molecules with similar 3D properties to known actives.
• Scaffold hopping: Detection of chemically diverse molecules that share electrostatic and shape similarity to a template.
• Virtual screening: Rapid screening of large virtual libraries against known active molecules using 3D overlap metrics.
• 3D QSAR preparation: Generation of aligned molecular sets for subsequent 3D Quantitative Structure-Activity Relationship modeling.
• Chemical space exploration: Facilitating discovery of novel compounds with desired 3D electrostatic and shape characteristics.

Methodology:

Performs rigid-body alignment using a graph-matching algorithm on points representing electrostatic potential and local surface shape, then optimizes overlays by maximizing volume overlap computed from atom-centered Gaussian functions and reports a numerical similarity index.