3D Shape and Pharmacophore-Based Analog Search
Go beyond 2D similarity.
Chemspace’s 3D Analog Search platform identifies true functional analogs by evaluating molecular shape and electrostatic potential in three-dimension-capturing bioactive conformations often missed by traditional 2D fingerprints. This enables effective scaffold hopping, lead optimization, and exploration of underrepresented areas of chemical space.
Our approach integrates state-of-the-art 3D shape similarity methods based on Atomic Property Fields (APF) with pharmacophore-based modeling, ensuring comprehensive recognition of both geometric and functional features. This powerful combination accelerates hit discovery with greater precision, supporting faster and more reliable decision-making in modern drug discovery workflows.
3D Shape-based screening
The Atomic Property Field (APF) is a 3D pharmacophoric potential represented on a continuous grid, used for ligand alignment, virtual screening, and scaffold hopping.
Derived from one or more high-affinity scaffolds, APF combines seven key physicochemical properties: hydrogen bond donors and acceptors, sp² hybridization, lipophilicity, size, electrostatics, and charge.
Each atom may contribute to several fields simultaneously, and when similar atoms appear in consistent spatial regions, they reinforce a strong pharmacophore signal thus helping identify crucial interaction features and relationships across compounds.
Pharmacophore-based screening
Pharmacophore-based screening is a 3D ligand-based approach that identifies compounds sharing essential interaction features with known active molecules.
A pharmacophore represents the spatial arrangement of key chemical features such as hydrogen bond donors and acceptors, aromatic rings, hydrophobic centers, and charged groups, required for biological activity.
By matching these features across molecular databases, pharmacophore screening enables efficient virtual screening, scaffold hopping, and lead optimization - highlighting compounds with similar binding potential even when their chemical structures differ.
Available Datasets for Screening
- 7.8M in-stock screening collection
From the Enamine REAL Space:
- 100M Ro5 Diversity Subset
- 100M Beyond Ro5 Diversity Subset
- 100M Lead-Like Subset
- 100M CNS-Penetrant Subset
- Custom Subset (up to 100M compounds)
