title: Combining horizontal and vertical substructure relationships in scaffold hierarchies for activity prediction.
abstract: For a systematic exploration of structural relationships between molecular scaffolds, ∼24,000 unique scaffolds were extracted from 458 different target sets. Substructure relationships between these scaffolds were systematically determined. The scaffold tree data structure was utilized to study structural relationships between original scaffolds and derivative scaffolds obtained by rule-based decomposition. Leaf-to-root substructure relationships that resulted from rule-based decomposition were compared to leaf-to-leaf relationships between original scaffolds most of which were not part of the scaffold tree hierarchy. Decomposed scaffolds not contained in active target set compounds were prioritized on the basis of hierarchical scaffold patterns and additional substructure relationships. For high-priority virtual scaffolds, activity predictions were carried out, and these scaffolds were often found in external test compounds having the predicted activity. Taken together, our results suggest that leaf-to-root substructure relationships in scaffold trees should best be complemented with additional substructure relationships to determine high-priority virtual scaffolds for activity prediction.
authors.affiliation: Department of Life Science Informatics, B-IT, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany.
authors.forename: Ye
authors.initials: Y
authors.lastname: Hu
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D055808:Drug Discovery / Q000379:methods*; D048088:Informatics / Q000379:methods*; D013329:Structure-Activity Relationship; D014584:User-Computer Interface