文摘
Similarity-based methods for virtual screening are widely used. However, conventional searching using 2Dchemical fingerprints or 2D graphs may retrieve only compounds which are structurally very similar to theoriginal target molecule. Of particular current interest then is scaffold hopping, that is, the ability to identifymolecules that belong to different chemical series but which could form the same interactions with a receptor.Reduced graphs provide summary representations of chemical structures and, therefore, offer the potentialto retrieve compounds that are similar in terms of their gross features rather than at the atom-bond level.Using only a fingerprint representation of such graphs, we have previously shown that actives retrievedwere more diverse than those found using Daylight fingerprints. Maximum common substructures give anintuitively reasonable view of the similarity between two molecules. However, their calculation using graph-matching techniques is too time-consuming for use in practical similarity searching in larger data sets. Inthis work, we exploit the low cardinality of the reduced graph in graph-based similarity searching. Wereinterpret the reduced graph as a fully connected graph using the bond-distance information of the originalgraph. We describe searches, using both the maximum common induced subgraph and maximum commonedge subgraph formulations, on the fully connected reduced graphs and compare the results with thoseobtained using both conventional chemical and reduced graph fingerprints. We show that graph matchingusing fully connected reduced graphs is an effective retrieval method and that the actives retrieved arelikely to be topologically different from those retrieved using conventional 2D methods.