Mining the chemical quarry with joint chemical probes: an application of latent semantic structure indexing (LaSSI) and TOPOSIM (Dice) to chemical database mining

In this study we use a novel similarity search technique called latent semantic structure indexing (LaSSI) with joint chemical probes as queries to mine the MDL drug data report database. LaSSI is based on latent semantic indexing developed for searching textual databases. We use atom pair and topological torsion descriptors in our calculations. The results obtained with LaSSI are compared with another in-house similarity search technique TOPOSIM. The results from the similarity searches using joint chemical probes are significantly better than searches using single chemical probes for both LaSSI and TOPOSIM. The selected molecules are closely related in activity to their queries and are ranked among the top 300 scoring molecules of the 82 860 entries in the database. Our implementation of LaSSI is very fast and efficient in finding active compounds. The results also show that LaSSI consistently retrieves more diverse chemical structures representative of the joint chemical probes in comparison to TOPOSIM. The use of multimolecule topological probes to identify compounds complements the use of searching databases with 3D pharmacophore hypotheses.