The Effect of Adding Indirect Relationship to Turbo Similarity Searching

Abstract

Background:Turbo Similarity Searching (TSS) has been proved as one of the effective and simple searching method in Cheminformatics. Emerging from the conventional similarity searching, TSS depended on the concept of fusion where relationship between the target being sought and the compound in the database are indirect. Previous works has looked at only one level of indirect relationship and indicates that there are further potential that more levels of such relationship be added to TSS to increase its ability to recover more actives. Hence, in this work, we aimed to investigate the impact of the indirect relationship on TSS. Method:This study has further investigated the enhancement of TSS using additional layers of indirect relationship and fusion process. We implemented TSS by adding another layer of fusion between the target and database compound. Results:The experiments with MDDR database showed that the proposed new strategy described in this paper provide a way of enhancing the effectiveness of the TSS process in chemical databases. The experiments also showed that the increases in performance are particularly better when the sought actives are structurally diverse. Conclusion:We may conclude that the additional layers do increase the recall of TSS. Hence, the new TSS strategy could be used as an alternative to the old TSS.

Turbo Similarity Searching: Effect of Partial Ranking and Fusion Rules on ChEMBL Database

“…Then, the search results are fused to infer the final ranking as in group fusion. This led to the existence of the indirect relationship between the reference compound and the top hits of the TSS results [25] . Since TSS starts with one known active compound and assumes its NNs as the active compound for the group fusion phase of TSS, this indirect relationship acts as a quality controller to contextualise the search boundaries so that the relevant structural information dominates the searches i. e., structural commonalities.…”

“…This led to the existence of the indirect relationship between the reference compound and the top hits of the TSS results. [25] Since TSS starts with one known active compound and assumes its NNs as the active compound for the group fusion phase of TSS, this indirect relationship acts as a quality controller to contextualise the search boundaries so that the relevant structural information dominates the searches i. e., structural commonalities. This ensures that more relevant compounds will be retrieved at the top of the list of the group fusion output, hence, improving the recall.…”