The combination of Daylight fingerprints and the Tversky coefficient is a powerful method for performing core hopping, that is, scaffold (or lead) hopping where the main structural difference between the query and bioactive target molecule is located in the central core of the molecular structure. However, a major disadvantage of this approach is the fact that a large number of false positives (in the context of core hopping) are retrieved. The tool we have developed and which is described here can be used to postprocess the hits from Daylight Tversky similarity searches by fragmenting the molecules and subsequently annotating them in a way that assists the users in removing false positives and enables them to better focus on molecules of interest. To validate our approach, we have selected four biological targets for which scaffold hopping examples have been reported. We present results from searches in databases containing published activity data and the subsequent analysis of the hits aimed at establishing the potential of our approach.
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