Using Tversky similarity searches for core hopping: finding the needles in the haystack

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• Daylight fingerprints and Tversky coefficient enable scaffold hopping for drug discovery.
• A significant challenge is the high rate of false positives in these similarity searches.
• Effective filtering is crucial for identifying promising lead compounds.

Purpose of the Study:

• To develop a computational tool for postprocessing scaffold hopping search results.
• To reduce false positives and enhance the identification of relevant molecules.
• To validate the tool's efficacy using known scaffold hopping examples.

Main Methods:

• The developed tool fragments molecules from Daylight Tversky similarity searches.
• It annotates these fragments to aid in the removal of false positives.
• Validation involved searching databases for four biological targets with reported scaffold hopping cases.

Main Results:

• The postprocessing tool successfully aids in distinguishing true positives from false positives.
• Analysis of hits demonstrated the tool's potential in focusing on relevant molecules.
• The approach was validated across multiple biological targets.

Conclusions:

• The developed tool effectively addresses the false positive issue in scaffold hopping.
• This method enhances the efficiency of identifying novel drug candidates through core hopping.
• The approach shows significant promise for drug discovery and lead optimization.