Structured data sets of compounds with multi-target and corresponding single-target activity from biological assays

Area of Science:

• Drug discovery and medicinal chemistry
• Computational chemistry and cheminformatics

Background:

• Promiscuity analysis is crucial for understanding off-target effects in drug development.
• Existing compound data sets often lack comprehensive multi-target activity information.

Purpose of the Study:

• To create and provide accessible compound data sets for promiscuity analysis.
• To include both single-target (ST) and multi-target (MT) activity data.
• To account for confirmed inactivity against specific targets.

Main Methods:

• Extraction of compound and target annotations from screening assays.
• Identification of MT and ST compounds for specific target combinations.
• Ensuring completeness of test data for selected compounds.

Main Results:

• Characterization and organization of 1242 MT compounds active against >=5 targets.
• Characterization and organization of 6629 corresponding ST compounds.
• All data made freely available for research purposes.

Conclusions:

• The curated data sets facilitate robust promiscuity analysis.
• This resource supports the development of more selective and effective therapeutics.
• Future work includes target set-based promiscuity analysis and predictions on literature compounds.