Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• Understanding structure-activity relationships (SAR) is crucial for optimizing drug candidates.
• Analyzing combinatorial data sets for multiple biological endpoints presents a significant challenge.
• Rapid identification of critical substitutions affecting activity and selectivity is highly desirable.

Purpose of the Study:

• To present a general approach for describing SAR in combinatorial data sets with dual biological endpoints.
• To emphasize the rapid identification of substitutions with significant impact on activity and selectivity.
• To introduce dual-activity difference (DAD) maps as a tool for SAR analysis.

Main Methods:

• Development and application of dual-activity difference (DAD) maps for visual and quantitative SAR analysis.
• DAD maps analyze pairwise comparisons of substitutions around a molecular template.
• Application to a set of 106 pyrrolidine bis-diketopiperazines tested against two formylpeptide receptors.

Main Results:

• DAD maps enable visual and quantitative identification of activity switches, where substitutions oppositely affect activity against two targets.
• The approach rapidly identifies single- and double-target R-cliffs, indicating dramatic activity modifications from single or double substitutions.
• Demonstrated application to pyrrolidine bis-diketopiperazines reveals SAR insights for formylpeptide receptor modulators.

Conclusions:

• The DAD map approach provides a general and efficient method for SAR exploration of dual-endpoint data.
• This method facilitates the rapid discovery of substitutions critical for modulating compound activity and selectivity.
• The approach is broadly applicable to any analogue series with two biological activity endpoints.