The ups and downs of structure-activity landscapes

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Cheminformatics

Background:

• Structure-activity relationships (SARs) describe how molecular structure influences biological activity.
• SAR data can exhibit diverse patterns, including smooth activity changes and abrupt 'activity cliffs' caused by minor structural modifications.
• Traditional views of SAR data may not fully capture these complex relationships.

Purpose of the Study:

• To introduce and review the landscape view of SARs.
• To discuss historical and recent quantitative methods for characterizing SAR landscapes.
• To highlight applications in predictive modeling and SAR elucidation.

Main Methods:

• Conceptualizing SAR datasets as topographical landscapes (plains, hills, gorges).
• Reviewing early quantitative approaches to SAR landscape encoding.
• Discussing recent methods for direct characterization of SAR landscapes, focusing on activity cliff detection and SAR type resolution.

Main Results:

• The landscape view provides an intuitive framework for understanding SAR complexity.
• Recent methods enable direct characterization and visualization of SAR landscapes.
• Applications include improved predictive model development and detailed SAR elucidation from literature data.

Conclusions:

• The SAR landscape approach offers a rigorous and intuitive alternative to standard SAR data analysis.
• Visualizing SAR as a landscape aids in identifying critical structural changes and understanding activity cliffs.
• This perspective enhances drug discovery by providing deeper insights into structure-activity relationships.