structureactivity

Structureactivity, often written as structure-activity relationships (SAR), is the study of how the chemical structure of a compound influences its biological activity. The goal is to identify which structural features promote or reduce activity and to quantify these effects to guide the design of more effective molecules. SAR is central to medicinal chemistry, toxicology, and environmental chemistry, supporting lead optimization and risk assessment.

Historically, SAR emerged in the mid-20th century with Corwin Hansch and colleagues, who introduced systematic substituent constants and quantitative approaches that evolved into QSAR, quantitative structure-activity relationships. In modern practice, SAR combines experimental activity data with computational descriptors to interpret and predict activity across related compounds.

Key concepts include evaluating substituent effects, scaffold and bioisostere generalization, and using descriptors that capture properties such as lipophilicity, electronic effects, steric bulk, hydrogen-bonding capacity, and topological features. Structures are commonly represented as SMILES or InChI, with data linked to biological assays and activity metrics such as IC50 or EC50.

Analytical approaches range from qualitative rules within congeneric series to quantitative QSAR models, including regression-based methods, dimension reduction, and machine-learning techniques. Local SAR focuses on narrow series with incremental changes, while global SAR seeks broader generalizations across chemotypes.

Limitations include data quality, assay context, and applicability domain. SAR remains a critical, iterative framework for understanding how structure drives activity and for guiding the optimization of chemical leads.