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The problem of how to explore structure-activity relationships (SARs) systematically is still largely unsolved in medicinal chemistry. Recently, data analysis tools have been introduced to navigate activity landscapes and to assess SARs on a large scale. Initial investigations reveal a surprising heterogeneity among SARs and shed light on the relationship between 'global' and 'local' SAR features. Moreover, insights are provided into the fundamental issue of why modeling tools work well in some cases, but not in others.