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Abstract
We report the comparison of two small-molecule collections synthesized at KU at two different eras. We used a machine learning tool to classify the compounds in these collections by their predicted protein targets. The analyses shine light on the evolution of medicinal chemistry research at the University of Kansas, and reveal several new associations between compounds and protein targets.
