Exploring the full potential of bioactive natural products and phenotypic screening hits for drug discovery and design requires profound understanding of the macromolecular targets involved. We present a computational method for target prediction, and showcase its practical applicability, taking the marine anticancer compound (±)-marinopyrrole A as an example. With an overall accuracy of 67%, the ligand-based method employed identified the natural product as a potent glucocorticoid, cholecystokinin, and orexin receptor antagonist. The results of this study demonstrate the utility of fast computational target assessment for medicinal chemistry and chemical biology.