Polypharmacology across 759 putative protein targets

The entry 'Polypharmacology across 759 putative protein targets' is not a single biological molecule or therapeutic target but the title of a significant chemical systems biology study (Xie et al., 2009, PLoS Computational Biology). This research analyzed the multi-target binding profile of the FDA-approved drug Sunitinib (Sutent) across a broad panel of the human proteome to identify potential off-targets and explain its complex clinical effects. Polypharmacology refers to the ability of a single small molecule to interact with multiple distinct proteins, which can lead to both therapeutic synergy and unintended toxicities. In this specific study, computational docking was used to predict interactions between Sunitinib and 759 different protein structures, revealing that the drug's activity extends far beyond its primary targets like VEGFR and PDGFR. Because this name represents a dataset or a research finding encompassing hundreds of distinct proteins, it cannot be classified as a single receptor, enzyme, or transporter. It serves as a key example in biotech for understanding how drugs achieve systemic efficacy through a network of interactions rather than a single target.

Other names

Sunitinib polypharmacology profileXie et al. 759 target datasetProteome-wide drug-target interaction profile

Simultaneous inhibition of multiple receptor tyrosine kinases and non-kinase off-targets identified through proteome-wide screening.