Polypharmacological network of predicted targets (None)

A polypharmacological network of predicted targets is a computational framework used to identify and visualize the multiple biological molecules—such as receptors, enzymes, and transporters—that a single drug compound is predicted to interact with (Hopkins, 2008, Nature Chemical Biology). This approach moves beyond the traditional one drug, one target model, acknowledging that many therapeutic agents achieve their efficacy through the modulation of multiple pathways simultaneously (Anighoro et al., 2014, Medical Research Reviews). These networks are typically constructed using in silico techniques, including molecular docking, machine learning, and chemogenomic screening, to map the potential binding landscape of a molecule across the proteome (Peters, 2013, Expert Opinion on Drug Discovery). By analyzing these networks, researchers can predict therapeutic outcomes, identify potential off-target toxicities, and explore opportunities for drug repurposing. This systems-level perspective is essential for addressing complex, multifactorial diseases like cancer and neurodegeneration, where single-target interventions may be insufficient.

Other names

Network pharmacologyMulti-target profileIn silico target networkDrug-target interaction network

Not applicable as this is a computational concept rather than a biological molecule.