A pervasive problem in identifying promising drug targets is that it can be difficult to ascertain which component of a complicated signaling network should be perturbed in order to produce the desired alteration of the system readout. Schoeberl et al. show the feasibility of a systems-level analysis for this purpose. Cancer is a known consequence of excessive signaling through the ErbB receptor tyrosine kinase family, which includes four related receptors and a dozen or so ligands (such as epidermal growth factor or EGF) that can act in various combinations. Their computational model suggested that binding to the ErbB3 receptor (which itself is mute with respect to kinase activity) with an affinity in the low nanomolar range in addition to disrupting binding by the ligand HRG1-β and signaling in response to the ligand betacellulin would be key. MM-121 is a monoclonal antibody with these in vitro attributes, and it also inhibited tumor xenografts in mice.
Sci. Signal. 2, ra31 (2009).