Characterization of the mutational landscape of tumors is important to understanding disease etiology but does not provide mechanistic insight into the functional role of specific mutations. A new study introduces a statistical mechanical framework that draws on biophysical data from SH2 domain–phosphoprotein interactions to predict the functional effects of mutations in cancer.