Mutations leading to activation of proto-oncogenic protein kinases (PKs) are a type of drivers crucial for understanding tumorogenesis and as targets for antitumor drugs. However, bioinformatics tools so far developed to differentiate driver mutations, typically based on conservation considerations, systematically fail to recognize activating mutations in PKs. Here, we present the first comprehensive analysis of the 407 activating mutations described in the literature, which affect 41 PKs. Unexpectedly, we found that these mutations do not associate with conserved positions and do not directly affect ATP binding or catalytic residues. Instead, they cluster around three segments that have been demonstrated to act, in some PKs, as “molecular brakes” of the kinase activity. This finding led us to hypothesize that an auto inhibitory mechanism mediated by such “brakes” is present in all PKs and that the majority of activating mutations act by releasing it. Our results also demonstrate that activating mutations of PKs constitute a distinct group of drivers and that specific bioinformatics tools are needed to identify them in the numerous cancer sequencing projects currently underway. The clustering in three segments should represent the starting point of such tools, a hypothesis that we tested by identifying two somatic mutations in EPHA7 that might be functionally relevant.