Mutations leading to activation of proto-oncogenic protein kinases (PKs) are crucial for understanding tumorigenesis and as targets for anti-tumor drugs. However, bionformatics tools developed so far to differentiate driver mutations, that are usually based on conservation or functional considerations, repeteadly fail to predict the effects of activating mutations.
This database presents the first curated dataset of activating and inactivating mutations of PKs, based on experimental evidence. It determines if a particular mutation has been described in the scientific literature as having activating or inactivating effects. If this is not the case, it also allows to explore the possible funcional impact of the mutation. This is done by using a multiple sequence aligment in order to determine if the mutation is located within regions where activating mutations in PKs are described in this dataset.