Computational methodology for mechanistic profiling of kinase domain mutations in cancers

We present a computational modeling and simulation approach to delineate molecular-level mechanisms of activation of protein receptor tyrosine kinases and describe clinical implications of mutations in the Anaplastic Lymphoma Kinase (ALK) receptor tyrosine kinase in pediatric neuroblastoma. We show here that our results shed molecular-level insight into the various mechanisms governing such transforming mutations at the level of kinase activity and are remarkably consistent with experimental observations. We expect that the current study on ALK with suitable validation will transform our computational approach to enable future predictions of driver oncogenic mutations with low false-positive rates, and can hence serve an important in silico tool toward personalized cancer therapy.