MIMP: predicting the impact of mutations on kinase-substrate phosphorylation.

Journal: Nature methods
Published Date:

Abstract

Protein phosphorylation is important in cellular pathways and altered in disease. We developed MIMP (http://mimp.baderlab.org/), a machine learning method to predict the impact of missense single-nucleotide variants (SNVs) on kinase-substrate interactions. MIMP analyzes kinase sequence specificities and predicts whether SNVs disrupt existing phosphorylation sites or create new sites. This helps discover mutations that modify protein function by altering kinase networks and provides insight into disease biology and therapy development.

Authors

  • Omar Wagih
    The Donnelly Centre, University of Toronto, Toronto, Canada.
  • Jüri Reimand
    The Donnelly Centre, University of Toronto, Toronto, Canada.
  • Gary D Bader
    The Donnelly Centre, University of Toronto, Toronto, Canada.