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

Nat Methods. 2015 Jun;12(6):531-3. doi: 10.1038/nmeth.3396. Epub 2015 May 4.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Sequence
  • Artificial Intelligence*
  • Mutation, Missense
  • Phosphorylation
  • Phosphotransferases / genetics
  • Phosphotransferases / metabolism*
  • Polymorphism, Single Nucleotide / genetics*
  • Signal Transduction
  • Software*
  • Substrate Specificity

Substances

  • Phosphotransferases