MIMP: predicting the impact of mutations on kinase-substrate phosphorylation.
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.
The Donnelly Centre, University of Toronto, Toronto, Canada.
Omar
0000000221620431
O
Wagih
The Donnelly Centre, University of Toronto, Toronto, Canada.
Jüri
J
Reimand
The Donnelly Centre, University of Toronto, Toronto, Canada.
Gary D
0000000301858861
GD
Bader
D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D020125:Mutation, Missense; D010766:Phosphorylation; D010770:Phosphotransferases / Q000235:genetics / Q000378:metabolism*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D015398:Signal Transduction; D012984:Software; D013379:Substrate Specificity
D010770:Phosphotransferases