Computational Models for Activated Human MEK1: Identification of Key Active Site Residues and Interactions.

Abstract

MEK1 is a protein kinase in the MAPK cellular signaling pathway that is notable for its dual specificity and its potential as a drug target for a variety of cancer therapies. While much is known about the key role of MEK1 in signaling events, understanding of the structural features that sustain MEK1 function remains limited because of the absence of crystal or NMR structural insights into the phosphorylated and activated form of MEK1. In this work, homology modeling was used to overcome this limitation and generate computational models of the doubly phosphorylated active MEK1 conformation. A variety of models were generated using crystal structures of active protein kinases as homology model templates. These models were equilibrated using molecular dynamics simulations, and each model was validated against several known structural characteristics of activated kinases. The best model structures were used in docking studies with ATP and a small peptide sequence that represents the activation loop of ERK2 to identify the most important residues in stabilizing protein docking and phosphorylation. These results provide insights for the pursuit of structure-guided mutagenesis and drug design.