@article{159921,
  keywords = {phosphorylation, MEK, ERK, MAPK pathway, pathogenic mutations, kinase, multisite protein phosphorylation, Bayesian parameter inference, kinetic parameters, structurally identifiable kinetic model},
  author = {Eyan Yeung and Sarah McFann and Lewis Marsh and Emilie Dufresne and Sarah Filippi and Heather A. Harrington and Stanislav Y. Shvartsman and Martin W{\"u}hr},
  title = {Inference of Multisite Phosphorylation Rate Constants and Their Modulation by Pathogenic Mutations},
  abstract = { Summary Multisite protein phosphorylation plays a critical role in cell regulation [1, 2, 3]. It is widely appreciated that the functional capabilities of multisite phosphorylation depend on the order and kinetics of phosphorylation steps, but kinetic aspects of multisite phosphorylation remain poorly understood [4, 5, 6]. Here, we focus on what appears to be the simplest scenario, when a protein is phosphorylated on only two sites in a strict, well-defined order. This scenario describes the activation of ERK, a highly conserved cell-signaling enzyme. We use Bayesian parameter inference in a structurally identifiable kinetic model to dissect dual phosphorylation of ERK by MEK, a kinase that is mutated in a large number of human diseases [7, 8, 9, 10, 11, 12]. Our results reveal how enzyme processivity and efficiencies of individual phosphorylation steps are altered by pathogenic mutations. The presented approach, which connects specific mutations to kinetic parameters of multisite phosphorylation mechanisms, provides a systematic framework for closing the gap between studies with purified enzymes and their effects in the living organism. },
  year = {2020},
  journal = {Current Biology},
  issn = {0960-9822},
  url = {http://www.sciencedirect.com/science/article/pii/S0960982219316859},
  doi = {10.1016/j.cub.2019.12.052},
  language = {eng},
}