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University of Michigan

Department of Biological Chemistry

and Bioinformatics Program


Welcome to the Young Lab


Our laboratory utilizes a combination of experimental and computational approaches to study problems in protein kinases and cell signaling. Protein kinases represent one of the fundamental components of cell signal cascades that propagate signals for fundamental cellular processes including growth, differentiation, and metabolism. In higher organisms, hundreds of diverse protein kinases have evolved different molecular mechanisms to regulate the signaling states of distinct but often co-existing signaling pathways. In an example of regulation in a family of proteins we study, the Cyclin Dependent family of Kinases (CDKs), these kinases have evolved to require the binding of additional proteins, the cyclins, in order to activate their catalytic activity. Some examples of additional molecular mechanisms that have evolved to regulate catalytic activity in protein kinases include the interactions of additional domains with the catalytic core, phosphorylation-stabilized conformational transitions, the binding of external inhibitory proteins, and protein kinase localization. Our goal is to understand these regulatory mechanisms from a structural perspective, using the CDK family as a model.

Computer Modeling
From a computational approach, we employ molecular modeling approaches based upon atomic resolution chemical potential energy functions that are capable of describing detailed molecular properties of the proteins we study. Historically carried out largely on supercomputers, these simulations are now routinely carried out on clusters composed of pc-class computers linked together. Among other things, this modeling approach is used to describe the molecular motions of proteins in an in vitro environment. Coupling these models with x-ray crystallography and in vitro enzymatic assays enables us to study regulatory mechanisms from a protein dynamics, structure, and activity based perspective.

Research Areas